ABSTRACT
Background
More details about human movement patterns are needed to evaluate relationships between daily travel and malaria risk at finer scales. A multi-agent mobility simulation model was built to simulate the movements of villagers between home and their workplaces in two townships in Myanmar.
Methods
An agent-based model (ABM) was built to simulate daily travel to and from work based on responses to a travel survey. Key elements for the ABM were lan dcover, travel time, travel mode, occupation, malaria prevalence, and a detailed road network. Most visited network segments (MVS) for different occupations and for malaria-positive cases were extracted and compared. Data from a separate survey was used to validate the simulation.
Results
Mobility characteristics for different occupation groups showed that while certain patterns were shared among some groups, there were also patterns that were unique to an occupation group. Forest workers were estimated to be the most mobile occupation group, and also had the highest potential malaria exposure associated with their daily travel in Ann Township. In Singu Township, forest workers were not the most mobile group; however, they were estimated to visit regions that had higher prevalence of malaria infection over other occupation groups.
Conclusions
Using an ABM to simulate daily travel generated mobility patterns for different occupation groups. These spatial patterns va ried by occupation. Our simulation identified occupations at a higher risk of being exposed to malaria and where these exposures were more likely to occur.
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