ArticleEmerging infectious diseases2021
Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018-2020.
Article in Emerging infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 13 citations in OpenAlex.
- Evaluation of contact tracing performance during an Ebola virus disease outbreak in a complex security environment: the case of North Kivu province, Democratic Republic of the Congo, 2018-2020.Conflict and health · 2025Article
- Factors Associated with Reliable Contact Tracing During the 2021 Ebola Virus Disease Outbreak in Guinea.Journal of epidemiology and global health · 2024Article
- Performance of a safe and dignified burial intervention during an Ebola epidemic in the eastern Democratic Republic of the Congo, 2018-2019.BMC medicine · 2023Article
- A community-based contact isolation strategy to reduce the spread of Ebola virus disease: an analysis of the 2018-2020 outbreak in the Democratic Republic of the Congo.BMJ global health · 2023Article
- Improving estimates of pertussis burden in Ontario, Canada 2010-2017 by combining validation and capture-recapture methodologies.PloS one · 2023Article
- Investigation of and Strategies to Control the Final Cluster of the 2018-2020 Ebola Virus Disease Outbreak in the Eastern Democratic Republic of Congo.Open forum infectious diseases · 2022Article
- Sensitivity of contact-tracing for COVID-19 in Thailand: a capture-recapture application.BMC infectious diseases · 2022Article
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14 authors at 6 institutions in 6 countries.
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No grant is acknowledged in the PubMed record.
Abstract
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.
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