Asian Pacific Journal of Tropical Medicine
Spatiotemporal dynamics and forecasting of dengue incidence in Northeastern Thai border provinces, 2014-2023
- Article
- Figures
- Metrics
- Preview PDF
- Reference
- Related
- Cited by
- Materials
Abstract:
Objective:To identify the underexplored nature of localized, long term spatiotemporal patterns (2014-2023) and predictive modeling feasibility in these regions. The analysis specifically explored the potential for robust forecasting of dengue incidence trends. Methods: Dengue incidence trends were analyzed across five northeastern Thai provinces: Sisaket (SSK), Ubon Ratchathani (UBN), Yasothon (YST), Amnat Charoen (ACR), and Mukdahan (MDH) over a ten-year period (2014-2023). Analysis of Kruskal– WallisH test followed by post hoc Dunn’s tests with Bonferroni adjustment were used for inter-provincial comparisons. Seasonal Trend Decomposition using Loess (STL) and Seasonal Index calculations were applied to identify seasonal patterns, and Simple Linear Regression to assess the influence of monthly rainfall on dengue seasonality. Additionally, a negative binomial regression analysis was conducted, and spatial autocorrelation was investigated using Moran's I analysis. Results: The analysis revealed significant spatiotemporal heterogeneity and distinct cyclical patterns in dengue incidence. Pronounced annual peaks consistently occurred during the rainy season (June-September), with major epidemics observed in 2015, 2019, and 2023. Inter-provincial comparisons revealed statistically significant differences in monthly dengue incidence across the study area (H=10.08, P=0.039). Post-hoc Dunn’s tests indicated that UBN and SSK had higher transmission burden compared to YST and MDH. Seasonal Index calculations confirmed July as the predominant overall peak month (indices 1.4-2.5), with minimal dengue activity from January to March. While rainfall significantly influenced seasonality across all provinces. A negative binomial regression analysis indicated that all of the variables included in the model had no statistically significant relationship with dengue incidence. Furthermore, a Moran'sI analysis revealed a significant clustering effect only in YST (I =0.314, P=0.037). Conclusions: The finding underscores the critical requirement for adopting a highly focused approach, necessitating a shift toward region-specific interventions to effectively combat dengue and sustain progress toward good health and well-being for all.
Keywords:
Project Supported:
Clc Number:
Publication ethics
Academic misconduct statement
Mobile website
