Quantifying Human Movement Patterns for Public Health
Human travel affects important processes in public health and infectious disease dynamics. Refined spatial and temporal data are needed to accurately model how the dynamics of human travel contribute to epidemiological patterns of disease as well as access to healthcare resources. Here, I address a number of key issues related to modeling human mobility patterns and applications for understanding the spatial spread of infectious diseases and geographic access to public health resources. Using large sources of behavioral data anonymously collected from mobile phones within two African countries, I first analyze the utility of these data to quantify human mobility patterns as well as the usefulness of common modeling frameworks. Then I compare these data to two more common sources of human travel data: the national census and a comprehensive travel survey. Next, I use these data to assess the impact of human travel on the movement of malaria parasites. The final component of my thesis focuses on the utility of this data source to generally understand the role of geographic isolation on travel patterns to better understand the disparity between areas with various levels of access to public resources and the uptake of preventative healthcare such as immunizations and antenatal care.
- Engineering and Public Policy
- Doctor of Philosophy (PhD)