Date of Graduation
Statler College of Engineering and Mineral Resources
Civil and Environmental Engineering
The association of cholera with the climatic processes is well documented. However the effects of changing climate on occurrence of cholera is not yet evaluated, perhaps due to unavailability of geophysical data and their quantitative linkages with cholera. Global climate models (GCMs) outputs are available at coarse resolution of 200-300km, but the diseases usually occur at 10-15 km, therefore, it is rather challenging to link any GCM outputs with a disease. The goal of this research is to develop algorithms that can link diarrheal diseases with changing climatic conditions. Within this context, cholera is used as a model disease due to availability of epidemiological information for over four decades. The Bengal Delta region of the South Asia has a unique pattern of cholera outbreaks with one in spring and other in the autumn season.;A new framework using data mining technique along with optimization method, Support Vector Machine -- Particle Swarm Optimization (SVM-PSO) was developed to downscale GCM output to link with local hydroclimate processes. The method is used following traditional (such as downscale precipitation, then to river discharge) and non-traditional (downscale river discharge directly thereby reducing uncertainty) routes of hydroclimatic principles. Two different types of models were developed to link climate change with cholera including logistical regression and copula based probabilistic algorithms.;Three research objectives of this dissertation were to (i) develop algorithms to traditionally link geophysical processes with cholera and investigate changing patterns of climate on disease occurrence; (ii) develop statistical algorithms to downscale non-traditional geophysical processes and to link with cholera, and compare it with the traditional approach, and (iii) provide a conceptual systems approach to mechanistically simulate cholera under changing climate. The motivation to use several different techniques is to avoid any mathematical manipulation of the results and interpretations; thus providing a robust means to understand as to what will happen to cholera under changing climate. A mechanistic model using systems approach was developed that linked several hydroclimate variables with cholera outbreaks in the Bengal Delta. The model results suggest that probability of extreme cholera is likely to decrease in the next few decades, provided the regional geomorphology of river systems remains unaltered.
Nasr Azadani, Fariborz, "Hydroclimatic assessment of changing climate on diarrheal diseases with reference to cholera" (2016). Graduate Theses, Dissertations, and Problem Reports. 6296.