Towards estimating true cholera burden: a systematic review and meta-analysis ofVibrio choleraepositivity
Authors: Wiens Kirsten E. , Xu Hanmeng , Zou Kaiyue , Mwaba John , Lessler Justin , Malembaka Espoir B. , Demby Maya N. , Bwire Godfrey , Qadri Firdausi , Lee Elizabeth C. , Azman Andrew S. 
Published: October 2022

AbstractBackgroundCholera surveillance relies on clinical diagnosis of acute watery diarrhea. Suspected cholera case definitions have high sensitivity but low specificity, challenging our ability to characterize cholera burden and epidemiology. Our objective was to estimate the proportion of clinically suspected cholera that are trueVibrio choleraeinfections and identify factors that explain variation in positivity.MethodsWe conducted a systematic review of studies from 2000-2023 that tested ≥10 suspected cholera cases forV. choleraeO1/O139 using culture, PCR and/or a rapid diagnostic test. We searched PubMed, Embase, Scopus, and Google Scholar on October 16, 2021 and updated the search on April 19, 2023. We estimated diagnostic test sensitivity and specificity using a latent class meta-analysis. We estimatedV. choleraepositivity using a random-effects meta-analysis, adjusting for test performance.FindingsWe included 119 studies from 30 countries.V. choleraepositivity was lower in studies with representative sampling and lower minimum ages in suspected case definitions. After adjusting for test performance, on average 52% (95% Credible Interval: 24%, 80%) of suspected cases represented trueV. choleraeinfections. After adjusting for test performance and study methodology, odds of a suspected case having a true infection were 5.71 (Odds ratio 95% Credible Interval: 1.53, 15.43) times higher when surveillance was initiated in response to an outbreak than in non-outbreak settings. Variation across studies was high and a limitation of our approach and the resolution of the data was that we were unable to explain all the heterogeneity with study-level attributes, including diagnostic test used, setting, and case definitions.ConclusionsIn this study, we found that burden estimates based on suspected cases alone may overestimate the incidence of medically attended cholera by twofold. However, accounting for cases missed by traditional clinical surveillance is key to unbiased cholera burden estimates. Given the substantial variability in positivity between settings, extrapolations from suspected to confirmed cases, which is necessary to estimate cholera incidence rates without exhaustive testing, should be based on local data.Funding for this study was provided by the Bill and Melinda Gates Foundation and the National Institute of Allergy and Infectious Disease.Author SummaryWhy was this study done?Cholera surveillance typically relies on the clinical diagnosis of acute watery diarrhea (i.e., “suspected cholera”), but this definition has a low specificity for cholera.Our goal was to estimate the proportion of suspected cholera cases that are trueVibrio choleraeinfections and identify factors that contribute to variation in observed positivity.What did the researchers do and find?We conducted a systematic review of studies from 2000-2023 that tested suspected cholera cases forV. choleraeinfection using one of three different laboratory tests.We included 119 studies from 30 countries and found that, on average, half of suspected cholera cases represented trueV. choleraeinfections, after accounting for laboratory test accuracy.We also found high variability between studies and that the odds of a suspected case being a true infection were higher during outbreaks compared to non-outbreak settings.What do these findings mean?Our findings suggest that burden estimates based solely on suspected cases may overestimate the incidence of medically attended cholera by twofold.A limitation of our approach was that we couldn’t account for cases missed by clinical surveillance, which is crucial for unbiased overall cholera burden estimates and an important area for future work.The high variability across studies suggests also that local testing data should be used to inform assumptions about positivity when exhaustive testing is not feasible.