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- Title
Improved Assessment of Schistosoma Community Infection Through Data Resampling Method.
- Authors
Gurarie, David; Mondal, Anirban; Ndeffo-Mbah, Martial L
- Abstract
Background The conventional diagnostic for Schistosoma mansoni infection is stool microscopy with the Kato-Katz (KK) technique to detect eggs. Its outcomes are highly variable on a day-to-day basis and may lead to biased estimates of community infection used to inform public health programs. Our goal is to develop a resampling method that leverages data from a large-scale randomized trial to accurately predict community infection. Methods We developed a resampling method that provides unbiased community estimates of prevalence, intensity and other statistics for S mansoni infection when a community survey is conducted using KK stool microscopy with a single sample per host. It leverages a large-scale data set, collected in the Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) project, and allows linking single—stool specimen community screening to its putative multiday "true statistics." Results SCORE data analysis reveals the limited sensitivity of KK stool microscopy and systematic bias of single-day community testing versus multiday testing; for prevalence estimate, it can fall up to 50% below the true value. The proposed SCORE cluster method reduces systematic bias and brings the estimated prevalence values within 5%–10% of the true value. This holds for a broad swath of transmission settings, including SCORE communities, and other data sets. Conclusions Our SCORE cluster method can markedly improve the S mansoni prevalence estimate in settings using stool microscopy.
- Subjects
SCHISTOSOMA; SCHISTOSOMA mansoni; OPERATIONS research; HEALTH programs; CONSORTIA
- Publication
Open Forum Infectious Diseases, 2024, Vol 11, Issue 2, p1
- ISSN
2328-8957
- Publication type
Article
- DOI
10.1093/ofid/ofad659