2020 Ebola virus disease outbreak in Équateur Province, Democratic Republic of the Congo: a retrospective genomic characterisation.

BACKGROUND: The Democratic Republic of the Congo has had 15 Ebola virus disease (EVD) outbreaks, from 1976 to 2023. On June 1, 2020, the Democratic Republic of the Congo declared an outbreak of EVD in the western Équateur Province (11th outbreak), proximal to the 2018 Tumba and Bikoro outbreak and concurrent with an outbreak in the eastern Nord Kivu Province. In this Article, we assessed whether the 11th outbreak was genetically related to previous or concurrent EVD outbreaks and connected available epidemiological and genetic data to identify sources of possible zoonotic spillover, uncover additional unreported cases of nosocomial transmission, and provide a deeper investigation into the 11th outbreak. METHODS: We analysed epidemiological factors from the 11th EVD outbreak to identify patient characteristics, epidemiological links, and transmission modes to explore virus spread through space, time, and age groups in the Équateur Province, Democratic Republic of the Congo. Trained field investigators and health professionals recorded data on suspected, probable, and confirmed cases, including demographic characteristics, possible exposures, symptom onset and signs and symptoms, and potentially exposed contacts. We used blood samples from individuals who were live suspected cases and oral swabs from individuals who were deceased to diagnose EVD. We applied whole-genome sequencing of 87 available Ebola virus genomes (from 130 individuals with EVD between May 19 and Sept 16, 2020), phylogenetic divergence versus time, and Bayesian reconstruction of phylogenetic trees to calculate viral substitution rates and study viral evolution. We linked the available epidemiological and genetic datasets to conduct a genomic and epidemiological study of the 11th EVD outbreak. FINDINGS: Between May 19 and Sept 16, 2020, 130 EVD (119 confirmed and 11 probable) cases were reported across 13 Équateur Province health zones. The individual identified as the index case reported frequent consumption of bat meat, suggesting the outbreak started due to zoonotic spillover. Sequencing revealed two circulating Ebola virus variants associated with this outbreak-a Mbandaka variant associated with the majority (97%) of cases and a Tumba-like variant with similarity to the ninth EVD outbreak in 2018. The Tumba-like variant exhibited a reduced substitution rate, suggesting transmission from a previous survivor of EVD. INTERPRETATION: Integrating genetic and epidemiological data allowed for investigative fact-checking and verified patient-reported sources of possible zoonotic spillover. These results demonstrate that rapid genetic sequencing combined with epidemiological data can inform responders of the mechanisms of viral spread, uncover novel transmission modes, and provide a deeper understanding of the outbreak, which is ultimately needed for infection prevention and control during outbreaks. FUNDING: WHO and US Centers for Disease Control and Prevention.

Geo-Climatic Factors of Malaria Morbidity in the Democratic Republic of Congo from 2001 to 2019.

Background: Environmentally related morbidity and mortality still remain high worldwide, although they have decreased significantly in recent decades. This study aims to forecast malaria epidemics taking into account climatic and spatio-temporal variations and therefore identify geo-climatic factors predictive of malaria prevalence from 2001 to 2019 in the Democratic Republic of Congo. Methods: This is a retrospective longitudinal ecological study. The database of the Directorate of Epidemiological Surveillance including all malaria cases registered in the surveillance system based on positive blood test results, either by microscopy or by a rapid diagnostic test for malaria was used to estimate malaria morbidity and mortality by province of the DRC from 2001 to 2019. The impact of climatic factors on malaria morbidity was modeled using the Generalized Poisson Regression, a predictive model with the dependent variable Y the count of the number of occurrences of malaria cases during a period of time adjusting for risk factors. Results: Our results show that the average prevalence rate of malaria in the last 19 years is 13,246 (1,178,383−1,417,483) cases per 100,000 people at risk. This prevalence increases significantly during the whole study period (p < 0.0001). The year 2002 was the most morbid with 2,913,799 (120,9451−3,830,456) cases per 100,000 persons at risk. Adjusting for other factors, a one-day in rainfall resulted in a 7% statistically significant increase in malaria cases (p < 0.0001). Malaria morbidity was also significantly associated with geographic location (western, central and northeastern region of the country), total evaporation under shelter, maximum daily temperature at a two-meter altitude and malaria morbidity (p < 0.0001). Conclusions: In this study, we have established the association between malaria morbidity and geo-climatic predictors such as geographical location, total evaporation under shelter and maximum daily temperature at a two-meter altitude. We show that the average number of malaria cases increased positively as a function of the average number of rainy days, the total quantity of rainfall and the average daily temperature. These findings are important building blocks to help the government of DRC to set up a warning system integrating the monitoring of rainfall and temperature trends and the early detection of anomalies in weather patterns in order to forecast potential large malaria morbidity events.

Ebola Virus Disease Outbreak - Democratic Republic of the Congo, August 2018-November 2019.

On August 1, 2018, the Democratic Republic of the Congo Ministry of Health (DRC MoH) declared the tenth outbreak of Ebola virus disease (Ebola) in DRC, in the North Kivu province in eastern DRC on the border with Uganda, 8 days after another Ebola outbreak was declared over in northwest Équateur province. During mid- to late-July 2018, a cluster of 26 cases of acute hemorrhagic fever, including 20 deaths, was reported in North Kivu province.* Blood specimens from six patients hospitalized in the Mabalako health zone and sent to the Institut National de Recherche Biomédicale (National Biomedical Research Institute) in Kinshasa tested positive for Ebola virus. Genetic sequencing confirmed that the outbreaks in North Kivu and Équateur provinces were unrelated. From North Kivu province, the outbreak spread north to Ituri province, and south to South Kivu province (1). On July 17, 2019, the World Health Organization designated the North Kivu and Ituri outbreak a public health emergency of international concern, based on the geographic spread of the disease to Goma, the capital of North Kivu province, and to Uganda and the challenges to implementing prevention and control measures specific to this region (2). This report describes the outbreak in the North Kivu and Ituri provinces. As of November 17, 2019, a total of 3,296 Ebola cases and 2,196 (67%) deaths were reported, making this the second largest documented outbreak after the 2014-2016 epidemic in West Africa, which resulted in 28,600 cases and 11,325 deaths.† Since August 2018, DRC MoH has been collaborating with partners, including the World Health Organization, the United Nations Children's Fund, the United Nations Office for the Coordination of Humanitarian Affairs, the International Organization of Migration, The Alliance for International Medical Action (ALIMA), Médecins Sans Frontières, DRC Red Cross National Society, and CDC, to control the outbreak. Enhanced communication and effective community engagement, timing of interventions during periods of relative stability, and intensive training of local residents to manage response activities with periodic supervision by national and international personnel are needed to end the outbreak.

Medical countermeasures during the 2018 Ebola virus disease outbreak in the North Kivu and Ituri Provinces of the Democratic Republic of the Congo: a rapid genomic assessment.

BACKGROUND: The real-time generation of information about pathogen genomes has become a vital goal for transmission analysis and characterisation in rapid outbreak responses. In response to the recently established genomic capacity in the Democratic Republic of the Congo, we explored the real-time generation of genomic information at the start of the 2018 Ebola virus disease (EVD) outbreak in North Kivu Province. METHODS: We used targeted-enrichment sequencing to produce two coding-complete Ebola virus genomes 5 days after declaration of the EVD outbreak in North Kivu. Subsequent sequencing efforts yielded an additional 46 genomes. Genomic information was used to assess early transmission, medical countermeasures, and evolution of Ebola virus. FINDINGS: The genomic information demonstrated that the EVD outbreak in the North Kivu and Ituri Provinces was distinct from the 2018 EVD outbreak in Équateur Province of the Democratic Republic of the Congo. Primer and probe mismatches to Ebola virus were identified in silico for all deployed diagnostic PCR assays, with the exception of the Cepheid GeneXpert GP assay. INTERPRETATION: The first two coding-complete genomes provided actionable information in real-time for the deployment of the rVSVΔG-ZEBOV-GP Ebola virus envelope glycoprotein vaccine, available therapeutics, and sequence-based diagnostic assays. Based on the mutations identified in the Ebola virus surface glycoprotein (GP12) observed in all 48 genomes, deployed monoclonal antibody therapeutics (mAb114 and ZMapp) should be efficacious against the circulating Ebola virus variant. Rapid Ebola virus genomic characterisation should be included in routine EVD outbreak response procedures to ascertain efficacy of medical countermeasures. FUNDING: Defense Biological Product Assurance Office.

2018 Ebola virus disease outbreak in Équateur Province, Democratic Republic of the Congo: a retrospective genomic characterisation.

BACKGROUND: The 2018 Ebola virus disease (EVD) outbreak in Équateur Province, Democratic Republic of the Congo, began on May 8, and was declared over on July 24; it resulted in 54 documented cases and 33 deaths. We did a retrospective genomic characterisation of the outbreak and assessed potential therapeutic agents and vaccine (medical countermeasures). METHODS: We used target-enrichment sequencing to produce Ebola virus genomes from samples obtained in the 2018 Équateur Province outbreak. Combining these genomes with genomes associated with known outbreaks from GenBank, we constructed a maximum-likelihood phylogenetic tree. In-silico analyses were used to assess potential mismatches between the outbreak strain and the probes and primers of diagnostic assays and the antigenic sites of the experimental rVSVΔG-ZEBOV-GP vaccine and therapeutics. An in-vitro flow cytometry assay was used to assess the binding capability of the individual components of the monoclonal antibody cocktail ZMapp. FINDINGS: A targeted sequencing approach produced 16 near-complete genomes. Phylogenetic analysis of these genomes and 1011 genomes from GenBank revealed a distinct cluster, confirming a new Ebola virus variant, for which we propose the name "Tumba". This new variant appears to have evolved at a slower rate than other Ebola virus variants (0·69 × 10-3 substitutions per site per year with "Tumba" vs 1·06 × 10-3 substitutions per site per year without "Tumba"). We found few sequence mismatches in the assessed assay target regions and antigenic sites. We identified nine amino acid changes in the Ebola virus surface glycoprotein, of which one resulted in reduced binding of the 13C6 antibody within the ZMapp cocktail. INTERPRETATION: Retrospectively, we show the feasibility of using genomics to rapidly characterise a new Ebola virus variant within the timeframe of an outbreak. Phylogenetic analysis provides further indications that these variants are evolving at differing rates. Rapid in-silico analyses can direct in-vitro experiments to quickly assess medical countermeasures. FUNDING: Defense Biological Product Assurance Office.