Effects of climate on pathogen spread
Many regions have seen their populations being affected at times by diseases such as malaria in epidemic outbreaks that appear to follow climatic anomalies, especially those of inter-annual temperature. It is understood that climate suitability played a role in the expansion and persistence of these pathogens. Association of climatic conditions with the dynamics of these diseases suggest that these pathogens could further affecting millions of populations in these regions. I am interested in using mechanistic modeling approaches to fit malaria incidence data to project effects into the future given, for instance, climate change scenarios.
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Spatial dynamics of human mobility
Host movement is a critical determinant of the spatial dynamics and patterns of any infectious disease, and, in particular, the study of human movement provides unique opportunities and challenges for understanding patterns of infectious disease transmission. I have developed models based on gravity and conditional autoregression of individual human movement that lay the foundation for future research in this area. Mobility models rely on data obtained from different sources including national censuses, air travel data, mobile phone networks, and other “big data” sources related to social media use. Current applications of these models include quantifying variation in human movement among regions of contrasting malaria and Zika epidemiology in Ethiopia and Colombia respectively, as well as investigating how physical and demographic factors such as population, economic status, and access to roads affect human mobility.
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Spatial dynamics of pathogen transmission
One fundamental geographic question is that of spatial pattern and scale. That is, at what scales are spatial patterns consistent and discernible? I have led a study on geospatial analysis to fit spatial correlation functions over data on environmental factors such as temperature and humidity. While these concepts are not typically applied in the realm of disease transmission, owing to the complexity related to spatial patterns of disease, they remain important in understanding the spatial scale at which disease transmissions patterns are consistent and discernible. I have laid the theoretical foundations for answering such questions by deriving metrics from mechanistic models of transmission that integrate data about spatial variation and movement of humans at a range of spatial scales. Using simulations from these models and spatially explicit disease incidence data, I investigate at what scale models can be used to successfully predict spatially variable patterns of disease prevalence.
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