자료유형 | 학위논문 |
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서명/저자사항 | Environmental Infectious Disease Dynamics in Relation to Climate and Climate Change. |
개인저자 | Gorris, Morgan Elizabeth. |
단체저자명 | University of California, Irvine. Earth System Science - Ph.D.. |
발행사항 | [S.l.]: University of California, Irvine., 2019. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
형태사항 | 170 p. |
기본자료 저록 | Dissertations Abstracts International 81-04B. Dissertation Abstract International |
ISBN | 9781687985231 |
학위논문주기 | Thesis (Ph.D.)--University of California, Irvine, 2019. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
Advisor: Randerson, James T |
이용제한사항 | This item must not be sold to any third party vendors. |
요약 | Climate change poses multiple threats to human health, including changes in the burden of infectious diseases. Rising temperatures and shifts in precipitation patterns may reshape the geographical distributions of pathogenic organisms and disease vectors, potentially placing new communities at risk. Projections of environmental infectious diseases in response to climate change will help public health officials create disease surveillance programs and mitigation strategies. A precursor to modeling these projections is a basic understanding of the relationships between each infectious disease and the environment.My dissertation examined how climate conditions influence two different environmental infectious diseases in the United States: coccidioidomycosis (Valley fever) and West Nile virus. In my first study, I examined the climate and environmental conditions that structure the spatiotemporal dynamics of Valley fever incidence. To do so, I compiled a Valley fever case dataset for the southwestern U.S. From this study, I found areas endemic to Valley fever are described by hot and dry climate thresholds. In my second study, I used these climate thresholds to create a predictive model of the area currently endemic to Valley fever. Then, I used climate projections to create the first maps of future Valley fever endemicity. In my third chapter, I used machine learning to explore which climate conditions structure West Nile virus incidence throughout the U.S. I found the highest disease incidence in the northern Great Plains, which is categorized by dry and cold winters. This predictive model of disease incidence may be used for future projections of West Nile virus risk in response to climate change.The collective results of my dissertation help us understand how climate conditions influence two of the most important environmental infectious diseases in the U.S. and how climate change may affect the future burden of each disease. I am now sharing the results from my dissertation with the U.S. Environmental Protection Agency, state health agencies and epidemiologists, and physicians in hopes to alleviate the future burden of disease. |
일반주제명 | Climate change. Environmental studies. Epidemiology. |
언어 | 영어 |
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