Early warning systems for malaria outbreaks in Thailand: an anomaly detection approach.

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.

Understanding malaria treatment-seeking preferences within the public sector amongst mobile/migrant workers in a malaria elimination scenario: a mixed-methods study.

BACKGROUND: Migration flows and the emerging resistance to artemisinin-based combination therapy in the Greater Mekong Sub-region (GMS) create programmatic challenges to meeting the AD 2030 malaria elimination target in Myanmar. The National Malaria Control Programme (NMCP) targeted migrant workers based mainly on the stability of their worksites (categories 1: permanent work-setting; categories 2 and 3: less stable work-settings). This study aims to assess the migration patterns, malaria treatment-seeking preferences, and challenges encountered by mobile/migrant workers at remote sites in a malaria-elimination setting. METHODS: A mixed-methods explanatory sequential study retrospectively analysed the secondary data acquired through migrant mapping surveys (2013-2015) in six endemic regions (n = 9603). A multivariate logistic regression model was used to ascertain the contributing factors. A qualitative strand (2016-2017) was added by conducting five focus-group discussions (n = 50) and five in-depth interviews with migrant workers from less stable worksites in Shwegyin Township, Bago Region. The contiguous approach was used to integrate quantitative and qualitative findings. RESULTS: Among others, migrant workers from Bago Region were significantly more likely to report the duration of stay ≥ 12 months (63% vs. 49%) and high seasonal mobility (40% vs. 35%). Particularly in less stable settings, a very low proportion of migrant workers (17%) preferred to seek malaria treatment from the public sector and was significantly influenced by the worksite stability (adjusted OR = 1.4 and 2.3, respectively for categories 2 and 1); longer duration of stay (adjusted OR = 3.5); and adjusted OR < 2 for received malaria messages, knowledge of malaria symptoms and awareness of means of malaria diagnosis. Qualitative data further elucidated their preference for the informal healthcare sector, due to convenience, trust and good relations, and put migrant workers at risk of substandard care. Moreover, the availability of cheap anti-malarial in unregistered small groceries encouraged self-medication. Infrequent or no contact with rural health centres and voluntary health workers worsened the situation. CONCLUSIONS: Mitigating key drivers that favour poor utilization of public-sector services among highly mobile migrant workers in less stable work-settings should be given priority in a malaria-elimination setting. These issues are challenging for the NMCP in Myanmar and might be generalized to other countries in the GMS to achieve malaria-elimination goals. Further innovative out-reach programmes designed and implemented specific to the nature of mobile/migrant workers is crucial.

Projecting malaria elimination in Thailand using Bayesian hierarchical spatiotemporal models.

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.

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.

Migrants and malaria risk factors: a study of the Thai-Myanmar border.

The objective of this study was to investigate factors influencing self-reported malaria among migrants living along the Thai-Myanmar border. Songkaria Village, with 1600 inhabitants and 290 households in Sangkhla Buri District, Kanchanaburi Province, was selected for the study due to its intense malaria transmission. One hundred twenty-five households were randomly selected. Household members were interviewed about the history of malaria, socioeconomic status and knowledge and practices in regard to malaria using a structured questionnaire. Of the respondents, 10%, 42%, and 48% belonged to the Thai, Mon, and Karen ethnic groups, respectively. About 40 % of Thai and Karen migrants and almost 30% of Mon migrants reported having suffered from malaria at least once. Multivariate analysis focused on migrants. The results identified three independent factors for previous malaria: a high risk occupation, ie working primarily in the forest [odds ratio (OR), 3.55; 95% confidence interval 1.3-10.0], ability to read Thai [OR, 4.13 (1.5-11.7)], and correct knowledge about malaria symptoms [OR, 5.18 (1.1-23.5)]. Working conditions among migrants played a major role in acquiring malaria. They could not afford to apply additional preventive measures, such as using a mosquito net or repellent to be used while working. The concept of enhancing the environment for migrants to enable them to protect themselves against malaria needs to be examined. Ways and means of improving the economic conditions of migrants should be considered to minimize exposure to the vector.

Mekong malaria. II. Update of malaria, multi-drug resistance and economic development in the Mekong region of Southeast Asia.

In an expansion of the first Mekong Malaria monograph published in 1999, this second monograph updates the malaria database in the countries comprising the Mekong region of Southeast Asia. The update adds another 3 years' information to cover cumulative data from the 6 Mekong countries (Cambodia, China/Yunnan, Lao PDR, Myanmar, Thailand, Viet Nam) for the six-year period 1999-2001. The objective is to generate a more comprehensive regional perspective in what is a global epicenter of drug resistant falciparum malaria, in order to improve malaria control on a regional basis in the context of social and economic change. The further application of geographical information systems (GIS) to the analysis has underscored the overall asymmetry of disease patterns in the region, with increased emphasis on population mobility in disease spread. Of great importance is the continuing expansion of resistance of P. falciparum to antimalarial drugs in common use and the increasing employment of differing drug combinations as a result. The variation in drug policy among the 6 countries still represents a major obstacle to the institution of region-wide restrictions on drug misuse. An important step forward has been the establishment of 36 sentinel sites throughout the 6 countries, with the objective of standardizing the drug monitoring process; while not all sentinel sites are fully operational yet, the initial implementation has already given encouraging results in relation to disease monitoring. Some decreases in malaria mortality have been recorded. The disease patterns delineated by GIS are particularly instructive when focused on inter-country distribution, which is where more local collaborative effort can be made to rationalize resource utilization and policy development. Placing disease data in the context of socio-economic trends within and between countries serves to further identify the needs and the potential for placing emphasis on resource rationalization on a regional basis. Despite the difficulties, the 6-year time frame represented in this monograph gives confidence that the now well established collaboration is becoming a major factor in improving malaria control on a regional basis and hopefully redressing to a substantial degree the key problem of spread of drug resistance regionally and eventually globally.