A simulation-based method to inform serosurvey designs for estimating the force of infection using existing blood samples
File(s)journal.pcbi.1011666.pdf (2.57 MB)
Published version
Author(s)
Type
Journal Article
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.
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.
Date Issued
2023-11
Date Acceptance
2023-11-06
Citation
PLoS Computational Biology, 2023, 19 (11)
ISSN
1553-734X
Publisher
Public Library of Science (PLoS)
Journal / Book Title
PLoS Computational Biology
Volume
19
Issue
11
Copyright Statement
© 2023 Vicco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License URL
Identifier
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011666
Subjects
Biochemical Research Methods
Biochemistry & Molecular Biology
BURDEN
Life Sciences & Biomedicine
Mathematical & Computational Biology
Science & Technology
Publication Status
Published
Article Number
e1011666
Date Publish Online
2023-11-27