Off-campus South Dakota State University users: To download campus access theses, please use the following link to log into our proxy server with your South Dakota State University ID and password.
Non-South Dakota State University users: Please talk to your librarian about requesting this thesis through interlibrary loan.
Dissertation - University Access Only
Doctor of Philosophy (PhD)
Department / School
Geospatial Science and Engineering
Michael C. Wimberly
This dissertation research examined the spatial and temporal patterns of malaria with multiple environmental and climate factors in the highlands of Ethiopia. The research aimed at achieving three main objectives; (i) to assess the potential for using remotely-sensed environmental variables to develop time series models of malaria cases; (ii) to develop a map of land cover, including seasonal wetlands, over the Amhara region and assess the influence of wetlands on the spatial distribution of malaria; and (iii) to explore potential long-term seasonal influences of climatic variability on malaria during the peak epidemic season. The following are the major findings of this research. First, there was strong positive spatial association of malaria incidence with the distribution of wetlands. Second, temporal associations of remotely sensed environmental variables, including rainfall, land-surface temperature (LST), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and evapotranspiration (ET) with malaria cases were found with lags ranging from one to three months. Third, the addition of malaria surveillance, in addition to environmental variables, in models that predict malaria yielded better model fit. Fourth, preceding weather factors influenced malaria incidence during peak transmission seasons and malaria incidence during the early peak malaria was correlated with the late peak season. Overall, the study demonstrated the utility of multi-sensor satellite data to assess the spatial and temporal variability of malaria environmental factors. The approach used in this research can be applied in the development of future malaria early warning systems to enable public health decision makers to effectively plan malaria control and elimination strategies.
Library of Congress Subject Headings
Malaria -- Ethiopia -- ʼAmāra kelel -- Prevention
Includes bibliographical references (pages 148-151)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Midekisa, Alemayehu Abebe, "Integrating Multi-Sensor Satellite Data For Malaria Early Warning in the Amhara Region of Ethiopia" (2014). Electronic Theses and Dissertations. 2062.