TY - JOUR
T1 - Estimating cholera incidence with cross-sectional serology
AU - Azman, Andrew S.
AU - Lessler, Justin
AU - Luquero, Francisco J.
AU - Bhuiyan, Taufiqur Rahman
AU - Khan, Ashraful Islam
AU - Chowdhury, Fahima
AU - Kabir, Alamgir
AU - Gurwith, Marc
AU - Weil, Ana A.
AU - Harris, Jason B.
AU - Calderwood, Stephen B.
AU - Ryan, Edward T.
AU - Qadri, Firdausi
AU - Leung, Daniel T.
N1 - Funding Information:
A.S.A., J.L., T.R.B., A.I.K., F.C., A.K., J.B.H., D.T.L., and F.Q.'s work was funded by grants from the Bill and Melinda Gates Foundation (OPP1171700 to A.S.A. and J.L. and OPP1191944 to A.S.A., J.L., T.R.B., A.I.K., F.C., A.K., J.B.H., D.T.L., and F.Q.) and the NIH grants R01 AI135115 (to D.T.L., A.S.A., and F.Q.), R01 AI106878 (to E.T.R. and F.Q.), R01 AI103055 (to J.B.H. and F.Q.), R01AI130378 (to D.T.L., T.R.B., and F.Q.), D43 TW005572 (to T.R.B.), K08AI123494 (to A.A.W.), K08AI100923 (to D.T.L.), and K43TW010362 (to T.R.B.). The original data from Bangladesh were collected through grants from the NIH (U01AI058935 to S.B.C., F.Q., and E.T.R.).
Publisher Copyright:
© 2019 American Association for the Advancement of Science. All Rights Reserved.
PY - 2019
Y1 - 2019
N2 - 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. cholerae O1 (AUC range, 88.4 to 98.4%). In simulated serosurveys, our models accurately estimated annual incidence in both endemic and epidemic settings, even with sample sizes as small as 500 and annual incidence as low as two infections per 1000 individuals. Crosssectional serosurveys may be a viable approach to estimating cholera incidence.
AB - 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. cholerae O1 (AUC range, 88.4 to 98.4%). In simulated serosurveys, our models accurately estimated annual incidence in both endemic and epidemic settings, even with sample sizes as small as 500 and annual incidence as low as two infections per 1000 individuals. Crosssectional serosurveys may be a viable approach to estimating cholera incidence.
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U2 - 10.1126/scitranslmed.aau6242
DO - 10.1126/scitranslmed.aau6242
M3 - Article
C2 - 30787170
AN - SCOPUS:85061969156
SN - 1946-6234
VL - 11
JO - Science translational medicine
JF - Science translational medicine
IS - 480
M1 - aau6242
ER -