With the heaviest malaria burden in the region, Myanmar is central to the newly launched campaign to eliminate malaria from Southeast Asia. Malaria prevalence, incidence, and transmission risk are both highly heterogeneous and do not fully overlap, posing serious challenges for targeting elimination interventions. Research that enhances the understanding of space-time malaria risk dynamics and transmission pathways will improve elimination prospects. Project 3 addresses Research Area B, Transmission, focusing on the two major transmission pathways: human and mosquito. A suite of geospatial techniques will be introduced to model vector and parasite presence/abundance in space and time and establish relationships between human mobility and malaria transmission at multiple scales.
The first aim will establish spatially explicit relationships between environmental conditions, vector abundance, and malaria burden along a multi-seasonal temporal gradient to enable the development of a predictive malaria risk system at study sites in Myanmar and near its borders with China and Bangladesh. This will be accomplished through applying a combination of field sampling of mosquito abundance at high temporal density, DNA- based speciation of mosquitos, Plasmodium falciparum and Plasmodium vivax presence/abundance (from Project 1), satellite-derived environmental parameters, and random forest analytical framework. Tools will be developed to forecast falciparum and vivax malaria burden as a function of environmental conditions. The modeling results will be compared with the outcomes of Project 1 serological analyses that quantify the exposure of study participants to site-specific parasite sub- populations as defined in Project 2 genomic epidemiology studies.
Aim 2 will identify spatial drivers for malaria transmission and the relationships between patterns of human mobility and risk. Spatial network modeling approaches will be used to study human mobility at the village level based on the daily activities of individuals as reported through travel histories and traffic analyses. Longer-distance movements at a regional level, reported through travel histories and other travel data (e.g. rail, water travel, airways) will be used to assess regional transmission patterns and how populations may become vulnerable to infection. Human mobility patterns will also be linked to genetic information from Project 2 about parasite population structure and movement to assess the relationships between population movements and parasite migration. Together with the Mapping Core, this project will improve the ability of National Malaria Control Programs to target interventions much more precisely?and therefore more effectively and efficiently?than is possible with current tools and approaches.
