A simulation-based method to inform serosurvey design for estimating the force of infection using existing blood samples
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Published:2023-11-27
Issue:11
Volume:19
Page:e1011666
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ISSN:1553-7358
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Container-title:PLOS Computational Biology
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language:en
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Short-container-title:PLoS Comput Biol
Author:
Vicco AnnaORCID,
McCormack Clare P.,
Pedrique Belen,
Amuasi John H.ORCID,
Awuah Anthony Afum-AdjeiORCID,
Obirikorang Christian,
Struck Nicole S.,
Lorenz Eva,
May Jürgen,
Ribeiro Isabela,
Malavige Gathsaurie Neelika,
Donnelly Christl A.ORCID,
Dorigatti IlariaORCID
Abstract
The extent to which dengue virus has been circulating globally and especially in Africa is largely unknown. Testing available blood samples from previous cross-sectional serological surveys offers a convenient strategy to investigate past dengue infections, as such serosurveys provide the ideal data to reconstruct the age-dependent immunity profile of the population and to estimate the average per-capita annual risk of infection: the force of infection (FOI), which is a fundamental measure of transmission intensity.
In this study, we present a novel methodological approach to inform the size and age distribution of blood samples to test when samples are acquired from previous surveys. The method was used to inform SERODEN, a dengue seroprevalence survey which is currently being conducted in Ghana among other countries utilizing samples previously collected for a SARS-CoV-2 serosurvey.
The method described in this paper can be employed to determine sample sizes and testing strategies for different diseases and transmission settings.
Funder
Drugs for Neglected Diseases initiative
Foundation Blanceflor Boncompagni Ludovisi
Wellcome Trust
UK National Institute for Health and Care Research Health Protection Research Unit (NIHR HPRU) in Emerging and Zoonotic Infections in partnership with Public Health England
French Development Agency
Médecins Sans Frontières International
Swiss Agency for Development and Cooperation
UK aid
Publisher
Public Library of Science (PLoS)
Subject
Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics