Fine-scale maps of malaria incidence to inform risk stratification in Laos

Abstract

Abstract Background Malaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017–2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data. Methods A Bayesian geostatistical framework incorporating population data and treatment-seeking propensity was developed. The models incorporated static and dynamic factors and accounted for spatial heterogeneity. Results Results showed a significant decline in malaria cases in Laos over the five-year period and a shift in transmission patterns. While the north became malaria-free, the south experienced ongoing transmission with sporadic outbreaks. Conclusion The risk maps provided insights into changing transmission patterns and supported risk stratification. These risk maps are valuable tools for malaria control in Laos, aiding resource allocation, identifying intervention gaps, and raising public awareness. The study enhances understanding of malaria transmission dynamics and facilitates evidence-based decision-making for targeted interventions in high-risk areas.