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 vi...

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Autores principales:	Jonathan A. Polonsky, Dankmar Böhning, Mory Keita, Steve Ahuka-Mundeke, Justus Nsio-Mbeta, Aaron Aruna Abedi, Mathias Mossoko, Janne Estill, Olivia Keiser, Laurent Kaiser, Zabulon Yoti, Patarawan Sangnawakij, Rattana Lerdsuwansri, Victor J. Del Rio Vilas
Formato:	article
Lenguaje:	EN
Publicado:	Centers for Disease Control and Prevention 2021
Materias:	Ebola Ebolavirus viruses contact tracing disease outbreaks Democratic Republic of the Congo Medicine R Infectious and parasitic diseases RC109-216
Acceso en línea:	https://doaj.org/article/3f8e91e7003b4ad4834d17b60f9d0432
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spelling	oai:doaj.org-article:3f8e91e7003b4ad4834d17b60f9d04322021-11-22T12:57:13ZNovel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–202010.3201/eid2712.2049581080-60401080-6059https://doaj.org/article/3f8e91e7003b4ad4834d17b60f9d04322021-12-01T00:00:00Zhttps://wwwnc.cdc.gov/eid/article/27/12/20-4958_articlehttps://doaj.org/toc/1080-6040https://doaj.org/toc/1080-6059 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. Jonathan A. PolonskyDankmar BöhningMory KeitaSteve Ahuka-MundekeJustus Nsio-MbetaAaron Aruna AbediMathias MossokoJanne EstillOlivia KeiserLaurent KaiserZabulon YotiPatarawan SangnawakijRattana LerdsuwansriVictor J. Del Rio VilasCenters for Disease Control and PreventionarticleEbolaEbolavirusvirusescontact tracingdisease outbreaksDemocratic Republic of the CongoMedicineRInfectious and parasitic diseasesRC109-216ENEmerging Infectious Diseases, Vol 27, Iss 12, Pp 3063-3072 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Ebola Ebolavirus viruses contact tracing disease outbreaks Democratic Republic of the Congo Medicine R Infectious and parasitic diseases RC109-216
spellingShingle	Ebola Ebolavirus viruses contact tracing disease outbreaks Democratic Republic of the Congo Medicine R Infectious and parasitic diseases RC109-216 Jonathan A. Polonsky Dankmar Böhning Mory Keita Steve Ahuka-Mundeke Justus Nsio-Mbeta Aaron Aruna Abedi Mathias Mossoko Janne Estill Olivia Keiser Laurent Kaiser Zabulon Yoti Patarawan Sangnawakij Rattana Lerdsuwansri Victor J. Del Rio Vilas Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020
description	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.
format	article
author	Jonathan A. Polonsky Dankmar Böhning Mory Keita Steve Ahuka-Mundeke Justus Nsio-Mbeta Aaron Aruna Abedi Mathias Mossoko Janne Estill Olivia Keiser Laurent Kaiser Zabulon Yoti Patarawan Sangnawakij Rattana Lerdsuwansri Victor J. Del Rio Vilas
author_facet	Jonathan A. Polonsky Dankmar Böhning Mory Keita Steve Ahuka-Mundeke Justus Nsio-Mbeta Aaron Aruna Abedi Mathias Mossoko Janne Estill Olivia Keiser Laurent Kaiser Zabulon Yoti Patarawan Sangnawakij Rattana Lerdsuwansri Victor J. Del Rio Vilas
author_sort	Jonathan A. Polonsky
title	Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020
title_short	Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020
title_full	Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020
title_fullStr	Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020
title_full_unstemmed	Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020
title_sort	novel use of capture-recapture methods to estimate completeness of contact tracing during an ebola outbreak, democratic republic of the congo, 2018–2020
publisher	Centers for Disease Control and Prevention
publishDate	2021
url	https://doaj.org/article/3f8e91e7003b4ad4834d17b60f9d0432
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Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018–2020

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