Why the study?
Environmental surveillance sensitivity depends on appropriate sampling site selection, which is difficult in low-income countries with informal sewage networks.
Population
78 environmental surveillance sites matched to 1345 samples in 21 states of Nigeria
Design
Surveillance study evaluated with mixed-effects logistic regression and random forests machine learning
Authors
Loading...
Optimizing surveillance sites may improve poliovirus detection in Nigeria; leaves open prospective validation of machine learning models.
Simple measurement of sewage properties and catchment population estimation can improve environmental surveillance site selection and increase sensitivity for detecting enteroviruses.
Hamisu et al. (2020) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: