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Delayed detection of poliovirus outbreaks is a major threat to polio eradication. Direct molecular Detection and Nanopore Sequencing (DDNS) of stool samples shows promise as a faster method to detect and confirm polio cases compared with cell culture but has not been assessed prospectively during routine surveillance. We report on the implementation of prospective testing of all stool samples received from suspected polio cases and their contacts in the Democratic Republic of Congo between 10th August 2021 to 4th February 2022. DDNS detected polioviruses in 62/2339 (2.7%) of samples whilst the standard algorithm of cell culture, qPCR and Sanger sequencing detected 51/2339 (2.2%). The sensitivity and specificity of DDNS was not significantly different from cell culture. DDNS provided the VP1 sequence required for case confirmation on average 7 days after sample receipt compared with 30 days for the standard algorithm, allowing detection of three new cVPDV2 outbreaks a mean of 23 days earlier (range 6-30 days) and was estimated to cost less per sample tested. The mean sequence similarity between sequences obtained by the two methods was 99.98%. Continued implementation of DDNS in DRC and expansion to other countries will allow further evaluation of this method and inform its potential recommendation by the Global Polio Laboratory Network.

During the 2018-2020 Ebola virus disease (EVD) outbreak in North Kivu province in the Democratic Republic of Congo, EVD was diagnosed in a patient who had received the recombinant vesicular stomatitis virus-based vaccine expressing a ZEBOV glycoprotein (rVSV-ZEBOV) (Merck). His treatment included an Ebola virus (EBOV)-specific monoclonal antibody (mAb114), and he recovered within 14 days. However, 6 months later, he presented again with severe EVD-like illness and EBOV viremia, and he died. We initiated epidemiologic and genomic investigations that showed that the patient had had a relapse of acute EVD that led to a transmission chain resulting in 91 cases across six health zones over 4 months. (Funded by the Bill and Melinda Gates Foundation and others.).

On 1 August 2018, the Democratic Republic of the Congo (DRC) declared its tenth Ebola virus disease (EVD) outbreak. To aid the epidemiologic response, the Institut National de Recherche Biomedicale (INRB) 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 27 July 2018 and 27 April 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 (EBOV) infections in DRC in the period analyzed. 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. Phylogeographic analysis of 792 Ebola virus genomes from the 2018 oubreak in the Democratic Republic of the Congo integrated into an end-to-end surveillance program demonstrates the feasibility of using genomic sequencing data to inform the public health epidemic response in near-real time.

The Democratic Republic of the Congo declared its tenth Ebola virus disease outbreak in July 2018, which has circulated primarily in the Nord Kivu province. In addition to standard epidemiologic surveillance and response efforts, 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. Here we report 538 new genomes from this outbreak; together with previously available sequence data (n = 48 genomes), this represents an unprecedented 17% of all laboratory-confirmed infections. To support outbreak response efforts, we reconstructed spatiotemporal transmission dynamics at broad and at fine scales as new data were available and disseminated the results via an interactive narrative-based platform. Our innovative system enables actionable information sharing between scientists and epidemiologists coordinating the day-to-day response on the time scales necessary to guide response efforts. The development of this genomic surveillance pipeline, within a resource-limited setting, represents significant technological and scientific progress in genomic epidemiology. Here we present a phylodynamic analysis of the outbreak as of February 2020, and describe the types of epidemiologic dynamics that we monitor the genomic data for, including resolution of co-circulating transmission chains, detection of superspreading events, inference of regions that act as transmission sources and sinks, and differentiation of closely linked cases versus propagated transmission. These findings have ameliorated the current outbreak response and are directly applicable to future outbreaks.