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Fatal meningoencephalitis associated with Ebola virus persistence in two survivors of Ebola virus disease in the Democratic Republic of the Congo: a case report study

Collaborators.

• EBOV Persistence Study Group : Anja De Weggheleire ,  Gnakub N Soke ,  Raymond Pallawo ,  Gouressy Ibrahima ,  Victor Epaso Gelege ,  John Kombe-Ngwama ,  Grace Kahambwe-Ekoko ,  Mathias Mossoko Gbe ,  Pierre-Céleste Adikey Limne ,  Etienne Yuma-Kibondo ,  Eddy Kinganda-Lusamaki ,  Adrienne Amuri Aziza ,  Yannick Tutu Tshia N'kasar ,  Elias Mumbere Kalemekwa ,  Divine Kitsa-Mutsumbirwa ,  Noella Mulopo-Mukanya ,  Fyfy Mbelu-Matulu ,  Marie-Anne Kavira-Muhindo ,  Jacques Kwizera Sendegeya ,  Hugo Kavunga-Membo

Affiliations

• 1 Department of Virology, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Service of Microbiology, Department of Medical Biology, Kinshasa University Hospital, University of Kinshasa, Kinshasa, Democratic Republic of the Congo; Rodolphe Mérieux Institut National de Recherche Biomédicale-Goma Laboratory, Goma, Democratic Republic of the Congo. Electronic address: [email protected].
• 2 Department of Virology, Institut National de Recherche Biomédicale, Kinshasa, Democratic Republic of the Congo; Service of Microbiology, Department of Medical Biology, Kinshasa University Hospital, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
• 3 US Centers for Disease Control and Prevention, Atlanta, GA, USA.
• 4 Health Emergencies Programme, WHO, Geneva, Switzerland.
• 5 Clinical Monitoring Program Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.
• 6 Zoonotic and Emerging Disease Research Unit, US Department of Agriculture National Bio and Agro-Defense Facility, Manhattan, KS, USA; National Institute for Allergy and Infectious Diseases-National Institutes of Health, Rockville, MD, USA.
• 7 Programme Nationale d'Urgences et Actions Humanitaires, Ministry of Health, Kinshasa, Democratic Republic of the Congo.
• 8 National Institute for Allergy and Infectious Diseases-National Institutes of Health, Rockville, MD, USA.
• 9 University of Nebraska Medical Center, Omaha, NE, USA; PraesensBio, Omaha, NE, USA.
• 10 TransVIHMI, Université de Montpellier-IRD-INSERM, Montpellier, France.
• 11 Department of Clinical Sciences, Institute of Tropical Medicine Antwerp, Antwerp, Belgium.
• 12 Department of Biomedical Sciences, Institute of Tropical Medicine Antwerp, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
• 13 University of Nebraska Medical Center, Omaha, NE, USA; Biosurv International, Salisbury, UK.
• PMID: 39236738
• DOI: 10.1016/S2666-5247(24)00137-X

Background: During the 2018-20 Ebola virus disease outbreak in the Democratic Republic of the Congo, thousands of patients received unprecedented vaccination, monoclonal antibody (mAb) therapy, or both, leading to a large number of survivors. We aimed to report the clinical, virological, viral genomic, and immunological features of two previously vaccinated and mAb-treated survivors of Ebola virus disease in the Democratic Republic of the Congo who developed second episodes of disease months after initial discharge, ultimately complicated by fatal meningoencephalitis associated with viral persistence.

Methods: In this case report study, we describe the presentation, management, and subsequent investigations of two patients who developed recrudescent Ebola virus disease and subsequent fatal meningoencephalitis. We obtained data from epidemiological databases, Ebola treatment units, survivor programme databases, laboratory datasets, and hospital records. Following national protocols established during the 2018-20 outbreak in the Democratic Republic of the Congo, blood, plasma, and cerebrospinal fluid (CSF) samples were collected during the first and second episodes of Ebola virus disease from both individuals and were analysed by molecular (quantitative RT-PCR and next-generation sequencing) and serological (IgG and IgM ELISA and Luminex assays) techniques.

Findings: The total time between the end of the first Ebola virus episode and the onset of the second episode was 342 days for patient 1 and 137 days for patient 2. In both patients, Ebola virus RNA was detected in blood and CSF samples during the second episode of disease. Complete genomes from CSF samples from this relapse episode showed phylogenetic relatedness to the genome sequenced from blood samples collected from the initial infection, confirming in-host persistence of Ebola virus. Serological analysis showed an antigen-specific humoral response with typical IgM and IgG kinetics in patient 1, but an absence of an endogenous adaptive immune response in patient 2.

Interpretation: We report the first two cases of fatal meningoencephalitis associated with Ebola virus persistence in two survivors of Ebola virus disease who had received vaccination and mAb-based treatment in the Democratic Republic of the Congo. Our findings highlight the importance of long-term monitoring of survivors, including continued clinical, virological, and immunological profiling, as well as the urgent need for novel therapeutic strategies to prevent and mitigate the individual and public health consequences of Ebola virus persistence.

Funding: Ministry of Health of the Democratic Republic of the Congo, Institut National de Recherche Biomédicale, Infectious Disease Rapid Response Reserve Fund, US Centers for Disease Control and Prevention, French National Research Institute for Development, and WHO.

Published by Elsevier Ltd.

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Conflict of interest statement

Declaration of interests We declare no competing interests.

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• Published: 15 September 2021

Resurgence of Ebola virus in 2021 in Guinea suggests a new paradigm for outbreaks

• Alpha Kabinet Keita   ORCID: orcid.org/0000-0003-4377-341X 1 , 2   na1 ,
• Fara R. Koundouno 3 , 4   na1 ,
• Martin Faye 5   na1 ,
• Ariane Düx 6   na1 ,
• Julia Hinzmann 4 , 7 , 8   na1 ,
• Haby Diallo 1 ,
• Ahidjo Ayouba 2 ,
• Frederic Le Marcis   ORCID: orcid.org/0000-0001-8302-0864 1 , 2 , 9 ,
• Barré Soropogui 3 ,
• Kékoura Ifono 3 , 4 ,
• Moussa M. Diagne 5 ,
• Mamadou S. Sow 1 , 10 ,
• Joseph A. Bore 3 , 11 ,
• Sebastien Calvignac-Spencer   ORCID: orcid.org/0000-0003-4834-0509 6 ,
• Nicole Vidal 2 ,
• Jacob Camara 3 ,
• Mamadou B. Keita 12 ,
• Annick Renevey 4 , 7 ,
• Amadou Diallo 5 ,
• Abdoul K. Soumah 1 ,
• Saa L. Millimono 3 , 4 ,
• Almudena Mari-Saez 6 ,
• Mamadou Diop 5 ,
• Ahmadou Doré 3 ,
• Fodé Y. Soumah 10 ,
• Kaka Kourouma 12 ,
• Nathalie J. Vielle 4 , 13 ,
• Cheikh Loucoubar 5 ,
• Ibrahima Camara 1 ,
• Karifa Kourouma 3 , 4 ,
• Giuditta Annibaldis 4 , 13 ,
• Assaïtou Bah 3 ,
• Anke Thielebein 4 , 7 ,
• Meike Pahlmann 4 , 7 ,
• Steven T. Pullan 8 , 11 ,
• Miles W. Carroll 8 , 11 ,
• Joshua Quick 14 ,
• Pierre Formenty   ORCID: orcid.org/0000-0002-9482-5411 15 ,
• Anais Legand 15 ,
• Karla Pietro 16 ,
• Michael R. Wiley 16 , 17 ,
• Noel Tordo 18 ,
• Christophe Peyrefitte 5 ,
• John T. McCrone   ORCID: orcid.org/0000-0002-9846-8917 19 ,
• Andrew Rambaut   ORCID: orcid.org/0000-0003-4337-3707 19 ,
• Youssouf Sidibé 20 ,
• Mamadou D. Barry 20 ,
• Madeleine Kourouma 20 ,
• Cé D. Saouromou 20 ,
• Mamadou Condé 20 ,
• Moussa Baldé 10 ,
• Moriba Povogui 1 ,
• Sakoba Keita 21 ,
• Mandiou Diakite 22 , 23 ,
• Mamadou S. Bah 22 ,
• Amadou Sidibe 9 ,
• Dembo Diakite 10 ,
• Fodé B. Sako 10 ,
• Fodé A. Traore 10 ,
• Georges A. Ki-Zerbo 13 ,
• Philippe Lemey   ORCID: orcid.org/0000-0003-2826-5353 24 ,
• Stephan Günther   ORCID: orcid.org/0000-0002-6562-0230 4 , 7 , 13 ,
• Liana E. Kafetzopoulou 4 , 7 , 24 ,
• Amadou A. Sall 5 ,
• Eric Delaporte 2 , 25 ,
• Sophie Duraffour 4 , 7 , 13   na2 ,
• Ousmane Faye 5   na2 ,
• Fabian H. Leendertz   ORCID: orcid.org/0000-0002-2169-7375 6   na2 ,
• Martine Peeters 2   na2 ,
• Abdoulaye Toure 1 , 12   na2 &
• N’. Faly Magassouba 3   na2  

Nature volume  597 ,  pages 539–543 ( 2021 ) Cite this article

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• Ebola virus
• Epidemiology

Seven years after the declaration of the first epidemic of Ebola virus disease in Guinea, the country faced a new outbreak—between 14 February and 19 June 2021—near the epicentre of the previous epidemic 1 , 2 . Here we use next-generation sequencing to generate complete or near-complete genomes of Zaire ebolavirus from samples obtained from 12 different patients. These genomes form a well-supported phylogenetic cluster with genomes from the previous outbreak, which indicates that the new outbreak was not the result of a new spillover event from an animal reservoir. The 2021 lineage shows considerably lower divergence than would be expected during sustained human-to-human transmission, which suggests a persistent infection with reduced replication or a period of latency. The resurgence of Zaire ebolavirus from humans five years after the end of the previous outbreak of Ebola virus disease reinforces the need for long-term medical and social care for patients who survive the disease, to reduce the risk of re-emergence and to prevent further stigmatization.

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At least 30 outbreaks of Ebola virus disease (EVD) have been identified since the late 1970s, the most severe of which affected Guinea, Sierra Leone and Liberia from December 2013 to June 2016 1 , 2 . Guinea experienced a new outbreak of EVD in 2021, which started in Gouéké—a town about 200 km away from the epicentre of the 2013–2016 outbreak. The probable index case was a 51-year-old nurse, an assistant of the hospital midwife in Gouéké. On 21 January 2021, she was admitted to hospital in Gouéké suffering from headache, asthenia, nausea, anorexia, vertigo and abdominal pain. She was diagnosed with malaria and salmonellosis and was released two days later. Feeling ill again once at home, she attended a private clinic in Nzérékoré (40 km away) and visited a traditional healer, but died three days later. In the week after her death, her husband—as well as other family members who attended her funeral—fell ill, and four of them died. They were reported as the first suspect cases by the national epidemic alert system on 11 February. On 12 February, blood was taken from two suspect cases admitted to hospital in Nzérékoré. On 13 February, both of these patients were confirmed to have EVD by the laboratory in Guéckédou, which used a commercial real-time polymerase chain reaction with reverse transcription (qRT–PCR) assay (RealStar Filovirus Screen Kit, Altona Diagnostics). On 13 February, the husband of the index case—who travelled more than 700 km from Gouéké to Conakry, the capital city of Guinea, for treatment—was admitted to the Centre de Traitement Epidémiologique (CTEpi) in Nongo, Ratoma Commune. He presented with fever, nausea, asthenia, abdominal pain and lumbar pain and was strongly suspected to have EVD. A blood sample was analysed on the same day and was found to be positive for Ebola Zaire ( Zaire ebolavirus ; EBOV) according to the GeneXpert molecular diagnostic platform (Xpert Ebola test, Cepheid) and by an in-house qRT–PCR assay. Laboratory confirmation of EVD in the three suspect cases led to the official declaration of the epidemic on 14 February. By 5 March, 14 confirmed cases and 4 probable cases of EVD had been identified, leading to 9 deaths—including 5 confirmed cases as reported by the Agence Nationale de la Sécurité Sanitaire (ANSS) of Guinea. After a period of 25 days without new cases, two new cases were reported around Nzérékoré on 1 and 3 April, and on 19 June 2021 the outbreak was declared to be over. In total, 16 confirmed cases were reported, among which 12 people died.

Genomic characterization of the virus that caused the 2021 epidemic of EVD in Guinea was of immediate importance to public health. First, because diagnostic tools, therapeutics and vaccines with proven effectiveness in recent EVD outbreaks—such as in Guinea (2013–2016) and in the Equateur and North-Kivu/Ituri provinces of the Democratic Republic of the Congo (DRC) (2018–2020)—have primarily been developed for EBOV 3 , 4 , 5 . Second, to identify whether the outbreak resulted from a new zoonotic transmission event or from the resurgence of a viral strain that had circulated in a previous EBOV outbreak: it is known that EBOV can persist in the bodily fluids of patients who have survived EVD and can be at the origin of new transmission chains 6 , 7 , 8 . Although the Xpert Ebola test was developed to detect only EBOV strains and the in-house qRT–PCR assay uses a probe that is specifically designed to detect EBOV 9 , additional confirmation by sequence analysis was sought by targeting a short fragment in the viral protein 35 region of the sample from the patient who was hospitalized in Conakry. The phylogenetic tree (Supplementary Fig. 1 ) underscores that this highly conserved region can discriminate between Ebola virus species, and analysis confirmed that the virus that caused the new outbreak was of the species Zaire ebolavirus . This confirmed that available vaccines and the vast majority of molecular-diagnostic tools and therapeutics could be immediately applied.

To gain further insight into the genomic make-up of the viruses causing this outbreak, 11 complete or near-complete (greater than 95% recovery) and 8 partial (greater than 65% recovery) genomic sequences from 12 of the 14 confirmed cases were obtained by 3 different laboratories using different next-generation sequencing technologies (Table 1 ). To facilitate the public-health response and the evaluation of existing medical countermeasures, sequencing results were made publicly available on 12 March through joint posting ( https://virological.org/c/ebolavirus/guinea-2021/44 ). Blood and swab samples from 14 patients with confirmed EVD, sampled from 12 February to 4 March, were processed by the following methods: hybridization capture technology and sequencing on Illumina iSeq100, an amplicon-based protocol with EBOV-specific primer pools and sequencing on MinION (Oxford Nanopore Technologies (ONT)), and a hybrid-capture-based approach using a probe panel that included EBOV-specific targets followed by TruSeq exome enrichment, as previously described 5 . The data generated between the three groups were pooled and the sequence that had the highest quality was chosen for each patient. This enabled us to reconstruct 12 high-quality EBOV genomes that covered 82.9–99.9% of the reference genome (KR534588) (Table 1 ). The consensus EBOV sequences with the highest genome recovery (greater than 82.9%) from 12 different patients were used in further analyses.

Maximum likelihood phylogenetic reconstruction places the 12 genomes from the 2021 outbreak of EVD in Guinea as a single cluster among the EBOV viruses that were responsible for the 2013–2016 outbreak in West Africa (Figs. 1 , 2 ). The genomes from the 2021 outbreak share 10 substitutions (compared with KJ660346) that were accumulated during the 2013–2016 outbreak, including the A82V marker mutation for human adaptation in the glycoprotein that arose when the virus spread to Sierra Leone 11 , 12 . These patterns provide strong evidence of a direct link to human cases from the 2013–2016 outbreak rather than a new spillover from an animal reservoir. The 2021 lineage is nested within a clade that predominantly consists of genomes sampled from Guinea in 2014 (Fig. 2 ). The branch by which the 2021 cluster diverges from the previous outbreak exhibits only 12 substitutions, which is far fewer than would be expected from the evolution of EBOV during 6 years of sustained human-to-human transmission (Fig. 3 ). Using a local molecular-clock analysis, we estimate a 6.4-fold (95% highest posterior density (HPD) interval: 3.3-fold, 10.1-fold) lower rate along this branch. For comparison, we also estimate a 5.5-fold (1.6-fold, 10.8-fold) lower rate along the branch leading to the 2016 cases, which were linked to a patient who survived the disease and in whom the virus persisted for more than 500 days 7 , 13 . Rather than a constant long-term low evolutionary rate, some degree of latency or dormancy during persistent infection seems to be a more likely explanation for the low divergence of the genomes from the 2021 epidemic. We tested whether the 12 genomes from the 2021 epidemic, which were sampled over a time period of less than one month, contained sufficient temporal signal to estimate the time to most recent common ancestor (tMRCA) (Supplementary Fig. 2 ); however, we did not identify statistical support for sufficient divergence accumulation over this short timescale. We therefore calibrated our analysis using an evolutionary rate that reflects EBOV evolution under sustained human-to-human transmission (as estimated by the local molecular-clock analysis). This resulted in a tMRCA estimate of 22 January 2021 (95% HPD interval: 29 December 2020, 10 February 2021).

Most clades for single or multiple closely related outbreaks are collapsed and internal node support is proportional to the size of the internal node circles. The clades or tip circles are labelled with the locations and years of the outbreaks, and coloured according to the (first) year of detection.

A colour gradient (from purple to green for increasing divergence) is used to colour the tip circles. The 2021 genomes are shown with a larger circle in yellow.

This plot relates to the tree shown in Fig. 2. The regression is exclusively fitted to genomes sampled between 2014 and 2015. The same colours are used for the data points as in Fig. 2 . The dashed yellow lines highlight how the 2021 data points deviate from the relationship between sampling time and sequence divergence. According to this relationship, about 95 substitutions (95% prediction interval: 88–101) are expected on the branch ancestral to the 2021 cluster, whereas only 12 are inferred on this branch.

These results open up a new perspective on the relatively rare observation of EBOV re-emergence. It is assumed that all known filovirus outbreaks in humans are the result of independent zoonotic transmission events from bat reservoir species or from intermediate or amplifying hosts such as apes and duikers 6 . Here we clearly show that, even almost five years after the declaration of the end of an epidemic, new outbreaks could also be the result of transmission from humans who were infected during a previous epidemic. The viruses from the 2021 outbreak fall within the lineage of EBOV viruses obtained from humans during the 2014–2016 outbreak; as such, it is very unlikely that this new outbreak has an animal origin or is the result of a new cross-species transmission with the same lineage that remained latent in this natural host, which in that scenario would be at the basis of the West African cluster. The limited genomic divergence between 2014–2015 and 2021 is compatible with a slow long-term evolutionary rate. However, a relatively long phase of latency might be more likely than continuous slow replication. Independent of the mechanistic explanation, the virus most probably persisted at a low level in a human who had survived previous infection. Plausible scenarios of EBOV transmission to the index case include: sexual transmission by exposure to EBOV in semen from a male survivor; contact with body fluids from a survivor who had a relapse of symptomatic EVD (for example during healthcare—the index case was a healthcare worker); or relapse of EVD in the index case—although she was not known to have been infected previously, she could have had an asymptomatic or pauci-symptomatic EBOV infection during the previous outbreak. A detailed investigation of the family of the index case by anthropologists revealed that she was not known to have had EVD previously, nor were her husband or close relatives. However, among more distantly related family, 25 individuals had EVD during the previous outbreak. Only five survived, although the index case apparently had no recent contacts with this part of the family. Consultation of the hospital registers in Gouécké showed that all patients seen by the index case in January 2021 were in good health and were still in good health in March 2021. However, the index case also performed informal consultations outside the hospital environment, which could not be verified. An alternative scenario is that the nurse was not the actual index case, but was part of a small, unrecognized chain of human-to-human transmission in this area of Guinea. However, the diversity of the currently available genomes is limited, and molecular-clock analysis suggests a recent tMRCA, with a mean estimate close to the time that the nurse was first hospitalized and a 95% HPD boundary around the beginning of the year. This provides some reassurance that the outbreak was detected early.

The 2013–2016 outbreak in West Africa was the largest and most complex recent outbreak of EBOV, and involved more than 28,000 cases, 11,000 deaths and an estimated 17,000 survivors, mostly in Guinea, Liberia and Sierra Leone 2 . This large outbreak provided new information about the disease itself as well as about the medical, social and psychological implications for patients who survived the disease 14 , 15 , 16 . It was also possible to estimate, to some extent, the proportions of asymptomatic or pauci-symptomatic infections and to identify their role in specific unusual transmission chains 17 , 18 , 19 . Although the main route of human-to-human transmission of EBOV is direct contact with infected bodily fluids from symptomatic or deceased patients, some transmission chains in this outbreak were associated with viral persistence in semen 3 . Several studies demonstrated viral persistence in more than 50% of male survivors at 6 months after discharge from Ebola treatment units (ETU), and the maximum duration of persistence in semen has been reported to be up to 500–700 days after ETU discharge in a small number of male EVD survivors 9 , 20 , 21 , 22 . Transmission through other bodily fluids (such as breast milk and cervicovaginal fluids) is also suspected 8 , 23 , 24 , 25 . Furthermore, some immunological studies among survivors suggest a continuous or intermittent EBOV antigenic stimulation due to persistence of an EBOV reservoir in some survivors 26 , 27 , although this was not confirmed in another study 28 . Cases of relapse of EVD have also been sporadically reported and could be the origin of large transmission chains, as recently reported in the North-Kivu outbreak in DRC 29 . For example, the presence of EBOV RNA, 500 days after ETU discharge, in the breast milk of a woman who was not pregnant when she developed EVD has recently been reported. She attended the hospital owing to complications at 8 months of pregnancy, and a breast milk sample that was taken 1 month after delivery tested positive for EBOV RNA 9 . These examples illustrate that healthcare workers can be exposed to EBOV when taking care of patients who survived EVD but have an unrecognized relapse of their infection. The 2021 outbreak now highlights that viral persistence and reactivation is not limited to a two-year period, but can also occur on much longer timescales with late reactivation.

Active genomic surveillance has already shown the resurgence of previous strains in other outbreaks of the disease. For example, two EBOV variants circulated simultaneously within the same region during the recent 2020 outbreak in Equateur province, DRC 30 . Moreover, strains from the two consecutive outbreaks in Luebo, DRC, in 2007 and 2008, are also so closely related that it now seems difficult to exclude that the epidemic observed in 2008 was due to a resurgence event from patient who survived EVD in the 2007 outbreak 31 , 32 . However, the limited genomic sampling does not allow for a formal test of this hypothesis.

Although the majority of EVD outbreaks remained limited both in the number of cases and in geographic spread, the two largest outbreaks in West Africa (December 2013–June 2016) and in eastern DRC (August 2018–June 2020) infected thousands of individuals over wide geographic areas, leading to large numbers of EVD survivors. This means that the risk of resurgence is higher than ever before. Continued surveillance of EVD survivors is therefore warranted to monitor the reactivation and relapse of EVD infection and the potential presence of the virus in bodily fluids. This work and associated communications must be conducted with the utmost care for the wellbeing of EVD survivors. During the 2013–2016 outbreak in Guinea, patients who survived EVD had a mixed experience after discharge from ETUs. On the one hand, they were considered as heroes by non-governmental organizations and became living testimonies of a possible recovery 33 , 34 . On the other hand, they experienced different forms of stigmatization, such as rejection by family and friends, refusal of involvement in collective work, loss of jobs and housing, and sometimes self-isolation from social life and workplaces 35 . The human origin of the 2021 EVD outbreak, and the associated shift in our perception of EBOV emergence, call for careful attention to survivors of the disease. The concern that survivors will be stigmatized as a source of danger should be a matter of scrupulous attention 36 . This is especially true for the area of Gouécké, which is only 9 km away from Womey—a village that is emblematic of the violent reaction of the population towards the EVD response team during the 2013–2016 epidemic 37 .

Since the 2013–2016 EVD outbreak in Western Africa, genome sequencing has become a major component of the response to outbreaks 10 , 38 , 39 , 40 , 41 . The establishment of in-country sequencing and the building of capacity enabled a timely characterization of EBOV strains in the 2021 outbreak in Guinea. In addition to the importance of appropriate healthcare measures focused on survivors, the late resurgence of the virus also highlights the urgent need for further research into potent antiviral agents that can eradicate the latent virus reservoir in patients with EVD, and into efficient vaccines that provide long-term protection. In parallel, vaccination could also be considered to boost protective antibody responses in survivors of the disease 27 . The vaccination of populations in areas with previous EBOV outbreaks could also be promoted to prevent secondary cases.

Ethics statement

Diagnostic specimens were collected as part of the emergency response from the Ministry of Health of Guinea, and therefore consent for sample collection was waived. All preparation of samples for sequencing, genomic analysis and data analysis was performed on anonymized samples identifiable only by their laboratory or epidemiological identifier.

Confirmation of Ebola virus species by sequence analysis of the VP35 fragment at CERFIG

Viral RNA was extracted from 140 µl of whole blood collected from samples from the patient hospitalized in Conakry, using the Nuclisens kit (Biomerieux) and following the manufacturer’s instructions. Amplification of a small fragment of the VP35 region was attempted in a semi-nested PCR with a modified protocol as previously described 4 . First-round VP35 PCR products from positive samples were barcoded and pooled using the Native Barcoding Kit EXP-NBD104 (ONT). Sequencing libraries were generated from the barcoded products using the Genomic DNA Sequencing Kit SQK-LSK109 (ONT) and were loaded onto a R9 flow cell on a MinION (ONT). Genetic data were collected for 1 h. Basecalling, adapter removal and demultiplexing of .fastq files were performed with MinKNOW, v.4.1.22.  Fastq reads >Q11 were used for mapping a virus database with the Genome Detective tool ( https://www.genomedetective.com/app/typingtool/virus/ ). The generated consensus sequence was used for further analysis. For phylogenetic inference, we retrieved one sequence per outbreak from the haemorrhagic fever virus (HFV) database to which we added the newly generated VP35 sequence of the new outbreak. Phylogenetic analyses were performed using maximum likelihood methods using IQ-TREE with 1,000 bootstraps for branch support 42 , 43 . The general time-reversible (GTR) model plus a discrete gamma distribution were used as nucleotide substitution models.

Full-length genome sequencing of the new Ebola viruses

Genome sequencing at cerfig.

Whole-genome sequencing was attempted on viral extracts for samples that were positive for EBOV glycoprotein (GP) and nucleoprotein (NP) on the GeneXpert molecular diagnostic platform (Xpert Ebola Assay) with the GP and NP of Zaire ebolavirus . We extracted full nucleic acid using the QIAamp Viral RNA Mini Kit (Qiagen). After DNase treatment with TURBO DNA-free Kit (Ambion) and clean-up with RNA Clean & Concentrator Kit (Zymo Research), RNA was converted to double-stranded cDNA (ds-cDNA) using the SuperScript IV First-Strand Synthesis System (Invitrogen) and NEBNEXT mRNA Second Strand Synthesis Module (New England Biolabs). The resulting ds-cDNA was enzymatically fragmented with NEBNext dsDNA Fragmentase (New England Biolabs) and converted to dual indexed libraries with the NEBNext Ultra II DNA Library Prep Kit for Illumina (New England Biolabs) and NEBNext Multiplex Oligos for Illumina (New England Biolabs). To enrich EBOV in the libraries, we performed two rounds of hybridization capture (16 h at 65 °C) with custom-made biotinylated RNA baits (120 nucleotides, 2-fold tiling; Arbor Biosciences) covering representative genomes for Zaire ebolavirus (KC242801), Sudan ebolavirus (KC242783), Reston ebolavirus (NC_004161), Taï Forest ebolavirus (NC_014372), Bundibugyo ebolavirus (KC545395) and Marburg marburgvirus (FJ750956), following the myBaits Hybridization Capture for Targeted NGS protocol (v.4.01). After the second round, capture products were quantified using the Qubit 3.0 Fluorometer with Qubit dsDNA HS Assay Kit (Invitrogen), and pooled in equimolar amounts for sequencing on an Illumina iSeq using iSeq 100 i1 Reagents (2 × 150 cycles). Sequencing reads were filtered (adapter removal and quality filtering) with Trimmomatic 44 (settings: LEADING:30 TRAILING:30 SLIDINGWINDOW:4:30 MINLEN:40), merged with ClipAndMerge ( https://github.com/apeltzer/ClipAndMerge ), and mapped to the Zaire ebolavirus RefSeq genome (NC_002549) using BWA-MEM 45 . Mapped reads were sorted and deduplicated with SortSam and MarkDuplicates from the Picard suite (Broad Institute, Picard; http://broadinstitute.github.io/picard ). We generated consensus sequences using Geneious Prime 2020.2.3 ( https://www.geneious.com ), in which unambiguous bases were called when at least 90% of at least 20 unique reads were in agreement (20×, 90%). For samples with few mapped reads (0001, 0002, 0010, 0030), we also called a consensus at 2×, 90% and 5×, 90%.

Genome sequencing at PFHG

Sequencing at PFHG was performed using a mobile MinION facility deployed by BNITM to Guinea at the beginning of March 2021. A total of 13 EBOV-positive initial diagnostic samples processed at the Laboratoire des Fièvres Hémorragiques Virales de Gueckédou, the Laboratoire Régional de l’Hôpital de Nzérékoré were used for sequencing. If RNAs from diagnostic procedures performed by the peripheral laboratories was not sent to PFHG, samples were inactivated and RNA was extracted from 50 µl for whole blood EDTA, 70 μl of plasma from EDTA blood or from 140 µl of wet swabs using the QIAamp Viral RNA Mini Kit (Qiagen) following the manufacturer’s instructions. Tiled primers generating overlapping products combined with a highly multiplexed PCR protocol were used for amplicon generation 10 . At start of deployment, three different primer pools (V3 or pan_10_EBOV, V4 or pan_EBOV and Zaire-PHE or EBOV-Zaire-PHE) were tested and results were combined for the optimal recovery of consensus. A new primer pool V5 (EBOV-Makona-V5) was further designed and implemented to increase consensus recovery. Primer pools V3, V4 and V5 were designed by the ARTIC network and Zaire-PHE primer pools by Public Health England (PHE). For V3, 62 primers were used, while for V4 and V5, 61 primers pairs were used, to amplify products of around 400 nt in length. For Zaire-PHE, 71 primer pairs were used to amplify products of around 350 nt in length for the approximately 20 kb viral genome. All primer pools used can be found in Supplementary Table 1 . The multiplex PCR was performed as described by the most up-to-date ARTIC protocol for nCoV-2019 amplicon sequencing (nCoV-2019 sequencing protocol V3 (LoCost) V.3 ( https://artic.network/ncov-2019 ), adapted to include the EBOV-specific primer sets. In brief, RNA was directly used for cDNA synthesis using the LunaScript RT SuperMix (New England Biolabs) and the cDNA generated was used as template in the multiplex PCR, which was performed in two reaction pools using Q5 Hot Start DNA Polymerase (New England Biolabs). The resulting amplicons from the two PCR pools were pooled in equal volumes and the pooled amplicons were diluted 1:10 with nuclease-free water.

Sequencing libraries were prepared, barcoded and multiplexed using the Ligation Sequencing Kit (SQK-LSK109) from ONT combined with the Native Expansion pack (EXP-NDB104, EXP-NBD114, EXP-NBD196) following the ARTIC Network’s library preparation protocol (nCoV-2019 sequencing protocol v3 (LoCost) V.3 ( https://artic.network/ncov-2019 )). For the preparation of fewer than 11 samples, each sample was prepared in multiples to achieve the library concentration required for sequencing. In brief, the diluted pooled amplicons were end-repaired using the Ultra II End Prep Module (New England Biolabs) followed by barcode ligation using the Blunt/TA Ligase Master Mix and one unique barcode per sample. Equal volumes from each native barcoding reaction were pooled and subject to bead clean-up using 0.4× AMPure beads. The pooled barcoded amplicons were quantified using the Qubit Fluorometer (Thermo Fisher Scientific) and AMII adapter ligation was performed using the Quick T4 DNA Ligase (New England Biolabs) followed by an additional bead clean-up. The adaptor-ligated barcoded amplicon pool was quantified using the Qubit Fluorometer (Thermo Fisher Scientific) aiming for a minimum recovery of 15 ng sequencing library to load onto the flow cell.

Sequencing libraries were sequenced using R9.4.1 Flow Cells (FLO-MIN106D, ONT) on the Mk1C device (ONT) using MinKNOW v.21.02.2 with real-time high accuracy base-calling and stringent demultiplexing (minimum barcoding score = 60). Within the barcoding options, barcoding on both ends and mid-read barcodes were both switched on. Reads were demultiplexed and binned in a barcode specific folder only if a barcode above the minimum barcoding score was identified on both read ends and if mid-read barcodes were not identified. Sequencing runs were stopped after around 24 h, and base-calling was allowed to finish before data handling.

Bioinformatics data analysis was performed as per the ARTIC protocol using a combination of the ARTIC EBOV ( https://artic.network/ebov/ebov-bioinformatics-sop.html ) and ARTIC SARS-CoV-2 ( https://artic.network/ncov-2019/ncov2019-bioinformatics-sop.html ) pipelines. A few minor modifications to the ARTIC bioinformatics protocol were incorporated. The two initial steps described, base-calling with Guppy and demultiplexing, were omitted as these were both done on the Mk1C device in real-time during the sequencing run; subsequently, the bioinformatics analysis was initiated from the read-filtering step (ARTIC Guppyplex). In brief, the ARTIC Guppyplex program was used to collect reads for each barcode into a single fastq file, in the presence of a length filter to remove chimeric reads. Reads were filtered based on length with a minimum (option: --min-length) and maximum (option: --max-length) length cut-off based on the amplicon size used (For V3, V4 and V5 primer pools: --min-length 400 and --max-length 700, for Zaire-PHE primer pool: --min-length 350 and --max-length 650). The quality check was omitted because only reads with a quality score of greater than 7 were processed. After merging and filtering, the ARTIC MinION pipeline was used to obtain the consensus sequences. The data were normalized to 200 and, using the --scheme-directory option, the pipeline was directed to the respective primer scheme used for each barcode. Reads were aligned to the NCBI reference KJ660347 ( Zaire ebolavirus isolate H.sapiens-wt/GIN/2014/Makona-Gueckedou-C07) for data generated using V3, V4, and V5 primer pools and to NC_002549.1 ( Zaire ebolavirus isolate Ebola virus/H.sapiens-tc/COD/1976/Yambuku-Mayinga) for data generated using Zaire-PHE primer pools.

Sequencing at IPD

Viral RNA was extracted from 140 µl of whole blood samples using the QIAamp Viral RNA Mini Kit (Qiagen) according to the manufacturer’s instructions and eluted in nuclease-free water to a final volume of 60 µl. Extracted RNA was tested using qRT–PCR as previously described 46 . In brief, the DNA library was prepared and enriched using the Illumina RNA Prep with Enrichment (L) Tagmentation kit (Illumina) according to the manufacturer’s recommendations with a pan viral probe panel that included EBOV-specific targets 5 . The purified libraries were pooled and sequenced on the Illumina MiSeq platform using the MiSeq Reagents Kit v3 (Illumina) according to the manufacturer’s instructions. Illumina sequence reads were quality trimmed by Prinseq-lite and consensus EBOV genome sequences were generated using an in-house de novo genome assembly pipeline.

Phylogenetic analysis of full-length genome sequences

Phylogenetic inference.

The new EBOV genome sequences were embedded in different datasets for subsequent analyses. For phylogenetic reconstruction, we use a Zaire Ebola virus dataset consisting of 55 representative genomes from previous outbreaks and a Makona virus dataset consisting of 1,065 genomes sampled from Guinea, Sierra Leone and Liberia between 2014 and 2015. Multiple sequence alignment was performed using mafft 47 . We identified 6 T-to-C mutations in the genome from patient 11 that were indicative of mutations induced by adenosine deaminases acting on RNA. According to previous recommendations 48 , we masked these positions in this genome in all further analyses. Maximum likelihood trees were reconstructed using IQ-TREE under the GTR model with gamma (G) distributed rate variation among sites 49 . Temporal divergence plots of genetic divergence from the root of phylogenies against sampling time were constructed using TempEst 50 . To construct the temporal divergence plot for the Guinean 2021 genome data, we used a tree reconstructed under an HKY+G model.

Local molecular-clock model analysis

We used BEAST to fit a local molecular-clock model to a dataset consisting of 1,020 dated Makona virus genomes and one of the 2021 genomes (patient 1) 51 , 52 . We specified a separate rate on the tip branch for this genome as well as on the tip branch for a genome in a 2016 outbreak. We used the Skygrid coalescent model as a flexible nonparametric tree prior and an HKY+G substitution model 53 .

Guinea 2021 tMRCA estimation

Temporal signal was evaluated using the BETS procedure 54 . We estimated a slightly lower log marginal likelihood for a model that uses tip dates (−26,063.6) compared to a model that assumes sequences are sampled at the same time (−26,062.1). These BEAST analyses were performed using an exponential growth model, a strict molecular-clock model and an HKY+G substitution model. We specified a lognormal prior with a mean of 1 and a standard deviation of 5 on the population size and a Laplace prior with a scale of 100 on the growth rate.  Default priors were used for all other parameters. For the estimation of divergence time, we used a normal prior on the substitution rate with a mean of 0.001 and a standard deviation of 0.00004 based on the background EBOV rate estimated by the local molecular-clock analysis.

Reporting summary

Further information on research design is available in the  Nature Research Reporting Summary linked to this paper.

Data availability

Sequencing results were made publicly available on 12 March 2021 through joint posting on https://virological.org/c/ebolavirus/guinea-2021/44 . The sequences generated at CERFIG have been deposited to GitHub under project link https://github.com/kabinet1980/Ebov_Guinea2021/blob/main/EBOV_Guinea_2021_genomes_CERFIG.fasta and at the European Nucleotide Archive (ENA) under accession code PRJEB43650 . The sequences generated at PFHVG have been deposited to GitHub under project link https://github.com/PFHVG/EBOVsequencing and the genome sequences for the two samples at IPD are available at https://drive.google.com/drive/folders/14dfGdNjWw17TkjrEQKLCrwlJ4WBBHI6K . Genome sequences are also available at the NCBI GenBank under accession codes  ERX5245591 to ERX5245598 ; MZ424849 to MZ424862 ; MZ605320 and MZ605321 .

Code availability

All the codes for the analyses presented in this paper, including the analysis pipeline, is described in detail in Methods and is available in published papers and public websites or, for in-house pipelines, is available upon reasonable request from the corresponding author.

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Acknowledgements

We thank the ANSS and the Ministry of Health of the Republic of Guinea, the healthcare workers (medical doctors, nurses and laboratory technicians) from the treatment centres in Nzérékoré and Nongo, Conakry; the laboratory personnel in Guékédou, INSP (Conakry) and CERFIG (Conakry). CERFIG also acknowledges J. Gogarten and bioinformatics support from RKI. The UK Health Security Agency would like to thank Oxford Nanopore Technologies for the donation of reagents and equipment to support the setting up of the sequencing capacity at PFHG. BNITM thanks the ARTIC Network ( https://artic.network/ ). The work of CERFIG and TransVIHMI was supported in part by grants from the EBO-SURSY Project funded by the European Union, International Mixt Laboratory ‘RESPIRE’ of IRD (Institut de Recherche pour le Developpement), Montpellier Université d’Excellence (EBOHEALTH; I-Site MUSE, ANR-16-IDEX-0006) and Institut National de la Santé et de la Recherche Médicale (INSERM)/REACTing (REsearch and ACTion targeting emerging infectious diseases). The work of the RKI was partly funded by the German Ministry of Health ‘Global Protection Program’ project TRICE. F.L.M. received funding through the program ‘EBOVAC3 Bringing a prophylactic Ebola vaccine to licensure’ funded by Innovative Medicine Initiative (grant agreement number 800176) and run by London School of Hygiene and Tropical Medicine and INSERM. The work of PFHG and BNITM was supported by the German Federal Ministry of Health through support of the WHO Collaborating Centre for Arbovirus and Hemorrhagic Fever Viruses at the BNITM (agreement ZMV I1-2517WHO005), and through the Global Health Protection Programme (GHPP, agreements ZMV I1-2517GHP-704 and ZMVI1-2519GHP704), and by the Coalition for Epidemic Preparedness Innovations (CEPI). The work of BNITM and the UK Health Security Agency was further supported by the Research and Innovation Programme of the European Union under Horizon 2020 grant agreement no. 871029-EVA-GLOBAL. The European Mobile Laboratory (EMLab) coordinated by BNITM is a technical partner of the WHO Global Outbreak Alert and Response Network (GOARN) and the deployment of EMLab experts and sequencing capacities to Guinea was coordinated and supported by the GOARN Operational Support Team at WHO/HQ and the WHO country office in Guinea. The research leading to these results has received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 725422-ReservoirDOCS). The ARTIC Network receives funding from the Wellcome Trust through project 206298/Z/17/Z. P.L. acknowledges support by the Research Foundation – Flanders (‘Fonds voor Wetenschappelijk Onderzoek – Vlaanderen’, G066215N, G0D5117N and G0B9317N).

Author information

These authors contributed equally: Alpha K. Keita, Fara R. Koundouno, Martin Faye, Ariane Düx, Julia Hinzmann

These authors jointly supervised this work: Sophie Duraffour, Ousmane Faye, Fabian Leendertz, Martine Peeters, Abdoulaye Toure, N’Faly Magassouba

Authors and Affiliations

Centre de Recherche et de Formation en Infectiologie de Guinée (CERFIG), Université de Conakry, Conakry, Guinea

Alpha Kabinet Keita, Haby Diallo, Frederic Le Marcis, Mamadou S. Sow, Abdoul K. Soumah, Ibrahima Camara, Moriba Povogui & Abdoulaye Toure

TransVIHMI, Montpellier University/IRD/INSERM, Montpellier, France

Alpha Kabinet Keita, Ahidjo Ayouba, Frederic Le Marcis, Nicole Vidal, Eric Delaporte & Martine Peeters

Laboratoire du Projet des Fièvres Hémorragiques de Guinée (PFHG), Conakry, Guinea

Fara R. Koundouno, Barré Soropogui, Kékoura Ifono, Joseph A. Bore, Jacob Camara, Saa L. Millimono, Ahmadou Doré, Karifa Kourouma, Assaïtou Bah & N’. Faly Magassouba

Bernhard Nocht Institute for Tropical Medicine (BNITM), Hamburg, Germany

Fara R. Koundouno, Julia Hinzmann, Kékoura Ifono, Annick Renevey, Saa L. Millimono, Nathalie J. Vielle, Karifa Kourouma, Giuditta Annibaldis, Anke Thielebein, Meike Pahlmann, Stephan Günther, Liana E. Kafetzopoulou & Sophie Duraffour

Institut Pasteur de Dakar (IPD), Dakar, Senegal

Martin Faye, Moussa M. Diagne, Amadou Diallo, Mamadou Diop, Cheikh Loucoubar, Christophe Peyrefitte, Amadou A. Sall & Ousmane Faye

Robert Koch Institute (RKI), Berlin, Germany

Ariane Düx, Sebastien Calvignac-Spencer, Almudena Mari-Saez & Fabian H. Leendertz

German Center for Infection Research (DZIF), Partner Site Hamburg–Lübeck–Borstel–Riems, Hamburg, Germany

Julia Hinzmann, Annick Renevey, Anke Thielebein, Meike Pahlmann, Stephan Günther, Liana E. Kafetzopoulou & Sophie Duraffour

UK Health Security Agency, National Infection Service, Porton Down, Salisbury, UK

Julia Hinzmann, Steven T. Pullan & Miles W. Carroll

Ecole Nationale Supérieure de Lyon, Lyon, France

Frederic Le Marcis & Amadou Sidibe

Hôpital National Donka, Service des Maladies Infectieuses et Tropicales, Conakry, Guinea

Mamadou S. Sow, Fodé Y. Soumah, Moussa Baldé, Dembo Diakite, Fodé B. Sako & Fodé A. Traore

Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Joseph A. Bore, Steven T. Pullan & Miles W. Carroll

Institut National de Santé Publique de Guinée (INSP), Conakry, Guinea

Mamadou B. Keita, Kaka Kourouma & Abdoulaye Toure

World Health Organization (WHO), Conakry, Guinea

Nathalie J. Vielle, Giuditta Annibaldis, Georges A. Ki-Zerbo, Stephan Günther & Sophie Duraffour

Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK

Joshua Quick

Health Emergencies Program, World Health Organization (WHO), Geneva, Switzerland

Pierre Formenty & Anais Legand

PraesensBio, Lincoln, NE, USA

Karla Pietro & Michael R. Wiley

University of Nebraska Medical Center, Omaha, NE, USA

Michael R. Wiley

Institut Pasteur de Guinée, Conakry, Guinea

Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK

John T. McCrone & Andrew Rambaut

Hôpital Régional de Nzérékoré, Nzérékoré, Guinea

Youssouf Sidibé, Mamadou D. Barry, Madeleine Kourouma, Cé D. Saouromou & Mamadou Condé

Agence Nationale de Sécurité Sanitaire, Conakry, Guinea

Sakoba Keita

Direction Nationale des Laboratoires, Ministère de la Santé, Conakry, Guinea

Mandiou Diakite & Mamadou S. Bah

Université Gamal Abdel Nasser de Conakry, Conakry, Guinea

Mandiou Diakite

Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium

Philippe Lemey & Liana E. Kafetzopoulou

Infectious Diseases Departement, University Hospital Montpellier, Montpellier, France

Eric Delaporte

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A.A.S., A.K.K., A. Toure, E.D., F.H.L., F.R.K., L.E.K., M. Peeters, N.’F.M., O.F., S.D. and S.G. conceived and designed the study. A.B., A. Doré, A.K.K., A.K.S., A.M.-S., A.S., B.S., C.D.S., D.D., F.L., F.L.M. F.R.K., F.Y.S., F.A.T., F.B.S., G.A., H.D., I.C., J.A.B., J.C., K.I., Kaka Kourouma, Karifa Kourouma, S.L.M., M.B., M.B.K., M.C., M.D.B., M.K., M. Povogui, M.S.S., N.V., N.J.V., S.D. and Y.S. collected data and/or performed medical examinations and/or laboratory diagnostics. A.A., A. Düx, A. Renevey, B.S., H.D., J.A.B., J.H., K.I., K.P., M.F., M.M.D. and S.C.-S. performed sequencing and/or sequence validation. A.A., A. Rambaut, J.H., J.T.M., L.E.K., M.R.W., P.L., S.C.-S. and S.D. performed formal phylogenetic analysis. A. Diallo, C.L., F.L.M. and M. Diop performed data analysis. E.D., F.H.L., M. Peeters, M.W.C., S.D. and S.G. acquired funding. F.H.L., K.P., M.R.W. and S.C.-S. provided reagents. A.K.K., A.L., A. Thielebein, A. Toure, C.P., E.D., F.H.L., G.A.K.-Z., J.Q., M. Diakite, M. Pahlmann, M. Peeters, M.S.B., M.W.C., N.’F.M., N.T., P.F., S.D., S.G., S.K. and S.T.P. implemented the project. A. Düx, A.K.K., M. Peeters and S.C.-S. wrote the first draft of the manuscript. A.A.S., A. Düx, A.K.K., A.M.-S., A. Renevey, A. Rambaut, A. Toure, E.D., F.H.L., F.L., F.L.M. L.E.K., M.F., M.M.D., M. Peeters, N.’F.M., O.F., P.L., S.C.-S., S.D. and S.G. wrote and edited the manuscript. All authors read and approved the contents of the manuscript.

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Correspondence to Alpha Kabinet Keita .

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Keita, A.K., Koundouno, F.R., Faye, M. et al. Resurgence of Ebola virus in 2021 in Guinea suggests a new paradigm for outbreaks. Nature 597 , 539–543 (2021). https://doi.org/10.1038/s41586-021-03901-9

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Interdisciplinarity and Infectious Diseases: An Ebola Case Study

* E-mail: [email protected]

Affiliation Odum School of Ecology and Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, Georgia, United States of America

Affiliation DIVERSITAS, Muséum National d'Histoire Naturelle, Paris, France

Affiliation UMI IRD/UPMC 209 UMMISCO, Bondy, France

Affiliation INRA, UR346 Épidémiologie Animale, Saint Genès Champanelle, France

Affiliation UMR 5290 IRD-CNRS-Université de Montpellier, Centre IRD de Montpellier, Montpellier, France

Affiliations UMR 5290 IRD-CNRS-Université de Montpellier, Centre IRD de Montpellier, Montpellier, France, CESAB—Centre de Synthèse et d’Analyse sur la Biodiversité, Aix-en-Provence, France

Affiliation EcoHealth Alliance, New York, New York, United States of America

Affiliation Biology Program, Bard College, Annandale-on-Hudson, New York, United States of America

Affiliation Fondazione Edmund Mach, Department of Biodiveristy and Molecular Ecology, San Michele all’Adige (TN), Italy

Affiliation Facultad de Medicina Veterinaria Zootecnia, Universidad Nacional Autónoma de México, Ciudad Universitaria, México, Distrito Federal, México

Affiliation Institut Pasteur, Viral Populations and Pathogenesis, CNRS UMR 3569, Paris, France

Affiliation Centre de recherche de la Tour du Valat, Le Sambuc, Arles, France

Affiliation Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, Georgia, United States of America

• Vanessa O. Ezenwa, 
• Anne-Helene Prieur-Richard, 
• Benjamin Roche, 
• Xavier Bailly, 
• Pierre Becquart, 
• Gabriel E. García-Peña, 
• Parviez R. Hosseini, 
• Felicia Keesing, 
• Annapaola Rizzoli, 

Published: August 6, 2015

• https://doi.org/10.1371/journal.ppat.1004992
• Reader Comments

Citation: Ezenwa VO, Prieur-Richard A-H, Roche B, Bailly X, Becquart P, García-Peña GE, et al. (2015) Interdisciplinarity and Infectious Diseases: An Ebola Case Study. PLoS Pathog 11(8): e1004992. https://doi.org/10.1371/journal.ppat.1004992

Editor: Glenn F. Rall, The Fox Chase Cancer Center, UNITED STATES

Copyright: © 2015 Ezenwa 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 study is a contribution of the "Disentangling the Linkages between Biodiversity and Emerging Infectious Diseases" (BIODIS) working group. BIODIS is supported by the French Foundation for Biodiversity Research (FRB), the DIVERSITAS-ecoHEALTH project, and the French Centre for Synthesis and Analysis of Biodiversity (CESAB). CESAB receives financial support from DIVERSITAS and Fondation Total. VOE received support from a US Fulbright Scholar Award; BR and JFG were funded by an “Investissement d’Avenir” Laboratoire d’Excellence Centre d’Etude de la Biodiversité Amazonienne Grant (ANR-10-LABX-25-01); and GEGP received a postdoctoral fellowship from FRB/CESAB. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

High-profile epidemics such as Ebola, avian influenza, and severe acute respiratory syndrome (SARS) repeatedly thrust infectious diseases into the limelight. Because the emergence of diseases involves so many factors, the need for interdisciplinary approaches to studying emerging infections, particularly those originating from animals (i.e., zoonoses), is frequently discussed [ 1 – 4 ]. However, effective integration across disciplines is challenging in practice. Ecological ideas, for example, are rarely considered in biomedical research, while insights from biomedicine are often neglected in ecological studies of infectious diseases. One practical reason for this is that researchers in these fields focus on vastly different scales of biological organization ( Fig 1 ), which are difficult to bridge both intellectually and methodologically. Nevertheless, integration across biological scales is increasingly needed for solving the complex problems zoonotic diseases pose to human and animal well-being. Motivated by current events, we use Ebola virus as a case study to highlight fundamental questions about zoonoses that can be addressed by integrating insights and approaches across scales.

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Each level of the hierarchy reflects an increase in organizational complexity, with each level being primarily composed of the previous level’s basic units. Middle panels illustrate how the study of interactions between infectious disease agents and their hosts differs across the biomedical, public health, and ecological sciences. Specifically, biomedical sciences typically focus on lower- and medium-scale levels of biological organization (e.g., molecules, genes, and organs). In contrast, public health and ecological sciences typically focus on medium- and higher-scale levels of organization (individual, population, community, ecosystem, and environment). The filled circles and solid lines connecting the circles illustrate key cross scale biological interactions studied within each field. The right panel shows example knowledge gaps that can emerge from the “typical” segregation of research activities across the three fields. To better integrate our understanding of the causes and consequences of zoonotic infectious diseases, researchers must begin focusing on these types of missing links.

https://doi.org/10.1371/journal.ppat.1004992.g001

Ebola Severity: A Cell-to-Ecological Community Perspective

Zaire ebolavirus (EBOV), the virus responsible for the 2014 Ebola outbreak in West Africa, causes a deadly haemorrhagic disease in humans with case fatality rates ranging from 60%–88% [ 5 ]. Although well-known for its lethality, Ebola severity is variable at the individual level; some people die of infection, some survive, and some never develop symptoms [ 6 – 8 ]. Asymptomatic infection is poorly understood but may have important implications for how EBOV spreads. After a 1996 outbreak in Gabon, one study found that 45% of household contacts of symptomatic patients never developed disease symptoms despite becoming infected with the virus and mounting EBOV-specific immune responses [ 7 ]. Intriguingly, asymptomatic infection might also result from contact between humans and animals. As an example, a 2010 serological survey of over 4,000 people from 220 villages in Gabon found that 15% of people overall, and 19% of those in forested regions, had EBOV-specific immunoglobulin G (IgG) antibodies [ 9 ]. Detection of EBOV-specific T cell responses in a subset of IgG+ individuals corroborated that these individuals were exposed to EBOV. Based on the known epidemiology of Ebola in Gabon, the authors ruled out human-to-human transmission as a sufficient explanation for the high antibody prevalence. Instead, they hypothesized that human–animal contact, specifically human contact with noninfectious virus particles in the environment (e.g., by eating or handling fruit contaminated with the saliva of infected bats), may have triggered virus-specific immune responses. If the immune responses detected in Gabon are protective against subsequent EBOV infection, large-scale phenomena occurring at the level of the ecological community might interact with molecular and cellular-level processes to influence the severity of any given Ebola outbreak.

Using an epidemiological model, Bellan et al. [ 10 ] showed that accounting for asymptomatic infections that induce protective immunity reduced Ebola incidence projections for Liberia by 50%. Ultimately, the relative frequency of protective asymptomatic infections determines the size of this effect. Although the model was predicated on asymptomatic infection occurring during human-to-human transmission, asymptomatic cases that arise from environmental exposure, as hypothesized by Becquart et al. [ 9 ], could have similar dampening effects on epidemic spread. The frequency of such environmental exposure would depend on the animal community in a region. If certain bat species are the natural reservoirs of EBOV [ 11 ], their presence, relative abundance, and behaviour could all affect the frequency with which humans come into contact with them and thereby develop “environmentally-induced” immune protection. Of course, human contact with bats also triggers Ebola outbreaks [ 12 ], so understanding the context in which human–bat contact is protective (e.g., induces asymptomatic infection and immunity) rather than hazardous (e.g., causes symptomatic infection and epidemic spread) requires investigating phenomena occurring in both humans and bats, from the drivers and frequency of contact between humans, bats, and other relevant species to the characteristics of host cell–virus interactions upon contact.

Ecosystem Dynamics, Viral Evolution, and Human Epidemics

The Ebola outbreak in West Africa and punctuated outbreaks in Central Africa since the 1970s raise fundamental questions about what drives disease spillover to humans. Ebola outbreaks are not limited to human populations. Wildlife die-offs occur routinely before or during human epidemics, indicating that the virus circulates in a range of other mammal species, including great apes and forest antelopes [ 13 – 16 ]. Even though these species are not considered natural reservoirs, circulation of EBOV in these animals still has implications for human disease. First, human contact with these species can directly trigger disease outbreaks [ 17 ]. Second, these animals might affect spillover risk by influencing rates of virus evolution. Phylogenetic analysis of EBOV in great apes [ 18 ] suggests that genetic variation can accumulate rapidly during EBOV transmission in these populations. Importantly, virus evolution in animal hosts may facilitate the emergence of strains that spread more efficiently to humans or that cause more severe disease.

Although unknown for EBOV, the idea that virus circulation in wild species can drive changes that impact human–virus interactions has support for other RNA viruses such as SARS coronavirus and influenza A virus (see Table 1 ) [ 19 , 20 ]. Given evidence from these other viruses, understanding if and how animal hosts affect EBOV evolution is crucial. Doing this requires studies that connect large-scale environmental and ecosystem processes to small-scale genetic and molecular processes. For example, food web or habitat structure may determine the diets of target wildlife species, and host nutrition could affect rates of infection, virus replication, and shedding. Likewise, contact rates among species determine levels of cross species virus transmission, which may influence virus mutation or recombination rates. These examples, though speculative, highlight how cross scale chains of events might influence disease emergence in humans.

https://doi.org/10.1371/journal.ppat.1004992.t001

Towards a More Integrative Future

The Ebola outbreak in West Africa reminds us that zoonotic diseases continue to be a major threat. The benefits of cross scale research are evident for several high-profile zoonoses ( Table 1 ). Nevertheless, this type of work is far from the norm, and successful integration of research approaches across vastly different biological scales remains challenging. A first step toward greater integration involves student training. Training programs in infectious disease typically focus on a single or narrow range of biological scales, but more crosscutting approaches are needed. Training grants focused on multiscale literacy in infectious disease research should be a priority for funding agencies, for example. Professional societies could also lead the way by sponsoring workshops, symposia, and other events on integration across disciplines. The involvement of professional societies has the added benefit of allowing infectious disease researchers to expand their perspectives beyond their years of formal training. Updating our collective mind-set in these and other ways will put us in a much better position to tackle the next zoonotic disease threat.

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Ebola virus disease (EVD), formerly known as Ebola haemorrhagic fever, is a severe, often fatal illness affecting humans and other primates.

The virus is transmitted to people from wild animals (such as fruit bats, porcupines and non-human primates) and then spreads in the human population through direct contact with the blood, secretions, organs or other bodily fluids of infected people, and with surfaces and materials (e.g. bedding, clothing) contaminated with these fluids.

The average EVD case fatality rate is around 50%. Case fatality rates have varied from 25% to 90% in past outbreaks.

The first EVD outbreaks occurred in remote villages in Central Africa, near tropical rainforests. The 2014–2016 outbreak in West Africa was the largest and most complex Ebola outbreak since the virus was first discovered in 1976. There were more cases and deaths in this outbreak than all others combined. It also spread between countries, starting in Guinea then moving across land borders to Sierra Leone and Liberia.

It is thought that fruit bats of the Pteropodidae family are natural Ebola virus hosts.

The incubation period, that is, the time interval from infection with the virus to onset of symptoms, is from 2 to 21 days. A person infected with Ebola cannot spread the disease until they develop symptoms.

Symptoms of EVD can be sudden and include: fever, fatigue, muscle, pain, headache, and sore throat. This is followed by vomiting, diarrhea, rash, symptoms of impaired kidney and liver function, and in some cases internal and external bleeding (e.g. oozing from the gums, blood in the stools). Laboratory findings include low white blood cell and platelet counts and elevated liver enzymes.

It can be difficult to clinically distinguish EVD from other infectious diseases such as malaria, typhoid fever and meningitis. A range of diagnostic tests have been developed to confirm the presence of the virus.

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Epidemiology

The first cases of Ebola virus infection were reported in Zaire (now known as the Democratic Republic of the Congo [DRC]) in 1976. There were 318 cases and 280 deaths, an 88% case fatality rate. [24] Report of an International Commission. Ebola haemorrhagic fever in Zaire, 1976. Bull World Health Organ. 1978;56(2):271-93. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2395567/pdf/bullwho00439-0113.pdf http://www.ncbi.nlm.nih.gov/pubmed/307456?tool=bestpractice.com Transmission in this outbreak was traced back to the use of contaminated needles in an outpatient clinic at Yambuku Mission Hospital. Since then, frequent outbreaks have occurred in Central and Western Africa. [25] Peterson AT, Bauer JT, Mills JN. Ecologic and geographic distribution of filovirus disease. Emerg Infect Dis. 2004 Jan;10(1):40-7. https://wwwnc.cdc.gov/eid/article/10/01/03-0125_article http://www.ncbi.nlm.nih.gov/pubmed/15078595?tool=bestpractice.com

The most common species of Ebola virus responsible for outbreaks is the Zaire ebolavirus , the second most common species being the Sudan ebolavirus .

The Zaire ebolavirus was responsible for the outbreak that started in West Africa in 2014 and finished in 2016. It was first reported in March 2014, and is the largest outbreak since the virus was first discovered in 1976. Genetic sequencing has shown that the virus isolated from infected patients in the 2014 outbreak is 97% similar to the virus that first emerged in 1976. [26] Centers for Disease Control and Prevention. Advanced molecular detection and Liberian Ebola. Mar 2019 [internet publication]. https://www.cdc.gov/amd/stories/ebola.html ​ It has also been responsible for smaller outbreaks in the DRC since then. The  Zaire ebolavirus has a reported case fatality rate of up to 90% in previous outbreaks. [4] Leroy EM, Gonzalez JP, Baize S. Ebola and Marburg haemorrhagic fever viruses: major scientific advances, but a relatively minor public health threat for Africa. Clin Microbiol Infect. 2011 Jul;17(7):964-76. https://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.2011.03535.x/full http://www.ncbi.nlm.nih.gov/pubmed/21722250?tool=bestpractice.com Direct comparison of case fatality rates between different Ebola treatment centers and outbreaks should be interpreted with caution as many variables can introduce bias and skew even large cohort data. The case fatality rate during the 2014 outbreak was up to 64.3% in hospital admissions, [18] WHO Ebola Response Team. Ebola virus disease in West Africa: the first 9 months of the epidemic and forward projections. N Engl J Med. 2014 Oct 16;371(16):1481-95. https://www.nejm.org/doi/full/10.1056/NEJMoa1411100#t=article http://www.ncbi.nlm.nih.gov/pubmed/25244186?tool=bestpractice.com falling to 31.5% in some treatment centers in West Africa, [27] Ansumana R, Jacobsen KH, Idris M, et al. Ebola in Freetown area, Sierra Leone - a case study of 581 patients. N Engl J Med. 2015 Feb 5;372(6):587-8. https://www.nejm.org/doi/full/10.1056/NEJMc1413685 http://www.ncbi.nlm.nih.gov/pubmed/25539447?tool=bestpractice.com and around 20% in patients managed outside West Africa. [28] New York Times. How many Ebola patients have been treated outside of Africa? January 2015 [internet publication]. https://www.nytimes.com/interactive/2014/07/31/world/africa/ebola-virus-outbreak-qa.html

In contrast to this, the Sudan ebolavirus has a lower case fatality rate of 39% to 65% in previous outbreaks, with the largest outbreak occurring in 2000 in Uganda (425 cases). [4] Leroy EM, Gonzalez JP, Baize S. Ebola and Marburg haemorrhagic fever viruses: major scientific advances, but a relatively minor public health threat for Africa. Clin Microbiol Infect. 2011 Jul;17(7):964-76. https://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.2011.03535.x/full http://www.ncbi.nlm.nih.gov/pubmed/21722250?tool=bestpractice.com [29] World Health Organization. Disease outbreak news. ​Ebola disease caused by Sudan ebolavirus – Uganda. January 2023 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON433 There has only been one outbreak of Bundibugyo ebolavirus : in 2007 in western Uganda, and this outbreak had a case fatality rate of 25%. [6] Roddy P, Howard N, Van Kerkhove MD, et al. Clinical manifestations and case management of Ebola haemorrhagic fever caused by a newly identified virus strain, Bundibugyo, Uganda, 2007-2008. PLoS One. 2012 Dec 28;7(12):e52986. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0052986 http://www.ncbi.nlm.nih.gov/pubmed/23285243?tool=bestpractice.com

Recent outbreaks

2022: an outbreak of  Sudan ebolavirus  disease in Uganda started on September 20, 2022 and was declared over on January 11, 2023, with a total of 142 confirmed cases and 55 deaths (case fatality rate 39%). This was the first outbreak caused by  Sudan ebolavirus in Uganda since 2012.​​ [29] World Health Organization. Disease outbreak news. ​Ebola disease caused by Sudan ebolavirus – Uganda. January 2023 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2023-DON433

2022: one case was reported in the DRC on August 21, 2022 in the North Kivu province. The case, a 46-year old woman, died after being hospitalized for 23 days for symptoms thought to be related to her known comorbidities. [30] World Health Organization. Disease outbreak news: Ebola virus disease - Democratic Republic of the Congo. Aug 2022 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2022-DON404 No additional confirmed or probable cases were identified, and the outbreak was declared over on September 27, 2022.

2022: the fourteenth outbreak in the DRC started on April 23, 2022 in the Équateur province and was declared over on July 4, 2022, with a total of 5 cases and 5 deaths (case fatality rate 100%). It was the third outbreak in the province in the last four years. [31] World Health Organization. Ebola virus disease - Democratic Republic of the Congo. Jul 2022 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2022-DON398

2021: the thirteenth outbreak in the DRC started on October 8, 2021 in the North Kivu province and was declared over on December 16, 2021, with a total of 11 cases and 9 deaths (case fatality rate 82%). [32] World Health Organization. Disease outbreak news. Ebola virus disease – Democratic Republic of the Congo. Dec 2021 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2021-DON351

2021: a small outbreak was reported in Guinea on February 14, 2021 and was declared over on June 19, 2021, with a total of 23 cases and 12 deaths (case fatality rate 52%). This was the first outbreak in Guinea since the 2014-2016 West Africa outbreak. [33] World Health Organization. Disease outbreak news. Ebola virus disease – Guinea. Jun 2021 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2021-DON328

2021: the twelfth outbreak in the DRC started on February 7, 2021 in the North Kivu province and was declared over on May 3, 2021, with a total of 12 cases and 6 deaths (case fatality rate 50%). [34] World Health Organization. Disease Outbreak News. Ebola - Democratic Republic of the Congo. May 2021 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/2021-DON325

2020: the eleventh outbreak in the DRC started on June 1, 2020 in the Équateur province and was declared over on November 18, 2020, with a total of 130 cases and 55 deaths (case fatality rate 42%). [35] World Health Organization. Disease outbreak news: Ebola virus disease - Democratic Republic of the Congo. Nov 2020 [internet publication]. https://www.who.int/emergencies/disease-outbreak-news/item/ebola-virus-disease-democratic-republic-of-the-congo-draft

2018-2020: the world’s second largest outbreak in the north Kivu and Ituri provinces of the DRC in 2018 was declared over on June 25, 2020, with a total of 3481 cases and 2299 deaths (case fatality rate 66%). [36] World Health Organization. Ebola health update: north Kivu/Ituri, DRC, 2018-2020. Jul 2020 [internet publication]. https://www.who.int/emergencies/situations/Ebola-2019-drc-

2018: small outbreak in the DRC with 54 cases and 33 deaths (case fatality rate 61%).​ [2] World Health Organization. Ebola virus disease fact sheet. Apr 2023 [internet publication]. https://www.who.int/news-room/fact-sheets/detail/ebola-virus-disease

2014-2016: the world’s largest outbreak started in the DRC in 2014 and finished in 2016, with over 28,000 cases and 11,000 deaths (case fatality rate 46%). [2] World Health Organization. Ebola virus disease fact sheet. Apr 2023 [internet publication]. https://www.who.int/news-room/fact-sheets/detail/ebola-virus-disease ​​

The WHO declares an outbreak is over when no confirmed or probable cases are detected for a period of 42 days (i.e., twice the maximum incubation period) since the last potential exposure to the last case occurred; however, WHO recommends heightened surveillance and response activities during the 42-day period and for at least 6 months after. [37] World Health Organization. WHO recommended criteria for declaring the end of the Ebola virus disease. Mar 2020 [internet publication]. https://www.who.int/publications/m/item/who-recommended-criteria-for-declaring-the-end-of-the-ebola-virus-disease-outbreak

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Sustainable strategies for Ebola virus disease outbreak preparedness in Africa: a case study on lessons learnt in countries neighbouring the Democratic Republic of the Congo

Caroline s. ryan.

1 WHO Sub-Regional Office for Africa, Nairobi, Kenya

Marie-Roseline D. Belizaire

2 WHO Country Office, Bangui, Central African Republic

Miriam Nanyunja

Olushayo oluseun olu.

3 WHO Country Office, Juba, South Sudan

Yahaya Ali Ahmed

4 WHO Regional Office for Africa, Brazzaville, Congo

Anderson Latt

5 WHO Sub-Regional Office for Africa, Dakar, Senegal

Matthew Tut Kol

6 Africa Centres for Disease Control and Prevention, Addis Ababa, Ethiopia

Bertrand Bamuleke

7 WHO Country Office, Brazzaville, Congo

Jayne Tusiime

Nadia nsabimbona, ishata conteh, shamiso nyashanu, patrick otim ramadan, solomon fisseha woldetsadik, jean-pierre mulunda nkata.

8 WHO Country Office, Bujumbura, Burundi

Jim T. Ntwari

Senya d. nzeyimana, leopold ouedraogo, georges batona, vedaste ndahindwa.

10 WHO Country Office, Kigali, Rwanda

Elizabeth A. Mgamb

9 WHO Country Office, Asmara, Eritrea

Magdalene Armah

Joseph francis wamala, argata guracha guyo, alex yao sokemawu freeman, alexander chimbaru.

11 WHO Country Office, Kampala, Uganda

Innocent Komakech

12 WHO Country Office, Luanda, Angola

Walter M. Firmino

Grace e. saguti.

13 WHO Country Office, Dar Es Salaam, Tanzania

Faraja Msemwa

Shikanga o-tipo.

14 WHO Country Office, Lusaka, Zambia

Precious C. Kalubula

Ngoy nsenga, ambrose otau talisuna, associated data.

Not applicable.

From May 2018 to September 2022, the Democratic Republic of Congo (DRC) experienced seven Ebola virus disease (EVD) outbreaks within its borders. During the 10th EVD outbreak (2018–2020), the largest experienced in the DRC and the second largest and most prolonged EVD outbreak recorded globally, a WHO risk assessment identified nine countries bordering the DRC as moderate to high risk from cross border importation. These countries implemented varying levels of Ebola virus disease preparedness interventions. This case study highlights the gains and shortfalls with the Ebola virus disease preparedness interventions within the various contexts of these countries against the background of a renewed and growing commitment for global epidemic preparedness highlighted during recent World Health Assembly events.

Several positive impacts from preparedness support to countries bordering the affected provinces in the DRC were identified, including development of sustained capacities which were leveraged upon to respond to the subsequent coronavirus disease 2019 (COVID-19) pandemic. Shortfalls such as lost opportunities for operationalizing cross-border regional preparedness collaboration and better integration of multidisciplinary perspectives, vertical approaches to response pillars such as surveillance, over dependence on external support and duplication of efforts especially in areas of capacity building were also identified. A recurrent theme that emerged from this case study is the propensity towards implementing short-term interventions during active Ebola virus disease outbreaks for preparedness rather than sustainable investment into strengthening systems for improved health security in alignment with IHR obligations, the Sustainable Development Goals and advocating global policy for addressing the larger structural determinants underscoring these outbreaks.

Conclusions

Despite several international frameworks established at the global level for emergency preparedness, a shortfall exists between global policy and practice in countries at high risk of cross border transmission from persistent Ebola virus disease outbreaks in the Democratic Republic of Congo. With renewed global health commitment for country emergency preparedness resulting from the COVID-19 pandemic and cumulating in a resolution for a pandemic preparedness treaty, the time to review and address these gaps and provide recommendations for more sustainable and integrative approaches to emergency preparedness towards achieving global health security is now.

From May 2018 to September 2022, the Democratic Republic of Congo (DRC) experienced seven Ebola virus disease (EVD) outbreaks within its borders [ 1 , 2 ]. Observations during the larger among these seven outbreaks showed that the country and most neighboring at-risk countries were not prepared despite lessons learnt from previous experience, not least the unprecedented West Africa EVD outbreak [ 3 – 5 ]. The revised International Health Regulations (IHR 2005) and several international policy frameworks have since been established to guide countries worldwide to build functional emergency preparedness and response capacities for all emergency events of significant threat to humans [ 6 – 13 ] . However, developing the legal and regulatory mechanisms, physical infrastructure, human resources, tools and processes to meet IHR 2005 compliance assumes a foundation of a functional health system [ 14 ]. This is far from the reality in the context of Ebola endemic areas in the DRC and the majority of countries bordering these increasingly habitual events. The coronavirus disease 2019 (COVID-19) pandemic demonstrated to the world that policy guidelines for response capacities, even in high income countries with assumed robust health systems, did not necessarily translate into practice [ 15 ]. In view of the fact that countries in sub-Saharan Africa will continue to carry the burden of endemic and emerging infectious disease outbreaks including EVD outbreaks, it is imperative that lessons learnt from previous preparedness and response efforts to these events are well documented so as to inform future response efforts.

This case study thus highlights some of the gains and shortfalls with the EVD preparedness interventions against the background of the renewed and growing commitment for global epidemic preparedness highlighted during the 73 rd , 74 th and 75 th World Health Assembly (WHA) events [ 16 ] and establishment of a new global hub for pandemic and epidemic intelligence [ 17 ]. Focusing specifically on countries neighbouring the DRC during that country’s tenth and eleventh EVD outbreaks, the findings of this case study were synthesized from various sources such as reports of joint monitoring exercises [ 18 ], simulations [ 19 – 21 ] and field support missions as well as descriptive reports captured during regular telecommunication sessions with country focal points and members of the field teams directly engaged with the coordination and roll out of EVD preparedness activities in priority countries. Many of the authors were also directly engaged in EVD preparedness activities and participated in coordination meetings at regional and country levels that provided insights into the key issues, challenges and lessons learnt from the EVD preparedness in the priority countries.

The tenth and eleventh EVD outbreaks in the DRC (2018–2022)

The most recent outbreak of EVD in the DRC declared on August 21, 2022 is the fifteenth outbreak since the first EVD outbreak was reported in the country and globally in 1976 [ 2 ]. The ninth, eleventh and fourteenth outbreaks occurred in Equateur Province in Western DRC whilst the tenth, twelfth, thirteenth and fifteenth occurred within eastern DRC’s conflict affected Provinces of Ituri, North and South Kivu [ 22 – 26 ]. Among these, the tenth EVD outbreak was the world’s second largest and the first to occur within an active conflict zone, making it the most complex and prolonged experienced in the DRC [ 22 ]. The peak of the tenth outbreak occurred in April 2019 when up to 120 newly confirmed cases were reported weekly [ 22 ]. Over the 23-month period of the tenth outbreak, 29 health areas across 9 health zones in three provinces were affected, namely North and South Kivu and Ituri provinces. A total of 3463 cases including 2280 deaths, 1004 children (29%), 173 health workers, and 1171 recoveries were recorded [ 22 ].

The eleventh EVD outbreak was declared following laboratory confirmation of samples taken during investigation of a suspected cluster of deaths in Equateur Province on June 1, 2020 and prior to the ending of the tenth outbreak [ 26 ]. The nature of this outbreak was low intensity, but cases emerged sporadically across a broad area affecting 42 health areas in 13 of the 18 health zones of the province [ 21 ]. The wide geographical emergence of cases led to concerns of possible new introductions from zoonotic spillover or resurgence from viral persistence or latent infection from previously infected Ebola survivors as almost two thirds of confirmed cases were not registered contacts. From early October 2020 the number of reported cases reduced dramatically, and the outbreak was declared over on November 18, 2020. This outbreak recorded a total of 130 confirmed cases, 55 deaths and 75 recoveries [ 26 ].

The high-risk countries neighbouring the DRC EVD outbreaks

Based on a World Health Organization risk assessment, nine countries sharing borders with the DRC during the tenth EVD outbreak were considered as moderate to high-risk and referred to as “priority countries”. The priority countries were further classified into priority one and two depending on their geographic proximity to the epi-center of the outbreak, volume of cross border movement and shared transport routes. As a result, Burundi, Rwanda, South Sudan and Uganda were identified as priority one countries and Angola, Central African Republic (CAR), Congo, Tanzania and Zambia as priority two.

Further consideration was given to the priority one countries based on their geographic, infrastructural, political and socio-economic contexts as determinants of their respective population vulnerabilities and health system capacities. Uganda had experienced six EVD outbreaks between 2000 and 2019 and demonstrated progressive capacity for detection and containment since the first and largest outbreak occurred in Northern Uganda in 2000 resulting in 224 deaths [ 27 , 28 ]. This was evidenced during the DRC’s tenth EVD outbreak when three confirmed cases were rapidly identified and managed having crossed into Uganda in June 2019 [ 29 ]. South Sudan experienced three EVD outbreaks in 1976, 1979 and 2004 respectively within the former Sudan [ 30 – 32 ]. South Sudan and CAR are both conflict-affected countries experiencing protracted and complex humanitarian crises, internally displaced populations and highly fragile health systems. Communities in the priority countries are socially and economically interconnected and highly mobile across shared borders with the DRC and each other. Political stability in Uganda and Rwanda lend them to support hosting large numbers of refugees and access to cross border health and other public services.

Between October 2018 and December 2019, over 70 million USD was provided by the international donor community to the priority one countries for EVD preparedness [ 33 ]. Efforts to sustain preparedness capacities were retained up until the outbreak was declared over on June 25, 2020 despite dwindling resources. The priority countries updated their EVD National Contingency Plans in late 2019, some adopting a strategy for transitioning capacities developed during EVD preparedness to other public health emergencies. However, with the emergence of COVID-19 in early 2020, funding secured for implementation of 2020 transition plans was mostly repurposed to the COVID-19 response. The key pillars supported under EVD preparedness programmes in these countries were coordination, surveillance at the community, points of entry and health facility levels, laboratory diagnosis, case management, infection prevention and control, risk communications and community engagement, operational support and logistics and preventive vaccination of frontline health workers [ 34 ].

Using the same risk assessment criteria for allocating countries into priority one and two categories for EVD preparedness during the tenth EVD outbreak, the Republic of Congo and CAR were classified as priority one countries during DRC’s eleventh EVD outbreak. Despite their high-risk status and weak preparedness capacities, external funding to support either of these countries for EVD preparedness during the eleventh and fourteenth EVD outbreaks was negligible.

Keys lessons from the EVD preparedness programmes in countries adjacent to the DRC outbreaks

The lessons learnt from the outbreaks captured the benefits of EVD preparedness in the countries bordering the DRC that were at high-risk of cross border transmission during the DRC’s tenth, eleventh and subsequent EVD outbreaks. The reports and experiences also captured several shortfalls in implementation processes. The gaps between building detection and response capacities in a sustainable manner in alignment with global policy frameworks as stipulated under Article 44 of the IHR 2005 and other international frameworks are highlighted and discussed.

National and local capacity building during EVD outbreaks as a more sustainable approach to emergency preparedness

Experiences from the priority countries showed how national capacities built under several pillar areas were leveraged upon to respond to the COVID-19 response. Capacities in national and sub-national multi-sectoral coordination were strengthened, the need for institutionalization of infection prevention and control was realized and a heightened appreciation for the role of risk communication and community engagement in public health was acknowledged [ 28 , 33 , 34 ]. In South Sudan, surveillance capacities developed during EVD preparedness resulted in the early detection and aversion of a yellow fever outbreak in November 2018 [ 34 ]. Rwanda and Uganda reported that surveillance strengthened in the high-risk districts under EVD preparedness was easily translated to the COVID-19 response [ 35 ]. The extent to which the EVD preparedness investments mitigated the impact of subsequent outbreaks and the COVID-19 pandemic in the priority countries is an area requiring further exploration and quantification.

However, in some cases during these EVD outbreaks, some countries continue to depend on external intervention and a significant proportion of donor funding to conduct a response. For example, following emergence of the DRC’s eleventh EVD outbreak on June 1, 2020 in Equateur Province, little evidence of local capacity developed during the ninth outbreak, occurring in the same location less than two years earlier, was evident. Most of the response pillar areas had to be re-established and re-operationalized by external partners resulting in a delayed response. A similar situation was observed during the EVD outbreak in Guinea in 2021 and to a less extent in Beni in 2020 and 2021. One pillar area where the gap in national capacity is most evident is in critical care specific to managing EVD patients. In the majority of EVD outbreaks critical patient management was conducted by external partner organizations due to inadequately trained healthcare workers in critical care capacities within the health sector of sub-Saharan African countries [ 36 ].

Building local capacity from the existing pool of experienced human resources in countries and communities [ 36 ] or sharing this capacity between countries in the region was not fully exploited as a more sustainable investment in EVD preparedness at that time. While Rwanda sent a national team to Beni during the tenth EVD outbreak to acquire patient management capacity, CAR was unable to do this due to lack of funding during the DRCs eleventh outbreak. The gap in investment into building national critical care capacity became particularly evident during the COVID-19 response in several countries in the region [ 37 , 38 ] when deployment of scarce international emergency medical teams was necessitated.

Community participation and perceptions in EVD preparedness in the countries neighbouring DRC

During EVD preparedness interventions in the priority countries, the role of the local community was mostly limited to rumour tracking, community volunteer roles such as social mobilization activities, health promotion and community surveillance. There were lost opportunities to capture gender disaggregated data, community perspectives and suggestions on how existing local capacities and knowledge could be identified, leveraged upon and actively engaged in broader roles in preparedness and response operations. For example, communities in the DRC and some of the priority countries argued that large deployments of international personnel during EVD outbreaks undermined local expertise and little opportunity remained for integration and sustaining the skills developed during preparedness and response after these personnel left [ 39 ].

EVD preparedness interventions during the tenth outbreak benefitted from increasing integration between epidemiology, public health and clinical medicine with the social sciences (more specifically the discipline of anthropology) to understanding the social, cultural and political pathways of Ebola emergence and the perceptions of the community and individuals to the disease and their acceptance of the associated public health interventions. An increase in activities supporting and implementing participatory and evidence-based field work was observed in the neighbouring countries during the tenth EVD outbreak providing more nuanced understandings to inform more effective interventions [ 40 , 41 ]. While anthropology is not a new discipline in Ebola response [ 42 , 43 ], the utilization of anthropological findings to the extent of informing policies, programme planning and approaches to a broader array of interventions beyond communications and community engagement is yet to be fully realized as was evident from the preparedness activities in countries neighbouring the DRC.

Quality of EVD preparedness and response capacity building interventions

EVD outbreaks are usually accompanied by rapid investment into the response phase allowing little time for formal planning of good quality training programmes. During the preparedness and response phase of these outbreaks, national staff and community volunteers were provided with basic trainings to implement field level activities under several pillar areas. Trainings were largely undertaken by an array of partner agencies in an ad hoc manner using multiple methods such as sensitizations, briefings, orientations, theoretical and practical workshops [ 28 , 33 ]. An independent evaluation of EVD preparedness conducted in Uganda in 2020 identified how on occasions several partners were conducting trainings in the same area with the same theme and objectives [ 35 ]. While duplication is not a new phenomenon in development contexts, more effort is required for its identification and prevention through effective coordination mechanisms. In addition, mapping trainees, evaluating retention of their knowledge or application of the skills transferred in the medium to long term is seldom undertaken. Evidence that capacity is transferred into sustainable outcomes such as employment opportunities within the health system or engagement in other public health emergencies and improved quality of care beyond periods of active EVD response are also lacking.

There were few examples demonstrating effective coordination of EVD preparedness trainings or establishment of formal procedures for reviewing the structure, mode of delivery and quality of the training content, assessing the capacity of the trainers or selection process of the participants. The collaboration between the academic and public health sectors for EVD preparedness capacity in the priority countries during the tenth EVD outbreak was a new development and represented an opportunity for countries to encourage inter-regional partnerships between higher level institutions to ensure institutionalization of training programmes for EVD outbreak preparedness and response.

Increased recognition of the need for sustainable context appropriate research and innovations

The importance of research and development in EVD outbreaks cannot be overemphasized, particularly the development of vaccines and therapies for high impact pathogens including EVD [ 44 ]. The low intensity outbreaks observed during DRC’s eleventh, twelfth, thirteenth and fourteenth EVD outbreaks may have resulted from the roll out of the investigative rVSV-ZEBOV-GP Zaire ebolavirus vaccine during the ninth and tenth outbreaks in these same locations. Studies on the duration of vaccine efficacy are ongoing [ 45 – 47 ]. However, a key concerning observation during these outbreaks, is that while funding to support research and development of experimental therapies and vaccines during EVD outbreaks is high, support to these same communities to access these life-saving and oftentimes unaffordable products after licensing is limited.

Observations show that countries seeking vaccination of high-risk health workers in districts bordering the eleventh, twelfth and thirteenth outbreaks failed to access adequate quantities of the licensed vaccine. Furthermore, little attention was targeted towards local clinical research into homegrown interventions which could reduce mortality in low resource settings. For example, allocation of research funding to explore the contribution of supportive care interventions such as blood volume enhancers including intravenous fluids, colloid and crystalloid solutions, blood transfusion and parenteral nutrition as life-saving interventions in patient management during EVD preparedness was lacking in the DRC and other at-risk countries during the EVD outbreaks.

EVD outbreaks were frequently accompanied by a cascade of medico-technical innovations such as the use of robots to monitor patient body temperatures at airports in some African countries and piloting drones to transport EVD alert samples across the equatorial forests of Equateur Province raising serious safety concerns are some examples. Whilst technological interventions can address gaps in response operations and reduce costs, such innovations need to be informed by public health principles.

Sustainable solutions for EVD case management

When the eleventh EVD outbreak emerged in Equateur Province at the end of May 2020, temporary facilities constructed during the ninth outbreak to isolate and treat patients either no longer existed or were unfit for purpose. This demanded rapid construction of inferior quality structures that were poorly managed in the initial phase of the response due to weak partner co-ordination. In some communities, in addition to fear and stigma, reports of poor patient care of those admitted at the treatment centers translated into additional fear, avoidance to report alerts and resistance to allow access to safe and dignified burial teams to respond to community deaths. Reversing mistrust required considerable time and investment, not only by improving the physical infrastructure and system of care but through intensive community engagement. In the 2021 EVD outbreak in Guinea mistrust remained among communities from bad experiences associated with Ebola Treatment Centers (ETCs) during the West African outbreak (2014–2016) [ 48 ].

The design and materials used to construct ETCs have witnessed several innovative improvements in the past decade. These innovations materialized in response to the need for improved health worker and patient safety, improved comfort and visibility for the patient of their surroundings and for family members, reduced time constraints to monitor and treat patients and a reduction in personal protective equipment (PPE) use and waste management costs without compromising infection prevention. The concept of transit centers introduced in North Kivu during the tenth EVD outbreak using semi-permanent materials as extensions to existing permanent structures helped to buffer community fear.

Building permanent or semi-permanent structures for isolating and treating patients versus temporary structures became an area of considerable debate between donors and countries throughout EVD preparedness efforts in the at-risk countries. The argument for not investing in infrastructural projects lies in the assumption that such projects are highly costly, take time to complete and funds might be misused or diluted into a larger funding pool resulting in a poor-quality product that does not serve the intended purpose. Another argument against permanent structures is that the location of an EVD outbreak cannot be known in advance, therefore constructing permanent buildings in several locations in expectation of a confirmed case is not feasible. Temporary structures are considered suitable to serve the purpose for the duration of the project and pose a lower risk for the investment. However, in practice it has been shown that the cost of constructing and maintaining a temporary ETC is equivalent and (in some cases) more costly to construct and maintain than semi-permanent/permanent structures. Temporary structures inevitably decompose over time due to exposure to weather and represent poor value for money. Many of the at-risk countries expressed preference for semi-permanent/permanent structures or renovation of existing buildings as a more sustainable and cost-effective solution that can be repurposed to general isolation facilities for other infectious diseases following EVD outbreaks. In South Sudan, the semi-permanent structure built during EVD preparedness in 2019 was sustained and continued to be used throughout the COVID-19 response [ 32 ]; this design was adopted for use in other countries such as Burundi.

However, despite attempts to humanize ETC design in recent years, all EVD outbreaks in the DRC between 2018 and 2022 continue to see patients treated in temporary structures. The consensus that emerged is that there is “no one size fits all solution”. Each outbreak evolves and behaves differently and can emerge in a variety of contexts warranting different design options. Decision making processes at country level requires further dialogue and review of case studies from EVD preparedness inclusive of community perspectives.

Integrating EVD readiness into existing health systems and programmes

The large influx of funding and resources associated with epidemics has in the past resulted in the duplication of efforts and implementation of short-term interventions that fail to strengthen country capacity in the longer term often representing missed opportunities. A key lesson from the EVD preparedness in the priority countries was the need to leverage existing health programmes and identify existing systems and use them as entry points for integrating EVD preparedness. This is more pertinent in view of the more recent discovery that latent EVD infections lasting for several years could trigger outbreaks as was seen in the case of the 2020–2021 outbreaks in Guinea [ 50 , 51 ]. This further underscores the need for longer-term and sustainable approaches to EVD preparedness in Africa.

Another example was the need for enhanced integration of EVD surveillance into the Integrated Disease Surveillance and Response (IDSR) system, the primary disease surveillance system for the general population, used in the priority countries. In South Sudan for example, a project approach under EVD preparedness resulted in an EVD alert management system limited to high-risk districts for EVD that ran parallel to the existing IDSR system [ 33 ]. This was acknowledged as a lost opportunity that could have integrated EVD surveillance into nationwide training of health workers and roll out of the third Edition IDSR for all priority infectious diseases to health facilities in the country. Although the detection and aversion of a yellow fever outbreak identified under EVD surveillance was a benefit of the vertical surveillance model described above, the system was not sustained beyond the funding period.

A similar observation was noted for enhancing community surveillance which gained a lot of traction during EVD preparedness, but its momentum waned following withdrawal of Ebola specific funding [ 28 ]. This is largely due to funding reporting mechanisms which demand results on the performance of specific activities under vertical disease programmes within a fixed time frame dictated by the length of the funding period. This approach encourages “new” or duplicated systems that undermine existing systems and resources, particularly the role of the community, that could be leveraged upon. Such lost opportunities justify a need for more coordinated, informed and negotiated planning processes.

Impact of conflict on EVD preparedness in the countries neighbouring DRC

South Sudan and CAR are both conflict-affected countries experiencing protracted and complex humanitarian crises, internally displaced populations and highly fragile health systems. Uganda, Rwanda and Burundi host large numbers of refugees. This presence of internally displaced persons and refugees in the countries undergoing preparedness presented special challenges [ 33 ]. First, implementing preventive interventions such as hand washing was constrained by limited access to water and sanitation facilities in these populations. Second, crowded living conditions made social distancing and isolation of sick family members impracticable in such settings. Third, the weak health services in the displaced population in particular in the conflict affected countries in general constrained effective surveillance, infection prevention and control and other preparedness intervention. Fourth, the insecurity restricted free movement of staff and supplies in the high-risk areas thus limiting the geographic scope of the preparedness interventions in some cases. Nevertheless, South Sudan reported being able to overcome some of these challenges through available opportunities and the use of innovative approaches [ 33 , 34 ].

Cross border collaboration and regional coordination of EVD preparedness efforts

Cross border collaboration and regional coordination of preparedness and response efforts for EVD outbreaks is a critical factor in containing cross border transmission of outbreaks. Observations showed that progress in this preparedness area varied across the neighbouring countries during the tenth and eleventh EVD outbreaks in the DRC. In Uganda and Rwanda, the Ministries of Health successfully organized cross border meetings and signed Memoranda of Understanding for cross border collaboration with their counterparts in the DRC [ 28 ] which facilitated cross border surveillance, sharing of information and timely detection of cross border transmission of infection [ 29 , 35 ]. However, this was not the case in South Sudan largely due to ongoing conflicts and insecurity around the South Sudan/DRC border and the huge distance between the national and sub-national coordination hubs of the two countries. This was a missed opportunity for synchronization of preparedness interventions particularly surveillance, case management and immunization.

Although several regional coordination meetings involving the DRC and the priority countries were held [ 49 ], these were one-off events where plans were initiated but did not translate into ongoing regional coordination of preparedness efforts. A partners’ regional coordination platform based in Nairobi, Kenya was established but towards the end of the tenth EVD outbreak in October 2019 when momentum for EVD preparedness investment was waning. Political will for cross-border and inter-regional coordination efforts was high on government agendas at this point and donors were willing to support ongoing activities to facilitate lessons learned symposiums, cross border simulation exercises and after action reviews. Unfortunately this critical period for reflection on EVD preparedness following the largest and most complex of the DRC outbreaks that posed the highest risk to the sub-region was rapidly overshadowed by the emergence of the COVID-19 response in early 2020.

Reflections on the lessons learned

A recurrent theme that emerged in the lessons learnt from EVD preparedness in countries bordering the DRC EVD outbreaks is a propensity towards implementing short-term vertical interventions during EVD outbreak preparedness and response rather than sustainable investment into strengthening systems for health security in alignment with IHR 2005 obligations, Universal Health Coverage and the Sustainable Development Goals (SDGs).

Since the first recorded EVD outbreaks in 1976, response interventions have been mostly reliant on international emergency funding and expertise. As a result, resources are limited to the timeframe of the outbreak period and withdrawn once the outbreak is declared over. In contexts such as the DRC and its neighbouring countries known to frequently experience or be at high-risk of EVD outbreaks, negligible national investments have been made to establish foundational preparedness elements on which emergency responses can rapidly become operational prior to arrival of external support. Unfortunately, the current approach for supporting EVD preparedness, follow a declared outbreak and is an extension of the response. Also, limiting EVD preparedness support to “operational readiness” after emergence of a nearby outbreak risks undermining the importance and volume of work required to build the foundation of preparedness in countries, particularly in contexts where weak health systems exist. Even more concerning than limiting EVD preparedness support is absence of support for preparedness in high-risk areas bordering outbreaks as observed in relation to the majority of DRC outbreaks following the tenth EVD outbreak. This is particularly concerning for CAR and Congo bordering Equatorial Province in western DRC, where no significant investment towards implementing EVD preparedness has occurred despite experiencing three outbreaks since 2018 across a shared landscape.

While extending EVD response capacities to support preparedness appears to make sense at several levels it has several limitations. In support of the argument, preparedness benefits from being an extension of a response in that having expertise, experience and capacities available during the response can inform and guide inputs and activities required for coordinating preparedness activities simultaneously. Also, the proximity of a response influences increased alert reporting in neighbouring areas due to enhanced awareness and surveillance activities. This also increases willingness of neighbouring countries to engage in preparedness activities and cross-border collaboration and finally it highlights gaps and funding needs. However, when EVD preparedness is limited to being an extension of the response, it falls within the timeline allocated for supporting the response. This does not allow sufficient time to develop national capacities and skills for countries to affect an independent response or generate a baseline of resilience to mitigate future events. Once the outbreak is declared over, support for the response and preparedness efforts initiated in bordering countries is withdrawn leaving these health systems in much the same state as prior to the outbreak. As the DRC’s tenth EVD outbreak phased down in the latter part of 2019, funding for additional EVD contingency plans waned, yet several gaps remained for the priority countries to reach a minimum level of capacity. Another limitation is that when preparedness support is an extension of a response it can become defined by the response, resulting in carbon copied approaches and activities, some of which tend to be reactive in nature allowing little scope to conceptualize more sustainable or context appropriate methods.

Constructing temporary ETCs versus permanent structures in EVD prone contexts is one example highlighted above. If issues such as ETC design, incentive payments to responders, mapping and co-ordination of local capacities, capturing community insight on their understanding and application of EVD preparedness measures and vaccination strategies were explored and resolved at country level outside the urgency of a response environment, analysis of previous case studies and lessons learnt could be more effectively reviewed to inform decision-making and planning processes for future responses.

In the event of public health threats with capacity to cross borders, building core capacities to prevent, detect and implement a public health response is a mandatory requirement of Member States under the revised IHR. However, the renewed commitment for post COVID-19 pandemic preparedness needs to look beyond the confines of a global health security agenda. Other factors such as the social determinants of health, local culture and human behavior are also critical in this regard. Poverty and its associated challenges of poor living conditions, inadequate access to water and sanitation, illiteracy, engagement in alternative means of sourcing food and livelihood such as forest activities and inaccessibility to conventional health services is one example why the poor are increasingly vulnerable to increasing EVD incidence in endemic areas. The global community including governments, regional blocks and development agencies thus need to look beyond the health aspects of EVD outbreaks and focus on the linkages between the social and political determinants of high impact disease emergence.

Some recommendations to inform more sustainable preparedness approaches for future EVD preparedness investments into EVD and other viral hemorrhagic fever (VHF) disease prone contexts have emerged from this case study are outline in Box ​ Box1 1 .

Recommendations

Global health security and health system strengthening are two sides of the same coin. Unfortunately, the lessons learnt from this case study demonstrate that rapid and temporary preparedness and mitigation measures in reaction to EVD outbreaks threatening international borders and regional health security on the Africa continent continue to be the preferred approach to EVD preparedness in high-risk contexts. Hard lessons learnt including those highlighted in this paper should drive advocacy for a shift from reactionary and short-lived interventions towards more sustainable long-term approaches to EVD and emergency preparedness which would build health system resilience in general. A starting point would be for countries including representatives from previously affected communities and global actors to create a space where the much-needed open dialogue can occur to review these and other best practices and lessons learnt around EVD preparedness long before outbreaks occur. From here resolutions, contextual view-points and recommendations can evolve to disentangle recurrent bottlenecks that emerge time and again during EVD response and preparedness. The time for this open dialogue, engagement and inclusive collaboration is now.

Acknowledgements

The authors acknowledge the support of the WHO Country Representatives to Angola, Burundi, CAR, Congo, Rwanda, South Sudan, Tanzania, Uganda and Zambia during the DRCs 10th and 11th EVD outbreaks. The support of the MoHs and partners in these countries is also much appreciated. The authors alone are responsible for the views expressed in this article, which do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated.

Abbreviations

Author contributions

CSR, MRDB, MN and OOO made substantial contributions to the conception of the work, interpretation of data, writing and preparation of the manuscript for submission. YAA, AL, MTK, BB, JT and GES contributed to revising the work. All authors read and approved the final manuscript.

No external funding was provided to undertake the study.

Availability of data and materials

Declarations.

All authors consented in writing to their inclusion in this article for publication.

The authors declare that they have no competing interests.