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www.mdpi.com/journal/ijerph Article Spatial Diffusion of Influenza Outbreak-Related Climate Factors in Chiang Mai Province, Thailand (2012)
BibTeX
@MISC{Nakapan12www.mdpi.com/journal/ijerpharticle,
author = {Supachai Nakapan and Nitin Kumar Tripathi and Taravudh Tipdecho and Marc Souris},
title = {www.mdpi.com/journal/ijerph Article Spatial Diffusion of Influenza Outbreak-Related Climate Factors in Chiang Mai Province, Thailand},
year = {2012}
}
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Abstract
Abstract: Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical
Keyphrases
chiang mai province influenza outbreak influenza outbreak-related climate factor climate factor climatic factor minimum temperature influenza risk zone statistical analysis northern thailand geographic information system influenza incidence rainy day spatial diffusion potential risk area south east asia multiple linear regression technique temperature difference relative humidity statistical model respiratory illness studied area tropical area significance correlation inverse distance weighted climate pattern chiang mai important leading cause
