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BackgroundA challenge in achieving the malaria-elimination target in the Greater Mekong Subregion, including Thailand, is the predominance of Plasmodium vivax malaria, which has shown extreme resilience to control measures. ObjectiveThis proof-of-concept study aimed to provide evidence for implementing primaquine mass drug administration (pMDA) as a strategy for P. vivax elimination in low-endemicity settings. MethodsThe study employed a mixed-methods trial to thoroughly evaluate the effectiveness, safety, acceptability, and community engagement of pMDA. The quantitative part was designed as a 2-period cluster-crossover randomized controlled trial. The intervention was pMDA augmented to the national prevention and control standards with directly observed treatment (DOT) by village health volunteers. The qualitative part employed in-depth interviews and brainstorming discussions. The study involved 7 clusters in 2 districts of 2 southern provinces in Thailand with persistently low P. vivax transmission. In the quantitative part, 5 cross-sectional blood surveys were conducted in both the pMDA and control groups before and 3 months after pMDA. The effectiveness of pMDA was determined by comparing the proportions of P. vivax infections per 1000 population between the 2 groups, with a multilevel zero-inflated negative binomial model adjusted for cluster and time as covariates and the interaction. The safety data comprised adverse events after drug administration. Thematic content analysis was used to assess the acceptability and engagement of stakeholders. ResultsIn the pre-pMDA period, the proportions of P. vivax infections in the pMDA (n=1536) and control (n=1577) groups were 13.0 (95% CI 8.2-20.4) and 12.0 (95% CI 7.5-19.1), respectively. At month 3 post-pMDA, these proportions in the pMDA (n=1430) and control (n=1420) groups were 8.4 (95% CI 4.6-15.1) and 5.6 (95% CI 2.6-11.5), respectively. No statistically significant differences were found between the groups. The number of malaria cases reduced in all clusters in both groups, and thus, the impact of pMDA was inconclusive. There were no major safety concerns. Acceptance among the study participants and public health care providers at local and national levels was high, and they believed that pMDA had boosted awareness in the community. ConclusionspMDA was associated with high adherence, safety, and tolerability, but it may not significantly impact P. vivax transmission. As this was a proof-of-concept study, we decided not to scale up the intervention with larger clusters and samples. An alternative approach involving a targeted primaquine treatment strategy with primaquine and DOT is currently being implemented. We experienced success regarding effective health care workforces at point-of-care centers, effective collaborations in the community, and commitment from authorities at local and national levels. Our efforts boosted the acceptability of the malaria-elimination initiative. Community engagement is recommended to achieve elimination targets. Trial RegistrationThai Clinical Trials Registry TCTR20190806004; https://www.thaiclinicaltrials.org/show/TCTR20190806004

Abstract Background Malaria continues to pose a significant health threat. Rapid identification of malaria infections and the deployment of active surveillance tools are crucial for achieving malaria elimination in regions where malaria is endemic, such as certain areas of Thailand. In this study, an anomaly detection system is introduced as an early warning mechanism for potential malaria outbreaks in countries like Thailand. Methods Unsupervised clustering-based, and time series-based anomaly detection algorithms are developed and compared to identify abnormal malaria activity in Thailand. Additionally, a user interface tailored for anomaly detection is designed, enabling the Thai malaria surveillance team to utilize these algorithms and visualize regions exhibiting unusual malaria patterns. Results Nine distinct anomaly detection algorithms we developed. Their efficacy in pinpointing verified outbreaks was assessed using malaria case data from Thailand spanning 2012 to 2022. The historical average threshold-based anomaly detection method triggered three times fewer alerts, while correctly identifying the same number of verified outbreaks when compared to the current method used in Thailand. A limitation of this analysis is the small number of verified outbreaks; further consultation with the Division of Vector Borne Disease could help identify more verified outbreaks. The developed dashboard, designed specifically for anomaly detection, allows disease surveillance professionals to easily identify and visualize unusual malaria activity at a provincial level across Thailand. Conclusion An enhanced early warning system is proposed to bolster malaria elimination efforts for countries with a similar malaria profile to Thailand. The developed anomaly detection algorithms, after thorough comparison, have been optimized for integration with the current malaria surveillance infrastructure. An anomaly detection dashboard for Thailand is built and supports early detection of abnormal malaria activity. In summary, the proposed early warning system enhances the identification process for provinces at risk of outbreaks and offers easy integration with Thailand’s established malaria surveillance framework.

Abstract Thailand has set a goal of eliminating malaria by 2024 in its national strategic plan. In this study, we used the Thailand malaria surveillance database to develop hierarchical spatiotemporal models to analyze retrospective patterns and predict Plasmodium falciparum and Plasmodium vivax malaria incidences at the provincial level. We first describe the available data, explain the hierarchical spatiotemporal framework underlying the analysis, and then display the results of fitting various space–time formulations to the malaria data with the different model selection metrics. The Bayesian model selection process assessed the sensitivity of different specifications to obtain the optimal models. To assess whether malaria could be eliminated by 2024 per Thailand’s National Malaria Elimination Strategy, 2017–2026, we used the best-fitted model to project the estimated cases for 2022–2028. The study results based on the models revealed different predicted estimates between both species. The model for P. falciparum suggested that zero P. falciparum cases might be possible by 2024, in contrast to the model for P. vivax, wherein zero P. vivax cases might not be reached. Innovative approaches in the P. vivax-specific control and elimination plans must be implemented to reach zero P. vivax and consequently declare Thailand as a malaria-free country.

Abstract Background Ivermectin mass drug administration (MDA) could accelerate malaria elimination in the Greater Mekong Subregion. This study was performed to characterize the bionomics of Anopheles in Surat Thani province, Thailand. Methods Mosquitoes were collected via human landing collections between February and October 2019. Anopheles mosquitoes were morphologically identified to species. Primary Anopheles malaria vectors were dissected to assess parity status, and a subset were evaluated for molecular identification and Plasmodium detection. Results A total of 17,348 mosquitoes were collected during the study period; of these, 5777 were Anopheles mosquitoes. Morphological studies identified 15 Anopheles species, of which the most abundant were Anopheles minimus (s.l.) (87.16%, n = 5035), An. dirus s.l. (7.05%, n = 407) and An. barbirostris s.l. (2.86%, n = 165). Molecular identification confirmed that of the An. minimus s.l. mosquitoes collected, 99.80% were An. minimus (s.s.) (n = 484) and 0.2% were An. aconitus (n = 1), of the An. dirus (s.l.) collected, 100% were An. baimaii (n = 348), and of the An. maculatus (s.l.) collected, 93.62% were An. maculatus (s.s.) (n = 44) and 6.38% were An. sawadwongporni (n = 3). No Anopheles mosquito tested was Plasmodium positive (0/879). An average of 11.46 Anopheles were captured per collector per night. There were differences between species in hour of collection (Kruskal–Wallis H-test: χ 2 = 80.89, P

BackgroundAfrican swine fever (ASF), a highly contagious disease affecting both domestic and wild pigs, has been having a serious impact on the swine industry worldwide. This important transboundary animal disease can be spread by animals and ticks via direct transmission and by contaminated feed and fomites via indirect transmission because of the high environmental resistance of the ASF virus. Thus, the prevention of the introduction of ASF to areas free of ASF is essential. After an outbreak was reported in China, intensive import policies and biosecurity measures were implemented to prevent the introduction of ASF to pig farms in Thailand. ObjectiveEnhancing prevention and control, this study aims to identify the potential areas for ASF introduction and transmission in Thailand, develop a tool for farm assessment of ASF risk introduction focusing on smallholders, and develop a spatial analysis tool that is easily used by local officers for disease prevention and control planning. MethodsWe applied a multi-criteria decision analysis approach with spatial and farm assessment and integrated the outputs with the necessary spatial layers to develop a spatial analysis on a web-based platform. ResultsThe map that referred to potential areas for ASF introduction and transmission was derived from 6 spatial risk factors; namely, the distance to the port, which had the highest relative importance, followed by the distance to the border, the number of pig farms using swill feeding, the density of small pig farms (

Objectives: Malaria cross-sectional surveys are rarely conducted in very low transmission settings. This study aimed to determine the prevalence and risk factors of Plasmodium infection in a near-elimination setting in southern Thailand. Methods: Two cross-sectional surveys were conducted in areas of active transmission in the Surat Thani province of Thailand in January and May 2019. PCR was used to detect Plasmodium infection. Results: The prevalence of Plasmodium blood infection was 0.45% and 0.61% in January and May 2019, respectively. The major parasite species was Plasmodium falciparum in January and Plasmodium vivax in May. Unexpectedly, Plasmodium knowlesi infections were also detected. Most infections, including those of Plasmodium knowlesi, were asymptomatic. Being male and staying outdoors at night-time were the only significant identified risk factors. Of people infected in January 28.0% were positive in May for the same parasite species, suggesting persistent asymptomatic infections. Conclusions: Despite the very low incidence rate in Surat Thani, most malaria infections were asymptomatic. Outdoor mosquito biting at night-time is likely an important mode of malaria transmission. Unexpectedly, asymptomatic Plasmodium knowlesi infection was found, confirming previous reports of such infection in mainland Southeast Asia.

Abstract Background Tak Province, at the Thai–Myanmar border, is one of three high malaria incidence areas in Thailand. This study aimed to describe and identify possible factors driving the spatiotemporal trends of disease incidence from 2012 to 2015. Methods Climate variables and forest cover were correlated with malaria incidence using Pearson’s r. Statistically significant clusters of high (hot spots) and low (cold spots) annual parasite incidence per 1000 population (API) were identified using Getis-Ord Gi* statistic. Results The total number of confirmed cases declined by 76% from 2012 to 2015 (Plasmodium falciparum by 81%, Plasmodium vivax by 73%). Incidence was highly seasonal with two main annual peaks. Most cases were male (62.75%), ≥ 15 years (56.07%), and of Myanmar (56.64%) or Thai (39.25%) nationality. Median temperature (1- and 2-month lags), average temperature (1- and 2-month lags) and average relative humidity (2- and 3-month lags) correlated positively with monthly total, P. falciparum and P. vivax API. Total rainfall in the same month correlated with API for total cases and P. vivax but not P. falciparum. At sub-district level, percentage forest cover had a low positive correlation with P. falciparum, P. vivax, and total API in most years. There was a decrease in API in most sub-districts for both P. falciparum and P. vivax. Sub-districts with the highest API were in the Tha Song Yang and Umphang Districts along the Thai–Myanmar border. Annual hot spots were mostly in the extreme north and south of the province. Conclusions There has been a large decline in reported clinical malaria from 2012 to 2015 in Tak Province. API was correlated with monthly climate and annual forest cover but these did not account for the trends over time. Ongoing elimination interventions on one or both sides of the border are more likely to have been the cause but it was not possible to assess this due to a lack of suitable data. Two main hot spot areas were identified that could be targeted for intensified elimination activities.

Abstract Background In low malaria transmission areas, many people acquire multiple malaria infections within a single season. This study aimed to describe the pattern and epidemiological profile of malaria recurrence in a hypoendemic area of western Thailand and identify factors associated with having multiple malaria episodes. Methods An open cohort of 7000 residents in seven clusters along the Thai-Myanmar border was followed during a 6.5-year period (2011–mid 2017). Symptomatic and asymptomatic malaria infections were detected by passive case detection (PCD), weekly household visit, and mass blood surveys every 4–6 months. Malaria recurrence was defined as subsequent parasitaemic episodes occurred later than 7 days after receiving anti-malarial treatment. This study focused on analysis of recurrent episodes that occurred within 1 year after treatment. Numbers of malaria cases with single and multiple episodes were compared between clusters. Kaplan–Meier curve was performed to determine the intervals of recurrent episodes by Plasmodium species and age groups. The ordinal logistic model was used to determine factors associated with multiple malaria episodes, and to compare with single episodes, and those with no malaria infection. Results The cumulative incidence of malaria in the study area was 5.2% over the 6.5 years. Overall, 410 malaria patients were detected. Of these patients, 20% and 16% had multiple malaria episodes during the entire period and within 1 year after initial treatment, respectively. About 80% of repeated malaria episodes were caused by the same Plasmodium species as the primary infections. The median interval and interquartile range (IQR) between the first and second episode was 88 (43–175) days for all parasites, 56 (35–133) days for two Plasmodium falciparum episodes, and 90 (59–204) days for two Plasmodium vivax episodes. The interval between the episodes was increased with age. Factors significantly associated with multiple episodes of malaria infection included male sex, young age, Karen ethnicity, forest-related occupation, and having other malaria infected persons in the same house in the same period. Conclusions People who have multiple malaria episodes may play an important role in maintaining malaria transmission in the area. Understanding epidemiological profiles of this group is important for planning strategies to achieve the elimination goal.

BackgroundThailand is among the top five countries with effective COVID-19 transmission control. This study examines how news of presence of COVID-19 in Thailand, as well as varying levels of government restriction on movement, affected human mobility in a rural Thai population along the border with Myanmar.MethodsThis study makes use of mobility data collected using a smartphone app. Between November 2019 and June 2020, four major events concerning information dissemination or government intervention give rise to five time intervals of analysis. Radius of gyration is used to analyze movement in each interval, and movement during government-imposed curfew. Human mobility network visualization is used to identify changes in travel patterns between main geographic locations of activity. Cross-border mobility analysis highlights potential for intervillage and intercountry disease transmission.ResultsInter-village and cross-border movement was common in the pre-COVID-19 period. Radius of gyration and cross-border trips decreased following news of the first imported cases. During the government lockdown period, radius of gyration was reduced by more than 90% and cross-border movement was mostly limited to short-distance trips. Human mobility was nearly back to normal after relaxation of the lockdown.ConclusionsThis study provides insight into the impact of the government lockdown policy on an area with extremely low socio-economic status, poor healthcare resources, and highly active cross-border movement. The lockdown had a great impact on reducing individual mobility, including cross-border movement. The quick return to normal mobility after relaxation of the lockdown implies that close monitoring of disease should be continued to prevent a second wave.

Cross-border disease transmission is a key challenge for prevention and control of outbreaks. Variation in surveillance structure and national guidelines used in different countries can affect their data quality and the timeliness of outbreak reports. This study aimed to evaluate timeliness and data quality of national outbreak reporting for four countries in the Mekong Basin Disease Surveillance network (MBDS). Data on disease outbreaks occurring from 2010 to 2015 were obtained from the national disease surveillance reports of Cambodia, Lao PDR, Myanmar, and Vietnam. Data included total cases, geographical information, and dates at different timeline milestones in the outbreak detection process. Nine diseases or syndromes with public health importance were selected for the analysis including: dengue, food poisoning & diarrhea, severe diarrhea, diphtheria, measles, H5N1 influenza, H1N1 influenza, rabies, and pertussis. Overall, 2,087 outbreaks were reported from the four countries. The number of outbreaks and number of cases per outbreak varied across countries and diseases, depending in part on the outbreak definition used in each country. Dates on index onset, report, and response were >95% complete in all countries, while laboratory confirmation dates were 10%-100% incomplete in most countries. Inconsistent and out of range date data were observed in 1%-5% of records. The overall timeliness of outbreak report, response, and public communication was within 1-15 days, depending on countries and diseases. Diarrhea and severe diarrhea outbreaks showed the most rapid time to report and response, whereas diseases such as rabies, pertussis and diphtheria required a longer time to report and respond. The hierarchical structure of the reporting system, data collection method, and country's resources could affect the data quality and timeliness of the national outbreak reporting system. Differences in data quality and timeliness of outbreak reporting system among member countries should be considered when planning data sharing strategies within a regional network.