dengue related research papers

• Open access
• Published: 03 September 2024

Trends and insights in dengue virus research globally: a bibliometric analysis (1995–2023)

• Yumeng Liu   ORCID: orcid.org/0000-0002-3124-0627 1 ,
• MengMeng Wang 2 ,
• Ning Yu 2 ,
• Wenxin Zhao 2 ,
• Peng Wang 2 ,
• He Zhang 2 ,
• Wenchao Sun 3 ,
• Ningyi Jin 1 , 2 &
• Huijun Lu 2  

Journal of Translational Medicine volume  22 , Article number:  818 ( 2024 ) Cite this article

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Dengue virus (DENV) is the most widespread arbovirus. The World Health Organization (WHO) declared dengue one of the top 10 global health threats in 2019. However, it has been underrepresented in bibliometric analyses. This study employs bibliometric analysis to identify research hotspots and trends, offering a comprehensive overview of the current research dynamics in this field.

We present a report spanning from 1995 to 2023 that provides a unique longitudinal analysis of Dengue virus (DENV) research, revealing significant trends and shifts not extensively covered in previous literature. A total of 10,767 DENV-related documents were considered, with a notable increase in publications, peaking at 747 articles in 2021. Plos Neglected Tropical Diseases has become the leading journal in Dengue virus research, publishing 791 articles in this field—the highest number recorded. Our bibliometric analysis provides a comprehensive mapping of DENV research across multiple dimensions, including vector ecology, virology, and emerging therapies. The study delineates a complex network of immune response genes, including IFNA1, DDX58, IFNB1, STAT1, IRF3, and NFKB1, highlighting significant trends and emerging themes, particularly the impacts of climate change and new outbreaks on disease transmission. Our findings detail the progress and current status of key vaccine candidates, including the licensed Dengvaxia, newer vaccines such as Qdenga and TV003, and updated clinical trials. The study underscores significant advancements in antiviral therapies and vector control strategies for dengue, highlighting innovative drug candidates such as AT-752 and JNJ-1802, and the potential of drug repurposing with agents like Ribavirin, Remdesivir, and Lopinavir. Additionally, it discusses biological control methods, including the introduction of Wolbachia-infected mosquitoes and gene-editing technologies.

This bibliometric study underscores the critical role of interdisciplinary collaboration in advancing DENV research, identifying key trends and areas needing further exploration, including host-virus dynamics, the development and application of antiviral drugs and vaccines, and the use of artificial intelligence. It advocates for strengthened partnerships across various disciplines to effectively tackle the challenges posed by DENV.

The Dengue virus (DENV) is a global public health threat transmitted primarily by mosquitoes [ 1 ]. Dengue fever manifests with symptoms including fever, headache, eye pain, muscle and joint pain, and skin rash [ 2 , 3 ]. Dengue fever is prevalent in tropical and subtropical regions, resulting in millions of infections and thousands of deaths annually. It has expanded to non-traditional areas, including the United States and Europe, with significant case surges in the Americas in 2015 and 2019 and a notable outbreak in the Western Pacific in 2013. For a comprehensive overview of global dengue cases and related deaths since 1995, see Table S1 in the supplementary materials, which includes World Health Organization data, although some information may be incomplete due to COVID-19-related disruptions [ 3 ]. Recent epidemiological trends show a concerning expansion in Dengue’s geographic and demographic scope, exacerbated by climate change and urbanization that facilitate vector breeding and shorten the viral incubation period. Studies predict an increase in the global population at risk from 53% in 2015 to 63% by 2080 [ 4 ]. First identified in Myanmar in 1943 by American virologists Albert Sabin and Robert Phillips, DENV was isolated from a patient’s blood sample, laying the foundation for subsequent research on the virus [ 5 ]. The Dengue virus, a single-stranded RNA virus of the Flavivirus genus, comprises four serotypes (DENV-1, DENV-2, DENV-3, DENV-4). Each confers lifelong immunity against itself but leaves individuals susceptible to the other serotypes, complicating prevention efforts and contributing to the severity of outbreaks [ 6 ].

Many commonly used vector control strategies, such as insecticide spraying, have failed to curb disease incidence but continue to be employed in the absence of robust evidence for their effectiveness or optimal implementation. However, advancements in understanding dengue epidemiology, immune response, and innovative control measures, including effective management, vaccines, and novel mosquito control methods, could significantly enhance dengue control efforts.

To tackle the complex challenges posed by the Dengue virus (DENV), this study employs bibliometric analysis to assess the breadth and impact of DENV-related research across various disciplines. Integrating existing studies is crucial to encapsulate the comprehensive scope of DENV research, covering aspects such as transmission dynamics, clinical manifestations, treatment options, and preventive measures. This approach is vital to identify critical research gaps and new potential areas of study, which are essential for advancing our understanding of the virus.

Data source

Data for this bibliometric analysis were retrieved from two primary databases: Web of Science (WOS) Science Citation Index Expanded (SCI-EXPANDED) and Scopus. These databases are widely recognized and extensively utilized in academic research, providing access to a broad array of high-quality academic journals. The selection of these databases enhances the comprehensiveness and credibility of our findings. The SCI-EXPANDED offers extensive coverage of scientific literature, particularly within the natural sciences, and includes high-impact journals, thereby ensuring the quality and reliability of the data. Scopus, as a multidisciplinary database, spans a wide range of subjects including science, technology, medicine, social sciences, arts, and humanities. Its broad coverage and high-quality data make it an indispensable resource for academic research. However, it is important to note that both SCI-EXPANDED and Scopus have a higher representation of English-language literature and high-impact journals, which may result in the underrepresentation of non-English literature and research published in lower-impact journals. Additionally, despite their extensive coverage, literature from certain specific fields may be underrepresented in these databases.

These databases are particularly well-suited for research on the Dengue virus (DENV) due to their reliable indexing in disciplines such as virology and public health. This study, covering the period from 1995 to 2023, focuses on the increase in Dengue-related publications and advancements in scientific databases, with an emphasis on research articles and reviews.

Research methods

In this study, we employed a variety of software tools to conduct comprehensive bibliometric analyses. VOSviewer (versions 1.6.18 and 1.6.20) and Pajek were utilized to analyze countries, institutions, journals, co-cited journals, authors, co-cited authors, and keyword co-occurrence, facilitating the construction of collaboration, co-citation, and co-occurrence networks. The visualization maps produced by VOSviewer and Scimago Graphica provided insightful visual representations of these networks. Pajek offered additional network analysis capabilities, particularly effective for handling large networks with its advanced features for detailed analysis and visualization. CiteSpace (version 6.1.R1) was employed to generate dual-map overlays of journals and to analyze references with Citation Bursts. The R package “bibliometrix” (version 3.2.1) was used to analyze thematic evolution and identify the 15 most active authors in DENV research. Microsoft Office Excel 2019 facilitated the quantitative analysis of publications. Gene visualization analysis was conducted using VOSviewer, while keyword visualization was performed using the R packages ComplexHeatmap (version 2.16.0) and circlize (version 0.4.16). Gene information was sourced from the Citexs Big Data Analysis Platform ( https://www.citexs.com ), which generated relevant visualizations to delineate the current research landscape, identify key research areas, and discern trends. The document selection and analysis process is illustrated in Fig. 1 .

Despite their powerful capabilities, tools like VOSviewer, Pajek, CiteSpace, and various R packages have limitations such as steep learning curves, complexity in data integration, and challenges in interpretation. These tools may also face performance issues with large datasets and might not fully capture the qualitative aspects of research trends. Therefore, a combination of multiple tools and methodologies is often necessary to achieve a comprehensive and accurate bibliometric analysis.

Flowchart Illustrating the Document Selection and Analysis Process for Dengue Virus Research

Global trends and collaborative dynamics in dengue virus research

Over the past 30 years, Dengue virus research has shown a significant upward trend, peaking at 747 articles in 2021. This growth can be divided into three phases: slow (1991–2002, under 120 publications annually), fast (2003–2013, 120–600 publications annually), and rapid (2014–2023, over 640 publications annually), likely influenced by global infectious disease outbreaks (Fig.  2 a). From 2021 to 2023, 45.5% of these publications were in high-impact, Q1 journals (Fig.  2 b).

Overview of Dengue Virus (DENV) Research Publication Trends and Distributions. ( a ) Temporal trends in publications from 1980 to 2020; ( b ) classification of these publications into journal quartiles from 1995 to 2023, using Journal Citation Reports (JCR) rankings; ( c ) geographical distribution of these publications by continent, categorized by the same journal quartiles. Quartiles are determined by the journal’s rank within its category, divided by the total number of journals in that category, and expressed as a percentile: Q1 (top 25%), Q2 (25–50%), Q3 (50–75%), and Q4 (bottom 25%). For journals spanning multiple WOS categories, the harmonic mean of Category Expected Citations is used to determine quality

Geographical analysis reveals significant disparities in research quality across continents. Europe leads with 59.36% of its publications in the top quartile, followed by Central America and the Caribbean (57.14%), and North America (51.17%) (Fig.  2 c). Geographical disparities in research output and quality are notable across different regions, and are influenced by a range of factors. Addressing these factors and proposing solutions is crucial for promoting global academic equality and enhancing research quality.

Analysis of the top 20 corresponding authors’ countries shows variations in self-citation percentage (SCP) and most cited paper (MCP) metrics. The United States leads with the highest SCP (1281) and MCP (885), highlighting its significant contribution to the field. China and India also emerge as key players, supported by robust research infrastructures and extensive funding (Fig.  3 a). Visual maps from VOSviewer and Scimago Graphic illustrate the collaborative landscape, with the United States, China, and India leading in publications and collaborations (Fig.  3 b). This global network underscores the importance of international partnerships in advancing Dengue virus research.

Global Collaboration in Dengue Virus (DENV) Research from 1995 to 2023. ( a ) Displays the top 20 countries ranked by the number of corresponding authors in DENV research. ( b ) Showcases a VOSviewer network visualization of international co-authorship among these countries, where each country is represented as a node. The size of each node indicates the quantity of publications or the centrality in the collaborative network—larger nodes suggest higher publication outputs or more extensive collaboration. Links between nodes illustrate collaborative relationships, and node colors denote clusters of countries with frequent research collaborations in DENV

Comprehensive gene and keyword analysis in dengue virus research

Using VOSviewer 1.6.18 for gene visualization and keyword co-occurrence analysis has revealed a complex landscape in Dengue virus research, covering six main clusters: vector ecology, clinical manifestations, virology, vaccine development, immune response, diagnostic methods, and disease epidemiology (Fig.  4 a and b). This extensive range highlights the breadth of research, from molecular interactions to epidemiological patterns. Specific attention is focused on the virus’s basic properties, including replication mechanisms and immune responses, as well as disease transmission and epidemic trends, emphasizing crucial aspects such as viral transmission routes and genetic diversity.

Keyword Analyses in Dengue Virus-Related Publications from 1995 to 2023. ( a ) A co-occurrence network of 16,833 unique keywords with 58 keywords occurring more than 200 times, organized into six color-coded clusters. ( b ) An overlay visualization showing the temporal progression of keywords, with early keywords in blue and more recent ones in yellow. ( c ) A heatmap detailing the trends of keyword usage over the study period. ( d ) A co-occurrence cluster analysis focusing on genes associated with the Dengue virus

The heatmap analysis from 1995 to 2023 shows an increased focus on keywords like “Aedes” (the primary vector), “antibody”, “ADE” (antibody-dependent enhancement), “dengue vaccine”, and “antiviral agents”, indicating heightened research activity in developing prevention and treatment methods (Fig.  4 c). Emerging keywords such as “covid-19” and “zika” indicate a shift towards research on new infectious diseases, with significant regional research activity in Brazil, Thailand, and Indonesia.

The co-occurrence clustering analysis of genes including IFNA1, DDX58, IFNB1, STAT1, IRF3, and NFKB1 has identified key molecular players in the immune response to Dengue infection. This analysis reveals complex networks of gene interactions via pathways such as Toll-like and RIG-I-like receptors, essential for recognizing viral components and initiating antiviral defenses (Fig.  4 d). Genes such as IFITM3, TBK1, and STAT2 have been identified as potential therapeutic targets for their roles in modulating the host’s immune response and controlling viral load.

Journal impact and citation dynamics in dengue virus research

Over 29.76% of Dengue virus-related publications have appeared in the top 10 journals, underscoring the significant concentration of research output in high-impact periodicals. For more information on these leading journals, refer to Table S2 in the supplementary materials, which lists the top 10 global journals in the field of Dengue. Notably, Plos Neglected Tropical Diseases leads with 791 articles, followed by the American Journal of Tropical Medicine and Hygiene with 579 articles, Journal of Virology with 322 articles, and BMC Infectious Diseases with 207 articles. Predominantly classified within the Q1 and Q2 quartiles, these journals have a profound impact on the scientific community, covering areas such as virology, immunology, epidemiology, and public health. These leading journals contribute significantly to various research domains within the field. For instance, Plos Neglected Tropical Diseases and the American Journal of Tropical Medicine and Hygiene are instrumental in advancing basic research and epidemiological research. The Journal of Virology plays a critical role in disseminating virological and immunological research, while BMC Infectious Diseases provides extensive coverage of clinical studies and the public health implications of research. This interdisciplinary approach is essential for addressing the multifaceted challenges of Dengue research.

A dual-map overlay analysis provides further insights by visualizing the diversity of research topics covered in these journals and the co-citation relationships among articles in the Dengue virus research field (Fig.  5 ). This analysis highlights the interconnectedness of research activities, with molecular biology, immunology, and clinical medicine prominently featured. It also reveals extensive collaboration across research domains, underscoring the pivotal role of molecular biogenetics as a frequently cited area in Dengue virus research. This network illustrates the depth of collaborative efforts and showcases the journals’ roles in fostering a comprehensive understanding of and response to global Dengue fever challenges.

Dual Map Overlay of Journals in Dengue Virus Research. This visualization illustrates the thematic distribution and citation flows among disciplines involved in Dengue studies. It highlights key citation trajectories between journals in Molecular Biology, Genetics, and other related fields, showcasing the interconnectivity of medical, clinical, and biological research in advancing our understanding of Dengue

The inaugural bibliometric analysis of the global research landscape on the dengue virus reveals a field predominantly characterized by descriptive and observational studies. From 1995 to 2023, the number of published papers peaked in 2021, with 747 articles. This surge suggests a rapid advancement and increased interest in Dengue virus research, potentially driven by emerging challenges and advancements in the field. These pivotal moments have often been marked by disease outbreaks, policy changes, or scientific breakthroughs. For instance, severe outbreaks in the Philippines and Brazil during 2019–2021 led to an increased focus on studying transmission patterns and developing effective prevention strategies [ 7 , 8 ]. Global health organizations and national governments have implemented new policies to combat the rising threat of Dengue. The World Health Organization’s comprehensive Dengue control strategy, launched in 2020, emphasized the need for enhanced surveillance, improved diagnostics, and vaccine development. These policies spurred increased funding and research initiatives, contributing to the surge in publications. Advances in genomics, proteomics, and bioinformatics have provided new tools and methodologies for studying the Dengue virus. Breakthroughs in vaccine development, such as the approval and rollout of the Dengvaxia vaccine, and innovative diagnostic methods have accelerated research efforts to evaluate efficacy and safety, understand virus-host interactions, and explore novel therapeutic targets. These pivotal events have directed research towards specific aspects of Dengue virus biology, immunology, and epidemiology, guiding the evolution of the field [ 9 ]. Initially dominated by basic research on viral properties, replication mechanisms, and vaccine development, the field has progressively expanded to encompass broader areas such as vector ecology [ 10 ], clinical manifestations [ 11 ], diagnostic methods [ 12 ], and disease epidemiology [ 13 , 14 ].

Geographical analysis reveals significant disparities in research quality across continents. Europe leads with 59.36% of its publications in the top quartile, followed by Central America and the Caribbean (57.14%), and North America (51.17%). These disparities are influenced by several factors. Research output is disproportionately lower in regions such as Sub-Saharan Africa, parts of the Middle East, and smaller island nations in the Pacific. Despite the presence of Dengue in these areas, they contribute relatively few research publications compared to regions like Southeast Asia and Latin America. Many underrepresented regions lack the necessary infrastructure, funding, and trained personnel to conduct extensive research. Limited access to advanced technologies and laboratories hampers local research efforts. In regions burdened by multiple infectious diseases (e.g., malaria, HIV/AIDS), public health resources and research funding are often directed towards more immediate health threats, sidelining Dengue research. Variations in Dengue virus transmission dynamics and environmental conditions might influence the intensity and focus of research activities. Regions with sporadic outbreaks may not prioritize Dengue research as highly as those with continuous high transmission rates. These disparities impact global Dengue virus research and control efforts by creating gaps in knowledge and hindering the development of universally effective interventions. Underrepresentation in research limits the understanding of region-specific transmission patterns, vector behavior, and population immunity, which are crucial for designing targeted control measures.

Comparison with existing literature

Spanning from 1995 to 2023, this study provides a unique longitudinal analysis of Dengue virus research, revealing significant trends and shifts using advanced bibliometric and statistical techniques like network and trend analyses. Our findings are consistent with and build upon prior bibliometric studies on Dengue virus and related arboviruses. By integrating disciplines like epidemiology, biology, and environmental science, the study provides an in-depth view of the field’s evolution and the challenges posed by the Dengue virus. It particularly highlights the impact of global climate change on disease transmission, offering insights not extensively covered in previous literature. For instance, the study titled “Dengue,” published in The Lancet in February 2024, includes data only up until October 10, 2022 [ 15 ]. In contrast, our research incorporates updated data, extending our analysis from 1995 to 2023. This expansion enables a more comprehensive analysis and deeper insights into long-term trends that elucidate the development and impact of Dengue fever.

Hotspots and frontiers

The analysis of keywords and gene clustering patterns highlights emerging trends and research priorities in DENV research. Key research focuses include vaccine development [ 16 , 17 ], novel antiviral therapies, virus transmission and control strategies, climate change and disease distribution, epidemiology and model predictions [ 18 , 19 , 20 ], and immune responses and pathogenic mechanisms [ 21 , 22 , 23 ]. The dynamic nature of DENV research is evident, with a recent pivot toward issues such as climate change and the emergence of viruses like Zika and chikungunya [ 24 , 25 , 26 , 27 ]. Since 2019, the focus has notably shifted toward antiviral activities [ 28 , 29 ] and the exploration of neutralizing antibodies [ 30 , 31 , 32 , 33 , 34 ] as critical areas of investigation. Effective antiviral strategies are essential to control the rising prevalence of Dengue virus infection and reduce mortality. The identified trends indicate a growing reliance on interdisciplinary approaches in DENV research. To comprehensively understand the transmission mechanisms and pathological processes of the dengue virus, future studies should continue to foster collaborations across fields such as epidemiology, molecular biology, climate science, and public health. Additionally, the hotspots reveal the rapid development of new diagnostic and therapeutic technologies. Future research should further promote innovation in areas such as nanotechnology, gene editing, and vaccine development to discover more effective prevention and treatment methods. Moreover, enhancing global data sharing and applying big data analytics can enable researchers to more accurately predict dengue outbreaks and develop more effective interventions. The analysis of research trends and hotspots can also provide evidence-based support for policy-making. Understanding regional patterns of virus transmission and high-risk factors can help formulate targeted control strategies. Furthermore, public health strategies can be significantly improved by integrating community involvement and education, environmental management, and continuous monitoring. Environmental factors play a significant role in virus transmission, as indicated by hotspot analyses. Public health strategies should establish and refine monitoring systems and emergency plans to ensure swift and effective action during outbreaks.

Vaccine development

The development of an effective dengue vaccine has been hindered by the immunological complexities of its four serotypes, requiring uniform protection to prevent antibody-dependent enhancement (ADE), a significant challenge for vaccine efficacy [ 35 , 36 ]. Several vaccine candidates have emerged, targeting either the structural E protein or the non-structural protein NS1, with various stages of development currently underway [ 37 , 38 , 39 ]. Currently, three primary vaccines are in use: Sanofi Pasteur’s Dengvaxia (CYD-TDV), the first licensed vaccine; this vaccine has shown an efficacy rate of approximately 60% but has been associated with an increased risk of severe dengue in seronegative individuals. This risk led to its restricted use to those who have had a previous dengue infection. Recent studies have continued to monitor its long-term efficacy and safety, providing critical data on its performance in diverse populations. Takeda’s Qdenga (TAK-003), approved in the EU in December 2022 and in Brazil in March 2023; Qdenga has demonstrated a higher efficacy rate, with recent studies showing an 80% reduction in hospitalizations and a 90% reduction in severe dengue cases among vaccinated individuals. where the vaccine was approved for ages 4–60, corroborate these findings, showing substantial decreases in dengue-related hospitalizations and severe cases. and the NIH’s TV003 has shown promise, with phase II trials indicating strong immunogenicity and a balanced response against all four serotypes. Phase III trials are ongoing, and preliminary data suggest high efficacy across different age groups and regions [ 40 ]. This vaccine’s simpler dosing schedule and robust immune response make it a strong candidate for broad use. For a comparison of the efficacy of licensed and Phase 3 live attenuated tetravalent Dengue vaccines across targeted populations, refer to Table  1 . Additional candidates, such as attenuated live, inactivated, recombinant, and DNA vaccines, are currently under clinical or preclinical evaluation. For a comprehensive overview of these vaccine candidates, refer to Table S3 in the supplementary materials.

Novel antiviral therapies

The urgent need for effective antiviral agents against the Dengue virus is underscored by the limited efficacy of currently available treatments [ 41 , 42 ]. Substantial efforts have been invested in identifying potent antivirals, with a notable shift toward repurposing existing drugs as a viable strategy [ 43 ]. However, drugs such as balapiravir, chloroquine, lovastatin, and celgosivir have shown limited success in clinical trials, highlighting the need for a targeted approach in developing novel therapies. Many repurposed drugs were originally designed to target different pathogens or disease mechanisms, which do not align well with the unique biology of the Dengue virus. For instance, chloroquine, primarily an anti-malarial drug, failed to exhibit significant antiviral activity against Dengue in clinical settings [ 44 ]. The pharmacokinetic profiles of some repurposed drugs are not suitable for achieving effective concentrations in tissues affected by Dengue. Additionally, toxicity at the required doses for antiviral efficacy can limit their use. Balapiravir, for instance, showed hepatotoxicity in clinical trials, making it unsuitable for Dengue treatment [ 45 ]. The potential for the development of viral resistance is another concern. Drugs like lovastatin, initially considered for their antiviral properties, may induce resistance mechanisms in the virus, reducing their long-term efficacy [ 46 ]. Lessons learned for future drug development include the importance of tailoring drug design to the specific viral and host mechanisms involved in Dengue pathogenesis. Additionally, a better understanding of the pharmacokinetic and pharmacodynamic requirements for effective antiviral activity is crucial. Future efforts should focus on identifying compounds that specifically target Dengue virus replication and its interaction with host cells.

Detailed information on the most promising candidates(see Table 2 ), such as AT-752 and JNJ-1802, can shed light on the potential breakthroughs in antiviral treatments for Dengue. AT-752-This candidate has shown potent in vitro activity against all four DENV serotypes. Phase I trials have indicated favorable pharmacokinetics and safety profiles, making it a promising candidate for further development. AT-752 targets the viral RNA polymerase, inhibiting viral replication. Early clinical data suggest that AT-752 can achieve therapeutic concentrations in the blood with minimal side effects, paving the way for phase II trials to assess its efficacy in Dengue patients. JNJ-1802-An inhibitor of the DENV NS4B protein, JNJ-1802 has demonstrated robust antiviral activity in preclinical models. It disrupts the viral replication complex, effectively reducing viral load. Early-phase clinical trials have shown promising results, with significant reductions in viral RNA levels in treated individuals. The safety profile has also been favorable, with no serious adverse events reported. Ongoing trials aim to determine the optimal dosing regimen and confirm its efficacy in larger patient cohorts. Additionally, research into host-targeted therapies, such as those modulating the immune response or viral entry pathways, is ongoing, with several candidates showing promise in preclinical studies. These approaches aim to enhance the host’s ability to combat the virus or prevent the virus from entering and replicating within host cells. Continued interdisciplinary research and innovative methodologies are crucial in addressing the challenges of treating DENV infections. For detailed information on recent advances, refer to Table S4 in the supplementary materials, which outlines the development of new antiviral drugs for Dengue. The integration of novel therapeutic approaches, combined with a deeper understanding of the virus-host interactions, holds the potential for significant breakthroughs in managing Dengue virus infections.

Virus transmission and control strategies

Recent advances in biological control methods have significantly shaped strategies to mitigate dengue fever transmission via vector mosquitoes. One notable approach is infecting Aedes mosquitoes with Wolbachia, an endosymbiotic bacterium that effectively reduces the mosquitoes’ ability to transmit the dengue virus [ 47 ]. Another method is the release of sterile mosquitoes through radiation or genetic modification, which controls population numbers by preventing offspring production after mating with wild mosquitoes [ 48 ]. Additionally, the use of CRISPR-Cas9 gene editing technology is emerging as a revolutionary approach to engineer mosquitoes that either cannot survive or transmit the dengue virus, although this remains experimental [ 48 ]. The application of nanotechnology in insecticides shows promise, enhancing the delivery and effectiveness of chemical controls with minimal environmental impact by targeting specific biological pathways in mosquitoes [ 49 ]. Furthermore, smart surveillance systems utilizing IoT (Internet of Things), AI (Artificial Intelligence), and big data are improving the monitoring and predictive analysis of vector populations and dengue transmission patterns, leading to more targeted and efficient control measures [ 50 ].

Epidemiology and model predictions

Recent advancements in epidemiological modeling have significantly enhanced our understanding of disease transmission in the context of climate change. Machine learning and AI models have become essential for processing large datasets and predicting disease spread patterns with high accuracy, leveraging complex nonlinear data to forecast trends and potential outbreaks [ 51 ]. Spatial statistical models, another critical tool, use geographic and environmental data to map the potential distribution of vectors like Aedes mosquitoes and predict regions at increased risk for dengue outbreaks [ 51 ]. Dynamic simulation models, such as the Susceptible-Exposed-Infectious-Recovered (SEIR) model, simulate transmission dynamics within populations using differential equations to describe interactions between hosts, pathogens, and the environment, providing a detailed predictive framework [ 52 ]. Additionally, regression analysis identifies key factors influencing transmission, while Geographic Information Systems (GIS) assess how environmental factors, exacerbated by climate variability, affect disease patterns. Integrating GIS with epidemiological data helps guide targeted interventions and resource allocation [ 53 ].

Immune responses and pathogenic mechanisms

Gene co-occurrence analysis has highlighted critical molecular mechanisms in Dengue virus infection, pinpointing key genes such as IFNA1, DDX58, and STAT1 that play significant roles in the host immune response. IFNA1 enhances antiviral gene expression and adaptive immunity [ 54 ]. DDX58 activates innate immune signaling upon viral RNA recognition [ 55 ], and STAT1 is crucial for cytokine production and immune cell activation [ 56 , 57 ]. Dysregulation of these genes can lead to severe outcomes in Dengue fever. Other important genes in the Toll-like and RIG-I-like receptor pathways, such as TLR3, TLR7, TLR9, IFNAR1, and MAVS, have been linked to virus recognition and response mechanisms [ 58 ]. The dynamic host immune response to Dengue virus involves innate immune sensor activation, cytokine production, and adaptive immune response induction. The virus employs evasion strategies that can lead to dysregulated immune responses and severe disease manifestations such as cytokine storm and tissue damage [ 30 , 59 , 60 , 61 ]. This understanding opens avenues for targeted therapies, such as viral RNA-sensor inhibitors or cytokine blockers, which could mitigate immune-mediated damage and improve outcomes in severe Dengue cases. Insights from gene co-occurrence studies suggest potential therapeutic targets in immune signaling, viral replication, and inflammation pathways, crucial for developing novel treatments to control viral replication and modulate immune responses in Dengue virus infection [ 62 ].

Strategic initiatives for global dengue research collaboration

Future research on Dengue virus (DENV) should prioritize international collaboration and interdisciplinary cooperation to effectively address global challenges. Establishing international research consortia and networks is essential, aiming to foster partnerships among countries, institutions, and disciplines to facilitate knowledge exchange, resource sharing, and collaborative research efforts. Initiatives like joint funding programs, collaborative research projects, and researcher exchange programs are crucial for promoting cross-cultural collaborations and interdisciplinary approaches. Leveraging the strengths of diverse stakeholders, such as researchers, policymakers, public health agencies, and community organizations, is key to driving innovation and accelerating progress in understanding and combating DENV globally. Future studies should explore Dengue virus dynamics, leveraging advanced technologies and data analysis methods to predict outbreaks and identify key environmental, social, and biological factors. Collaborative efforts among epidemiologists, virologists, entomologists, climatologists, and public health experts can provide a holistic understanding of transmission mechanisms and accelerate the development of targeted interventions. Integrating real-time surveillance systems, geographic information systems (GIS), and mathematical modeling can enhance the accuracy and timeliness of outbreak predictions, optimizing resource allocation for prevention and control. Community-based interventions, such as vector control programs and health education campaigns, are crucial in reducing transmission and mitigating the impact of outbreaks. Despite advancements, challenges in rapid diagnostics, effective antiviral treatments, and developing vaccines that are efficacious across all DENV serotypes remain. Addressing these challenges through innovative diagnostic technologies, novel vaccine platforms, and interdisciplinary collaboration is vital for progress. Moreover, emerging technologies like gene editing and biotechnology hold promise for new therapeutic interventions, underscoring the importance of international and interdisciplinary efforts in advancing DENV research and developing sustainable solutions for its control and prevention.

Conclusions

This bibliometric analysis reveals key trends and research gaps in DENV studies from 1995 to 2023, highlighting the importance of interdisciplinary approaches in understanding virus behavior, vaccine development, and prevention strategies. Although notable progress has been made, our analysis identifies several underexplored areas, including the interactions between DENV and its host, the socio-economic impacts of public health interventions, and the application of advanced technologies like artificial intelligence in epidemic prediction and management. Future research requires strengthened interdisciplinary collaboration, uniting experts from molecular biology, epidemiology, data science, and other fields to address comprehensively the challenges posed by DENV. By fostering such cooperation, we can bridge existing research gaps and pioneer new directions, ultimately achieving effective control and prevention of DENV.

Supplemental materials

To further enrich the understanding of our research, we have provided detailed Supplemental Materials. These include Table S1 , which presents data on global dengue cases and related deaths since 1995; Table S2 , which lists the top 10 global journals in the field of dengue; Table S3 , which details current dengue vaccine candidates under evaluation; and Table S4 , which summarizes recent advances in dengue antiviral drug development. These materials offer additional insights and broader context to the discussions presented in this paper.

Data availability

Not applicable.

Abbreviations

Dengue virus

The World Health Organization

The Web of Science

Science Citation Index Expanded

Self-citation percentage (SCP)

Most cited paper (MCP)

Corona Virus Disease 2019

Antibody-dependent enhancement

Interferon Alpha 1

DEAD (Asp-Glu-Ala-Asp) Box Polypeptide 58

Interferon Beta 1

Signal Transducer and Activator of Transcription 1

Interferon Regulatory Factor 3

Nuclear Factor Kappa B Subunit 1

Toll-like Receptors

RIG-I-like Receptors

Interferon-Induced Transmembrane Protein 3

TANK-Binding Kinase 1

Signal Transducer and Activator of Transcription 2

National Institutes of Health

Internet of Things

Artificial Intelligence

Susceptible-Exposed-Infectious-Recovered (a compartmental model in epidemiology)

Geographic Information System

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (2021YFC2301704) and CAMS Innovation Fund for Medical Sciences (2020-12 M-5-001).

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Liu, Y., Wang, M., Yu, N. et al. Trends and insights in dengue virus research globally: a bibliometric analysis (1995–2023). J Transl Med 22 , 818 (2024). https://doi.org/10.1186/s12967-024-05561-5

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Severe disease during both primary and secondary dengue virus infections in pediatric populations

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• Dengue virus
• Viral infection

Dengue is a global epidemic causing over 100 million cases annually. The clinical symptoms range from mild fever to severe hemorrhage and shock, including some fatalities. The current paradigm is that these severe dengue cases occur mostly during secondary infections due to antibody-dependent enhancement after infection with a different dengue virus serotype. India has the highest dengue burden worldwide, but little is known about disease severity and its association with primary and secondary dengue infections. To address this issue, we examined 619 children with febrile dengue-confirmed infection from three hospitals in different regions of India. We classified primary and secondary infections based on IgM:IgG ratios using a dengue-specific enzyme-linked immunosorbent assay according to the World Health Organization guidelines. We found that primary dengue infections accounted for more than half of total clinical cases (344 of 619), severe dengue cases (112 of 202) and fatalities (5 of 7). Consistent with the classification based on binding antibody data, dengue neutralizing antibody titers were also significantly lower in primary infections compared to secondary infections ( P  ≤ 0.0001). Our findings question the currently widely held belief that severe dengue is associated predominantly with secondary infections and emphasizes the importance of developing vaccines or treatments to protect dengue-naive populations.

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All the raw data analyzed are provided as source files in the main text and in the extended data material. Individual de-identified data for age, sex and clinical disease classification are provided as source data in the supplementary information. Source data are provided with this paper.

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Acknowledgements

This work was supported by National Institutes of Health grant no. ICIDR 1UO1A/115654; Department of Biotechnology (DBT), Government of India grant nos. BT/PR5132/MED/15/85/2012 and BT/PR8470/med/29/726/2013; and NIH-DBT Human Immunology Project Consortium grant no. AI090023. G. Medigeshi is supported by the Wellcome Trust-DBT India Alliance Intermediate fellowship (no. IA/S/14/1/501291). S. Kumar is supported by the DBT/Wellcome Trust India Alliance Early Career Fellowship grant no. IA/E/18/1/504307. The authors thank N. Khanna (International Centre for Genetic Engineering and Biotechnology (ICGEB)) for discussions, W. M. Orenstein (Emory Vaccine Center) for critical review of the manuscript, and S. Singh and A. Singh (ICGEB) for technical support.

Author information

These authors contributed equally: Charu Aggarwal, Hasan Ahmed.

Deceased: Mohit Singla

These authors jointly supervised this work: Rafi Ahmed, Rakesh Lodha, Anita Shet, Anmol Chandele, Kaja Murali-Krishna.

Authors and Affiliations

ICGEB Emory Vaccine Center, International Centre for Genetic Engineering and Biotechnology, New Delhi, India

Charu Aggarwal, Pragati Sharma, Elluri Seetharami Reddy, Kaustuv Nayak, Deepti Maheshwari, Yadya M. Chawla, Harekrushna Panda, Ramesh Chandra Rai, Sivaram Gunisetty, Priya Bhatnagar, Prabhat Singh, Manpreet Kaur, Kritika Dixit, Sanjeev Kumar, Kamal Gottimukkala, Keshav Saini, Prashant Bajpai, Gopinathan Pillai Sreekanth, Anmol Chandele & Kaja Murali-Krishna

Department of Biology, Emory University, Atlanta, GA, USA

Hasan Ahmed & Rustom Antia

Kusuma School of Biological Sciences, Indian Institute of Technology, New Delhi, India

Elluri Seetharami Reddy

Division of Pediatric Pulmonology and Intensive Care, Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, India

Mohit Singla, Sushil Kumar Kabra & Rakesh Lodha

Department of Pediatrics, Division of Infectious Disease, Emory University School of Medicine, Atlanta, GA, USA

Sivaram Gunisetty, Lalita Priyamvada, Siddhartha Kumar Bhaumik, Jens Wrammert & Kaja Murali-Krishna

Division of Infectious Diseases, St. John’s Research Institute, St. John’s National Academy of Health Sciences, Bengaluru, India

Syed Fazil Ahamed, Rosario Vivek & Anita Shet

The University of Trans-Disciplinary Health Sciences & Technology, Bengaluru, India

Rosario Vivek

TERI school of advanced studies, New Delhi, India

Priya Bhatnagar

Department of Clinical Virology, Christian Medical College, Vellore, India

Shobha Mammen, Anand Rajan & Asha Mary Abraham

Pediatric Infectious Diseases, Department of Pediatrics, Christian Medical College, Vellore, India

Valsan Philip Verghese

Department of Molecular Virology, National Institute of Virology, Pune, India

Paresh Shah & Kalichamy Alagarasu

Rollins School of Public Health, Emory University, Atlanta, GA, USA

Shenzhen Research Institute of Big Data, School of Data Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China

Emory Vaccine Center, Emory University School of Medicine, Atlanta, GA, USA

Carl W. Davis, Aftab Ansari, Rafi Ahmed & Kaja Murali-Krishna

Translational Health Science and Technology Institute, NCR Biotech Science Cluster, Faridabad, India

Guruprasad R. Medigeshi

Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA

International Vaccine Access Centre, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

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Contributions

M.S., S.F.A., R.V., S.M., A.R., V.P.V., A.M.A., S.K.K., R.L. and A.S. carried out patient recruitment and follow-up. C.A., H.A., P. Sharma, H.P., K.N., R.C.R., D.M., S.G., L.P., S.K.B., S.F.A., R.V., E.S.R., Y.M.C., P. Bhatnagar, P. Singh, M.K., K.D., S.K., K.G., K.S., P. Bajpai, G.P.S., P. Shah, A.K., T.Y., C.W.D., R. Antia and G.R.M. performed the experiments, analysis and interpretation. J.W., A.A., A.M.A., S.K.K., R. Ahmed, R.L., A.S., A.C. and K.M-K. were involved in study design, analysis and interpretation. C.A., H.A., R. Ahmed, R.L., A.S., A.C. and K.M-K. prepared the paper.

Corresponding authors

Correspondence to Rafi Ahmed , Rakesh Lodha , Anita Shet , Anmol Chandele or Kaja Murali-Krishna .

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Extended data

Extended data fig. 1 similar frequency of severe disease in primary versus secondary cases that were distinguished using stringent igm/igg ratios..

Pie charts show the frequency of Severe Dengue (SD), Dengue with warning signs (DW) and Dengue infection without warning signs (DI) cases in primary versus secondary dengue infections that were distinguished using more stringent IgM/IgG ratios indicated on left. The number of patients in each group is indicated below the pie chart. For all three classification methods, the proportion of severe disease was not significantly different between primary and secondary cases (p > 0.78, two-sided Fisher’s exact test). The 95% confidence interval for the percentages indicated in the pie charts are as below: IgM/IgG >1.32, primary: DI- 5.4-11.6, DW-53.4-64.4, SD-27.9-38.5, Secondary: DI- 6.7-13.1, DW-52.8-63.6, SD-27.4-37.6; IgM/IgG >1.4: primary: DI- 5.7-12.1, DW-52.2-63.5, SD-28.5-39.3, secondary: DI- 6.4-12.6, DW-53.8-64.4, SD-26.9-36.9; IgM/IgG >1.78: primary: DI- 5.8-13.0, DW-50.5-62.9, SD-28.7-40.6 and secondary: DI- 6.3-12.0, DW-54.8-64.6, SD-27.0-36.3 (Wilson CI).

Source data

Extended data fig. 2 frequency of severe disease in primary versus secondary dengue infections using who 1997 and who 2009 disease classification..

Data from a subset of the patients from the AIIMS Delhi site where disease severity was classified using both WHO 2009 and WHO 1997 criteria. a , Data shown by WHO 1997 disease classification. Pie charts show the frequency of the cases with dengue shock syndrome (DSS), dengue hemorrhagic fever (DHF); or dengue fever (DF) among a subset of dengue confirmed children that are recruited from AIIMS site among all cases (n = 171), primary dengue cases (n = 66) and secondary dengue cases (n = 105). DSS case frequency is not significantly different between the primary and secondary dengue infections, (p = 0.106, two-sided Fisher’s exact test). b , Data shown by WHO 2009 disease classification among the same group of the patients from panel a. Pie charts show the frequency of the cases with severe dengue (SD), dengue with warning signs (DW); or dengue infection without warning signs (DI) among all cases, primary dengue cases or secondary dengue cases. Severe dengue case frequency was not significantly different between the primary and secondary dengue infections, (p = 0.344, two-sided Fisher’s exact test).

Extended Data Fig. 3 Dengue specific responses in infants (≤1-year-old).

a , Scatter plot shows dengue specific IgM and IgG index values by capture Elisa (Panbio) for dengue confirmed infants (n = 34). p values were calculated using two-sided Mann-Whitney U tests b , Neutralizing antibody titers to the indicated infecting virus serotype in dengue confirmed infants where the infecting serotype was determined (n = 26). c . Scatter plots show dengue specific IgM index values by Panbio Capture ELISA among the infants with different grades of disease severity. Severe dengue (SD, n = 22); Dengue with warning signs (DW, n = 12). Note that there are no Dengue infection without warning signs (DI) cases since all the hospitalized infants were either SD or DW cases. p values (p = 0.087) were calculated using two-sided Mann-Whitney U tests. Non-significant p values (>0.05) are indicated as n.s. d . Scatter plots show neutralizing activity against the indicated infecting dengue virus serotypes among the infants with different grades of disease severity. Severe dengue (SD, n = 15); Dengue with warning signs (DW, n = 11). Note that there are no DI cases since all of the hospitalized infants were either SD or DW cases. p values (p > 0.999) were calculated using two- sided Mann-Whitney U tests. Non-significant p values (>0.05) are indicated as n.s.

Extended Data Fig. 4 Neutralization responses were below detection or significantly lower for infecting serotype in the primary dengue cases compared to secondary dengue cases.

Neutralizing antibody titers against the infecting virus serotype in primary (n = 38) and secondary (n = 50) from a subset of the patients from 2b, where the infecting serotype was identified. p values were calculated using Mann-Whitney U test.

Supplementary information

Supplementary information.

Individual-level data for age, sex and clinical disease classification.

Reporting Summary

Supplementary data.

Source data for individual-level data in the Supplementary Information.

Source Data Fig. 1

Similar frequency of severe disease in pediatric patients with primary versus secondary dengue infections.

Source Data Fig. 2

Comparison of neutralizing antibody responses between cases with primary and secondary dengue infection.

Source Data Extended Data Fig. 1

Similar frequency of severe disease in primary versus secondary cases that were distinguished using stringent IgM/IgG ratios.

Source Data Extended Data Fig. 2

Frequency of severe disease in primary versus secondary dengue infections using WHO 1997 and WHO 2009 disease classification.

Source Data Extended Data Fig. 3

Dengue specific responses in infants (≤1 year old).

Source Data Extended Data Fig. 4

Neutralization responses were below detection or significantly lower for infecting serotype in the primary dengue cases compared to secondary dengue cases.

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Aggarwal, C., Ahmed, H., Sharma, P. et al. Severe disease during both primary and secondary dengue virus infections in pediatric populations. Nat Med 30 , 670–674 (2024). https://doi.org/10.1038/s41591-024-02798-x

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• Published: 20 September 2021

A study on knowledge, attitudes and practices regarding dengue fever, its prevention and management among dengue patients presenting to a tertiary care hospital in Sri Lanka

• K. P. Jayawickreme   ORCID: orcid.org/0000-0001-9503-2854 1 ,
• D. K. Jayaweera 1 ,
• S. Weerasinghe 1 ,
• D. Warapitiya 1 &
• S. Subasinghe 1  

BMC Infectious Diseases volume  21 , Article number:  981 ( 2021 ) Cite this article

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The World Health Organization (WHO) has ranked dengue as one of the top ten threats to Global health in 2019. Sri Lanka faced a massive dengue epidemic in 2017, the largest outbreak in the country during the last three decades, consisting of 186,101 reported cases, and over 320 deaths. The epidemic was controlled by intense measures taken by the health sector. However, the reported dengue cases and dengue deaths in 2019 were significantly higher than that of 2018. Deaths were mostly due to delay in hospitalization of severe dengue patients. The mortality of dengue hemorrhagic fever is 2–5% if detected early and treated promptly, but is high as 20% if left untreated.

A descriptive cross-sectional study was done among patients with dengue fever presenting to the Sri Jayawardenepura General Hospital during October 2019. Data was collected using a questionnaire comprising 20 questions based on knowledge, attitudes and practices on dengue, which were categorized into questions on awareness of mortality and severity of dengue burden, prevention of dengue vector mosquito breeding and acquiring the infection, patient’s role in dengue management, and warning signs requiring prompt hospitalization.

The mean KAP score on all questions was 55%, while a majority of 65.2% patients scored moderate KAP scores (50–75%) on all questions, and only 7.6% had high KAP scores (> 75%). The highest categorical mean score of 62% was on awareness of dengue prevention, followed by 54% on awareness of dengue burden, and only 51% on dengue management. Only 5.3% patients scored high scores on awareness of dengue management, followed by 28.5%, and 40.9% patients scoring high scores on awareness of dengue burden, and awareness of prevention of dengue respectively. The mean KAP scores on all questions increased with increasing age category.

The population relatively has a better awareness of dengue prevention, as compared to awareness of dengue mortality and dengue management. The identified weak point is patient awareness of the patients’ role in dengue management, and identifying warning signs requiring prompt hospitalization. This results in delay in treatment, which is a major cause for increased mortality. There was a correlation between those who had good knowledge on dengue burden and those who were aware of patients’ role in dengue management. An action plan should be implemented to improve public awareness through education programs on the role of the public and patients in dengue management to drive a better outcome.

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The World Health Organization (WHO) has ranked dengue as one of the top ten threats to Global health in 2019 [ 1 ]. Brady et al. estimates a 3.9 billion prevalence of people, accounting to 40%-50% of the world’s population being at risk of infection. 128 countries worldwide are at risk of dengue infection, of which 70% of the global burden being in Asia [ 2 , 3 ]. The reported dengue cases to WHO increased from < 0.5 million in 2000 to > 3.34 million in 2016, characterized by a worldwide outbreak [ 4 ]. Although the world-wide numbers declined in 2017, there was a significant rise again in 2019 with 4.3 million cases worldwide. The highest number of dengue cases worldwide in 2019 in descending order were reported in Brazil, Philippines, Vietnam, Mexico, Nicaragua, Malaysia and India respectively, with Sri Lanka being placed in the 8th place worldwide, and in the 5th place in Asia [ 5 ]. Following a steady rise in annual dengue cases, Sri Lanka faced a massive dengue epidemic in 2017, which was the largest outbreak in the country during the last three decades, consisting of 186,101 reported cases, and over 320 deaths. The epidemic was controlled by intense measures taken by the health sector. However, the reported dengue cases rose again in 2019 reaching 102,746, being twice the number of reported cases of 51,659 in 2018, indicating re-emergence of an outbreak in 2019. A majority of cases being in the western province, with 20% in the Colombo district [ 6 ]. The dengue deaths in 2019 were 90; higher than the total dengue deaths in 2018 being 58, albeit with reduced mortality rate per overall cases [ 6 , 7 ]. The mortality of dengue fever is < 1%, and that of dengue hemorrhagic fever is 2–5% if detected early and treated promptly, but is high as 20% if dengue hemorrhagic fever is left untreated [ 8 ].

Dengue virus is a flavivirus transmitted by mosquito vectors, such as Aedes aegypti and Aedes albopictus. Dengue fever was first serologically confirmed in Sri Lanka in 1962 [ 9 ]. All four serotypes of dengue virus, DENV-1 to DENV-4 have been circulating in the country, and each serotype has many genotypes [ 9 ]. The most common cause for occurrence of new epidemics is the shift of the circulating serotype and genotype of the dengue virus, which is predisposed by increased foreign travel introducing new strains [ 9 ]. The dengue outbreak in 2003 was predominantly due to DENV-3 and DENV-4. The outbreaks in 2006, 2009 and 2010 was predominantly due to DENV-1 [ 9 ]. The predominant serotype in the 2017 epidemic was DENV-2 which was infrequent since 2009 [ 10 ]. The outbreak in 2019 was predominantly due to previously latent serotype DENV-3 [ 11 ].

The WHO published and implemented a “Global Strategy for Dengue Prevention And Control” targeting the years from 2012 to 2020, with the goals of improving dengue mortality, and morbidity by the year 2020, and estimating the true disease burden. The main elements of the global strategy were diagnosis and case management, integrated surveillance and outbreak preparedness, sustainable vector control, future vaccine implementation, basic operational and implementation research [ 12 ].This global strategy follows 10 priority areas for planning dengue emergency response, adapted from Rigau-Pérez and Clark in 2005, which also includes Engaging the community and relevant professional groups about dengue control as well as their participation in dengue prevention and control [ 13 ].

A recent study in Malaysia, showed that the population had only an average knowledge, and poor attitudes and practices on dengue prevention. They identified that a significant percentage had erroneous beliefs, such as fogging being the mainstay of dengue vector control. It had led them to a false sense of security, while evading actual measures that should be taken. They also identified that a proportion of people believed they had no responsibility in preventing dengue breeding, which needed urgent attention. They highlighted that it was impossible to reduce dengue prevalence without community participation, and concluded that measures were urgently required to educate the public to change their attitudes. The Communications for behavioral changes program on dengue prevention were subsequently implemented by Health departments of Malaysia to improve dengue awareness and prevention [ 14 ].

Although there had been a few studies on public awareness on dengue prevention, there was limited evidence focused on public awareness on their role in dengue prevention and management. It is therefore very important to take active measures to reduce the incidence and mortality of dengue, for which the responsibility lies not only with health professionals, but also with the general public. The purpose of this study is to identify the level of awareness in patients on preventing and managing dengue infection, and awareness of the patient’s role and responsibility in the above. Our goals were to identify areas in dengue control and management that need improvement, to implement policies that raise patient participation to deliver a better outcome of dengue infection, its complications and its management.

Study design

This is a descriptive cross-sectional study assessing the knowledge, attitudes, and practices on dengue fever, its prevention and the patient’s role in management, among the dengue patients presenting to a tertiary care hospital in Sri Lanka during the month of October 2019.

Study setting

The study was done among a random sample of 132 patients with dengue fever or dengue hemorrhagic fever who were admitted to adult medical wards for treatment at the Sri Jayawardenepura General Hospital during October 2019. These patients comprised people from draining areas of the western province of Sri Lanka.

Sample size

The number of patients who presented to the Sri Jayawardenepura General hospital in the month of October 2019 was 200. A sample size of 132 was calculated with a confidence interval of 95%, to match the population to assess a statistically significant result.

Participants

The study population was randomly selected among adult patients older than 13 years of age admitted with dengue infection to the medical wards of the Sri Jayawardenepura General Hospital during the month of October 2019.

Participants were not selected from the same family who would likely to be influenced by similar knowledge, to avoid bias of pseudo-replication.

Data collection

Data collection was commenced after obtaining the approval from the institutional Ethical Review committee of the Sri Jayawardenepura General Hospital and Postgraduate Training Centre (SJGH/20/ERC/017). Data was collected using a self-administered validated questionnaire regarding Knowledge, Attitudes, and Practices (KAP) on dengue in languages English, Sinhala, and Tamil which were translated and extensively reviewed for validation (Additional file 1 : Appendix S1, Additional file 2 : Appendix S2, Additional file 3 : Appendix S3).

Data was collected from randomly selected participants, only after informed written consent was obtained. The questionnaires were filled by the participants themselves using the validated questionnaire of the language convenient to them. The study investigators were with them while filling the questionnaire in case the participants needed to clarify any questions in order to ensure quality. The data was collected anonymously, while strict confidentiality of the responses and the results was maintained.

The questionnaire consisted of 20 questions which, comprised 5 questions on knowledge, 6 questions on attitudes, and 9 questions on practices on dengue fever and haemorrhagic fever, its prevention and patient’s role in management. Prior to analysis they were then re-categorized into questions on awareness of:

mortality and severity of dengue burden—5 questions

prevention of dengue vector mosquito breeding and acquiring the infection—5 questions

patient’s role in dengue management, and warning signs requiring prompt hospitalization—10 questions

The responses to each question was analyzed with percentage estimated of correct responses. The total marks scored by each participant to the whole questionnaire was estimated as a percentage, which has been defined as the “KAP score”. KAP score is an abbreviation used for the total score of the questions based on K nowledge, A ttitudes, and P ractices regarding dengue burden, dengue prevention and management in this study. The total results were categorized as “low” when KAP were < 50%, “moderate” when KAP scores were 50–75%, and “high” when KAP scores were > 75%.

Statistical methods

Data was analyzed using the SPSS (Statistical Package for the Social Sciences) software. All the questionnaire sheets were filled completely and none of the sheets were excluded. The mean of the KAP score of each category was calculated. The percentage of the population who scored low, moderate and high KAP scores was calculated separately. The responses to each of the 20 questions were analyzed separately to infer the areas which needed further improvement in awareness of the general public on dengue.

The study population comprised 61% males, and 39% females with a male: female ratio of 3:2. When categorizing by age, 42% of the study population was less than 30 years old, 36% were between 30 and 50 years old, and 22% were more than 50 years old. Of those who were between 30 and 50 years, 35% were graduates or diploma holders. Of those who were more than 50 years old, 21% were graduates or diploma holders. When categorizing by level of education, 10% of the population was currently schooling, 8% were adults educated up to less than ordinary level (O/L) at school who were not graduates or diploma holders, 18% were adults educated up to O/L at school who were not graduates or diploma holders, 34% were adults educated up to advanced level (A/L) at school who were not graduates or diploma holders, 24% were adults who had completed school education and were undergraduates, 6% were adults who had completed school education and were graduates or diploma holders (Table 1 ).

The mean KAP score of the sample population from the questionnaire was 55.04%. When categorizing the KAP scores as low (< 50%), moderate (50–75%), and high (> 75%), a majority of 65.2% of the population had moderate KAP scores. 27.3% had low KAP scores, and only 7.6% had high KAP scores (Fig. 1 ).

Percentage of the study population who scored under each KAP score level Category. When categorizing the KAP scores as low (< 50%), moderate (50–75%), and high (> 75%) scores, a majority of 65.2% of the population had moderate KAP scores. 27.3% had low KAP scores, and only 7.6% had high KAP scores

The KAP score achieved was higher with increasing age. The highest mean total KAP score of 57.86% was among those > 50 years of age, with those aged < 30 years having a mean KAP score of 53.48% and those aged 30–50 years having a mean KAP score of 55.21% (Fig. 2 ). The mean KAP score on awareness of dengue mortality and burden among the age categories < 30 years, 30–50 years, and > 50 years was 49.29, 56.88, and 58.57% respectively. The mean KAP score on awareness on prevention of dengue vector breeding and acquiring the infection among the age categories < 30 years, 30–50 years, and > 50 years was 63.57, 59.38, and 63.57% respectively. The mean KAP score on awareness of patients’ role in dengue management and warning signs requiring prompt hospital admission among the age categories < 30 years, 30–50 years, and > 50 years was 49.82, 52.08, and 51.79% respectively (Fig. 3 ).

The mean KAP score of each age category. The KAP score achieved was higher with increasing age. The highest mean KAP score of 57.86% was among those > 50 years of age, with those aged < 30 years having a mean KAP score of 53.48% and those aged 30–50 years having a mean KAP score of 55.21%

Comparison of the total KAP score, awareness on mortality and severity ofdengue burden, awareness on prevention of dengue vector breeding and acquiring the infection, and awareness on patient’s role in dengue management, and warning signs requiring prompt hospitalization under each age category

The mean KAP score was higher among those with higher educational qualification levels. The highest mean KAP score of 58.13% was among graduates and professional diploma holders of any field, and the lowest score of 49% was among adults educated in school up to below O/L. The mean total KAP score among those currently schooling was 54.62%. Adults who were not undergraduates, graduates, or diploma holders, who were out of school, but were educated at school up to O/L and those who had completed schooling after A/L had mean total KAP scores of 53.96 and 54.67% respectively. The mean KAP score on awareness of dengue mortality and severity of dengue burden among each of the age categories; schooling, adults educated less than O/L, adults educated up to O/L, adults educated up to A/L, under graduates, graduates or diploma holders were 50.77, 42, 60.83, 50.44, 58.75, and 55% respectively. The mean KAP scores on awareness on prevention of dengue vector breeding and acquiring the infection among each of the educational categories in above order were 60, 60, 60, 64, 60.94, 67.5% respectively. The mean KAP scores on awareness of the patient’s role in dengue management and warning signs requiring prompt hospital admission among each of the educational categories in above order were 53.85, 45, 44.58, 51.56, 55, 55% respectively (Fig. 4 ). The mean KAP score among females was 55.48%. and that of males was 54.75%.

Comparison of the total KAP score, awareness on mortality and severity of dengue burden, awareness on prevention of dengue vector breeding and acquiring the infection, and awareness on patient’s role in dengue management, and warning signs requiring prompt hospitalization under each educational category

When analyzing data by categorizing the questions by the awareness on the area assessed, the highest mean KAP score of 62.05% was on questions on awareness of prevention of dengue vector breeding and acquiring the infection, while the lowest mean KAP score of 51.06% was on questions on awareness of patient’s role in dengue management, and warning signs requiring prompt hospitalization. The mean KAP score on awareness of dengue mortality and severity of burden was 54.02% (Fig. 5 ). On analysis of questions related to awareness of dengue mortality and severity of burden, only 28.8% had high KAP scores, 40.9% had low KAP scores, and 30.3% had moderate KAP scores. On the analysis of questions related to awareness on dengue prevention, an equal percentage of 40.9% had low and high KAP scores respectively, and 18.2% had moderate KAP scores. Analysis of questions related to awareness on patient’s role in dengue management and warning signs prompting hospitalization showed, only 5.3% had high KAP scores, 62.9% had moderate KAP scores, and 31.8% had low KAP scores (Fig. 6 ).

Mean KAP score of each area assessed. 1. Mean KAP score on awareness of mortality and severity of dengue burden- 54%. 2. Mean KAP score on awareness of prevention of dengue breeding and acquiring the infection—62%. 3. Mean KAP score on awareness of patient’s role in dengue management, and warning signs requiring prompt hospitalization—51%

Comparison of percentage of the population who scored low (< 50%), moderate (50%-75%), and high (> 75%) KAP scores under each area assessed

There is no statistically significant correlation between the mean KAP scores on awareness of dengue mortality and severity of dengue burden, and the mean KAP scores on awareness on prevention of dengue vector breeding and acquiring infection according to the spearman’s test (p = 0.084). Although there is a statistically significant correlation between the mean KAP scores on awareness of dengue mortality and severity of dengue burden, and the mean KAP scores on awareness of patient’s role in dengue management and warning signs requiring prompt hospital admission according to the spearman’s test (p = 0.015).

The populations response to each individual question is shown in Table 2 . The percentage of the population who knew the correct answer for the questions on awareness of dengue burden and mortality were as follows: The number of reported dengue cases in Sri Lanka for the year during the outbreak in 2017 was close to 200,000 (42%), The number of reported dengue cases in the year 2019 is higher than that of 2018 (52%), Of 100 persons who get dengue fever only 1 or less persons would die per year when detected early and proper access to medical care (The mortality of dengue fever is < 1%) (60%), The mortality rate of dengue hemorrhagic fever is 2–5%, but is high as 20% if left untreated (60%), The WHO has ranked dengue as one of the top ten threats to Global health in 2019 (56%).

The percentage of the population who knew the correct answer for the questions on awareness of dengue prevention were as follows: all persons with dengue fever do not need to be notified to the Public Health Inspector (PHI) (39%), dengue vector mosquitoes breed in muddy water (52%), The peak biting times of the dengue mosquito is morning and evening (80%), If a person gets dengue fever once in their life, they will be immune to it and will not get dengue fever again (44%), discarded tires, coconut shells, and plastic containers collecting rain water in the garden should be destroyed to prevent dengue vector breeding (96%).

The percentage of the population who knew the correct answer to the questions on awareness of dengue management and warning signs which require prompt hospitalization were as follows: There is a special drug available to treat dengue fever (43%), papaya leaf juice increases the platelet count and thus helps treat dengue fever (33%), dengue patients with a platelet count < 150,000/mm 3 with a rapid drop are recommended to be admitted to hospital (85%), abdominal pain in a dengue patient is not an indication for hospital admission (32%), all pregnant mothers with dengue fever are recommended to be admitted in hospital irrespective of the platelet count (83%), NS1 antigen can be tested on any day since the onset of fever to diagnose dengue fever (23%), a negative report of dengue IgM antibody done on the second day since onset of fever means the patient does not have dengue fever (17%), When a dengue patient has a platelet count > 150,000/mm3 and does not meet criteria which require hospital admission, they should drink 2500 ml of oral fluids per day at home (40%), When a dengue patient has a platelet count > 150,000/mm3 and does not meet criteria which require hospital admission, they should check their Full blood count daily to assess the drop in platelet count (65%), dengue patients should avoid having red or brown drinks (89%).

Dengue virus has four serotypes. Acquisition of dengue infection due to one serotype does not give immunity against a subsequent infection with another serotype, though there is about a two years period of cross-protection [ 15 ]. All four serotypes share only 60–75% identity at amino acid level, and are thus considered as different viruses [ 14 ]. Infection from one serotype gives life-long immunity against that particular serotype [ 10 , 15 ]. Once the cross protection wanes off, secondary dengue infection is more severe than primary dengue infection [ 10 , 15 ]. However only 44% of the study population were aware that occurrence of dengue infection once, does not prevent occurrence of the disease again.

Dengue transmission increases during the rainy season in Sri Lanka, mostly in July, due to increasing dengue vector mosquito breeding places. Other causes for increase in the number of dengue cases is urbanization, climate change, and poor vector control and prevention of disease [ 10 ]. 96% of our cohort were aware of the need to destroy and clean water collecting areas, to prevent breeding of the dengue vector, while 84% of the cohort of a similar study done in the central province of Sri Lanka was aware of this same fact. This is probably because the latter study was done in 2015, prior to the dengue epidemic in 2017 [ 16 ]. Intense measures were taken in the country by which the epidemic in 2017 was controlled. This included clean-up campaigns, awareness programs, National dengue prevention and control, National Strategic framework (2016–2020) to align their action with the WHO Global strategy for dengue prevention and control (2012–2020), The Presidential Task Force on Dengue (PTF) and National dengue control unit of the Ministry of Health launched a rapid inter-sectoral program for prevention and control of dengue [ 7 ]. Awareness programs were held in rural and urban community gatherings, taught in school and institutions, shared on social media, television and radio [ 7 ]. However, data regarding the targeted population for these awareness programs was sparse. Dengue is ranked the third commonest notifiable disease in Sri Lanka, by which means the health sector can implement active vector control measures in the identified areas [ 17 ]. Only 39% of the study population was aware that all persons with dengue fever should be notified to the PHI. The low number of people who were aware of the importance of notifying dengue cases to the PHI, was probably due to the general public being unaware of the PHI’s role in dengue prevention, and lack of awareness of their responsibility in notifying cases, and it’s importance in vector control. Lack of notification of disease hinders action taken for vector control, which gives a falsely lower number of reported cases than the actual number. People should be educated on this to improve notification and vector control. Notification to the PHI of dengue patients managed at home or in the hospital should be made mandatory to avoid negligence in notification. This study population had a relatively good awareness about dengue breeding sites and biting times, probably due to awareness programs during the 2017 epidemic. Literature has shown the importance of improving knowledge on dengue prevention to control dengue outbreaks [ 18 ].

A study in Vietnam during the dengue epidemic in 2017 showed that 91% of the study population considered dengue to be dangerous to very dangerous [ 19 ]. Our study evaluated patients already being admitted for treatment of dengue at the Sri Jayawardenepura general hospital, comprising of patients from the western province, which has the highest dengue burden in the country. A similar study was done in the central province of Sri Lanka by Jayalath et al . among out patients visiting the Peradeniya hospital for reasons other than dengue. Jayalath et al. showed that 95% of their study population knew dengue was a severe disease [ 16 ]. 75% of the cohort of a similar study done among patients being admitted for treatment of dengue fever, in the northern province of Sri Lanka in 2017, knew that dengue was a severe disease [ 20 ]. Our study population had a moderate mean KAP score (54%) on questions on awareness on dengue severity and burden. 40.9% of the population had low awareness on severity and burden of dengue, and only 28.8% had high awareness on its severity and burden. This difference in evidence regarding awareness of severity of dengue in the above studies, could be because the questions by which awareness was evaluated was different in the three studies, and because our study, and the study in the northern province evaluated patients who had already acquired dengue fever and were admitted for treatment at that time. It could also be speculated that these populations acquired dengue infection due to their lack of awareness in prevention of disease.

This lack of awareness on the severity of dengue and it’s burden is probably due to most dengue patients uneventfully recovering from uncomplicated dengue fever, and due to successful dengue management by the healthcare system in the country. This study identified that those who had good awareness on the mortality and severity of the burden of dengue, also had a good awareness about their role in managing dengue, as well as warning signs requiring prompt hospital admission. It can be concluded that there is a strong correlation between those who have an appreciation of the gravity of the symptoms caused by dengue, and the likelihood of them educating themselves on dengue management and their active participation in it. Rozita et al. showed that people who were infected by dengue, or had a family member infected by the disease had better knowledge, attitudes and practices about dengue compared to those who did not [ 21 ]. A study in Singapore in 2017 after the country’s largest dengue epidemic showed that attitudes and practices regarding dengue among primary care physicians significantly improved after experiencing the epidemic [ 22 ]. Chanthalay S et al . showed that those who had better knowledge and attitudes regarding dengue are more likely to take precautions to prevent the disease [ 23 ]. Those who have good awareness will have a good understanding of the gravity and impact of the disease, will know the importance of preventing it, and will be aware of necessary preventive measures.

The mortality of dengue fever is < 1%, and that of dengue hemorrhagic fever is 2–5% if detected early and treated promptly, but is high as 20% if dengue hemorrhagic fever is left untreated [ 8 ]. In 2015 Malhi et al. reported that the presence of comorbidities like diabetes mellitus, hypertension, chronic kidney disease, allergies, asthma, ischemic heart disease and hepatic anomalies, as well as delay in identification and treatment were linked to increased mortality from dengue [ 24 ]. However, in 2017 a study by the same authors showed that 50% of dengue deaths were of previously healthy individuals with no comorbidities [ 25 ]. Therefore, the leading cause for dengue related complications and deaths is delayed identification and treatment of disease. This can be due to delays by the patient or health staff, mostly due to delayed patient presentation to the hospital [ 26 ].Studies have shown that late presentation of dengue fever to the hospital leads to increased development of dengue haemorrhagic fever, dengue shock syndrome, multi-organ involvement like acute kidney injury, and increased mortality [ 26 , 27 , 28 ]. According to the study findings, by identifying areas where the public has misconceptions and misunderstandings about dengue fever, its prevention and management, we can implement steps to improve those loop holes. By following correct practices, avoiding malpractices, and timely hospital admission, his will reduce dengue fatality, improve the outcome, and will also reduce the burden on the healthcare system.

The national Guidelines on dengue management indicates the need for hospital admission in a dengue patient if the platelet count is < 100,000, or platelet count between 100,000- 150,000 with a rapid drop in platelets, fever for three days with any warning signs such as abdominal pain, persistent vomiting, mucosal bleeding, lethargy and restlessness [ 29 ]. Irrespective of the above criteria, admission is required in dengue patients who are pregnant, elderly, obese, with comorbidities, or with adverse social circumstances [ 29 ]. In this study, 85 and 83% patients respectively were aware of the indication for admission as per the platelet count or if pregnant, but only 32% patients knew admission was indicated with warning signs like abdominal pain. Therefore, people need to be educated about warning signs of severe dengue infection. People who do not require admission must be educated about cautious self-management at home until they require admission [ 29 ]. By doing so there will be less likelihood to miss warning signs, will have improved outcome, and there will be less burden to hospital staff. Only 40% of patients knew about fluid management at home, but 89% knew to avoid red drinks.

Serological testing is important to confirm the diagnosis of dengue fever when the presentation is atypical or when unsure of the diagnosis. NS1 antigen is tested in the patient’s blood on the first few days of the disease and has a sensitivity of 60–90%. Dengue IgM antibody will be positive in the patient’s blood only after the 5th day of illness [ 29 ]. Therefore, patients should be educated about the ideal time to do each test to avoid false negatives being reported by doing the test at the wrong time of the illness. However, dengue infection cannot be excluded by a negative serological lab report. Few patients knew about the timing of testing, with only 23% and 17% being aware of the timing of testing, and sensitivity of NS1 antigen and dengue IgM respectively. It is important that health care professionals guide patients on the correct timing to do the serological tests. It would be prudent to do such serological tests only on request by a physician, to avoid patients testing at the wrong time, and getting a report which cannot be interpreted at that time of the illness. False negatives of serological testing can further be avoided by laboratory staff rechecking the patients’ day of the illness, and the physicians request form prior to drawing blood.

This study shows that people had misconceptions about dengue management. Only 43% knew there was no special drug to treat dengue fever. There is no particular drug to treat dengue, but is managed by careful monitoring and fluid tailoring resuscitation [ 29 ]. A tetravalent live attenuated dengue vaccine has been registered for use in several countries [ 15 ]. In sero-negative individuals it is believed that the vaccine mimics a silent natural infection, giving temporary cross-protection against all serotypes, and subsequently causing severe dengue infection when primarily infected [ 15 ]. However, its efficacy varies in different countries and is not currently recommended for use in Sri Lanka [ 15 ]. The use of papaya leaf juice in dengue management had recently gained interest, leading to many people consuming the juice assuming improvement of dengue infection. Research has shown papaya leaf juice to improve platelet counts, but has not shown to prevent or reduce fluid leaking in dengue hemorrhagic fever [ 30 ]. This can adversely cause early rise in platelet count masking the onset of fluid leaking, which can be detrimental in managing dengue hemorrhagic fever. 33% of our cohort believed papaya leaf juice helped treat dengue fever, while 13.4% of the cohort in a study done in Sri Lanka in 2015 believed the same to be true. This is probably because the concept of the effect of papaya leaf juice on platelet count came in to light only later on [ 16 ].

This study demonstrated an increasing trend in awareness on all categories, such as among people with a higher level of education, and maturity by age, indicating that education and maturity are important factors for improved awareness. Kumanan et al. showed a significant association between educational level and knowledge regarding dengue fever, and no significant association between educational level and preventive practices [ 20 ]. The trend in our study demonstrated on Fig. 3 suggests that responses in the awareness on dengue mortality and severity of dengue burden steadily increased with age, and strongly influence the mean total KAP scores. The highest awareness in all age categories was on dengue prevention and the lowest awareness in all categories was on patients’ role in dengue management and warning signs requiring prompt hospitalization (Fig. 3 ).

There was inadequate awareness among adults who dropped out of school prior to completion of the full school education up to advanced level even when they are older. This may demonstrate a population with lower level of understanding of the information given, and those who were not regularly educated at school regarding dengue infection as they dropped out. Those who drop out of school are also those who usually have a poor social background, and they may also have inadequate access to social media and electronic media to receive updates about dengue mortality, prevention and management. This highlights the need for any information to reach the people of all social backgrounds when implementing strategies to improve public awareness on dengue infection. Dissemination of information should be done in various ways targeting different populations of different levels of understanding. People with lower education levels should be the main target group requiring more advice and education regarding the patient’s role in dengue management.

This population has a relatively a better awareness on dengue prevention as compared to awareness of dengue mortality and dengue management. This is possibly due to prior media education of the public on prevention during the previous epidemic in 2017. The identified weak point is patient awareness on the patient’s role in dengue management, as well as identifying warning signs requiring prompt hospitalization. It causes delay in treatment, which is a major cause for increased mortality. The trend demonstrated on Fig. 5 suggests that responses in the dengue management and warning signs prompt hospitalization area strongly influence the total KAP scores. This indicates that patient awareness on the role of the public and patients on dengue management is critical in the outcome of dengue infection. An action plan should be implemented targeting improving public awareness by education programs on the role of the public and patients in dengue management, to improve outcome.

The general public play a major role in prevention and management of dengue fever, and influence the outcome. Jayalath et al. showed that 30% of their population believed the responsibility of dengue prevention lay with the public, while 66% believed both the public and the government were responsible [ 16 ]. In order to improve involvement of patients and the public in dengue prevention, control and management, attention should be paid on educating the public and patients on the disease.

Limitations and recommendations for future research

This study focused on 132 patients from one hospital. Therefore, the conclusions can be relevant only to draining areas in the vicinity of this hospital, and may not represent the knowledge, attitudes and practices in other parts of Sri Lanka. However, since majority of the dengue cases in the country are concentrated in the western province, of which a significant number of patients present to the Sri Jayawardenepura General Hospital, the findings of this study may represent the most dengue dense area in the country. Large scale future research from all parts of the country may be beneficial to infer the knowledge, attitudes, and practices of the country as whole.

The general public was educated about Dengue infection by various means, including messages on social media, electronic media, awareness programs at schools, and village meetings, posters and distribution of leaflets, during the dengue epidemic in 2017. This study did not extensively evaluate whether the study participants had been exposed to these prior teaching about Dengue infection, and if they did, by what means they were educated. However almost all the study participants had access to electronic and social media. This may not be the same when inferring on the population in some rural parts of Sri Lanka who may not have similar access to such media education. Awareness programs and active participation of the general public in dengue prevention and management should be implemented. We suggest future follow up research of the awareness on dengue infection among the public, before and after implementing formal dengue awareness strategies to assess the effectiveness of it. In addition to follow up research before and after implementing disease awareness steps, we also suggest future research to assess an association and comparison of dengue mortality and outcome before and after implementing practices to further educate the public, in order to identify its impact on dengue management and outcome.

The population has relatively a better awareness on dengue prevention, as compared to awareness of dengue mortality and dengue management. The identified weak point is patient awareness on the patient’s role in dengue management, and identifying warning signs requiring prompt hospitalization causing delay in treatment, which is a major cause for increased mortality. There was a correlation between those who had good knowledge on dengue burden and those who were aware of the patients’ role in dengue management. There is also an increasing trend in awareness on all categories, especially among people with a higher level of education, and maturity by age, indicating that education and maturity are important factors for improved awareness. An action plan should be implemented targeting improving public awareness on the role of the public and patients in dengue management to improve outcome.

Availability of data and materials

The raw data sets analyzed during the current study are available on reasonable request from the corresponding author.

Abbreviations

Dengue virus

Knowledge attitudes and practices

Ordinary level at school

Advanced level at school

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Acknowledgements

We all express our gratitude to all participants who consented to take part in this study.

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SS is a Consultant Physician [MBBS, MD, FRACP] Medical unit, Sri Jayawardenepura General Hospital. KPJ [MBBS], DKJ [MBBS] and DW [MBBS] are Registrars in Internal medicine, and SW is a Senior Registrar in Medicine at the Sri Jayawardenepura General Hospital.

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Data collection was done by KPJ, DKJ and DW. Analysis, interpretation of data, literature review and writing of the report was done by KPJ. SS and SW guided the study and corrected the final manuscript. All authors read and approved the final manuscript.

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Questionnaire in English.

Additional file 2: Appendix S2.

Questionnaire in Sinhala.

Additional file 3: Appendix S3.

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Jayawickreme, K.P., Jayaweera, D.K., Weerasinghe, S. et al. A study on knowledge, attitudes and practices regarding dengue fever, its prevention and management among dengue patients presenting to a tertiary care hospital in Sri Lanka. BMC Infect Dis 21 , 981 (2021). https://doi.org/10.1186/s12879-021-06685-5

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A new lineage nomenclature to aid genomic surveillance of dengue virus

Contributed equally to this work with: Verity Hill, Sara Cleemput, James Siqueira Pereira, Wim Dumon, Alex Ranieri Jerônimo Lima, Tulio de Oliveira, Nathan D. Grubaugh

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* E-mail: [email protected] (VH); [email protected] (ARJL); [email protected] (NDG)

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Affiliation Centro para Vigilância Viral e Avaliação Sorológica (CeVIVAS), Instituto Butantan, São Paulo, Brazil

Affiliations MRC-University of Glasgow Centre for Virus Research, Bearsden, Glasgow, United Kingdom, Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa

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Affiliation Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam

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Affiliation Arboviruses and Haemorrhagic Fever Viruses Unit, Virology Department, Institut Pasteur de Dakar, Dakar, Senegal

Affiliation Centro Estadual de Vigilância em Saúde da Secretaria de Saúde do Estado do Rio Grande do Sul (CDCT/CEVS/SES-RS), Rio Grande do Sul, Brazil

Affiliations Departamento de Entomologia, Instituto Aggeu Magalhães (IAM)-Fundação Oswaldo Cruz-FIOCRUZ, Recife, Brazil, Department of Arbovirology, Bernhard Nocht Institute for Tropical Medicine, WHO Collaborating Center for Arbovirus and Hemorrhagic Fever Reference, Hamburg, Germany, National Reference Center for Tropical Infectious Diseases. Bernhard, Hamburg, Germany

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Affiliations Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa, Department of Applied Sciences, Mbeya University of Science and Technology (MUST), Mbeya, Tanzania

Affiliations Department of Sciences and Technologies for Sustainable Development and One Health, Universita Campus Bio-Medico di Roma, Roma, Italy, Instituto René Rachou, Fundação Oswaldo Cruz, Minas Gerais, Brazil, Climate Amplified Diseases and Epidemics (CLIMADE), Minas Gerais, Brazil

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Affiliation Department of Preclinical Sciences, The University of the West Indies, St. Augustine Campus, St. Augustine, Trinidad and Tobago

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Affiliations Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa, KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa, Department of Global Health, University of Washington, Seattle, Washington, United States of America

•  [ ... ],

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Affiliations Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America, Yale Institute for Global Health, Yale University, New Haven, Connecticut, United States of America, Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America

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• Verity Hill, 
• Sara Cleemput, 
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• Robert J. Gifford, 
• Vagner Fonseca, 
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• Anderson F. Brito, 
• Gabriela Ribeiro, 
• Vinicius Carius de Souza, 

Published: September 16, 2024

• https://doi.org/10.1371/journal.pbio.3002834
• Reader Comments

This is an uncorrected proof.

Dengue virus (DENV) is currently causing epidemics of unprecedented scope in endemic settings and expanding to new geographical areas. It is therefore critical to track this virus using genomic surveillance. However, the complex patterns of viral genomic diversity make it challenging to use the existing genotype classification system. Here, we propose adding 2 sub-genotypic levels of virus classification, named major and minor lineages. These lineages have high thresholds for phylogenetic distance and clade size, rendering them stable between phylogenetic studies. We present an assignment tool to show that the proposed lineages are useful for regional, national, and subnational discussions of relevant DENV diversity. Moreover, the proposed lineages are robust to classification using partial genome sequences. We provide a standardized neutral descriptor of DENV diversity with which we can identify and track lineages of potential epidemiological and/or clinical importance. Information about our lineage system, including methods to assign lineages to sequence data and propose new lineages, can be found at: dengue-lineages.org .

Citation: Hill V, Cleemput S, Pereira JS, Gifford RJ, Fonseca V, Tegally H, et al. (2024) A new lineage nomenclature to aid genomic surveillance of dengue virus. PLoS Biol 22(9): e3002834. https://doi.org/10.1371/journal.pbio.3002834

Copyright: © 2024 Hill et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This publication was made possible by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (NIH) under Award Number DP2AI176740 (NDG), CTSA Grant Number UL1 TR001863 from the National Center for Advancing Translational Science (NCATS), a component of the NIH (CBFV), NIH Award Number 1 U01 AI151807-01 (KAH), Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS/FIOCRUZ 13/2022 – REDE SAÚDE-RS, grant process 23/2551-0000510-7 and FAPERGS 14/2022 - ARD/ARC, grant process 23/2551-0000852-1), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) through their productivity research fellowships (307209/2023-7; GLW), European Union’s Horizon 2020 research and innovation programme under grant agreement No 101000570, funding from philanthropist Mr. Narayana Murthy (17X6777), the Medical Research Council-São Paulo Research Foundation (FAPESP) CADDE partnership award (MR/S0195/1 and FAPESP 18/14389-0), Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grant process 21/11944-6 and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) through PhD scholarship (88887.969077/2024-00; JSP). The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SC and WD are affiliated with emweb. NDG is a paid consultant for BioNTech.

Abbreviations: AGA, Advanced Genome Aligner; BLAST, Basic Local Alignment Search Tool; DENV, dengue virus; EPA, Evolutionary Placement Algorithm; MLCA, maximum likelihood clade assignment; UTR, untranslated region

Introduction

Dengue virus (DENV: Flaviviridae ; Orthoflavivirus ) inflicts the heaviest global burden on public health of any mosquito-borne virus, causing more than 100 million infections per year [ 1 ]. Dengue incidence is increasing worldwide, with major outbreaks across endemic regions in the tropics in 2023 [ 2 ], and sustained local transmission in non-endemic regions such as the state of Florida in the United States [ 3 ] and Italy [ 4 , 5 ]. As DENV continues to spread, tracking the evolution at a high resolution is key to understanding its transmission patterns on local, regional, and global scales.

Dengue virus in its human-endemic cycle consists of 4 serotypes (DENV-1-4) that likely correspond to at least 4 successful spillover events from its ancestral sylvatic cycle ( Box 1 . Glossary) that took place several centuries ago [ 6 ]. Each serotype includes several genotypes that were designated in the late 1990s and early 2000s based on partial genetic sequences [ 7 , 8 ]. In addition, DENV-2 and DENV-4 include genotypes encompassing viruses from the sylvatic cycle. These serotypes and genotypes have provided the basis for decades of work characterizing the natural history, phenotypic diversity, and transmission dynamics of DENV. However, with recent large increases in global sequencing capacity and its integration into public health systems, additional granularity of DENV diversity is required. Several previous studies have already classified sub-genotypic diversity on a country or regional level (e.g., [ 9 – 11 ], but there is a need to standardize this discussion between research groups and countries to aid communication and facilitate identification of common patterns. The continued evolution and spread of DENV has led to the emergence of distinct evolutionary lineages within recognized genotypes. Further, with the implementation of interventions (e.g., vaccines, Wolbachia -infected mosquitoes to suppress DENV transmission) that may eventually select for specific viral lineages, it is imperative to have a precise and common language to monitor continued DENV transmission in different spatiotemporal scales, and that this is communicable to clinicians and public health officials who may not have a background in genomics.

Box 1. Glossary

Amplicon drop-outs.

The situation (during a gene amplification technique) when an amplicon, i.e., a segment of genetic material that undergoes amplification in the process of “amplicon sequencing,” is not amplified. The region of the genome covered by that amplicon therefore is not sequenced and is displayed as a series of “N”s in the consensus genome.

Antigenic distance

Difference between 2 antigens, i.e., the part of a pathogen or otherwise that the immune system responds to, therefore, a proxy of the difference in immune response to 2 pathogens.

Autochthonous transmission

Local transmission of a pathogen, i.e., not a travel-derived case.

The genetic make-up of an organism. Here, it is the second level of dengue virus classification based on their nucleotide sequence. There are multiple per each serotype, denoted by Roman numerals.

An insertion or deletion of a nucleotide base.

A clade in a phylogenetic tree that contains all of the descendants of a common ancestor, and none that are not descendants.

Recombination

Exchange of genetic material between 2 organisms or virus particles, leading to a genome which has mixed ancestry.

A way of grouping microorganisms, such as bacteria or viruses, based on molecules found on their surfaces. In this article, it is the highest level of dengue virus classification, based on their surface antigens. There are 4 dengue virus serotypes: DENV-1, DENV-2, DENV-3, and DENV-4.

Subdivision of a clade, which is an arbitrary grouping of branches on a phylogeny.

Substitution

A mutation where one nucleotide base is replaced by a different one.

Sylvatic cycle

Viral transmission between nonhuman primates and mosquitoes living in trees.

Here, we propose a system for the classification and nomenclature of DENV lineages that builds on existing serotype and genotype (see Box 1 ) classifications to (1) provide additional temporal and spatial granularity; and (2) standardize the discussion of important diversity globally. We take inspiration from the design of the pango nomenclature system, a hierarchical lineage system set up to track SARS-CoV-2 evolution [ 12 ], as well as lessons learned from its design and implementation. It also borrows from older systems, such as the H5 influenza nomenclature [ 13 ]. We discuss the design, validation, and application of our proposed DENV lineage system, show how it enhances resolution when monitoring circulating lineages, and introduce tools enabling end-users to assign lineages to their own sequences. By making the system compatible with existing classifications and showcasing its utility, we aim to achieve widespread uptake and introduce a truly standardized global language with which to discuss DENV genetic diversity.

Previously defined genotypes provide useful but not sufficient resolution

DENV is currently classified into 4 serotypes, which in turn include varying numbers of genotypes: 5 for DENV-1, 6 for DENV-2, 5 for DENV-3, and 4 for DENV-4 ( Fig 1 ). Genotype classification systems were originally based on greater than 6% pairwise genetic distance within the genotype, using a 240 nucleotide sequence (i.e., a single amplicon) of the envelope (E)/nonstructural protein 1 (NS1) protein coding region, as this arbitrary threshold split then-known DENV-1 diversity into manageable groups [ 7 ]. As more sequence data was generated, these were replaced by systems based on entire protein-coding regions, especially E, with which many of the current genotypes were designated 20 to 30 years ago [ 14 – 16 ]. Maintenance of this system is through continued usage, and there is no official body which regulates genotype designation.

This serotype/genotype nomenclature system still holds well with newer whole genome sequences, with some geographic distinction between continents. For example, within DENV-1 we found that the Americas are dominated by genotype V, whereas Asia and Oceania have more sequences of genotype I ( Fig 1A ). Further, much of the existing research uses genotypes to characterize circulating variants [ 17 ], ensure adequate genomic diversity for sequencing panels [ 18 , 19 ], identify new introductions leading to outbreaks [ 20 ], explore differences in viral fitness, and disease association [ 21 ]. However, there has been a huge increase in publicly available sequence data, both in terms of the number and the region from which samples are being sequenced, since these genotype classification systems were established. This has led to a similarly large increase in the known genetic diversity within each serotype. In particular, there are now groups of genomes that do not reliably fall into genotypes: 6.41% of DENV-1 sequences, 12.8% of DENV-2, 2.14% of DENV-3, and 9.75% of DENV-4 sequences are related to defined genotypes, but cluster basally to them (designated as “related” by Genome Detective Dengue Virus Typing tool [ 22 , 23 ]; Fig 1 ). A smaller number of genomes in each serotype do not fall into any currently defined genotype and are designated as “Unassigned” (0.60% DENV-1, 0.25% DENV-2, 0.14% DENV-3, and 0.10% DENV-4). This increase in the known genetic diversity of circulating lineages also leads to complexities on the sub-genotypic level, as some genotypes are now very large and highly diverse—5 out of 17 genotypes contain more than 1,000 whole genome sequences. Of particular note, DENV-1 genotype I contains 3,293 published sequences, which is more than 3 times the size of the entire DENV-4 whole genome data set that we used here ( n = 995). The large number of genomes in many of these genotypes, combined with increased air travel and the expanded range of the mosquito vectors [ 24 , 25 ], lead us to conclude that genotypes alone do not provide sufficient resolution for many epidemiological questions ( Fig 1 ). For example, the current genotype assignment does not provide additional epidemiological information compared to the serotype for DENV-1, DENV-2, and DENV-3 in the Americas, as they are dominated overwhelmingly by a single genotype for each serotype. Indeed, many previous studies in this region have already named sublineages within genotypes (e.g., lineage classification systems in Brazil and Nicaragua [ 9 , 26 – 29 ]). Therefore, while genotypes provide an important base for research, there is clearly a need for an updated classification system to include newly recognized global diversity and provide additional sub-genotype resolution in a systematic and standardized way.

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Maximum likelihood phylogenetic trees scaled by genetic distance for each DENV serotype: (A) DENV-1, (B) DENV-2, (C) DENV-3, and (D) DENV-4. Trees are colored by the current genotype classification obtained using the Genome Detective Dengue Virus Typing Tool [ 22 , 23 ]. Bar charts indicate the frequency of whole genomes sampled in each continent assigned to each existing genotype, and numbers at the end of each bar indicate the number of sequences in each data set. Note that every serotype has a dominant genotype across the Americas (i.e., North America, Caribbean, and South America). “Related” refers to sequences that are not reliably placed into the clade as there is considerable bootstrap support for the clade without the query as well as with the query. We note that there are no whole genomes in this data set (see Methods) which are assigned DENV-1III, only to its related genotype.

https://doi.org/10.1371/journal.pbio.3002834.g001

New lineage classification system design

To better describe the circulating diversity of DENV, we propose a new system that builds on the existing serotype/genotype system discussed above ( Fig 2 ). First, we updated the genotype definitions so that fewer genomes are unassigned or ambiguously classified as “related.” Then, we added 2 additional layers of resolution within the genotypes, major and minor lineages, with associated nomenclature.

We found that many DENV sequences fall basal to the genotype-defining nodes, meaning that they do not fit cleanly within the current classification system and are thus classified as “related” to a genotype ( Fig 1 ). We identified 16 categories of “related” genotypes within our global DENV genomic data set. We therefore moved the genotype-defining node closer to the root of the tree so that they were included in the main definition of the genotype. We did not remove any of the already defined genotypes, including a newly proposed DENV-1 genotype V [ 30 ]. We also propose a new genotype, named DENV-1 VII, for a clade containing 27 sequences primarily from the Democratic Republic of the Congo. Even after our adjustments, some unassigned sequences remain (2 sequences for each serotype, DENV-1 = 0.037%, DENV-2 = 0.051%, DENV-3 = 0.095%, DENV-4 = 0.20%), but these are mostly basal to other defined genotypes or singleton outliers. For DENV-1, DENV-2, and DENV-4, the sequences are sylvatic sequences from Malaysia, Borneo, and Australia. For DENV-3, these sequences are older (1953 and 1963) from Puerto Rico. These updated genotype definitions also still fit the original arbitrary definition of less than 6% pairwise genetic distance within a genotype, even across the whole genome. It is of note, however, that the pairwise distance within genotypes is highly variable ( S1A Fig ), and this variation is not related to the number of sequences within a genotype ( S1B Fig ).

Genotype-level classification has been expanded to include most previously unassigned genomes. Two additional layers of classification have been proposed, major and minor lineages, the rules of which are shown here. The nomenclature is described here in its shorthand form (e.g., DENV-3III_C.2), with each element highlighted by a dotted box. The new lineage classifications for serotypes 1, 2, and 4 are shown in S2 Fig .

https://doi.org/10.1371/journal.pbio.3002834.g002

We propose that Roman numerals are consistently used to refer to genotypes, thereby removing the current geography-based names for DENV-2 genotypes. We are motivated by 2 key reasons: (1) some of these genotypes are now very widespread and are not limited to the region that the name implies; and (2) geographical names can lead to discrimination, especially when they cause large outbreaks, and as such are against best practices for naming pathogens [ 31 ]. We use the standard Roman numerals for these genotypes instead, and the comparison between the systems can be found in S1 Table .

The new genotype definitions that we propose succeed in reducing the number of unassigned DENV sequences. Large geographical spaces, however, are still dominated by single genotypes within a serotype. Therefore, we propose 2 additional levels of classification: major and minor lineages (Figs 2 and S2 ). Major lineages, designated using letters of the Roman alphabet, are designed to help answer regional scale questions. Minor lineages, designated using numbers and full-stops, provide more fine-scale resolution, and therefore have a nomenclature more similar to SARS-CoV-2 pango lineages [ 12 ]. Importantly, like the existing genotypes, this lineage nomenclature system is evolutionarily neutral—i.e., they are designated based entirely on phylogenetic metrics and not on any possible phenotypic differences. This provides an a priori system for naming clades, thereby providing a framework to identify possible phenotypic changes when they arise. For example, the sudden growth of a single clade, which may indicate a change in transmissibility or immune evasion, may be more easily identified when many sequences are rapidly assigned to a lineage that is named consistently throughout the world. We also note that lineage definitions are based on the nodes of the phylogeny, rather than the tips.

Major and minor lineages are strictly hierarchical. We use the same defining rules for both levels of at least (1) 15 sequences (arbitrary cutoff); (2) 25 inferred nucleotide substitutions (across the whole genome) along the ancestral branch (arbitrary); and (3) one sister lineage at the same level—in other words, there cannot be an A lineage without a B lineage ( S3 Fig ). The first 2 rules aim to capture epidemiologically important lineages, which are stable between iterations of phylogenetic inference. The high phylogenetic distance is possible due to the high genomic diversity of DENV, and builds on experience in the pre-variant era of SARS-CoV-2. Due to its low global genetic diversity, SARS-CoV-2 lineages were defined on a single evolutionary event (i.e., a substitution, an indel, or a recombination event, see Box 1 [ 12 ]) and so would sometimes break monophyly (see Box 1 ) when new trees were inferred, causing issues with communication. Our thresholds are also high to avoid high levels of nesting in the names of the lineages at this stage, also a lesson learned from SARS-CoV-2 lineage system designs. The final rule on compulsory sister lineages is to ensure that each designation level provides new information that is usable for public health—i.e., not simply the same lineage circulating in the same area year after year, but a distinguishable clade that differentiates it from other geographical areas. Some manual curation was also performed on this initial designation step (see Methods); specifically, that moved some nodes closer to the present to break up some very large major lineages. To ensure that most sequences since 2,000 were in a major lineage in case of continued circulation, we also artificially added some additional lineages with more generous thresholds (10 substitutions and 5 sequences) to avoid the system being out of date at the start of its implementation. We do not anticipate needing to do this in future lineage releases as we will be designating major lineages prospectively, obviating the same very large unbroken diversity observed with retrospective designation.

Combining our updates to the genotype placements and the addition of lineages, sequences can be discussed using a formal longhand and a simpler shorthand nomenclature. For example, “Dengue virus serotype 3, genotype III, lineage C.2” can be abbreviated as “DENV-3III_C.2” (read as: “dengue three-three-C-dot-two”; Fig 2 ). New sublineages of DENV-3III_C.2 would be given names DENV-3III_C.2.1 and DENV-3III_C.2.2 and so on.

Applications of the new lineage system

After designing a new lineage classification system and applying it to the global DENV genomic data set, we evaluated its utility for addressing real-world public health questions. We specifically tested the lineage system based on its 2 key design principles: (1) to increase resolution with which to discuss genetic diversity; and (2) to standardize the discussion.

We first examined whether splitting the phylogenetic trees of each DENV serotype beyond genotypes led to increased temporal and spatial resolution. While some continents are now dominated by a single major lineage (e.g., DENV-3 and DENV-4 in South America), most continents have at least 2 major lineages designated for each serotype ( Fig 3 ). For example, almost all DENV-1 whole genome sequences in the Americas in this data set are genotype V, but we can now split the genotype V viruses circulating in this region into 7 major lineages ( Fig 3 ).

Each serotype’s new genotype (first column) and major lineage (second column). Genetic distance trees are colored by genotype or major lineage, and bar charts show the percentage of whole genome sequences in each continent by classification level. Note that major lineages break down genotypic diversity further and provide additional resolution and a continent level. Numbers by each bar represent the number of sequences in each continent by serotype.

https://doi.org/10.1371/journal.pbio.3002834.g003

To further explore this apparent increased resolution, we mapped the sampling location of every sequence in each level of lineage designation to identify whether geographic scope also narrows as classification level decreases. While some minor lineages are relatively widespread, we find several examples of increased geographic resolution with increased phylogenetic nesting ( Fig 4A ). For example, DENV-2 genotype II, also known as the Cosmopolitan genotype, has been identified in all regions where DENV circulates. When we assign sequences from this genotype to major lineages, the major lineage DENV-2II_A sampling locations occur only in the eastern hemisphere. When further exploring the minor lineages, 2II_A.2.1 and 2II_A.2.2 have been detected in south and east Asia, only 2II_A.2.2 has been detected in Africa, specifically Kenya ( Fig 4A ). In this scenario, if a related DENV was sequenced in East Africa, the minor lineage assignment would immediately provide clues about whether it was a potential new introduction from Asia to Africa (i.e., 2II_A.2.1) or whether it may have arisen autochthonously (see Box 1 ) within the region (i.e., 2II_A.2.2). In comparison, under the existing system, the hypothetical new lineage would simply be assigned to DENV-2 genotype II, which is one of the most diverse and widespread genotypes of DENV and little additional information would be gleaned without conducting phylogenetic analysis. We also show how the major lineages of DENV-1 genotype V, which dominates DENV-1 transmission in the Americas ( Fig 1 ), provide additional geographic resolution in this region ( Fig 4B ). For example, DENV-1V_B is sampled in Nicaragua, the US, Mexico, Venezuela, and Guatemala; whereas DENV-1V_E is dominated by sequences sampled in Brazil. Notably, DENV-1V_G is only found in Colombia and Trinidad and Tobago, 1V_H in Brazil, and 1V_J in the US. These major lineages therefore provide information on different patterns of circulation of DENV-1 in the Americas.

(A) Each map shows the number of sequences in the data set in each country classified as, respectively, DENV serotype 2 genotype II, serotype 2 genotype II major lineage A, and then 2 minor lineages of A.2.1 and A.2.2. The color represents the number of genome sequences from blue to purple running from low to high. (B) Map shows the distribution of the whole of DENV-1 genotype V and all of its constituent major lineages in the Americas. Major lineage 1V_A also has sequences from India, 1V_B and 1V_E have some from France, and 1V_D and 1V_D have some from Italy, although these are not shown here in the interests of space. Color represents the number of genome sequences. Base map layer downloaded from the Global Administrative Database ( https://gadm.org/download_world.html ).

https://doi.org/10.1371/journal.pbio.3002834.g004

In the absence of a global lineage classification system, individual research groups have labeled lineages using their own nomenclature systems to aid research and surveillance efforts. Although changing names can be challenging, it is important to have a standardized nomenclature system to aid discussion between different regions. This makes it easier to rapidly identify which lineages are the same in different countries and therefore which are spreading internationally, possibly indicating a relevant phenotypic property. For example, there has been a new introduction of DENV-3 genotype III from Asia into the Caribbean, which has since spread across the Americas and has been reintroduced into Asia and Africa [ 3 , 5 , 32 , 33 ]. This lineage spread may be connected to the large DENV-3 outbreaks in 2023 in the region, and so there is a risk of different research groups naming this lineage separately (e.g., “DENV-3 GIII-American-II lineage”) making it harder to detect the wider pattern of spread and phylogenetic relatedness. In the new system, this introduction has been designated a minor lineage 3III_B.3.2 ( S4A Fig ) and is distinct from another older Caribbean introduction, designated 3III_B.3.1 [ 34 ].

Further, our system has equivalents to many of the existing sublineages individually defined by other research groups. For example, 4 lineages of DENV-3 genotype III have been described in Brazil [ 10 ]. BR-I and BR-II fall into DENV-3III_C.2, and while the single sequence in BR-III is not in our data set as it is only an E sequence, its closest whole genome relative (GenBank accession: FJ898462) is also in 3III_C.2. Some sequences in BR-I are also assigned a sublineage, DENV-3III_C.2.2. The single sequence representing BR-IV is assigned to 3III_C.1. While three of the named Brazil lineages fall into the same major lineage in our system, it still provides a separation from the newly introduced 3III_B.3 lineage of the same genotype that we describe above ( S4A Fig ). Similarly, in DENV-2 genotype III, there are lineages in Brazil defined as BR1-4 [ 11 , 27 , 29 ]. In our system, BR1 is DENV2-2III_B, BR2 does not get assigned to a major lineage because it does not meet the size threshold required and so it remains part of the larger 2III, BR3 is DENV-2III_C, and BR4 is 2III_C.1.1 ( S4B Fig ). We note that only BR4 in DENV-2 is a 1:1 match with our lineage system and thus there may still be reason for research groups to use finer resolution of lineage classification for their specific needs. Our goal is not to restrict these activities, rather to argue for the use of common classifications for external communications. To aid this effort, we included lineage assignments for every whole genome sequence in our data set ( S2 Table ).

While we deliberately do not take phenotypic differences into account in the designation of lineages, it is important that they are captured by the neutral designation process. For example, in a study of DENV-2 in Nicaragua, the authors describe 3 sublineages which underwent lineage turnover from NI-1 to NI-2A and then to NI-2B [ 9 ]. They also describe an apparent increase in relative fitness of NI-2B compared to NI-1. We compared these lineages to our standardized nomenclature and found that NI-1 corresponds mostly to DENV-2III_D.1.3 (and some to 2III_D.1), NI-2A to 2III_D.1, and NI-2B to 2III_D.1.1 ( S4B Fig ). We therefore capture the lineage replacement and the apparent phenotypic difference between NI-1 and NI-2B (going from 2III_D.1.3/2III_D.1 to 2III_D.1.1). Further, 2III_D.1.1 (NI-2B), while mostly sampled in Nicaragua, has a subclade (see Box 1 ) which was sampled in Cuba and Costa Rica from 2019 to 2022 (circled in S4B Fig ), highlighting the importance of a standardized naming system between countries. A more recent paper [ 28 ] also described NI-3 sublineages, which correspond to 2III_D.1.2 in our system.

In order to explore potential phenotypic differences between lineages in a more systematic way, we used antigenic distance data (see Box 1 ) generated from different serotypes and genotypes in Thailand over a 20-year period [ 35 ]. We began by comparing within-classification pairwise antigenic distances by serotype ( S5A Fig ) and found that while there was a slight decrease between serotype, genotype, and major lineage, it was not significant or consistent. Indeed, DENV-1 had a gradual decrease in antigenic distance across all 3 levels, DENV-2 only decreased at the major lineage level, DENV-3 mostly decreased at the genotype level, and DENV-4 had no noticeable difference between classification levels. We then mapped the antigenic distances in 3D space ( S5B and S5C Fig ) and found that major lineages did not form distinct clusters. These results, however, may be complicated by not having a broad representation of the global major lineages. Therefore, we may expect to find more noticeable differences in pairwise antigenic distances among the serotype, genotype, and major lineage levels if this antigenic data set also included more diverse viruses (e.g., lineages from the Americas). Our results could also indicate that antigenic distance is more complex than a simple phylogenetically clustered trait. Indeed, the original authors found that antigenic distance varied more over time than between other circulating clades [ 35 ]. Regardless, our lineage system still provides a way to identify distinct lineages that may have an epidemiological advantage, which will be essential for evaluating the impact of antigenic distance on the immune landscape and therefore real-world effectiveness of new dengue vaccines.

By capturing known phenotypic diversity, providing additional geographic resolution, and standardizing discussion of important lineages, the lineage system proposed here builds on the success of the currently used genotypes and provides a necessary tool for monitoring DENV as it continues to spread worldwide.

System stability and assignment validation

After designing this system and showing that it is useful to describe existing genomic diversity and to standardize discussions of DENV evolution at a higher resolution than before, we performed a series of validation checks. A key element of any lineage system is that it is reliable with regards to the sampling structure of the data set and genome coverage. When testing both, we found that the proposed rules generate stable lineages with low coverage genomes and with different subsamples.

It can be challenging to obtain high coverage DENV genomes as viral load tends to decrease rapidly after the short viremic phase that often occurs prior to sample collection [ 42 ]. Further, while capacity for whole genome sequencing is increasing globally, mostly due to the genomic capacity accrued by public health and research institutes during the SARS-CoV-2 pandemic, many groups will preferentially sequence only the E coding region as this is all that is required for genotyping, and it is faster than whole genome sequencing. We therefore simulated low coverage genomes from a subset of the data set ( n = 309) by replacing nucleotides with N’s in runs of 200 to mimic amplicon drop-outs (see Box) at different percentages from 90% to 10% in 10% intervals, then 5% and 1%, and re-assigned them using the Genome Detective typing tool (see Box 2 ). The overall assignment accuracy for serotypes, genotypes, and major and minor lineages was high, even with very low genome coverage ( S6A Fig ). We found major lineage assignments to be 97% accurate at 5% genome coverage, and it drops to 87% accuracy at 1% genome coverage. For minor lineages, assignment accuracy is 93% and 76% at 5% and 1% genome coverage, respectively. Therefore, we recommend using DENV virus genome coverages at 5% and higher for accurate lineage assignment.

Box 2. Lineage assignment tools

The previous sections of this paper discussed the process of lineage designation—the development of a standardized new lineages classification system based on expert opinion. In addition, there is assignation, the process of providing a lineage call to a new sequence, which should be possible to do easily by research groups and public health professionals globally. Here, we provide options for lineage assignment using Genome Detective, GLUE, and NextClade. In the supplementary information, we also provide alignments and phylogenies of representative sequences from each of the lineages so that the reader may also try their own methods.

The Genome Detective Platform [ 23 ] is a microbial bioinformatics software suite that includes a generic framework for phylogenetic subtyping tools, allowing the creation of subtyping tools for any virus species. Currently, Genome Detective includes subtyping tools for 19 virus species, developed with subject matter experts globally [ 22 , 36 – 41 ]. A DENV subtyping tool was first developed in 2019 [ 22 ], and since version 4.0 it was updated to use the lineage designation scheme introduced in this work ( https://www.genomedetective.com/app/typingtool/dengue/ , see Methods and S8 – S10 Figs).

The GLUE framework is an open software environment for managing and analyzing virus sequence data [ 42 ]. It facilitates the development of “projects” that contain data and algorithms necessary for conducting comparative genomics investigations of specific viruses. GLUE incorporates a protocol for rapid phylogeny-based genotyping, maximum likelihood clade assignment (MLCA). Given a reference phylogeny and its corresponding alignment, MLCA uses maximum likelihood to efficiently estimate the optimal placement of a query sequence within the phylogeny. This approach has been used to implement subtyping tools for various viruses, including hepatitis C virus, rabies virus, and bluetongue virus [ 42 – 44 ]. A GLUE project focused on DENV (Dengue-GLUE) is available for local installation and incorporates an MLCA-based subtyping procedure utilizing the lineage designation scheme introduced here ( https://github.com/giffordlabcvr/Dengue-GLUE ).

Nextclade is a robust pathogen classification tool designed to assign genome sequences to clades or variants by aligning them with a reference sequence (Aksamentov et al. 2021 ). This tool is available both as a command-line utility and as a web application, making it highly effective for managing large sequence data sets and facilitating integration into bioinformatics protocols related to genomic surveillance. The build for this dengue classification system can be found here: https://clades.nextstrain.org/?dataset-name=community/v-gen-lab/dengue/denv1 , https://clades.nextstrain.org/?dataset-name=community/v-gen-lab/dengue/denv2 , https://clades.nextstrain.org/?dataset-name=community/v-gen-lab/dengue/denv3 , https://clades.nextstrain.org/?dataset-name=community/v-gen-lab/dengue/denv4 .

We further tested the tool and the system by trimming whole genome sequences keeping only the E coding region and again assigned them using Genome Detective. Serotypes, major lineages, and minor lineages were all correctly assigned using E sequences only. Seven out of 309 had incorrect genotype assignments, which were all related to but not a part of DENV2 genotype I. This is therefore an accuracy of 98% for genotypes and 100% for other classification levels using only complete E sequences.

We also tested the impact of sampling artifacts on lineage designation by randomly subsampling the data set 10 times and rebuilding the trees to see if the same monophyletic clades emerged. We found that they generally did ( S6B Fig ), with DENV-1 having the highest mean of different clades (0.01, 95% CI: 0.0 to 0.034), and DENV-2 having no different clades in any of the subsamples. DENV-3 and -4 were in between with 0.004 (95% CI: 0.0 to 0.017) and 0.006 (95% CI: 0.0 to 0.023), respectively.

Each level of classification can therefore be reliably assigned using a freely available, user-friendly tool even with only E sequences and with very low coverage genomes. Our lineage system is also robust to the sampling bias inherent in almost any genomic data set. This system is therefore robust and reliable for real DENV genomic data sets.

Case studies with additional sequencing data

To ensure that this system is applicable to new data at an appropriate resolution, we tested it using data not included in the original designation process. We used whole genome sequences from Vietnam and Brazil to check that the system works in different global regions, and E sequences from Tanzania to ensure that it works with partial genomes.

Sequences from every country were successfully assigned a major lineage, and many also had minor lineages ( S7 Fig ). In Vietnam, there was mostly a single genotype in each of the 4 serotypes that accumulated higher resolution as time went on—this suggests that transmission was driven by continued circulation of the same lineages rather than reintroduction ( Fig 5A–5D ). In the south of Brazil, we found the opposite: lineage frequency dynamics were similar to the rest of the country with a slight lag, suggesting importations from elsewhere in Brazil ( Fig 5E and 5F ). Despite our training data set containing fewer sequences from Africa compared to Asia and the Americas, sequences from Tanzania were successfully assigned. The lineages identified were mostly similar to those found in Asia, especially China. Few minor lineages were assigned, however, suggesting that while major lineages can be successfully assigned with partial sequences, there may be some resolution missing compared to using whole genomes. Full case study reports can be found in the supplementary text. We note that the Brazil and Vietnam sequences have now been included in the designation set, and additional lineages have been designated based on them.

Bar graphs shown for (A) DENV-1, (B) DENV-2, (C) DENV-3, and (D) DENV-4. (E) Time series of whole genome sequences from Rio Grande do Sul, Brazil, by year. (F) Lineage assignments of whole genome sequences from the rest of Brazil in this data set (non-case study sequences from Rio Grande Do Sul have been removed).

https://doi.org/10.1371/journal.pbio.3002834.g005

Limitations and future sustainability

There are limitations to the system we have proposed here. First, there is likely unrecognized diversity due to global inequity in sequencing capacity, especially in Africa ( S11A Fig ). This unrecognized diversity also limits the conclusions we can draw with lineage assignments, as similar circulating lineages in under-sampled regions may not be epidemiologically connected to one other, and may be independent introductions. This is compounded by our decision to use whole genomes to build the system and not explicitly include E coding region sequences, which tend to be older. Our lineages are therefore influenced by the number of whole genome sequences available ( S11B Fig ), and indeed the number of lineages is strongly correlated with the number of sequences on the country level ( p < 0.001, S11C Fig ). We hope that as sequencing capacity continues to build and expand globally, this disparity will decrease, while still being able to define new lineages when new diversity is captured.

On a local level, our system does not always provide enough resolution for specific epidemiological questions—some minor lineages are still relatively widespread. This is due to trying to have fewer lineages at the start of the system implementation to ease discussion, and thereby help with uptake. We also note that the new system is not a 1:1 relationship with existing regionally defined lineages. This is partially because, in some cases, previous lineages were defined based on a single sequence or a small group of sequences, which does not meet our criteria for lineage designation, but may be helpful on a regional level for defining introductions. Therefore, this system does not replace local-level phylogenetic analysis, and simply provides a first, quick pass at describing the diversity in a data set.

Any lineage system must be easy to maintain and have an intrinsic stability, especially as the DENV genomic data set continues to grow. We deliberately chose rules to define lineages which are computer-readable (and indeed initially designated them using custom scripts) to reduce the person-time required to generate new lineages.

We envision 2 main ways that new lineages could be suggested going forward. First, individual research teams can submit a github issue to a public github repository (information at https://dengue-lineages.org/ ) using a standard form. If accepted, these suggestions will be given a “putative” designation and the label claimed until they have been reviewed so that the study can proceed with relevant lineage information. These putative lineages will then be formally incorporated into the nomenclature system during an annual review process. The second method of new lineage designation will be during this annual review, where proposals for previously undesignated diversity would be generated using automated scripts. Alternatively, these proposals could be generated with an automated lineage designation tool such as recently described [ 43 ]. We did not use this tool here because our initial designation required some manual curation and integration into the current serotype/genotype system, but this will not be required in the future and so this tool may be useful. We hope that these 2 methods of lineage proposal balance the need for up-to-date information for those conducting surveillance, without requiring a large amount of effort to maintain.

These new lineage proposals would then be submitted to a designated international committee for decision-making. At this stage, the lineage designation rules and thresholds would also be reviewed. We note in particular the phylogenetic distance threshold, which we selected in the interests of stability and keeping the number of lineages manageable. However, part of the reason these long branches exist is the relative undersampling of DENV in some geographic regions. In an ideal world with more routine DENV sequencing, there would be fewer very long branches in the phylogeny, and we hope this may be the case going forwards. We would not, however, change thresholds for existing lineages so as not to change results of already completed work, or change the defining nodes of existing lineages or genotypes to ensure stability.

Finally, in the interests of usability and fitting better into existing work, we provided assignment tools already used for subtyping DENV and other viruses—Genome Detective, GLUE, and NextClade. We note that our system is open and we are supportive of the development of any other tools to assign sequences to these lineages. We believe this will also help with sustainability, as opposed to designing a new tool specifically for this lineage system which would also require maintenance.

DENV is a globally important virus that causes high levels of morbidity each year. With increasing globalization and climate change, viruses can traverse continents with ease, leading to increased global genetic mixing. As worldwide genomic sequencing capacity increases, genomic epidemiology becomes a more powerful tool for understanding how DENV spreads and causes outbreaks. The recent influx of genomes must be categorized beyond existing genotypes to provide rapid and understandable epidemiological conclusions.

Here, we present a lineage system, drawing inspiration from the design and uses similar systems implemented for SARS-CoV-2 [ 12 ], rabies [ 44 ], and mpox viruses [ 45 ]. We propose major and minor lineages in addition to slightly adjusting the existing genotypes to capture current diversity. We ensure that these lineages are mostly stable despite phylogenetic uncertainty and low coverage genomes by having a high inferred substitution threshold for defining a lineage.

Our system assigns E-only sequences at least to major lineages and in some cases to minor lineages. This is important as many previous studies only include E sequences, and there are still approximately double the number of E sequences as whole genomes on GenBank. We still encourage the sequencing of whole genomes going forward as they contain more genetic information for phylogenetic placement and analyses, as well as requiring a shorter time period of sampling to accurately estimate rates of evolution [ 46 ]. Further, natural selection acts on the whole genome and so losing information on how the nonstructural proteins evolve may hamper efforts to design and monitor the effectiveness of potential antivirals and vaccines. For these reasons, while a lot of important conclusions can and have been obtained with E sequencing, we encourage, where possible, for the whole genome sequencing of DENV.

Our proposed lineage system provides additional resolution for the discussion of potentially important global DENV diversity and provides a conceptual framework that could be extended to incorporate hierarchical lineage classifications for other arboviruses with broadly defined genotypes (e.g., chikungunya and West Nile viruses). As DENV continues to circulate, the volume of genomic data increases, and new interventions are rolled out that may lead to important viral adaptation, this will become an imperative. By creating stable lineages that work well in different dengue-endemic regions, our system has the potential to enhance DENV genomic surveillance and epidemiology across the globe ( https://dengue-lineages.org/ ).

Ethics statement

The Institutional Review Boards (IRB) from the Yale University Human Research Protection Program determined that pathogen genomic sequencing of de-identified remnant diagnostic samples as conducted in this study is not research involving human subjects (Yale IRB Protocol ID: 2000033281).

Data set generation

We downloaded all DENV sequences with more than 70% of the genome covered and a year of collection listed released on GenBank until the 28 July 2023 and released on GISAID between 1 January 2022 and 28 July 2023. We matched sequences between these 2 databases to remove duplicates to create a near-complete publicly available full whole genome data set (DENV-1 = 5,657, DENV-2 = 4,106, DENV-3 = 2,166, DENV-4 = 1,045). We then aligned all of the sequences by serotype using MAFFT v.7.490 [ 47 ] and manually curated it in Geneious v.2022.1.1, including trimming the untranslated regions (UTRs). We removed sequences which were extremely divergent and those with frame-breaking insertions (DENV-1 = 2, DENV-2 = 1, DENV-3 = 1). We later updated this data set with additional GenBank sequences up until the 8 July 2024 to keep it as up to date as possible during the review process.

We then inferred first pass maximum likelihood trees by serotype using IQTree v2.1.4 [ 48 ]. We used the program’s model selector on the smallest data set (DENV-4) to gauge the best nucleotide substitution model to use, and it returned a transition model with empirical base frequencies and a free rate model with 6 categories (TIM +F+R6). We then rooted this tree using a molecular clock assumption in TempEST [ 49 ] and a heuristic residual mean squared model. We used the root-to-tip plot produced by this rooted tree to prune molecular clock outliers, a reliable indicator of quality control issues [ 50 ]. Most of the outliers that we found here were resequencing of commonly used virus stocks.

The final data set sizes used for developing the lineage system were DENV-1 = 6,975, DENV-2 = 5,390, DENV-3 = 2,519, and DENV-4 = 1,215. We assigned each of these sequences to existing genotypes using Genome Detective Dengue Virus Typing tool [ 22 ].

Lineage system design

Our aims in the design of this system were to break up large clades in the genotypes to provide sufficient resolution to capture epidemiologically relevant patterns; but, drawing on our experience from SARS-CoV-2 nomenclature, not to have many fine-scaled lineages which are hard to discuss, and require regular updating.

With the above datasets, we inferred a new maximum likelihood tree for each serotype separately using the TIM+F+R6 nucleotide substitution model as suggested by IQTree’s model finder.

We separated clades using custom preorder tree traversal scripts using the criteria of ( 1 ) 15 sequences; ( 2 ) a branch length of 25 substitutions for major lineages and 20 for minor lineages; and ( 3 ) presence of a sister lineage. Branch length was calculated by multiplying the IQTree divergence length in substitutions by the relevant alignment length. The length and size thresholds were obtained by testing different combinations to obtain an optimal level of resolution where major clades were split up, but no more than 2 sublevels of minor lineages were present. Major and minor lineages were assigned using the same rules and at the same time but were given different nomenclature.

At this point, we performed a second designation step to ensure that as many potentially epidemiologically significant lineages as possible have been captured by at least a major lineage. The aim here was to avoid a situation where a lineage, possibly from a country or region which is undersampled, could cause an outbreak in the near future without having any assignment beyond a genotype. To do so, we found all clusters containing only sequences sampled after 2,000 without a major lineage designation, and designated further major lineages using a more generous threshold of a minimum size of 5 sequences and a minimum branch length of 10 substitutions. Any clusters that did not meet these criteria, even those with sequences after 2,000, were left unassigned, as they would not be very stable between tree building iterations if they did not meet the substitution threshold.

Finally, we performed some manual curation. As the current data set sizes between serotypes vary by a factor of 5, rules which work well for DENV-3 and DENV-4 can lead to a high level of nesting in DENV-1 and DENV-2. For DENV-1, we moved the defining node for 1V_B closer to the present to enable us to maintain the strict hierarchy of the lineages and add up to major lineage G to break up the diversity. We also did this for 1I_A and added up lineages up to K, 1VI_A to add a sister lineage B (this was a lineage generated by the second designation step where sister lineages were not mandatory), 2II_B to add lineages up to G, and 2III_B to add lineages C and D. It is worth noting that for all of the manual changes we made, a lineage never has fewer than 10 substitutions along the branch before it.

All tree visualizations were generated using baltic ( https://github.com/evogytis/baltic ).

Generating representative trees

For the assignment tools, it was necessary to make representative trees and alignments of each of the levels of designation. To do this, we used the phylogenetic distance matrix, calculated using the python package DendroPy [ 51 ], which gives pairwise phylogenetic distance between each pair of sequences. We took 5 sequences with coverage of over 90% which were furthest apart from each other in each of the genotypes, major lineages, and minor lineages.

It was also important to ensure that the most basal sequence of each clade was present; otherwise, other basal sequences may be under-assigned. We did this first by checking if the lineage-defining node had an immediate descendent node which was a tip, and this node was added to the representative data set. If there was not a node which was a tip, the sequence in the lineage with the lowest distance to the root (i.e., fewest SNPs) was included.

Alignments were generated, and trees were obtained by pruning them from the larger trees using jclusterfunk ( https://github.com/snake-flu/jclusterfunk ).

Genome detective

The subtyping tool for genome detective ( https://www.genomedetective.com/app/typingtool/dengue/ ) takes a fasta file or sequences as a text input ( S8 Fig ) and has 2 main steps to assign a lineage to a sequence.

The first step is species identification, which for the DENV subtyping tool is to identify the serotype. Basic Local Alignment Search Tool (BLAST) N and BLASTX are used to identify a maximum of 3 potential hits. For each of these potential hits, we then use the Advanced Genome Aligner (AGA) [ 52 ] to align the query against the reference and compute the overlap and concordance score. Finally, we select the reference with the highest product of overlap and concordance score. If this species corresponds to the species for which the tool was developed, we proceed to the clade identification. In practice, the species identification step will sometimes identify at a taxonomic level deeper than species, if there is a reference sequence in NCBI RefSeq for this deeper level. In particular, for the DENV subtyping tool, this first step will identify the serotype.

Once the serotype has been identified, maximum likelihood phylogenies containing the query sequence and representative sequences for each lineage are constructed to identify the clade that is most likely to contain the query. The most recent dengue subtyping tool uses IQ-TREE 2 for its analysis, a change from previous versions which used PAUP* [ 53 ]. This is because the former is not a pure hill-climbing algorithm and so is less likely to get stuck in a local optimum. Every clade we wish to identify is defined by approximately 5 representative sequences (see above). We compare the bootstrap value of the node containing some or all of the representative sequences and the query, and identify the most likely cluster. Then, we compare the support values for nodes containing only the representative sequences (outer support) against the representative group plus the query (inner support). This allows us to estimate how likely it is that the query sequence falls inside the cluster. If the bootstrap support for the most likely cluster is lower than 50%, or the most likely cluster is the outgroup, the sequence cannot be assigned. If the bootstrap support for the most likely cluster is higher than 50%, but the inner support is not significantly higher than the outer support, the sequence is assigned as “related to, but not part of” the cluster. If the bootstrap support is higher than 50%, and the inner support is significantly higher than the outer support, the sequence is assigned to the most likely cluster.

Hierarchical clade identification is a stepwise process. Once a clade is identified, the process will reiterate to identify the subclade, if any subclades exist. In other words, once the genotype (e.g., 3II) has been identified, the tool will proceed to try assigning the major lineage (e.g., 3II_A), and once this has been assigned, it will continue to the minor lineage (e.g., 3II_A.1), and then to further minor lineages (e.g., 3 II_A.1.2). Unlike previously developed subtyping tools, which could only identify clade and subclade, the current DENV tool can support an arbitrary amount of assignment levels. This is necessary to enable an evolving lineage system particularly useful when deeper levels of minor lineage are possible. Outputs are a live-updating page with lineage assignments ( S9 Fig ), and on clicking the sequence ID, details of the phylogenetic analysis which lead to the lineage assignment ( S10 Fig ).

The GLUE framework is an open software environment for the management and analysis of sequence data [ 42 ]. GLUE implements a protocol for rapid phylogeny-based genotyping called “maximum likelihood clade assignment” (MLCA). The MLCA method uses maximum likelihood (ML) to optimally place a query sequence within a previously generated reference phylogeny, and then classifies the sequence based on its positioning relative to reference sequences. Although MLCA computes a clade assignment for each query sequence individually, it can also be applied to batches of sequences.

The arguments passed to MLCA are (1) the query sequence; (2) a reference phylogeny containing at least 1 reference sequence for each clade category; and (3) the multiple sequence alignment used to construct the phylogeny. The algorithm first uses the MAFFT program [ 49 ] to add the query sequence to the alignment. The extended alignment and the reference phylogeny are then passed as arguments to the RAxML program’s Evolutionary Placement Algorithm (EPA) [ 56 ], which suggests the optimal placement of a query sequence within a fixed reference tree. Finally, the output phylogeny from RAxML is parsed by the GLUE engine, and a classification is assigned based on topological relationships and evolutionary distances relative to reference sequences.

A GLUE project for DENV (Dengue-GLUE) was constructed, and this project was used to implement an MLCA-based genotyping procedure for DENV. We constructed an ML reference phylogeny for each dengue serotype using the reference sequences established in this study. These phylogenies, along with their corresponding clade categories, were then integrated into the Dengue-GLUE framework. When a query sequence is submitted to Dengue-GLUE’s genotyping system, it is initially assigned to a DENV serotype using BLAST [ 54 ]. Subsequently, the sequence is classified via MLCA, based on the reference phylogeny for that particular serotype.

Nextclade assignments are based on the substitutions that define lineages. As this system was not explicitly based on specific substitutions, nucleotide and amino acid substitution calls were performed for all branches of the representative trees using Augur Ancestral and Augur Translate tools, respectively [ 55 ]. The substitutions were relative to a reference sequence for each serotype, downloaded from GenBank: NC_001477.1 (DENV-1), NC_001474.2 (DENV-2), NC_001475.2 (DENV-3), and NC_002640.1 (DENV-4). Substitutions were only called on the polyprotein, and so the ends of the reference sequences were masked.

The identification of substitutions associated with previously classified branches was done manually to ensure accurate substitution association with the developed classification. Unique substitutions were prioritized due to their ability to differentiate clades. However, in the absence of or presence of only a single unique substitution, homoplasies were also considered.

A substitution table, adhering to the standards set by the Augur Clades tool, was generated. The annotated phylogenetic tree was exported using Augur Export v2 and combined with quality parameters, alignment, and reference files for the construction of the Nextclade v3 data set.

Case studies

Clinical specimens from Vietnam were sampled mostly from Southern Vietnam between 2010 and 2023. They were sequenced at the Yale School of Public Health using the recently developed amplicon sequencing DengueSeq protocol [ 19 ]. Libraries were prepared using the Illumina COVIDSeq test (RUO version) with the pan-serotype primer pools, and sequenced on the Illumina NovaSeq 6000 or X Plus (paired-end 150) at the Yale Center for Genome Analysis. Consensus sequences were generated by mapping reads to dengue reference genomes through the DengueSeq bioinformatics pipeline using default settings (minimum frequency threshold of 0.75 and minimum depth of 10 to call consensus).

Methods for generating sequences from Brazil can be found here [ 56 ] and from Tanzania can be found here [ 57 ].

To assign lineages to each of the case study data sets, we used the representative sequences described above. We always split up serotypes for each analysis. We aligned new data with representative sequences using MAFFT v7.490, and then built a maximum likelihood tree using IQTree using the representative tree as a constraints tree and the TIM+F+R6 substitution model, as above. We rooted trees using the same roots as we inferred using the molecular clock assumption as above.

Finally, we annotated the resultant rooted trees using custom scripts to find the lineage-defining nodes. Lineages were assigned to new sequences based on them being descendants of these lineage-defining nodes.

Validation tests

For the completeness analysis, we took a subset of the full data set ( n = 309) evenly sampled from different lineages and serotypes. We replaced bases with Ns in runs of 200 to replicate amplicon drop-outs. We therefore tested genomes which we artificially lowered from 10% to 90% coverage in 10% intervals, and 5% and 1%. We also artificially cropped the whole genome sequences to only the E coding region. We assigned these sequences using the genome detective dengue subtyping tool.

For the stability analysis, we built trees with 10 different subsamples of the data, and assessed whether the same lineages would be designated using the algorithm developed here using the same custom python scripts.

Connecting new lineages to currently used lineages

For DENV-2 lineages from Brazil denoted BR1-4 [ 27 , 29 ] and NI-3 from Nicaragua [ 28 ], we were able to use tip labels on tree figures in the papers to compare to assigned sequences in the new system. For NI-1 and NI-2 lineages, sampled in Nicaragua [ 9 ], we used lineage defining amino acid substitutions (Table 2 in [ 9 ]). We took the sequences from the paper, identified substitutions at the relevant position, and put them in sets based on having the same amino acid substitution in common.

Data availability

All sequences used to design the lineage system are from Genbank and GISAID, accession numbers in S2 Table . Custom scripts and alignments of representative sequences from Genbank can be found on our github ( https://github.com/DENV-lineages/lineages-paper ).

Sequences for the Vietnam case study can be found on Genbank under accession numbers PP269455-PP270050, in bioproject PRJNA1072696. For the case study from Tanzania, sequences were drawn from [ 57 ], and can be found on Genbank under accession numbers OM920035-OM920066 for DENV-3 and OM920075-OM920415 for DENV-1. Sequences for the Brazil case study can be found on GISAID under accession numbers EPI_ISL_17733558 ‐ EPI_ISL_191469691.

Supporting information

S1 table. roman numeral equivalents for geographical names of denv-2 genotypes..

https://doi.org/10.1371/journal.pbio.3002834.s001

S2 Table. Genbank and GISAID accession numbers of sequences used with assignments.

https://doi.org/10.1371/journal.pbio.3002834.s002

S3 Table. Information on each of the major and minor lineages.

https://doi.org/10.1371/journal.pbio.3002834.s003

S4 Table. GISAID acknowledgements table.

https://doi.org/10.1371/journal.pbio.3002834.s004

S1 Fig. Pairwise genetic distance of new genotypes.

(A) Distribution of pairwise genetic distance within each genotype, colored by serotype. (B) Regression of the number of sequences in each genotype compared to the average pairwise genetic distance.

https://doi.org/10.1371/journal.pbio.3002834.s005

S2 Fig. New lineage system for serotypes 1, 2, and 4.

Each row is a serotype and each column, respectively, is new genotype, major lineage and minor lineage. Note that there are many more minor lineages for serotypes 1 and 2, as they have much larger data sets currently compared to serotype 4. Serotype 3 shown in Fig 2 .

https://doi.org/10.1371/journal.pbio.3002834.s006

S3 Fig. Schematic displaying assigning new lineages.

All 4 putative lineages displayed in the top 2 trees are valid lineages as they meet all 3 criteria of branch length, clade size, and having a sister lineage at the same distance from the root in terms of node number. Invalid lineages are shown along the bottom, with the focal putative lineage shown in purple.

https://doi.org/10.1371/journal.pbio.3002834.s007

S4 Fig. Comparison of previously used sublineages to proposed system.

(A) Maximum likelihood tree of DENV-3 genotype III, colored by new lineage designation, with lineages BRI-IV and novel Caribbean introduction indicated. (B) Maximum likelihood tree of DENV-2 genotype III, colored by new lineage designation, with lineages BR1-4 and NI-1 to NI-3 indicated. The circled clade indicates recent circulation of NI-2B/2III_D.1.1, which is suggested to have a transmission advantage [ 9 ], in Cuba and Puerto Rico.

https://doi.org/10.1371/journal.pbio.3002834.s008

S5 Fig. Antigenic distance at different levels of classification.

(A) Distribution of antigenic distance in each level of classification, with serotype in green, genotype in purple and major lineage in yellow. Minor lineage is excluded due to a lack of antigenic data across minor lineages. (B) 3D map of sequences in antigenic space by serotype, colored by genotype. (C) 3D map of sequences in antigenic space by serotype, colored by major lineage

https://doi.org/10.1371/journal.pbio.3002834.s009

S6 Fig. Validation.

(A) Average correctness of genome detective assignments at different classification levels using artificially downsampled sequences across 5 replicates. Each line corresponds to a different classification level. Error bar is not visible. (B) Assessment of clade stability compared to different subsamples of the sequence data set.

https://doi.org/10.1371/journal.pbio.3002834.s010

S7 Fig. Phylogenies of lineage assignments for case studies.

(A) DENV-1-4 whole genome sequences from Vietnam, time series 2010–2023. (B) DENV-1 and DENV-2 whole genome sequences from Brazil, time series from 2015–2023. (C) DENV-1 and DENV-3 E sequences from Tanzania.

https://doi.org/10.1371/journal.pbio.3002834.s011

S8 Fig. Genome Detective dengue subtyping tool starting page.

The user can either upload a fasta file, or manually add sequences in the text field.

https://doi.org/10.1371/journal.pbio.3002834.s012

S9 Fig. Genome Detective dengue subtyping tool results overview.

The results overview shows a short summary of the different assignments.

https://doi.org/10.1371/journal.pbio.3002834.s013

S10 Fig. Genome Detective dengue subtyping tool phylogenetic analysis details.

An example of the analysis details for a major lineage.

https://doi.org/10.1371/journal.pbio.3002834.s014

S11 Fig. Sampling distribution of DENV whole genome sequences.

(A) Sampling location of whole genome sequences by country. (B) Number of lineages sampled in each country. (C) Linear regression of the number of whole genome sequences against the number of lineages in each country ( p < 0.001). Base map layer downloaded from the Global Administrative Database ( https://gadm.org/download_world.html ).

https://doi.org/10.1371/journal.pbio.3002834.s015

S12 Fig. Case study 1: Temporal dengue virus lineage distributions from Vietnam.

Number of dengue virus whole genome sequences mostly from Ho Chi Minh City, Vietnam assigned to each lineage over time for (A) DENV-1, (B) DENV-2, (C) DENV-3, and (D) DENV-4.

https://doi.org/10.1371/journal.pbio.3002834.s016

S13 Fig. Case study 2: Temporal dengue virus lineage distributions from Brazil.

(A) Time series of whole genome sequences from Rio Grande do Sul, Brazil by year. (B) Lineage assignments of whole genome sequences from the rest of Brazil in this dataset (non-case study sequences from Rio Grande Do Sul have been removed).

https://doi.org/10.1371/journal.pbio.3002834.s017

S14 Fig. Case study 3: Geographical dengue virus lineage distributions assigned to sequences from Tanzania.

(A) Major lineage 1III_A which all DENV-1 sequences in these data sets are assigned to. (B) Major lineage 3III_B which all DENV-3 sequences are assigned to. All maps include all sublineages of each lineage, and colors show the number of whole genome sequences in the training dataset which are in each country or territory. Base map layer downloaded from the Global Administrative Database ( https://gadm.org/download_world.html ).

https://doi.org/10.1371/journal.pbio.3002834.s018

Acknowledgments

We thank all the groups over the years that have made their data available on Genbank and GISAID, without which projects like this would not be possible. An acknowledgements table for GISAID sequences can be found in S4 Table . We thank the participants of Pan-American Dengue Conference 2023, members of the American Committee on Arthropod-Borne Viruses and Zoonotic Viruses (ACAV) at the American Society of Tropical Medicine and Hygiene (ASTMH) meeting 2023, and participants of the Pan American Health Organization arboviral genomic surveillance meeting in Puerto Rico 2024 for their feedback on this system. We also thank Dr Gilberto Santiago, Dr Maria Kelly, and Dr Jorge Munoz for their feedback. We thank Dr Angkana Huang, Dr Lin Wan, Dr Henrik Salje, and Dr Derek Cummings for their help with the antigenic data analysis.

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September 17, 2024

Mosquitoes use infrared detection to help find people

At a glance.

• Aedes aegypti , a type of mosquito that spreads diseases such as dengue and Zika, can sense infrared radiation to help locate and bite people.
• This ability relies on specific proteins found in the tip of mosquito antennae, providing potential new targets for bite prevention.

Mosquitos have a fine-tuned ability to find and bite people. This includes Aedes aegypti , which can transmit viruses that cause deadly diseases such as dengue, yellow fever, and Zika.

Female mosquitoes use a range of cues to hunt us for our blood, including odor molecules from our skin and carbon dioxide released when we breathe. But these can disperse through air and be affected by wind. Up close, Ae. aegypti can also sense body heat transferred through air. But they must be very close—within four inches—of a person to perceive this.

Scientists have thought that the ability to detect thermal infrared radiation (IR) which can be detected at greater distances, might help mosquitoes home in on people. IR, sometimes called infrared light, is released by heat sources and is outside the range human eyes can detect. Previous research had suggested that mosquitoes can’t detect IR, either. However, such studies only looked at IR in isolation, not combined with other cues that mosquitoes use to find their prey.

In a new study, researchers led by Dr. Craig Montell from the University of California, Santa Barbara, tested whether IR emanating from skin could play a role in helping mosquitoes home in on people. The team built a special testing chamber that allowed them to manipulate the levels of odor, heat, and carbon dioxide. They enabled it to block conductive and convective heat to make sure mosquitoes were sensing thermal IR to orient towards their prey.

When female mosquitoes land, they start probing around to find a vein for a blood meal. The team also designed a computer program to identify this host-seeking behavior from collected videos. Results were published on August 21, 2024, in Nature .

As observed previously, IR alone did not draw Ae. aegypti to a surface and trigger host-seeking behavior. However, adding IR to human odor and carbon dioxide doubled the number of mosquitoes drawn to a surface to start probing.

Since Ae. aegypti prefer to bite people around dawn and dusk, the researchers looked at whether sensitivity to IR changed with shifts in environmental temperature. They found that mosquitoes were more attracted to thermal IR from a source at skin temperature when the environmental temperature was lower than that of human skin. When the environment heated up to match the temperature of human skin, as it would in midday, the mosquitoes lost their ability to sense thermal IR.

The team also found that mosquitoes could sense IR while in flight at a distance of more than two and a half feet away.

To better understand how Ae. aegypti senses IR, the researchers used imaging and genetic manipulation to examine mosquito antennae. They found that a heat-activated protein called TRPA1, found in neurons at the tips of antennae, was necessary for IR sensing. At lower intensities of thermal IR, such as when a target is further away, TRPA1 received help from two proteins called opsins. Opsins are specialized proteins that are used to detect light. At the end of the antenna, they function to help detect thermal IR.

“Despite their diminutive size, mosquitoes are responsible for more human deaths than any other animal,” says Dr. Nicolas DeBeaubien, who helped lead the study. “Our research enhances the understanding of how mosquitoes target humans and offers new possibilities for controlling the transmission of mosquito-borne diseases.”

IR sensing, for example, could potentially be exploited in large-scale mosquito control, such as by adding IR emitters to mosquito traps.

—by Sharon Reynolds

Related Links

• Skin Compounds Associated with Attractiveness to Mosquitoes
• How Mosquitoes Distinguish People from Animals
• Universal Mosquito Vaccine Tested
• How Mosquitoes Detect People
• Battling Bites: Blocking Mosquito-Borne Diseases
• From A to Zika: Understanding Emerging Diseases
• Mosquito Control (EPA)
• Infrared Waves

References:  Thermal infrared directs host-seeking behaviour in Aedes aegypti mosquitoes. Chandel A, DeBeaubien NA, Ganguly A, Meyerhof GT, Krumholz AA, Liu J, Salgado VL, Montell C. Nature . 2024 Aug 21. doi: 10.1038/s41586-024-07848-5. Online ahead of print. PMID: 39169183.

Funding:  NIH’s National Institute of Allergy and Infectious Diseases (NIAID); US Army Research Office; Institute for Collaborative Biotechnologies.

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The vaping research conundrum

17 September 2024

Auckland Bioengineering Institute , Health and medicine , Science and technology

How digital twins are helping researchers understand the impact of vaping on our future lungs

When lung researcher Morgan Seal was a Masters student and tutoring maths in her spare time, she noticed her young students would sometimes mysteriously go missing.

The girls were sneaking out of class so they could go vape. It shocked and worried her – that teenage girls who had no history of smoking were taking up vaping. She wondered what it was doing to those young lungs – and what it might do in the future.

But there’s a problem. Because vaping is relatively new – the first e-cigarettes containing nicotine arrived in New Zealand in 2018, but they didn’t really get popular until seven or eight years ago – we can’t yet look at the long-term impact of vaping on actual lungs, Seal told Jonny Vahry in an interview for bFM’s Ready Steady Learn show.

Now Seal is helping find out what the impact of vaping could be in the future, using mathematical modelling methods. Her work is contributing to developing digital twins of the lungs. Working under Associate Professor Kelly Burrowes in the Lungs and Respiratory Group at the Auckland Bioengineering Institute (ABI), Seal is looking at vaping and the damaging inflammation in the lungs and airways, including how chemicals travelling in the lungs during vaping might exacerbate conditions like asthma.

“There’s no data about what the effects of vaping are going to be in 10, 20 years time, she says. “But at ABI we can put together mathematical models where you take the physiology of the lungs [how the lungs work] and put it into a computer, then you can investigate the physiology that way.”

Digital twins also make it possible to check out the many variables that make research into vaping so complicated, she says.

For a start there are all the different flavours, each with their different chemical profile and potential for damage. Then there’s the temperature variation – different e-cigarette models vaporise at different temperatures and that affects what sort of chemical reactions are occurring in someone’s body.

"And there’s also something called ‘puff topography’, which is how long and how deep you breathe in when you’re vaping – that is, how much of those chemicals are getting into your lungs, and how far into the lungs they are going.”

Each different individual variable has the potential to alter the impact of vaping on someone’s lungs, Seal says. And that’s another reason why it’s difficult to do comparative research on real people who vape. 

“It’s why mathematical modelling is so useful because we are able to study vaping in a standardised way.”

Our research is aiming to predict the long-term health effects of vaping before they become widespread in the rapidly growing vaping population

Associate Professor Kelly Burrowes Auckland Bioengineering Institute

Associate Professor Kelly Burrowes leads the vaping research team at the Auckland Bioengineering Institute. She says research shows vapes contain toxic chemicals, although there are fewer of them than in cigarettes and they are present at lower concentrations.

But that doesn’t mean there are no harmful health impacts.

“Our research is testing several hypotheses to determine whether vaping leads to the same/similar health impacts as smoking,” she wrote in a Newsroom article in May entitled “ Vaping and how to stop another chemical generation ."

“This includes studying inflammation (the body’s normal defence mechanism), lung lymphatics (which coordinate the immune system response of the lungs) and cardiovascular impacts… Our current research is aiming to predict the long-term health effects of vaping before they become widespread in the rapidly growing vaping population.”

World leading, but not in a good way

Already the numbers are worrying. Latest figures show New Zealand has one of the highest youth vaping rates in the world, with 18 percent of 14 to 15-year-olds reported to be regular vapers. This compares with overseas studies which found, for example, 7.6 percent of UK 11 to 17-year-olds and 5 percent of New South Wales 14 to 17-year-olds reported vaping.

“Though e-cigarettes have been welcomed into New Zealand as a smoking cessation aid, there has been an unexpected uptake of vaping by never-smokers,” Burrowes says. Among daily vapers aged 18-24, 37 percent are never-smokers and in those aged 15-17, the proportion of never-smokers is even higher at 76 percent. 

“Māori are also over-represented in vaping prevalence rates, with one survey showing that a quarter of 14 to 15-year-old Māori females are vaping daily.”

Morgan Seal thinks back to her maths tutoring days and worries about those ‘missing’ girls and the impact of vaping on their health, and also on Aotearoa’s healthcare system in the future.

“Since the biggest uptake is in teenagers and young adults this is something we are going to see reflected in our healthcare 10 or 20 years down the line, if there are more and more illnesses associated with it.

“We know if you vape you are more likely to have asthma, and we also know vaping makes these conditions worse. We know, for example, you are more likely to die as a result of vaping if you have asthma. “But we don’t know whether vaping causes lung disease, because we don’t have enough data.

“We need more information.”

Media queries

Nikki Mandow I Media adviser Mob 021 174 3142 Email  nikki.mandow@auckland.ac.nz

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• Up in smoke: standing up for smokefree legislation
• Vaping: The good, the bad and the maybes

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Dengue infection in India: A systematic review and meta-analysis

Affiliations.

• 1 Department of Epidemiology, National Institute of Epidemiology, Chennai, Tamil Nadu, India.
• 2 School of Public Health, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India.
• 3 Campbell Collaboration, New Delhi, India.
• 4 Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India.
• PMID: 30011275
• PMCID: PMC6078327
• DOI: 10.1371/journal.pntd.0006618

Introduction: Dengue is the most extensively spread mosquito-borne disease; endemic in more than 100 countries. Information about dengue disease burden, its prevalence, incidence and geographic distribution is critical in planning appropriate control measures against dengue fever. We conducted a systematic review and meta-analysis of dengue fever in India.

Methods: We searched for studies published until 2017 reporting the incidence, the prevalence or case fatality of dengue in India. Our primary outcomes were (a) prevalence of laboratory confirmed dengue infection among clinically suspected patients, (b) seroprevalence in the general population and (c) case fatality ratio among laboratory confirmed dengue patients. We used binomial-normal mixed effects regression model to estimate the pooled proportion of dengue infections. Forest plots were used to display pooled estimates. The metafor package of R software was used to conduct meta-analysis.

Results: Of the 2285 identified articles on dengue, we included 233 in the analysis wherein 180 reported prevalence of laboratory confirmed dengue infection, seven reported seroprevalence as evidenced by IgG or neutralizing antibodies against dengue and 77 reported case fatality. The overall estimate of the prevalence of laboratory confirmed dengue infection among clinically suspected patients was 38.3% (95% CI: 34.8%-41.8%). The pooled estimate of dengue seroprevalence in the general population and CFR among laboratory confirmed patients was 56.9% (95% CI: 37.5-74.4) and 2.6% (95% CI: 2-3.4) respectively. There was significant heterogeneity in reported outcomes (p-values<0.001).

Conclusions: Identified gaps in the understanding of dengue epidemiology in India emphasize the need to initiate community-based cohort studies representing different geographic regions to generate reliable estimates of age-specific incidence of dengue and studies to generate dengue seroprevalence data in the country.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Fig 1. Flow diagram showing the article…

Fig 1. Flow diagram showing the article selection in the systematic review on dengue in…

Fig 2. Distribution of median age of…

Fig 2. Distribution of median age of laboratory confirmed dengue cases by year of study,…

Fig 3. Prevalence (proportion) of laboratory confirmed…

Fig 3. Prevalence (proportion) of laboratory confirmed dengue among clinically suspected patients in India.

Fig 4. Seroprevalence of dengue in India.

Error bars indicate 95% confidence intervals. Diamonds show…

Fig 5. Studies reporting case fatality ratio…

Fig 5. Studies reporting case fatality ratio among laboratory confirmed dengue cases in India.

Fig 6. Proportion of secondary infection among…

Fig 6. Proportion of secondary infection among laboratory confirmed dengue cases in India.

Error bars…

Fig 7. Proportion of severe dengue infections…

Fig 7. Proportion of severe dengue infections among laboratory confirmed dengue cases in India.

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Hidden Debt Revelations

How reliable are public debt statistics? This paper quantifies the magnitude, characteristics, and timing of hidden debt by tracking ex post data revisions across a comprehensive new database of more than 50 vintages of World Bank debt statistics. In a sample of debt data covering 146 countries and 53 years, the paper establishes three new stylized facts: (i) debt statistics are systematically under-reported; (ii) hidden debt accumulates in boom years and tends to be revealed in bad times, often during IMF programs and sovereign defaults; and (iii) in debt restructurings, higher hidden debt is associated with larger creditor losses. The novel data is used to numerically discipline a quantitative sovereign debt model with hidden debt accumulation and an endogenous monitoring decision that triggers revelations. Model simulations show that hidden debt has adverse effects on default risk, debt-carrying capacity and asset prices and is therefore welfare detrimental.

We received valuable comments from Fernando Arce, Tamon Asonuma, Gadi Barlevy, Volker Clausen, Aitor Erce, Stelios Fourakis, Juan Carlos Hatchondo, Aart Kraay, Leonardo Martinez, Julian Martinez-Iriarte, Marti Mestieri, Ugo Panizza, Juan Passadore, Carmen Reinhart, Diego Rivetti, Juan Sanchez, Zachary Stangebye, and Christoph Trebesch as well as from seminar participants at the Kiel Institute, the Inter-American Development Bank, the University of Duisburg-Essen, the Ruhr Graduate School in Economics, the World Bank, the University of Rochester, the University of Michigan, Purdue University, the Chicago Fed, the Richmond Fed, the 2024 NBER IFM Spring Meeting, the 2023 SED Annual Meeting and the 2023 Annual Meeting of the Verein für Socialpolitik. We thank Evis Rucaj and the entire team of the World Bank Development Data Group for answering countless questions on the International Debt Statistics. Gregor Ilsinger and Robert Remy provided excellent research assistance. We thank the German Federal Ministry for Economic Affairs and Climate Action and the German Federal Ministry of Finance for their financial support. All views expressed in this paper are those of the authors. They do not necessarily represent the views of the World Bank. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Different domains of dengue research in the Philippines: A systematic review and meta-analysis of questionnaire-based studies

Rhanye mac guad.

1 Faculty of Pharmacy, Department of Pharmaceutical Life Sciences, Universiti Malaya, Kuala Lumpur, Malaysia

2 Faculty of Medicine and Health Science, Department of Biomedical Science and Therapeutics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

Rogie Royce Carandang

3 Department of Community and Global Health, Graduate School of Medicine, University of Tokyo, Tokyo, Japan

Judilynn N. Solidum

4 College of Pharmacy, University of the Philippines, Manila, Philippines

Andrew W. Taylor-Robinson

5 School of Health, Medical & Applied Sciences, Central Queensland University, Brisbane, QLD, Australia

6 College of Health & Human Sciences, Charles Darwin University, Casuarina, NT, Australia

7 College of Health Sciences, Vin University, Gia Lam District, Hanoi, Vietnam

Yuan Seng Wu

8 Centre for Virus and Vaccine Research, School of Medical and Life Sciences, Sunway University, Selangor, Malaysia

9 Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Selangor, Malaysia

Yin Nwe Aung

10 Faculty of Medicine & Health Sciences, UCSI University, Port Dickson, Negeri Sembilan, Malaysia

Wah Yun Low

11 Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia

12 Asia-Europe Institute, Universiti Malaya, Kuala Lumpur, Malaysia

Maw Shin Sim

Shamala devi sekaran, nornazirah azizan.

13 Department of Pathology and Microbiology, Faculty of Medicine and Health Science, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

Associated Data

All relevant data are within the paper and its Supporting Information files.

Dengue is the most rapidly spreading mosquito-borne viral disease of humans worldwide, including southeast Asia region. This review provides a comprehensive overview of questionnaire-related dengue studies conducted in the Philippines and evaluates their reliability and validity in these surveys.

A review protocol constructed by a panel of experienced academic reviewers was used to formulate the methodology, research design, search strategy and selection criteria. An extensive literature search was conducted between March–June 2020 in various major electronic biomedical databases including PubMed, EMBASE, MEDLINE and ScienceDirect. A systematic review and meta-analysis (PRISMA) were selected as the preferred item reporting method.

Out of a total of 34 peer-reviewed dengue-related KAP studies that were identified, 15 published from 2000 to April 2020 met the inclusion criteria. Based on the meta-analysis, a poor mean score was obtained for each of knowledge (68.89), attitude (49.86) and preventive practice (64.69). Most respondents were equipped with a good knowledge of the major clinical signs of dengue. Worryingly, 95% of respondents showed several negative attitudes towards dengue prevention, claiming that this was not possible and that enacting preventive practices was not their responsibility. Interestingly, television or radio was claimed as the main source of gaining dengue information (range 50–95%). Lastly, only five articles (33.3%) piloted or pretested their questionnaire before surveying, of which three reported Cronbach’s alpha coefficient (range 0.70 to 0.90).

This review indicates that to combat the growing public health threat of dengue to the Philippines, we need the active participation of resident communities, full engagement of healthcare personnel, promotion of awareness campaigns, and access to safe complementary and alternative medicines. Importantly, the psychometric properties of each questionnaire should be assessed rigorously.

Introduction

Mosquito-borne pathogens, such as the causative agents of malaria, chikungunya, Zika and dengue, are major contributors to the global burden of human infectious disease [ 1 ]. In particular, the geographical distribution of dengue virus has increased alarmingly in recent decades to become a worldwide public health concern [ 2 ]. Currently, this flavivirus is reported in around 130 countries, with up to 400 million new cases of clinical infection recorded annually [ 3 ]. It is hyperendemic in southeast Asian countries, including Cambodia [ 4 ], Malaysia [ 5 ], Thailand [ 6 ], Bhutan [ 7 ], Brunei [ 8 ], Indonesia [ 9 ], Myanmar [ 10 ], Vietnam [ 11 ] and the Philippines [ 2 , 12 ]. The World Health Organization (WHO) projects that in excess of 2.5 billion people live in dengue-endemic areas, a significant contributing factor to an estimated annual death toll of 25,000 [ 13 ]. Nonetheless, the possibility of unapparent and under-reported infections should be recognized, not only due to accelerating geographical spread but also passive case detection; for instance, failure to detect persons with dengue who do not seek health care or to report all symptomatic dengue patients [ 14 , 15 ].

In common with many other tropical countries the risk level of dengue in the Philippines is considered as frequent or continuous due to regular outbreaks or ongoing transmission [ 16 ]. This is affected by several factors such as seasonal meteorological patterns (mean temperature, average relative humidity, and total rainfall) [ 17 ], increased urbanisation and volume of international air travel [ 18 ] that has led to an increase in the viability/reproduction/range of Aedes vector mosquitoes. Despite the fact that the first published report of a dengue epidemic in southeast Asia is from 1954, dengue outbreaks in the Philippines were documented in hospital records as early as 1926 [ 19 ]. During the years 2000–2011 all 17 administrative regions of the Philippines reported increased incidence of dengue, especially in the most populated urban areas, with all four virus serotypes co-circulating and exhibiting temporal and spatial variation. It is estimated that 80% of dengue-related deaths occurred in individuals ≤ 20 years old, with the highest number of cases in children between 5–14 years of age [ 18 ]. Most recently, in 2019 the Philippines Department of Health (DOH) issued a dengue alert in several regions due to a drastically elevated (85%) clinical case load over a six-month period [ 20 , 21 ]. Although the overall incidence of dengue in the Philippines has risen more than eight-fold between 2000 to 2019, this could be partly due to the altered reporting and recording system of dengue cases employed by the WHO and the Philippines DOH.

Several measures to prevent or control mosquito behaviour and breeding have been recommended in order to combat the spread of dengue virus. These actions include: personal protection from mosquito bites; provision of public engagement activities to educate local communities to improve household participation rates against the mosquito vector; emergency use of insecticides in outbreaks to achieve reactive vector control; and rolling out a range of local government-led proactive mosquito control and surveillance initiatives [ 22 , 23 ]. Similarly, the Philippines DOH has developed national programmes for dengue prevention and control, comprising surveillance, case management and diagnosis, integrated vector management, outbreak response, health promotion and advocacy, and research. Moreover, the DOH has implemented a so-called 4S strategy (Search and destroy, Seek early consultation, Self-protection measures, Say yes to fogging only during outbreaks) to strengthen the policy’s effectiveness [ 24 ]. Both the Philippines Integrated Disease Surveillance and Response and the Department of Virology of the Research Institute for Tropical Medicine took part in this programme, particularly in regard to surveillance.

For questionnaire-based research, different behaviours and perceptions are used to measure social aspects of dengue in the Philippines, such as knowledge, attitude and preventive practices (KAP), dengue vaccine acceptance, the health belief model (HBM) association with dengue, and complementary and alternative medicines (CAM) to treat dengue. Far-reaching conclusions have been drawn from questionnaire surveys conducted in other endemic countries, providing a useful guide to decision makers in setting health policy priorities [ 25 ], assessing dissemination, application and cost-effectiveness of current guidelines, and closing important gaps in our knowledge of patterns of dengue transmission [ 26 ]. Studies have suggested that a combination of multidisciplinary and bottom-up approaches is more likely to be successful and sustainable way to combat dengue [ 27 ]. Prevention and control should be promoted in school and university curricula, as should the crucial role of healthcare volunteers in implementing effective social networks to raise dengue awareness of householders that may influence their attitudes and behaviour towards dengue [ 28 ]. Despite this, there has been a limited number of questionnaire-based studies in the Philippines compared to neighbouring countries, such as Malaysia, Thailand, and Indonesia.

Furthermore, the collective scopes have not been discussed previously in the context of researching a pattern for guidance. In addition, the accuracy of findings from questionnaire-based studies is a matter of concern, as the accuracy of results depends largely on the reliability of the questionnaires used in the survey [ 29 ]. A comprehensive review of questionnaire-based dengue-related studies is required to highlight the findings from all relevant previously published work on the behavioural and practice aspects related to dengue prevention, to assess the validity and reliability of questionnaires used in such research, as well as to draw broad conclusions. Thus, this systematic review and meta-analysis aims to summarize existing questionnaire-based studies conducted in the Philippines, which may help to improve survey design relating to different domains on the behavioural and practice aspects related to dengue infection. In addition, it highlights future research needs and serves as a valuable reference for policymaking or health interventions focusing on the Filipino population.

Methodology

Study design.

The research protocol is in line with recommendations outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [ 13 ] ( S1 Appendix ).

Search strategy

The methodology, research design, search strategy and selection criteria were based on the review protocol ( S2 Appendix ) developed by the team of researchers who comprise experts in public health, infectious diseases and clinical medicine. An extensive literature search was conducted during March–June 2020 using various major electronic biomedical databases, such as PubMed, Goggle Scholar, EMBASE, MEDLINE and ScienceDirect. A checklist of preferred reporting items for systematic reviews and meta-analysis (PRISMA) [ 30 ] was used to present the flow of research strategy, consisting of selection, including and excluding the relevant articles, as shown in Fig 1 .

Screening and eligibility

All articles in English that were collected, compiled and eventually included in this review, reported a peer-reviewed dengue questionnaire-related research study conducted in the Philippines and published between January 2000 –April 2020. Moreover, any article considered as part of the review was cross-checked through references and in-text citations to ensure the inclusion of all relevant articles. In this review, we offered no restrictions on the type of participants included in the study; community residents, university students, in-patients, parents, and caregivers were included. For the intervention/exposure, all questionnaire-related dengue studies conducted in the Philippines were included. We did not have any comparison group in this review. Regarding the outcomes, we summarized the main findings that reported dengue-related knowledge, attitude, and practices.

A non-questionnaire-based study (13 studies), simple reports with no evidence of peer review (three studies) and conference proceedings or theses (three studies) were excluded due to lack of information for data extraction and/or evidence of peer review. The relevance of each article was determined using individual keywords or a string combining ‘dengue’, ‘questionnaire’ and ‘Philippines’. Additionally, the Boolean operators “AND”, “OR” and “NOT” were used to link categories of keywords, thereby aiming to increase sensitivity and specificity of the query. No limits by sex, age and ethnicity of study participants as well as language of the articles were imposed. Similar keyword(s) were applied to all electronic databases to search for articles.

Data extraction and management

The decision whether or not to include each article was made after reaching a consensus among the research team following group discussion between members via email. A total of 34 articles were retrieved electronically, with further papers that were not open access being acquired by emailing the paper’s corresponding author. After removing duplicate publications 14 articles were identified as either irrelevant or to not fulfil the abovementioned criteria, and hence each was excluded.

Risk of bias assessment

The remaining 20 articles were assessed further during the first round of review, undertaken by six expert reviewers (public health authorities and infectious diseases specialists) based on titles and abstracts, from which five articles were eventually excluded for not being a questionnaire-related study (e.g. a workshop protocol on dengue prevention and control or fieldwork on breeding sites of Aedes species mosquito). The second round of review was performed by three expert reviewers to ensure that based on the selection criteria only relevant articles were included in the final selection; no further papers were excluded. All papers fulfilling the inclusion criteria were critically appraised based on the eight critical appraisal tools of the critical appraisal skills programme (CASP) Checklist [ 31 ] (S3 & S4 Appendices). Therefore, this review contained a total of 15 articles, as indicated in Table 1 . In this systematic review, 15 papers related with knowledge, attitude and practice on dengue study in the Philippine were included. However, as the number of studies fewer than 10 in the meta-analysis, not all these papers recorded the same effect size. Therefore, an assessment of publication bias using graphical methods (e.g. funnel plot asymmetry) or statistical methods (e.g. Egger’s test) was not possible.

Statistical analysis

We conducted quantitative synthesis to derive meta-estimates of knowledge, perception and attitude of the study population and qualitative synthesis to describe the study population, study design, sampling methodology and outcomes presented in the paper. For each study, primary outcome (knowledge, attitude and practice score) and secondary outcome (percentage of population with good knowledge, acceptable attitude, and practice) were extracted. Knowledge, attitude and practice score were standardized to cent percent and pooled estimates are presented as mean and 95% confidence interval. Prevalence of population with good knowledge, acceptable attitude and practice were also identified, meta-analysed and presented also as mean and 95% confidence interval. Forest plots were used to display pooled estimates. Heterogeneity was tested using likelihood ratio test. Analyses were performed using STATA 16 statistical software. For meta-analysis interpretation, based on previous studies [ 27 , 40 ] the cut-off values used for standardized knowledge scores were as follows: < 64, poor; 64–80, good; > 80, very good.

Awareness and knowledge of dengue infection

Based on percentage scale, the mean knowledge score was 68.89 ( Fig 2 ). The current systematic review shows that most respondents (95%) held several erroneous beliefs: that (1) dengue transmission cannot be prevented; (2) elimination of larval breeding sites is the responsibility solely of public health staff and healthcare volunteers; (3) eliminating such sites is very complicated, poor use of public funds and a waste of time; (4) insecticide fogging is sufficient to prevent mosquitoes; (5) individuals who have experienced dengue infection once cannot be infected subsequently; and (6) a fit and healthy person will not get dengue infection [ 32 , 35 ].

In 2004, Kwon & Crizaldo [ 32 ] reported that more than half of participants (56.3%) had moderate knowledge of dengue, whereas in 2013 Yboa & Labrague [ 40 ] reported higher knowledge of dengue (91.6%) among rural residents in Samar Province, Philippines. This is despite the fact that the two studies employed different sampling techniques: the former used purposive random sampling [ 32 ], whereas the latter used convenience sampling [ 40 ] ( Fig 3 ). In terms of recognition of symptoms of dengue infection, most respondents answered correctly that fever is the major clinical feature of uncomplicated dengue [ 24 , 32 – 34 ] affecting infants, young children and adults [ 33 ]. Other symptoms claimed by respondents include chills, headache, pain upon eye movement, lower back ache, stomach ache, skin rashes, vomiting, bleeding of the nose and gums, muscle pain and diarrhoea [ 32 , 33 , 35 , 36 ].

Interestingly, most respondents answered correctly questions assessing their knowledge of dengue transmission. For instance, they identified that the dengue virus is transmitted to humans through the bite of an infectious female Aedes aegypti : 89.6%, [ 32 ]; 56.07%, [ 34 ]. Furthermore, the majority of respondents recognized that Aedes mosquitoes bite during daytime: 66.7%, [ 32 ]; 28.85–46%, [ 36 ]; 17–37.67%, [ 33 ]. However, an incorrect perception of biting time at night has also been reported; 64%, [ 34 ]. Up to 95.8% of survey participants correctly identified stagnant water collected in discarded tyres, trash cans and flowerpots as providing good breeding sites for mosquitoes [ 32 , 36 ]. More than 50% of respondents acknowledged that not all mosquitoes carry dengue, flies and ticks do not transmit the virus and that disease may be contracted through transfusion of infected blood [ 34 ], and also that heavy rainfall provides conditions favourable to rising numbers of mosquitoes responsible for dengue [ 33 ], due to formation of larval breeding sites [ 32 ]. Additionally, around 50% of respondents claimed that combating dengue vector mosquitoes is the only way to control infection [ 32 ], or that sleeping under a mosquito net prevents infection [ 37 ]. Only 25% of respondents realised either the possibility of contracting dengue if a family member had been infected with the virus or that the rainy season (June–February) is, historically at least, the only epidemic period for dengue infection in the Philippines [ 32 ].

The knowledge of survey participants regarding an individual’s risk of dengue infection was unsatisfactory as 23% thought that a fit and healthy person could not be infected more than once in a lifetime. Moreover, only 12.5% of respondents strongly agreed that it is possible to recover completely from infection [ 32 ]. A study by Herbuela et al. (2019) [ 38 ] demonstrated that knowledge of dengue is not always directly proportional to educational attainment; for instance, paediatric patients in senior high school knew more about dengue compared to those who were in college who had experienced dengue for the first time.

Attitude towards dengue infection

After standardising to percentage scale, the overall attitude score was 49.86, reflecting a poor attitude among Philippines populations towards dengue ( Fig 4 ).

It is of interest to note that those patients who were high school seniors or who experienced a longer stay in hospital tended to have a better attitude towards dengue. However, this association decreased as the patients aged [ 38 ]. Other positive attitudes of Filipino communities when infected with dengue were reported [ 36 ]. These included consulting a physician, taking plenty of rest, drinking copious water when affected by the disease, and seeking herbal medicine (mangagaw, tawa-tawa or gatas-gatas). Drinking apple tonic, installing residential door and window screens, sleeping under mosquito nets, and burning mosquito coils and dried leaves were each also mentioned as a method used to prevent dengue.

Furthermore, two studies have demonstrated a good attitude towards dengue among mothers of young children in Malaybalay, the capital city of the province of Bukidnon. They believed that dengue is a serious disease (60%); it cannot be treated at home (92.5%); it is preventable (70.7%); it can be prevented by controlling breeding sites of mosquitoes (69.6%); government is not solely responsible for control (71.7%); and control requires active community participation (95%) [ 32 , 34 ]. Lennon (2004) reported that students from Dumaguete, a city on Negros Island in the southern Philippines, showed a positive attitude towards dengue control and prevention as they practised the following: (1) cleaning inside their house and its immediate surroundings; (2) eliminating collection of stagnant water by keeping opened cans and other vessels upturned or in a suitable place; and (3) applying insecticide spray, all of which are measures of mosquito larvae control [ 39 ]. However, Lennon (2004) also mentioned that lack of knowledge and correct behaviour (characterized as ignorance, apathy, laziness, perceived lack of time and/or lack of cooperation) among students could manifest in poor attitudes towards combatting dengue.

Preventive practice towards dengue infection

After standardising to percentage scale, the overall practice score was 64.69%, indicating that preventive practice towards dengue among Filipino populations is acceptable regardless of a poor attitude score ( Fig 5 ). Based on previous studies, the most preferred options for preventive practice were “search and destroy mosquito breeding sites” including covering water storage containers after use (> 90%), examining toilet cisterns for mosquito larvae (88%), regular disposal of refuse into garbage bins (> 80%) [ 33 , 35 ]. Progressively less popular options included using mosquito nets/mosquito coils in the house (77%), checking and cleaning roof gutters during the rainy season (69%), and insecticide fogging (67%) [ 32 , 35 , 40 , 41 ].

Further results showed that the best self-protection method was covering water storage containers immediately after use (92%) [ 32 , 33 , 40 ], screening of windows (88%), use of mosquito bed nets (92%) or using an electric fan [ 33 , 35 , 40 , 41 ]. Some survey respondents (63%) reported that they had used professional pest control in an attempt to prevent dengue infection [ 40 , 41 ]. Other preventive measures that have been practised by respondents are: (1) traditional fogging to disperse mosquitoes, especially during the afternoon; (2) wearing long-sleeved shirts and trousers, especially by small children. A recent study by Rufo & Amparado (2017) indicated the practices of scrubbing water storage vessels and cleaning roof guttering at least once a week or a preference for fogging to be important means of dengue management practice [ 24 ]. Additionally, Herbuela et al. (2019) revealed that mosquito larvae-eating fish, screen windows and dengue vaccination were each identified as a protective factor against dengue infection, of which the biological control method of using larvivorous fish was the strongest factor in the model with an adjusted odds ratio (AOR) of 8.69 (95% CI: 3.67–20.57, p ≤ 0.001) [ 38 ].

In contrast, a study in Lugait, a municipality in the province of Misamis Oriental, identified several negative practices performed by resident communities [ 33 ]. These included: (1) leaving water storage containers uncovered for more than a week inside the house (57.67%); (2) overwatering of flower vases and potted plants (21.67%); (3) the presence in the neighbourhood of plants such as bananas in which mosquitoes are known to shelter (65.33%); (4) discarding tyres, cans, bottles and other containers in which water may collect (43.33%); (5) rivers, ponds and puddles of water that form after raining (26.00%); (6) coconut shells (23.67%); (7) no proper drainage (13.67%); and (8) dirty surroundings (9.67%).

Treatment-seeking behaviour

In terms of treatment-seeking behaviour, most respondents associated fever as being the principal manifestation of dengue infection (86.5%) [ 24 ]. Interestingly, parents would preferentially choose to bring a child with fever to a district hospital (54.75%) rather than to a rural health unit (44.75%), private clinic (40.25%), tertiary hospital (27.50%) or quack doctor (7.5%).

Sociodemographic variables and KAP regarding dengue infection

Based on this meta-analysis, a significant positive correlation between knowledge and attitude domains was observed among paediatric patients with confirmed dengue infection, although this is not statistically strong (Spearman’s rank correlation coefficient, Rs = 0.2). However, Herbuela et al. (2019) reported that neither the knowledge nor the attitude of dengue patients correlated with their practices [ 38 ]. Other studies have also reported an insignificant association between sociodemographic variables, knowledge, attitude or practice regarding dengue among communities in the Philippines [ 24 , 32 , 36 , 40 ]. Sociodemographic and economic data collected include, for example, age, sex, education, migration background and ethnicity, religious affiliation, marital status, household, employment, and income.

Sources of information on dengue infection

It is noteworthy that most of the articles analysed reported the main source of information on dengue infection being provided by television (ranging from 49.7% to 93.8%) [ 32 , 33 , 37 , 40 ] and radio (73.37%) [ 33 , 37 , 40 ]. Yet, respondents gained information from a variety of other sources: for instance, via health workers (80.33%) [ 32 ], (5.11%) [ 40 ]; schools (34.00%) [ 33 ]; internet (9.67%) [ 33 ]; posters (3.33%) [ 33 ]; and by speaking with neighbours and/or friends (4.20%) [ 32 , 33 , 37 ].

Dengue vaccination

In a hospital-based cross-sectional study, the acceptance rate of dengue vaccination was 81.3% (113 out of 139) among parents and caregivers. Completion of secondary or tertiary education (AOR = 0.22, 95% CI: 0.01–4.1, p < 0.0001) and lower income group (AOR = 2.8, 95% CI: 0.06–5.1, p < 0.0001) were the independent factors associated with dengue vaccine acceptance [ 40 ]. On the other hand, a community-based survey revealed that 95.5% (193 out of 202) of primary caregivers accepted dengue vaccination, a very high rate [ 42 ].

Based on this meta-analysis, good attitude towards vaccination (AOR = 10.62, 90% CI: 1.73–26.28) and large household size (AOR = 9.63, 90% CI: 2.04–45.38) were each positively associated with vaccine acceptance within a community. In contrast, good knowledge of dengue (AOR = 0.10, 90% CI: 0.03–0.74) and age of 44 years or more (AOR = 0.14, 90% CI: 0.03–0.61) were two factors that negatively influenced acceptance rate [ 43 ].

For the aspect of willingness to pay (WTP) for a single dengue vaccine and the household demand function for dengue vaccines, Palanca-Tan (2008) reported that the mean WTP for a vaccine ranged from USD 27–32, and the household demand averaged two persons per household [ 44 ]. For lower income groups with less capacity to pay, a mass vaccination campaign programme was suggested instead, through which at least part of the financial costs is covered.

Complementary and alternative dengue prevention

Indigenous communities in the province of Pangasinan, located on the island of Luzon, use Euphorbia hirta , locally known as tawa-tawa, as a Filipino tradition for dengue [ 45 ]. The most widely used treatments are decoctions of the leaves and bark. The plant extract was reported to be effective as a symptomatic CAM for dengue in the initial, febrile and recovery stages, as well as for supportive therapy [ 45 ].

Reliability and validity of questionnaire

Out of 15 articles reviewed, 5 had piloted or pretested the questionnaire [ 24 , 37 , 38 , 42 , 44 ] before surveying. Three articles that were adapted [ 34 , 38 , 40 ] and 8 articles containing a new questionnaire [ 32 , 33 , 35 , 36 , 39 , 42 , 43 , 45 ] were considered as having a high risk of bias on the questionnaire due to lack of evidence on reliability and validity.

This systematic review provides the first description and insight into questionnaire-based studies conducted in different dengue-endemic communities in the Philippines, where an upward trend of dengue cases has been reported for more than a decade [ 12 ]. Filipinos prefer a healthcare facility that provides a higher level of medical attention than those offering basic services despite the availability of the latter in the locality of respondents. Television and radio play an important role in delivering dengue information to resident communities. Although a high vaccination acceptance rate was reported among community residents, this needs to be re-assessed due to the ‘Dengvaxia’ dengue vaccine controversy. It was found that the majority of respondents have an inadequate KAP level regarding dengue, which is associated with several factors.

The Philippines, like many other countries in the tropics, is plagued by dengue [ 16 , 46 ]. For decades vector surveillance and control measures have remained the mainstay of dengue control and prevention programmes. There is a pressing need for these to be effective as dengue has no cure and patients are subjected only to symptomatic management after becoming infected [ 2 ]. Moreover, the only vaccine currently available, Dengvaxia®, has variable safety and efficacy by age and serostatus such that its licensure has proved controversial [ 47 ]. In fact, human living practices play a crucial role in maintaining dengue virus transmission via Ae . aegypti carriage by providing a suitable breeding environment and ready source of blood meal for this peridomestic dengue vector. Therefore, here we have focused on questionnaire-based studies in relation to different domains of human behaviour towards dengue, such as KAP, sources of information, preventive treatments, HBM and CAM. In addition, this review also analysed the reliability and validity of survey questionnaires used in the included articles. The findings reported herein stress that the development of a proactive dengue control programme should be prioritized in order to protect the health of all layers of Filipino society, especially those located communities in highly endemic areas.

In this systematic review of the population of the Philippines, cut-off values were based on a 100-point scale (i.e. for instance, an 80.00% score is considered as good). Overall, the respondents achieved 68.89%, 49.85% and 64.69% scores for knowledge, attitude and preventive practices towards dengue, respectively. This KAP score revealed that more than half of the entire cohort had adequate knowledge regarding dengue, specifically of dengue infection per se and of its signs and symptoms. The level of knowledge among Filipinos revealed here is lower compared to studies conducted in Malaysia (more than 90%) [ 48 ] and Laos (70.9%) [ 49 ]. In comparison, 50% of the rural population in Kancheepuram district of Tamil Nadu, India [ 50 ] and the population of the earthquake- and tsunami-affected area of Aceh Indonesia [ 51 ] were knowledgeable about dengue symptoms. These findings shows that communities living in regions where the fatality rate from dengue is high have less knowledge, perhaps placing them at greater risk. Hence, increased mortality from dengue appears to be correlated with ignorance of its virus aetiology, vector transmission and disease symptoms, thereby reiterating the paramount importance of public health education programmes. Interestingly, a study conducted in Nepal reported corroborative findings that compared to participants resident in the lowlands a significantly lower proportion of those living in highland areas, which experience low dengue fatality rates, were able to correctly identify typical symptoms of dengue [ 28 ]. Similar to the observations made in the Philippines such differences may be attributed to intensified education and awareness campaigns in highly endemic areas leading to an increased level of knowledge. Due to the incrementally expanding distribution of Aedes mosquitoes as a direct result of climate change, future dengue awareness campaigns should target communities in both endemic and potentially endemic areas, not only in the Philippines but elsewhere in tropical and subtropical zones [ 52 ]. Among Filipino communities in areas of high endemicity for dengue, public health engagement should focus on those identified factors associated with attainment of knowledge. Plausibly, the meta-analysis also found an inverse association between level of education and knowledge of dengue, suggesting that a better understanding and comprehension of information on dengue does not necessarily depend on the level of education which a person has reached. It is recommended that in order to raise knowledge of dengue, public health campaign materials should be piloted and evaluated routinely with community members of all educational backgrounds, as well as training of personnel to deliver educational information effectively to address knowledge gaps regarding dengue in the community.

The current meta-analysis reveals a poor attitude (49.85%) and preventive practice (64.69%) towards dengue among communities in the Philippines. Approaching half of an urban community (43.80%) [ 32 ] held an erroneous belief that chemical fogging by the local government authority is adequate to reduce dengue transmission compared to only around a third reported for a similar Malaysian urban population (31.8%) [ 53 ]. In fact, existing policies should revisit the implementation of insecticide use, such as fogging periodically instead of sporadically and its deployment as an adjunct vector control method. A reduction in mosquito and larval density after fogging as measured by a drop in mean ovitrap index value from 71.67% to 69.42% has been reported [ 54 ]. However, sole dependency on preventive fogging may lead to the emergence of insecticide resistance [ 55 ]. Furthermore, of the included articles, two studies showed that some respondents believed that eliminating breeding sites is the exclusive responsibility of public health staff and healthcare volunteers (52.10% and 28.30%, respectively) [ 32 , 34 ]. These values are comparable with those reported by a previous study in an Indian population (49.00%) [ 56 ]. This attitude needs to change because achieving a reduction of the vector population and prevention of virus transmission requires the active participation of affected communities. In order to combat mosquito breeding, all residents should take personal responsibility to regularly clean their housing and immediate surroundings. Nonetheless, local government authorities should spearhead this effort as studies have reported that search and destroy practices require trained personnel to have good knowledge and skills to be able to remove Aedes breeding sites more effectively [ 2 ].

The negative behaviour among university students towards dengue prevention [ 38 , 39 ] could be explained by using the health belief model, conceivably due to weak confidence in the effectiveness of the proposed measures to control mosquitoes and thereby to prevent dengue transmission. A perception of reduced benefits coupled with elevated barriers may result in a lesser possibility of change, as reported in a Malaysian population [ 57 ]. Self-efficacy is another HBM construct that, in addition to the perceived threat of dengue and other parameters, encourages an individual to implement preventive practices. Not surprisingly, university students might have a low self-efficacy or confidence in doing something with which they are unfamiliar, which could have led to their low interest to carry out mosquito control tasks. In this context, although they have a higher level of education, and therefore may have the ability to understand various information on dengue [ 58 ], they may not have the self-confidence to perform regular, comprehensive environmental clean-up tasks, as claimed by studies conducted in Malaysia [ 59 ] and Pakistan [ 60 ]. Hence, it is important to identify the trigger for a person’s motivation to contribute to vector control initiatives. This is unlikely to be the same for different people or groups within a community where there will be several cultural and social factors at play. We suggest that a public health campaign should incorporate guidance on how to conduct steps of an environmental action plan for dengue control. Furthermore, this should be based on an HBM construct specific for the Filipino population in order to increase their self-efficacy and behaviours regarding mosquito control.

Pre- and post-educational intervention in Malaysia achieved via public health campaigns and further disseminated by discussion among students revealed that educational intervention was effective in generating awareness of dengue (mean scores for pre- and post-intervention were 10 ± 2.46 vs 12.61 ± 0.17, 8.82 ± 1.35 vs 9.01 ± 1.09 and 6.92 ± 2.5 vs 7.11 ± 2.49 for knowledge, attitude and practice, respectively) [ 61 , 62 ]. Educational intervention should include promotion of skills development that may help to reduce the perception among students of time as a limitation to performing mosquito control activities. Other studies have highlighted additional barriers to the effectiveness of public health campaigns, including not being conducted on a routine basis [ 63 ] and initiatives being driven from the top down, thus creating resistance from community residents to participate in interventions [ 64 ].

Most respondents claimed that fever is associated with dengue, prompting them to attend the nearest healthcare facility to seek treatment. This finding is in accordance with HBM, whereby self-regulation emphasizes that people have or can develop autonomy, self-control, self-direction and self-discipline due to the assumption that all behaviours are motivated by the desire to achieve goals that are personally important [ 65 ]. Following this principle, individuals make progress towards their goals by selecting and monitoring their behaviour over time [ 66 ]. In contrast, HBM also hypothesizes that fever is not sufficient a cue to action to make respondents proceed as for dengue. The uncertainty of the model’s conditions regarding the presence of fever increases the perception of susceptibility to dengue [ 67 ]. In a Venezuelan population, this explains a person’s intention to seek medical assistance as their first action if they suspect dengue infection, whereas treating at home would be their first choice in case of fever only [ 68 ]. Furthermore, most respondents prefer a healthcare facility that provides a higher level of medical attention than those offering basic services such as the barangay health stations, rural health units or private clinics which are readily available in the locality of respondents, reflecting the need to improve healthcare facilities in order to provide immediate and effective treatment to dengue patients. An interesting study in Cambodia reported a range of thought processes involved in the selection of healthcare facilities [ 69 ]. A lack of confidence over the quality of healthcare at the village level, suspicion as to the quality and provenance of locally available drugs, and real or perceived financial barriers to seeking care were predominant reasons for the sequence of treatment-seeking behaviours that was observed.

The systematic review also indicated no significant association between knowledge, attitude, and preventive practice regarding dengue was observed in Filipino populations. Although studies from Nepal [ 28 ], Indonesia [ 51 ], Vietnam [ 70 ] and Coimbatore, southern India [ 71 ] have each reported a positive association between KAP domains, other populations such as in Malaysia [ 72 , 73 ] and the Indian cities of Delhi and Kolkarta [ 74 , 75 ] have reported no correlation. An effective and sustainable strategy for combatting dengue is critically required when translating a community’s knowledge into good practices, such as the need to change their behaviour towards prevention of virus transmission. On account of this, carefully tailored practical approaches should be integrated into public health-related educational programmes, such as house-to-house inspections undertaken by healthcare personnel to conduct Aedes surveillance and to convey information and educate residents in a more personalised manner and familiar setting. Also, religious organisations, notably the predominant Roman Catholic Church in the Philippines, should be encouraged to influence and motivate habit change and to spur social mobilization, as is practised in other countries [ 76 , 77 ].

Sources of information on dengue fever infection

This systematic review demonstrates that the principal sources by which information on dengue is disseminated to communities in the Philippines are television and radio. These outlets are key to delivering important knowledge regarding dengue, suggesting a need to maximize mass media in educating the population. A similar finding has been reported elsewhere [ 51 , 78 , 79 ]. The reason that television and radio are significant predictors of adequate knowledge of dengue could be that globally, and especially in developing countries, these traditional forms of audio-visual broadcast media remain the most popular means of communication that appeal to all age groups and to every socioeconomic class, encompassing both literate and illiterate members of the community. Thus, this finding indicates that television and radio should be fully utilized as an effective and accessible way to promote dengue awareness among Filipino communities. Surprisingly, it was also found that healthcare workers in the Philippines held a subsidiary role as dengue informants, in contrast to the data reported by studies conducted in Indonesia [ 51 ], Chitradurga in southwest India [ 80 ] and Malaysia [ 62 ]. The disparate findings may be due to patients’ perceived trustworthiness and acceptance of healthcare services. This could lead to behavioural impacts among the community such as the notable recent Dengvaxia® vaccine controversy experienced in the Philippines [ 81 ]. Given this possibility, dengue intervention programmes may need to be reviewed stringently to enable healthcare workers to maximize their educational impact on patients and their family members during clinic consultations, house visits or community outreach events.

The acceptance rates of dengue vaccination in this systematic review, ranging from 81.3 to 95.5% [ 40 , 42 ], are comparable to those reported by two studies conducted in Aceh Indonesia (70% and 77.3%, respectively) [ 82 ], one in Bandung, Indonesia (94.2%) [ 83 ] and another in Penang, Malaysia (88.4%) [ 84 ]. Although a higher level of education is associated with a better attitude towards dengue vaccine acceptance [ 85 ], a negative association has also been found [ 83 ]. Nonetheless, education is considered as an intermediate factor that could be affected by other considerations, which may explain the conflicting result as a predictor of dengue vaccine acceptance. Thus far, the association of income class and vaccine acceptance is not fully explained. In fact, it was proposed that wealthier people are more likely to comply with dengue vaccination primarily because they would consider the cost more affordable compared to people in a lower income class [ 83 ]. However, this systematic review showed opposite findings. Given that the majority of respondents included in the analysed studies were of lower income status and that more people were accepting of dengue vaccination, this might have tipped the scales appreciably towards significance.

Nonetheless, a previous study in Metro Manila, the Philippines, indicated a sufficiently high WTP for dengue vaccination, with mean WTP ranging between USD 27–32 [ 44 ]. This is greater than mean figures reported from comparative studies conducted in other countries; in Indonesia (USD 13.60) [ 83 ] and (USD 4.04) [ 85 ], in Nha Trang, Vietnam (USD 26.10) [ 86 ]; and in Medellin, Colombia (USD 22.60) [ 87 ]. On the contrary, the WTP for dengue vaccination of consumers was marginally higher in Brazil (USD 33.61) [ 88 ] and markedly so in Thailand (USD 69.80) [ 87 ]. Interestingly, a Vietnamese study of dengue patients with a history of hospital admission (for any ailment, not necessarily dengue) showed their elevated WTP for a vaccine (USD 67.40) [ 86 ]. This is probably due to an inflated awareness of the escalation of dengue cases due to time spent on hospital wards combined with the occurrence of a large-scale dengue outbreak in southeast Asia at the time reiterating the potential health benefits of vaccination.

Complementary and alternative approaches to dengue control and prevention

In the Philippines the use of E . hirta to treat dengue exemplifies the importance of traditional medicine, particularly of herbal origin, to rural and remote communities lacking adequate vector control and with limited access to modern healthcare facilities, as reported previously [ 89 , 90 ]. Interestingly, the utilisation of herbal plants among community residents of Lugait in the Philippines has been reportedly endorsed by its local healthcare centres [ 32 ]. Similarly, in a study in the US, 53.10% of healthcare providers recommended at least one CAM to their patients [ 91 ]. This is in contrast to the perspectives of healthcare providers of using CAM as an adjunct to allopathic medicine in American Samoa [ 92 ] and Sierra Leone [ 93 ].

A recent systematic review of available scientific evidence reported the potential of E . hirta against dengue as it holds significant antiviral and platelet-increasing activities [ 94 ]. These conclusions may have been drawn due to this plant’s high concentration of reducing polyphenols as an active ingredient [ 95 ]. However, the mechanism of antimicrobial action remains to be determined, and the antiviral properties and its ability to stimulate blood platelet production are both currently under investigation [ 96 ]. Therefore, well-controlled clinical trials as well as contemporary pharmacological approaches, including activity-guided fractionation and elucidation of the mode of action in increasing platelet activity, are warranted to establish the potential use of E . hirta in a clinical setting.

Lack of evidence on questionnaire reliability and validity

This systematic review demonstrates a clear need to determine the psychometric properties of the questionnaires used in dengue surveys conducted in the Philippines in order that KAP assessments are reliable, and the results are valid. A KAP study is a focused evaluation that measure changes in human knowledge, attitudes and practices in response to a specific intervention. As such, it is a quantitative research method that has the power to reveal a wealth of useful information on a significant aspect of research investigation. Therefore, if the questionnaire is well-constructed and the survey conducted by trained operators, a KAP study should assist in obtaining relevant data in a highly reliable and valid manner [ 97 ]. Reliability and validity are extremely important qualities required in order to measure the accuracy and consistency of this and other survey tools [ 98 ].

The survey questions should provide reproducible results (reliability test) and be assessed in three major forms of reliability: test-retest; alternate form; and internal consistency [ 99 ]. An Rs of value 0.70 or greater is generally accepted and indicates good reliability [ 100 ]. Despite the need to determine reliability during pretesting only a small minority of studies have reported Cronbach’s alpha coefficients during the pilot study and thereby confirmed the adequacy of internal consistencies of these scales [ 29 ].

In regard to validity there are several subtypes, namely face, content, criterion and construct validity [ 101 ]. The underlying construct of the items should be analysed by factor analysis to predict the discriminant and convergent validity [ 29 , 102 ]. In this systematic review, the majority of articles reported neither the results of a pilot study nor those of a pretest questionnaire–if these were indeed actually undertaken. Reliability, content and construct validity of a KAP structured questionnaire should be carefully examined. It is crucial to harmonize and validate the content of all the surveys with the aim of reducing the variability of findings based on questionnaires used for data collection.

Strength and limitation

Several limitations of this review including inaccessibility of the original questionnaires which may have resulted in the heterogeneity of the findings in this review. Additionally, this could have resulted from the differences in statistical analysis or sociodemographic characteristics of the populations under study.

Conclusions

This systematic review demonstrates a good level of knowledge, attitude and preventive practice regarding dengue among the resident population of the Philippines, particularly in highly endemic areas. Moreover, there is no association between KAP domains. Therefore, there is a great need to prioritize public health campaigns to target identified factors based on HBM. This is in order to raise the level of knowledge of dengue, to influence attitudes towards vector control and prevention and thereby to increase the uptake of preventive practices. These goals can be achieved through the active participation of communities and engagement with healthcare personnel, in combination with promotion of dengue awareness and safe complementary medicines through the use of television and radio. Equally important, there is an urgent need to determine the psychometric properties of KAP questionnaires before use in future dengue surveys in the Philippines in order for such assessments to be valid and conducted reliably.

Supporting information

S1 appendix, s2 appendix, s3 appendix, s4 appendix, funding statement.

Rhanye Mac Guad and Nornazirah Binti Azizan obtained funding from Universiti Malaysia Sabah; Skim Penyelidikan Pensyarah Lantikan Baru (SLB0181-2018) and Skim Penyelidikan Bidang Keutamaan (SBK0414-2018), respectively. The funding body was not involved in the study's design, analysis, or data interpretation.

Data Availability