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.

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.

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.

Assessing Thailand's 1-3-7 surveillance strategy in accelerating malaria elimination.

BACKGROUND: Thailand's strong malaria elimination programme relies on effective implementation of its 1-3-7 surveillance strategy, which was endorsed and implemented nationwide in 2016. For each confirmed malaria patient, the Ministry of Public Health's Division of Vector Borne Diseases (DVBD) ensures completion of case notification within 1 day, case investigation within 3 days, and foci investigation within 7 days. To date, there has not been a comprehensive assessment of the performance and achievements of the 1-3-7 surveillance strategy although such results could help Thailand's future malaria elimination strategic planning. METHODS: This study examined adherence to the 1-3-7 protocols, tracked progress against set targets, and examined geographic variations in implementation of the 1-3-7 strategy in the programme's initial 5 years. An auto-regressive integrated moving average (ARIMA) time series analysis with seasonal decomposition assessed the plausible implementation effect of the 1-3-7 strategy on malaria incidence in the programme's initial 5 years. The quantitative analysis included all confirmed malaria cases from public health and non-governmental community facilities from October 2014 to September 2021 (fiscal year [FY] 2015 to FY 2021) (n = 77,405). The spatial analysis included active foci with known geocoordinates that reported more than five cases from FY 2018 to FY 2021. RESULTS: From FY 2017 to FY 2021, on-time case notification improved from 24.4% to 89.3%, case investigations from 58.0% to 96.5%, and foci investigations from 37.9% to 87.2%. Adherence to timeliness protocols did not show statistically significant variation by area risk classification. However, adherence to 1-3-7 protocols showed a marked spatial heterogeneity among active foci, and the ARIMA model showed a statistically significant acceleration in the reduction of malaria incidence. The 1-3-7 strategy national indicators and targets in Thailand have shown progressive success, and most targets were achieved for FY 2021. CONCLUSION: The results of Thailand's 1-3-7 surveillance strategy are associated with a decreased incidence in the period following the adoption of the strategy although there is notable geographic variation. The DVBD will continue to implement and adapt the 1-3-7 strategy to accelerate progress toward malaria elimination. This assessment may be useful for domestic strategic planning and to other countries considering more intensive case and foci investigation and response strategies.

Progress and challenges of integrated drug efficacy surveillance for uncomplicated malaria in Thailand.

BACKGROUND: Integrated drug efficacy surveillance (iDES) was formally introduced nationally across Thailand in fiscal year 2018 (FY2018), building on a history of drug efficacy monitoring and interventions. According to the National Malaria Elimination Strategy for Thailand 2017-2026, diagnosis is microscopically confirmed, treatment is prescribed, and patients are followed up four times to ensure cure. METHODS: Routine patient data were extracted from the malaria information system for FY2018-FY2020. Treatment failure of first-line therapy was defined as confirmed parasite reappearance within 42 days for Plasmodium falciparum and 28 days for Plasmodium vivax. The primary outcome was the crude drug efficacy rate, estimated using Kaplan-Meier methods, at day 42 for P. falciparum treated with dihydroartemisinin-piperaquine plus primaquine, and day 28 for P. vivax treated with chloroquine plus primaquine; day 60 and day 90 efficacy were secondary outcomes for P. vivax. RESULTS: The proportion of patients with outcomes recorded at day 42 for P. falciparum malaria and at day 28 for P. vivax malaria has been increasing, with FY2020 follow-up rates of 61.5% and 57.2%, respectively. For P. falciparum malaria, day 42 efficacy in FY2018 was 92.4% (n = 249), in FY2019 93.3% (n = 379), and in FY2020 98.0% (n = 167). Plasmodium falciparum recurrences occurred disproportionally in Sisaket Province, with day 42 efficacy rates of 75.9% in FY2018 (n = 59) and 49.4% in FY2019 (n = 49), leading to an update in first-line therapy to pyronaridine-artesunate at the provincial level, rolled out in FY2020. For P. vivax malaria, day 28 efficacy (chloroquine efficacy) was 98.5% in FY2018 (n = 2048), 99.1% in FY2019 (n = 2206), and 99.9% in FY2020 (n = 2448), and day 90 efficacy (primaquine efficacy) was 94.8%, 96.3%, and 97.1%, respectively. CONCLUSIONS: In Thailand, iDES provided operationally relevant data on drug efficacy, enabling the rapid amendment of treatment guidelines to improve patient outcomes and reduce the potential for the spread of drug-resistant parasites. A strong case-based surveillance system, integration with other health system processes, supporting biomarker collection and molecular analyses, and cross-border collaboration may maximize the potential of iDES in countries moving towards elimination.

Implementation and success factors from Thailand's 1-3-7 surveillance strategy for malaria elimination.

Thailand's National Malaria Elimination Strategy 2017-2026 introduced the 1-3-7 strategy as a robust surveillance and response approach for elimination that would prioritize timely, evidence-based action. Under this strategy, cases are reported within 1 day, cases are investigated within 3 days, and foci are investigated and responded to within 7 days, building on Thailand's long history of conducting case investigation since the 1980s. However, the hallmark of the 1-3-7 strategy is timeliness, with strict deadlines for reporting and response to accelerate elimination. This paper outlines Thailand's experience adapting and implementing the 1-3-7 strategy, including success factors such as a cross-sectoral Steering Committee, participation in a collaborative regional partnership, and flexible local budgets. The programme continues to evolve to ensure prompt and high-quality case management, capacity maintenance, and adequate supply of lifesaving commodities based on surveillance data. Results from implementation suggest the 1-3-7 strategy has contributed to Thailand's decline in malaria burden; this experience may be useful for other countries aiming to eliminate malaria.

A foci cohort analysis to monitor successful and persistent foci under Thailand's Malaria Elimination Strategy.

BACKGROUND: Thailand's success in reducing malaria burden is built on the efficient "1-3-7" strategy applied to the surveillance system. The strategy is based on rapid case notification within 1 day, case investigation within 3 days, and targeted foci response to reduce the spread of Plasmodium spp. within 7 days. Autochthonous transmission is still occurring in the country, threatening the goal of reaching malaria-free status by 2024. This study aimed to assess the effectiveness of the 1-3-7 strategy and identify factors associated with presence of active foci. METHODS: Data from the national malaria information system were extracted from fiscal years 2013 to 2019; after data cleaning, the final dataset included 81,012 foci. A Cox's proportional hazards model was built to investigate factors linked with the probability of becoming an active focus from 2015 to 2019 among foci that changed status from non-active to active focus during the study period. We performed a model selection technique based on the Akaike Information Criteria (AIC). RESULTS: The number of yearly active foci decreased from 2227 to 2013 to 700 in 2019 (68.5 %), and the number of autochthonous cases declined from 17,553 to 3,787 (78.4 %). The best Cox's hazard model showed that foci in which vector control interventions were required were 18 % more likely to become an active focus. Increasing compliance with the 1-3-7 strategy had a protective effect, with a 22 % risk reduction among foci with over 80 % adherence to 1-3-7 timeliness protocols. Other factors associated with likelihood to become or remain an active focus include previous classification as an active focus, presence of Plasmodium falciparum infections, level of forest disturbance, and location in border provinces. CONCLUSIONS: These results identified factors that favored regression of non-active foci to active foci during the study period. The model and relative risk map align with the national malaria program's district stratification and shows strong spatial heterogeneity, with high probability to record active foci in border provinces. The results of the study may be useful for honing Thailand's program to eliminate malaria and for other countries aiming to accelerate malaria elimination.