RESUMO
INTRODUCTION: Thailand's malaria surveillance system complements passive case detection with active case detection (ACD), comprising proactive ACD (PACD) methods and reactive ACD (RACD) methods that target community members near index cases. However, it is unclear if these resource-intensive surveillance strategies continue to provide useful yield. This study aimed to document the evolution of the ACD programme and to assess the potential to optimise PACD and RACD. METHODS: This study used routine data from all 6 292 302 patients tested for malaria from fiscal year 2015 (FY15) to FY21. To assess trends over time and geography, ACD yield was defined as the proportion of cases detected among total screenings. To investigate geographical variation in yield from FY17 to FY21, we used intercept-only generalised linear regression models (binomial distribution), allowing random intercepts at different geographical levels. A costing analysis gathered the incremental financial costs for one instance of ACD per focus. RESULTS: Test positivity for ACD was low (0.08%) and declined over time (from 0.14% to 0.03%), compared with 3.81% for passive case detection (5.62%-1.93%). Whereas PACD and RACD contributed nearly equal proportions of confirmed cases in FY15, by FY21 PACD represented just 32.37% of ACD cases, with 0.01% test positivity. Each geography showed different yields. We provide a calculator for PACD costs, which vary widely. RACD costs an expected US$226 per case investigation survey (US$1.62 per person tested) or US$461 per mass blood survey (US$1.10 per person tested). CONCLUSION: ACD yield, particularly for PACD, is waning alongside incidence, offering an opportunity to optimise. PACD may remain useful only in specific microcontexts with sharper targeting and implementation. RACD could be narrowed by defining demographic-based screening criteria rather than geographical based. Ultimately, ACD can continue to contribute to Thailand's malaria elimination programme but with more deliberate targeting to balance operational costs.