Leveraging geo-referenced malaria information to increase domestic financial support for malaria elimination in Thailand.

Thailand's National Malaria Elimination Strategy 2017-2026 seeks to increase domestic support and financing for malaria elimination. During 2018-2020, through a series of training sessions, public health officials in Thailand utilized foci-level malaria data to engage subdistrict-level government units known as Local Administrative Organizations (LAOs) with the aim of increasing their understanding of their local malaria situation, collaboration with public health networks, and advocacy for financial support of targeted interventions in villages within their jurisdictions. As a result of these efforts, total LAO funding support for malaria nearly doubled from the 2017 baseline to 2020. In 2021, a novel "LAO collaboration" feature was added to Thailand's national malaria information system that enables tracking and visualization of LAO financial support of malaria in areas with transmission, by year, down to the subdistrict level. This case study describes Thailand's experience implementing the LAO engagement strategy, quantifying and monitoring the financial support mobilized from LAOs, and results from a qualitative study in five high-performance provinces examining factors and approaches that foster successful local collaboration between LAOs, public health networks, and communities for malaria prevention and response. Results from the study showed that significant malaria endemicity or local outbreaks helped spur collaboration in multiple provinces. Increases in LAO support and involvement were attributable to four approaches employed by public health officials: (a) strengthening malaria literacy and response capacity of LAOs, (b) organizational leadership in response to outbreaks, (c) utilization of structural incentives, and (d) multisectoral involvement in malaria response. In two provinces, capacity building of LAOs in malaria vector control, following a precedent set by Thailand's dengue programme, enabled LAO personnel to play both funding and implementation roles in local malaria response. Wider replication of the LAO engagement strategy across Thailand may sustain gains and yield efficiencies in the fight against malaria as the vector-borne disease workforce declines. Lessons from Thailand's experience may be useful for malaria programmes in other geographies to support the goals and sustainability of elimination and prevention of re-establishment by improving financing through local collaboration between the health system and elected officials.

Malaria Stratification Mapping in Thailand to Support Prevention of Reestablishment.

Thailand aims to eliminate malaria by 2026, with 46 of the country's 77 provinces already verified as malaria free. However, these provinces remain susceptible to the reestablishment of indigenous transmission that would threaten the national goal. Thus, the country is prioritizing national and subnational prevention of reestablishment (POR) planning while considering the spatial heterogeneity of the remaining malaria caseload. To support POR efforts, a novel nonmodeling method produced a malaria stratification map at the tambon (subdistrict) level, incorporating malaria case data, demographic data, and environmental factors. The stratification analysis categorized 7,425 tambons into the following four risk strata: Local Transmission (2.9%), At Risk for Transmission (3.1%), High Risk for Reintroduction (2.9%), and Low Risk for Reintroduction (91.1%). The stratification map will support the national program to target malaria interventions in remaining hotspots and mitigate the risk of transmission in malaria-free areas.

Environmental Factors Linked to Reporting of Active Malaria Foci in Thailand.

Thailand has made substantial progress towards malaria elimination, with 46 of the country's 77 provinces declared malaria-free as part of the subnational verification program. Nonetheless, these areas remain vulnerable to the reintroduction of malaria parasites and the reestablishment of indigenous transmission. As such, prevention of reestablishment (POR) planning is of increasing concern to ensure timely response to increasing cases. A thorough understanding of both the risk of parasite importation and receptivity for transmission is essential for successful POR planning. Routine geolocated case- and foci-level epidemiological and case-level demographic data were extracted from Thailand's national malaria information system for all active foci from October 2012 to September 2020. A spatial analysis examined environmental and climate factors associated with the remaining active foci. A logistic regression model collated surveillance data with remote sensing data to investigate associations with the probability of having reported an indigenous case within the previous year. Active foci are highly concentrated along international borders, particularly Thailand's western border with Myanmar. Although there is heterogeneity in the habitats surrounding active foci, land covered by tropical forest and plantation was significantly higher for active foci than other foci. The regression results showed that tropical forest, plantations, forest disturbance, distance from international borders, historical foci classification, percentage of males, and percentage of short-term residents were associated with the high probability of reporting indigenous cases. These results confirm that Thailand's emphasis on border areas and forest-going populations is well placed. The results suggest that environmental factors alone are not driving malaria transmission in Thailand; rather, other factors, including demographics and behaviors that intersect with exophagic vectors, may also be contributors. However, these factors are syndemic, so human activities in areas covered by tropical forests and plantations may result in malaria importation and, potentially, local transmission, in foci that had previously been cleared. These factors should be addressed in POR planning.

The contribution of active case detection to malaria elimination in Thailand.

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.