Estimating cholera incidence with cross-sectional serology.

Science Translational Medicine
Andrew S AzmanDaniel T Leung

Abstract

The development of new approaches to cholera control relies on an accurate understanding of cholera epidemiology. However, most information on cholera incidence lacks laboratory confirmation and instead relies on surveillance systems reporting medically attended acute watery diarrhea. If recent infections could be identified using serological markers, cross-sectional serosurveys would offer an alternative approach to measuring incidence. Here, we used 1569 serologic samples from a cohort of cholera cases and their uninfected contacts in Bangladesh to train machine learning models to identify recent Vibrio cholerae O1 infections. We found that an individual's antibody profile contains information on the timing of V. cholerae O1 infections in the previous year. Our models using six serological markers accurately identified individuals in the Bangladesh cohort infected within the last year [cross-validated area under the curve (AUC), 93.4%; 95% confidence interval (CI), 92.1 to 94.7%], with a marginal performance decrease using models based on two markers (cross-validated AUC, 91.0%; 95% CI, 89.2 to 92.7%). We validated the performance of the two-marker model on data from a cohort of North American volunteers challenged with V. ch...Continue Reading

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Citations

Jan 1, 2020·Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America·Ashraful Islam KhanFirdausi Qadri
Nov 30, 2019·MSphere·Ana A WeilJason B Harris
Jun 17, 2020·Emerging Infectious Diseases·Hannah ClaphamClarence C Tam
May 29, 2020·Open Forum Infectious Diseases·Tai The DiepDaniel T Leung
Dec 19, 2020·International Journal of Environmental Research and Public Health·Amy Marie CampbellAngus Laurenson
May 21, 2021·PLoS Neglected Tropical Diseases·Tiffany Leung, Laura Matrajt
Aug 29, 2021·The Journal of Infectious Diseases·Sonia T HegdeEmily S Gurley
Oct 21, 2021·The Journal of Infectious Diseases·Anita S Iyer, Jason B Harris

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Methods Mentioned

BETA
ELISA
ELISAs

Software Mentioned

randomForest R
JAGS
scam
R
ggplot2
cvAUC

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