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Human influenza A virus infections i...
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Agustian, Dwi.
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Human influenza A virus infections in rural communities in Indonesia: A small area spatial analysis.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Human influenza A virus infections in rural communities in Indonesia: A small area spatial analysis./
作者:
Agustian, Dwi.
面頁冊數:
98 p.
附註:
Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
Contained By:
Dissertation Abstracts International75-09B(E).
標題:
Epidemiology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3622542
ISBN:
9781303943577
Human influenza A virus infections in rural communities in Indonesia: A small area spatial analysis.
Agustian, Dwi.
Human influenza A virus infections in rural communities in Indonesia: A small area spatial analysis.
- 98 p.
Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
Thesis (Ph.D.)--University of Colorado Denver, Anschutz Medical Campus, 2014.
This item is not available from ProQuest Dissertations & Theses.
In Indonesia, although the number of human fatalities from avian influenza is the largest globally, human influenza A is not a priority. There have been no studies on influenza A's burden, its risk factors, and its geographical distribution in the community. This information is important for the disease control and prevention. The aim of this dissertation is to explore the ecological risk factors of human influenza A infections and its influence on the disease spatial patterns, and to predict the disease spatial burden in rural Indonesia.
ISBN: 9781303943577Subjects--Topical Terms:
568544
Epidemiology.
Human influenza A virus infections in rural communities in Indonesia: A small area spatial analysis.
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In Indonesia, although the number of human fatalities from avian influenza is the largest globally, human influenza A is not a priority. There have been no studies on influenza A's burden, its risk factors, and its geographical distribution in the community. This information is important for the disease control and prevention. The aim of this dissertation is to explore the ecological risk factors of human influenza A infections and its influence on the disease spatial patterns, and to predict the disease spatial burden in rural Indonesia.
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I conducted influenza A passive surveillance study in community health care setting and population census-mapping in two rural communities of Indonesia from 2008-2011. Reverse transcription-polymerase chain reaction was used for influenza A subtype identification. To identify the ecological risk factors, the cases from the passive surveillance and the controls from the population census were used to model the binary outcomes for influenza A/H3N2, A/pH1N1, and A/non-subtypeable infections in the household by Generalized Estimating Equation. To investigate influenza A clustering, I utilized purely spatial Scan statistics with Poisson discrete model with and without covariates adjustment. To estimate the population based disease burden, a zero inflated Poisson prediction model at the household level was built. Data from two sites used for model building and cross validation.
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A household with young children is associated with influenza A/H3N3(OR=5.0, 95%CI:3.8-6.6), A/pH1N1(OR=3.5, 95%CI:2.7-4.6), and A/Non-subtypeable infections (OR=3.7, 95%CI:2.4-5.9). Having more than 15 birds in the house is also associated with influenza A/H3N3(OR=5.0, 95%CI:2.0-12.8), A/pH1N1(OR=11.1, 95%CI:5.7-21.7), and A/Non-subtypeable(OR=12.9, 95%CI:4.0-41.9) infections. There are distinct locations for A/H3N3, A/pH1N1, and A/non-subtypeable most likely clusters, with relative risk of 11(p-value <0.001), 144(p-value <0.001), and 1087(p-value <0.001) respectively. Households with young children, keeping birds in the house, and neighborhood community health care utilization explained approximately 88%, 80%, and 100%, of the A/H3N3, A/pH1N1, and A/non-subtypeable clusters respectively. We estimate that there were 9051 (95% CI: 1,867 -- 36,205) of human influenza A cases or equal to incidence rate of 0.018 person-year from the population who were seeking care.
520
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To reduce the human influenza A transmission in the population, vaccination or a prevention program should target households with young children or/and birds. The influenza A cluster detection in this study are very useful tools for geographical-based epidemic control. Using population census data and controlling for passive surveillance bias we are able to show the spatial distribution of human influenza A morbidity in the area. This information is beneficial for public health program planning and geographical priority set up in the setting where resources are limited.
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