Understanding the population risk from malaria by counting human mobility and malaria risk

Authors: Yao Li*, Department of Geographical Science, University of Maryland, Kathleen Stewart, Department of Geographical Science, University of Maryland
Topics: Geographic Information Science and Systems, Medical and Health Geography
Keywords: Malaria, prevalence, human mobility
Session Type: Paper
Day: 4/8/2020
Start / End Time: 1:45 PM / 3:00 PM
Room: Governors Square 16, Sheraton, Concourse Level
Presentation File: No File Uploaded


Much effort has been made to control malaria over the past decades in South-East Asia Confirmed cases of P. Falciparum and P. vivax malaria were reduced by 46%, and mortality by 60%. However, for areas where malaria still exists albeit at low levels of transmission, mass controls are not necessarily efficient. To bridge this gap, we need a better understanding of the factors and how local people put themselves at risk. Here we present an intersection analysis between human mobility and malaria risk information. Respectively, an agent-based model to simulate the movements of villagers in Singu Township, located in central Myanmar and an ecological niche modeling will be applied to calculate malaria risk surface for Singu Township. Travel history data was collected in 37 villages in Singu Township between 2018 and 2019. This research will help us to understand the patterns of movements of these local people as a step towards understanding how mobility could be impacting their risk as well as the transmission of malaria in this area.

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