Optimizing the timing of an end-of-outbreak declaration: Ebola virus disease in the Democratic Republic of the Congo

Following the apparent final case in an Ebola virus disease (EVD) outbreak, the decision to declare the outbreak over must balance societal benefits of relaxing interventions against the risk of resurgence. Estimates of the end-of-outbreak probability (the probability that no future cases will occur...

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Bibliographic Details
Published in:Science advances 2024-07, Vol.10 (27), p.eado7576
Main Authors: Hart, William S, Buckingham, Jack M, Keita, Mory, Ahuka-Mundeke, Steve, Maini, Philip K, Polonsky, Jonathan A, Thompson, Robin N
Format: Article
Language:English
Subjects:
Democratic Republic of the Congo - epidemiology
Disease Outbreaks
Ebolavirus
Epidemiology
Hemorrhagic Fever, Ebola - epidemiology
Hemorrhagic Fever, Ebola - prevention & control
Humans
Markov Chains
Monte Carlo Method
Public Health
SciAdv r-articles
Social and Interdisciplinary Sciences and Public Health
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Summary:Following the apparent final case in an Ebola virus disease (EVD) outbreak, the decision to declare the outbreak over must balance societal benefits of relaxing interventions against the risk of resurgence. Estimates of the end-of-outbreak probability (the probability that no future cases will occur) provide quantitative evidence that can inform the timing of an end-of-outbreak declaration. An existing modeling approach for estimating the end-of-outbreak probability requires comprehensive contact tracing data describing who infected whom to be available, but such data are often unavailable or incomplete during outbreaks. Here, we develop a Markov chain Monte Carlo-based approach that extends the previous method and does not require contact tracing data. Considering data from two EVD outbreaks in the Democratic Republic of the Congo, we find that data describing who infected whom are not required to resolve uncertainty about when to declare an outbreak over.
ISSN:2375-2548
2375-2548
DOI:10.1126/sciadv.ado7576