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.
Background:The use of antiretroviral drugs (ARV) to prevent mother-to-child HIV transmission (PMTCT) promises to be effective. However, limited data on the adverse effects of ARV among pregnant women and pregnancy outcomes have been reported in clinical practice.Objectives:This study aimed to assess adverse effects and outcomes among pregnant HIV-infected women receiving antiretroviral drugs for either antiretroviral therapy (ART) or PMTCT.Study Design:This cohort study was at Chonburi Hospital, Thailand, in 2002-2006.Results:A total of 246 pregnant HIV-infected women with the median age (range) of 27 (16-41) years were included in this study. ART was initiated in 16.3% for treatment during ANC, 66.7% for PMTCT during ANC, and 17.1% for PMTCT in labor. Adverse effects, especially anemia, were significantly associated with continuing combined ART in pregnancy (p<0.001). 88.9% delivered normal-term neonates. The prevalence of pre-term delivery was 10.2%. Overall, 24 adverse events from 21 pregnant women (8.5%) were noted. A significantly higher prevalence of pre-term delivery was noted in the groups continuing combined ART, or initiating of PMTCT during labor rather than ANC (p=0.02). The incidence of low Apgar scores was 3.6%, and these were associated with initiation of PMTCT during labor (p=0.004).Conclusion:Adverse ARV events were more numerous among the pregnant women who needed ART than PMTCT. ANC is beneficial and strongly recommended for all pregnant HIV-infected women for better pregnancy outcomes.
Background: The ability to produce timely and accurate estimation of dengue cases can significantly impact disease control programs. A key challenge for dengue control in Thailand is the systematic delay in reporting at different levels in the surveillance system. Efficient and reliable surveillance and notification systems are vital to monitor health outcome trends and early detection of disease outbreaks which vary in space and time.Methods: Predicting the trend in dengue cases in real-time is a challenging task in Thailand due to a combination of factors including reporting delays. We present decision support using a spatiotemporal nowcasting model which accounts for reporting delays in a Bayesian framework with sliding windows. A case study is presented to demonstrate the proposed nowcasting method using weekly dengue surveillance data in Bangkok at district level in 2010. Results:The overall real-time estimation accuracy was 70.69% with 59.05% and 79.59% accuracy during low and high seasons averaged across all weeks and districts. The results suggest the model was able to give a reasonable estimate of the true numbers of cases in the presence of delayed reports in the surveillance system. With sliding windows, models could also produce similar accuracy to estimation with the whole data. Conclusions:A persistent challenge for the statistical and epidemiological communities is to transform data into evidence-based knowledge that facilitates policy making about health improvements and disease control at the individual and population levels. Improving real-time estimation of infectious disease incidence is an important technical development. The effort in this work provides a template for nowcasting in practice to inform decision making for dengue control.
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