Document Detail

Modeling and predicting seasonal influenza transmission in warm regions using climatological parameters.
MedLine Citation:
PMID:  20209164     Owner:  NLM     Status:  MEDLINE    
BACKGROUND: Influenza transmission is often associated with climatic factors. As the epidemic pattern varies geographically, the roles of climatic factors may not be unique. Previous in vivo studies revealed the direct effect of winter-like humidity on air-borne influenza transmission that dominates in regions with temperate climate, while influenza in the tropics is more effectively transmitted through direct contact.
METHODOLOGY/PRINCIPAL FINDINGS: Using time series model, we analyzed the role of climatic factors on the epidemiology of influenza transmission in two regions characterized by warm climate: Hong Kong (China) and Maricopa County (Arizona, USA). These two regions have comparable temperature but distinctly different rainfall. Specifically we employed Autoregressive Integrated Moving Average (ARIMA) model along with climatic parameters as measured from ground stations and NASA satellites. Our studies showed that including the climatic variables as input series result in models with better performance than the univariate model where the influenza cases depend only on its past values and error signal. The best model for Hong Kong influenza was obtained when Land Surface Temperature (LST), rainfall and relative humidity were included as input series. Meanwhile for Maricopa County we found that including either maximum atmospheric pressure or mean air temperature gave the most improvement in the model performances.
CONCLUSIONS/SIGNIFICANCE: Our results showed that including the environmental variables generally increases the prediction capability. Therefore, for countries without advanced influenza surveillance systems, environmental variables can be used for estimating influenza transmission at present and in the near future.
Radina P Soebiyanto; Farida Adimi; Richard K Kiang
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2010-03-01
Journal Detail:
Title:  PloS one     Volume:  5     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2010  
Date Detail:
Created Date:  2010-03-08     Completed Date:  2011-01-11     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101285081     Medline TA:  PLoS One     Country:  United States    
Other Details:
Languages:  eng     Pagination:  e9450     Citation Subset:  IM    
Global Change Data Center, NASA Goddard Space Flight Center, Greenbelt, Maryland, United States of America.
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MeSH Terms
Hong Kong
Influenza, Human / epidemiology*,  transmission*
Models, Theoretical
Regression Analysis
Tropical Climate

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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