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Wavelets and Multilevel Analysis to Determine Spatial Dependencies of Seasonal Influenza, Weather and Pollution Association Across Chile 2010-2016
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Wavelets and Multilevel Analysis to Determine Spatial Dependencies of Seasonal Influenza, Weather and Pollution Association Across Chile 2010-2016. |
| 개인저자 | Garcia, Christian Rodrigo Garcia. |
| 단체저자명 | University of Pittsburgh. Graduate School of Public Health. |
| 발행사항 | [S.l.]: University of Pittsburgh., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 193 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-03B. Dissertation Abstract International |
| ISBN | 9781085746564 |
| 학위논문주기 | Thesis (Dr.P.H.)--University of Pittsburgh, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
Advisor: Harrison, Lee H. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 요약 | Influenza virus causes high burden of disease, especially in older adults and young children. The dynamics of influenza are not completely understood. Weather, population movement, and virus survival interact in complex fashion to produce annual epidemics. Chile is a country with a large range of latitudes with a public healthcare sector that covers 74% of the population. Influenza surveillance, pollution and weather data are periodically reported and publicly available. In our work we aimed to determine the spatial dependencies of influenza and the association between weather, pollution and influenza cases across Chile. For our purposes we used data from the Ministry of Health, national air pollution surveillance, national meteorological service between 2010 and 2016. We used cross-wavelet analysis to determine the timing relation between influenza-like surveillance and laboratory surveillance system. Also, we used wavelet transform and phase difference to determine the relationship between latitude and epidemic timing and to determine the presence of local waves of influenza between health networks. Finally, we used a zero-inflated negative binomial multilevel model to determine the association between influenza cases, weather and pollution across hospitals.Influenza-like illness had no difference in timing compared to laboratory-confirmed influenza A. A north to south pattern of influenza epidemic was found, especially in the central zone of the country where most of the population lives. Population size and latitude were associated to start and peak day of annual epidemics of seasonal influenza. Local outgoing and incoming travelling waves of influenza were found in 11 and 10 health networks, respectively. Local waves were located principally in the center and in the south of the country and were associated to population size. Finally, influenza cases were negatively associated with maximum temperature, minimum temperature and had a positive association with the concentration of particulate matter <2.5 關m (PM2.5).Public Health Significance: Our findings can help decision-makers to prepare influenza season, prioritize areas for early vaccination campaigns, establish standards for pollution, and set a baseline to compare the impact of policies to reduce particulate matter. |
| 일반주제명 | Public health. Epidemiology. |
| 언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
