Abstract

The study evaluates a public health intervention aimed at improving active case finding and testing strategies. Using data-driven optimization and statistical modeling, the authors analyze how testing locations and resource allocation impact detection rates of cases. The results highlight the importance of targeted strategies to improve efficiency and effectiveness in identifying infections, especially in contexts with limited resources and heterogeneous population mobility patterns.