Mapping residual malaria transmission in Vietnam

Area of Science:

• Epidemiology and Biostatistics
• Geospatial Analysis in Public Health
• Infectious Disease Modeling

Background:

• Vietnam aims to eliminate malaria by 2030, facing challenges from imported cases and residual transmission.
• Understanding spatial and temporal variations in malaria risk is critical for effective control strategies.
• Geostatistical modeling of vulnerability and receptivity is essential for preventing malaria reintroduction.

Purpose of the Study:

• To model the spatiotemporal heterogeneity of malaria vulnerability (importation rate) and receptivity (reproduction number) in Vietnam.
• To identify high-risk regions and time periods for malaria transmission.
• To provide data-driven insights for targeted malaria elimination interventions.

Main Methods:

• Utilized malaria case data from 2019 to 2022 to train network and geostatistical models.
• Estimated vulnerability based on the abundance of imported malaria cases.
• Quantified receptivity using a transmission model incorporating environmental covariates.

Main Results:

• Significant spatiotemporal heterogeneity observed in malaria vulnerability and receptivity metrics.
• Malaria importations are concentrated in the South Central Coast and Central Highlands.
• The reproduction number, while averaging less than one, temporarily exceeds one in specific locations and seasons, particularly in forested areas.

Conclusions:

• Despite overall declining trends, localized areas with elevated malaria transmission potential pose a risk to elimination goals.
• Predictive maps highlighting spatiotemporal variations in risk can guide the deployment of targeted interventions.
• Addressing pockets of high receptivity and vulnerability is key to achieving and sustaining malaria elimination in Vietnam.