Maladie virale à Ebola à Mangina, en République Démocratique du Congo: Une épidémie bien différente des précédentes: Ebola virus disease in Mangina, the Democratic Republic of the Congo: An other history

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Nouvel épisode de la maladie à virus Ebola à Bikoro

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Rapid Confirmation of the Zaire Ebola Virus in the Outbreak of the Equateur Province in the Democratic Republic of Congo: Implications for Public Health Interventions.

Ten days after the declaration of the Ebola outbreak in the Democratic Republic of Congo, rapid identification of the species Zaire Ebola virus using partial gene amplification and nanopore sequencing backed up the use of the recombinant vesicular stomatitis virus-Zaire Ebola virus vaccine in the recommended ring vaccination strategy

New filovirus disease classification and nomenclature.

The recent large outbreak of Ebola virus disease (EVD) in Western Africa resulted in greatly increased accumulation of human genotypic, phenotypic and clinical data, and improved our understanding of the spectrum of clinical manifestations. As a result, the WHO disease classification of EVD underwent major revision

The implementation of infection prevention and control measures and health care utilisation in ACF-supported health facilities during the COVID-19 pandemic in Kinshasa, Democratic Republic of the Congo, 2020

Background Infection prevention and control (IPC) was a central component of the Democratic Republic of the Congo’s COVID-19 response in 2020, aiming to prevent infections and ensure safe health service provision. Objectives We aimed to assess the evolution of IPC capacity in 65 health facilities supported by Action Contre la Faim in three health zones in Kinshasa (Binza Meteo (BM), Binza Ozone (BO), and Gombe), investigate how triage and alert validation were implemented, and estimate how health service utilisation changed in these facilities (April–December 2020). Methods We used three datasets: IPC Scorecard data assessing health facilities’ IPC capacity at baseline, monthly and weekly triage data, and monthly routine data on eight health services. We examined factors associated with triage and isolation capacity with a mixed-effects negative binomial model and estimated changes in health service utilisation with a mixed-model with random intercept and long-term trend for each health facility. We reported incidence rate ratios (IRRs) for level change when the pandemic began, for trend change, and for lockdown and post-lockdown periods (Gombe). We estimated cumulative and monthly percent differences with expected consultations. Results IPC capacity reached an average score of 90% by the end of the programme. A one-point increase in the IPC score was associated with +6% and +5% increases in triage capacity in BO and Gombe, respectively, and with +21% and +10% increases in isolation capacity in the same zones. When the pandemic began, decreases were seen in outpatient consultations (IRR: 0.67, 95% confidence interval (CI) [0.48–0.95] BM&BO-combined; IRR: 0.29, 95%CI [0.16–0.53] Gombe), consultations for respiratory tract infections (IRR: 0.48, 95%CI [0.28–0.87] BM&BO-combined), malaria (IRR: 0.60, 95%CI [0.43–0.84] BM&BO-combined, IRR: 0.33, 95%CI [0.18–0.58] Gombe), and vaccinations (IRR: 0.27, 95%CI [0.10–0.71] Gombe). Maternal health services decreased in Gombe (ANC1: IRR: 0.42, 95%CI [0.21–0.85]). Conclusions The effectiveness of the triage and alert validation process was affected by the complexity of implementing a broad clinical definition in limited-resource settings with a pre-pandemic epidemiological profile characterised by infectious diseases with symptoms like COVID-19. Readily available testing capacity remains key for future pandemic response to improve the disease understanding and maintain health services

Identification of Dengue and Chikungunya Cases Among Suspected Cases of Yellow Fever in the Democratic Republic of the Congo

International audienceFor more than 95% of acute febrile jaundice cases identified through surveillance for yellow fever, a reemerging arthropod-borne viral disease, no etiological exploration is ever done. The aim of this study was to test for other arthropod-borne viruses that can induce the same symptoms in patients enrolled in the yellow fever surveillance in the Democratic Republic of the Congo (DRC). Of 652 patients included in the surveillance of yellow fever in DRC from January 2003 to January 2012, 453 patients that tested negative for yellow fever virus (YFV) immunoglobulin M (IgM) antibodies were selected for the study. Real-time polymerase chain reaction was performed for the detection of dengue, West Nile, Chikungunya, O'nyong-nyong, Rift Valley fever, Zika, and YFV. The average age of patients was 22.1 years. We reported 16 cases (3.5%; confidence interval [CI]: 0.8-5.2) of dengue (serotypes 1 and 2) and 2 cases (0.4%; CI: 0.0-1.0) of Chikungunya. Three patients were co-infected with the two serotypes of dengue virus. Three cases of dengue were found in early July 2010 from the city of Titule (Oriental province) during a laboratory-confirmed outbreak of yellow fever, suggesting simultaneous circulation of dengue and yellow fever viruses. This study showed that dengue and Chikungunya viruses are potential causes of acute febrile jaundice in the DRC and highlights the need to consider dengue and Chikungunya diagnosis in the integrated disease surveillance and response program in the DRC. A prospective study is necessary to establish the epidemiology of these diseases

Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018-2020

Despite its critical role in containing outbreaks, the efficacy of contact tracing, measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of contact tracing by applying unilist capture-recapture methods on data from the 2018-2020 outbreak of Ebola virus disease in the Democratic Republic of the Congo. To compute sensitivity, we applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved case-patients with any contacts and infected contacts. Geometric distributions were the best-fitting models. Our results indicate that contact tracing efforts identified almost all (n = 792, 99%) of case-patients with any contacts but only half (n = 207, 48%) of case-patients with infected contacts, suggesting that contact tracing efforts performed well at identifying contacts during the listing stage but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the ongoing coronavirus pandemic

Evaluation of Early Warning, Alert and Response System for Ebola Virus Disease, Democratic Republic of the Congo, 2018–2020

The 10th and largest Ebola virus disease epidemic in the Democratic Republic of the Congo (DRC) was declared in North Kivu Province in August 2018 and ended in June 2020. We describe and evaluate an Early Warning, Alert and Response System (EWARS) implemented in the Beni health zone of DRC during August 5, 2018-June 30, 2020. During this period, 194,768 alerts were received, of which 30,728 (15.8%) were validated as suspected cases. From these, 801 confirmed and 3 probable cases were detected. EWARS showed an overall good performance: sensitivity and specificity >80%, nearly all (97%) of alerts investigated within 2 hours of notification, and good demographic representativeness. The average cost of the system was US $438/case detected and US$1.8/alert received. The system was stable, despite occasional disruptions caused by political insecurity. Our results demonstrate that EWARS was a cost-effective component of the Ebola surveillance strategy in this setting

New filovirus disease classification and nomenclature

The recent large outbreak of Ebola virus disease (EVD) in Western Africa resulted in greatly increased accumulation of human genotypic, phenotypic and clinical data, and improved our understanding of the spectrum of clinical manifestations. As a result, the WHO disease classification of EVD underwent major revision.Federal funds from the National Cancer Institute, National Institutes of Health (NIH), under Contract No. HHSN261200800001E (I.C.). G.I. is grateful for support from the Italian Ministry of Health, grant Ricerca Corrente, Research programme n.1. The UK Public Health Rapid Support Team (D.G.B.) is funded by the UK Department of Health and Social Care.https://www.nature.com/nrmicrohj2020Veterinary Tropical Disease