Research in this area focuses on the underlying factors that affect human health, particularly in less wealthy areas which are quite vulnerable to the impacts of environmental variability and change infectious disease epidemiology as it relates to time, space and climate change. Our faculty use novel machine learning algorithms, geospatial and informatics tools to improve inferential techniques to understand spatiotemporal patterns of disease dynamics.
Dr. Ubydul Haque
Dr. Uyen-Sa Nguyen
Dr. Malinee Neelamegam
- Annan E, Guo J, Angulo-Molina A, Yaacob WFW, Aghamohammadi N, Guetterman T, Yavaşoglu SI, Bardosh K, Dom NC, Zhao B, Lopez-Lemus UA, Khan L, Nguyen USDT, Haque U. Community acceptability of dengue fever surveillance using unmanned aerial vehicles: A cross-sectional study in Malaysia, Mexico, and Turkey. Travel Medicine and Infectious Disease. 1016/j.tmaid.2022.102360
- Jailos Lubinda, Ubydul Haque, Yaxin Bi, Busiku Hamainza, Adrian J. Moore. Near-term climate change impacts on sub-national malaria transmission. Sci Rep. 2021; 11: 751. doi: 10.1038/s41598-020-80432-9.
- S. Rahman, Chamsai Pientong, Sumaira Zafar, Tipaya Ekalaksananan, Richard E. Paul, Ubydul Haque, Joacim Rocklöv, Hans J. Overgaard. Mapping the spatial distribution of the dengue vector Aedes aegypti and predicting its abundance in northeastern Thailand using machine-learning approach. One Health. 2021 Dec; 13: 100358. doi: 10.1016/j.onehlt.2021.100358.