Literature DB >> 29173968

Causality test of ambient fine particles and human influenza in Taiwan: Age group-specific disparity and geographic heterogeneity.

Cathy W S Chen1, Ying-Hen Hsieh2, Hung-Chieh Su3, Jia Jing Wu1.   

Abstract

Influenza is a major global public health problem, with serious outcomes that can result in hospitalization or even death. We investigate the causal relationship between human influenza cases and air pollution, quantified by ambient fine particles <2.5μm in aerodynamic diameter (PM2.5). A modified Granger causality test is proposed to ascertain age group-specific causal relationship between weekly influenza cases and weekly adjusted accumulative PM2.5 from 2009 to 2015 in 11 cities and counties in Taiwan. We examine the causal relationship based on posterior probabilities of the log-linear integer-valued GARCH (generalized autoregressive conditional heteroscedastic) model with covariates, which enable us to handle characteristics of influenza data such as integer-value, lagged dependence, and over-dispersion. The resulting posterior probabilities show that the adult age group (25-64) and the elderly group in New Taipei in the north and cities in southwestern part of Taiwan are strongly affected by ambient fine particles. Moreover, the elderly group is clearly affected in all study sites. Globalization and economic growth have resulted in increased ambient air pollution (including PM2.5) and subsequently substantial public health concerns in the West Pacific region. Minimizing exposure to air pollutants is particularly important for the elderly and susceptible individuals with respiratory diseases.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Ambient fine particles; Bayesian MCMC method; Generalized Poisson; Integer-valued GARCH; Over-dispersion; Posterior odds ratio

Mesh:

Substances:

Year:  2017        PMID: 29173968     DOI: 10.1016/j.envint.2017.10.011

Source DB:  PubMed          Journal:  Environ Int        ISSN: 0160-4120            Impact factor:   9.621


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