Suchergebnisse

Background: During the five decades since their discovery, filoviruses of four species have caused human hemorrhagic fever outbreaks: Marburg (MARV) marburgvirus, and Zaire (EBOV), Sudan (SUDV) and Bundybugyo (BDBV) ebolaviruses. The largest, devastating EBOV epidemic in West Africa in 2014-16, has been followed by outbreaks of MARV in Uganda, 2017, and EBOV in Democratic Republic of Congo, 2018, emphasizing the need to develop preparedness to diagnose all filoviruses. Objectives: The aim of this study was to optimize a new filovirus RT-qPCR to detect all filoviruses, define its limits of detection (LOD) and perform a field evaluation with outbreak samples. Study design: A pan-filovirus RT-qPCR targeting the L gene was developed and evaluated within the EbolaMoDRAD (Ebola virus: modern approaches for developing bedside rapid diagnostics) project. Specificity and sensitivity were determined and the effect of inactivation and PCR reagents (liquid and lyophilized format) were tested. Results: The LODs for the lyophilized pan-filovirus L-RT-qPCR assay were 9.4 copies per PCR reaction for EBOV, 9.9 for MARV, 1151 for SUDV, 65 for BDBV and 289 for Tai Forest virus. The test was set at the Pasteur Institute, Dakar, Senegal, and 83 Ebola patient samples, with viral load ranging from 5 to 5 million copies of EBOV per reaction, were screened. The results for the patient samples were in 100% concordance with the reference EBOVspecific assay. Discussion: Overall, the assay showed good sensitivity and specificity, covered all filoviruses known to be human pathogens, performed well both in lyophilized and liquid-phase formats and with EBOV outbreak clinical samples. ; Peer reviewed

Background During the five decades since their discovery, filoviruses of four species have caused human hemorrhagic fever outbreaks: Marburg (MARV) marburgvirus, and Zaire (EBOV), Sudan (SUDV) and Bundybugyo (BDBV) ebolaviruses. The largest, devastating EBOV epidemic in West Africa in 2014-16, has been followed by outbreaks of MARV in Uganda, 2017, and EBOV in Democratic Republic of Congo, 2018, emphasizing the need to develop preparedness to diagnose all filoviruses. Objectives The aim of this study was to optimize a new filovirus RT-qPCR to detect all filoviruses, define its limits of detection (LOD) and perform a field evaluation with outbreak samples. Study design A pan-filovirus RT-qPCR targeting the L gene was developed and evaluated within the EbolaMoDRAD (Ebola virus: modern approaches for developing bedside rapid diagnostics) project. Specificity and sensitivity were determined and the effect of inactivation and PCR reagents (liquid and lyophilized format) were tested. Results The LODs for the lyophilized pan-filovirus L-RT-qPCR assay were 9.4 copies per PCR reaction for EBOV, 9.9 for MARV, 1151 for SUDV, 65 for BDBV and 289 for Taï Forest virus. The test was set at the Pasteur Institute, Dakar, Senegal, and 83 Ebola patient samples, with viral load ranging from 5 to 5 million copies of EBOV per reaction, were screened. The results for the patient samples were in 100% concordance with the reference EBOV-specific assay. Discussion Overall, the assay showed good sensitivity and specificity, covered all filoviruses known to be human pathogens, performed well both in lyophilized and liquid-phase formats and with EBOV outbreak clinical samples.

On August 1, 2018, the Democratic Republic of the Congo declared its tenth Ebola virus disease outbreak. To aid the epidemiologic response, the Institut National de Recherche Biomédicale implemented an end-to-end genomic surveillance system, including sequencing, bioinformatic analysis, and dissemination of genomic epidemiologic results to frontline public health workers. We report 744 new genomes sampled between July 27, 2018 and April 27, 2020 generated by this surveillance effort. Together with previously available sequence data (n = 48 genomes), these data represent almost 24% of all laboratory-confirmed Ebola virus infections in DRC in the analyzed period. We inferred spatiotemporal transmission dynamics from the genomic data as new sequences were generated and disseminated the results to support epidemiologic response efforts. Here, we provide an overview of how this genomic surveillance system functioned, present a full phylodynamic analysis of 792 Ebola genomes from the Nord Kivu outbreak, and discuss how the genomic surveillance data informed response efforts and public health decision-making.