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Article: Effects of geographic scale on population factors in acute disease diffusion analysis

TitleEffects of geographic scale on population factors in acute disease diffusion analysis
Authors
Issue Date2015
Citation
Journal of Acute Disease, 2015, v. 4 n. 4, p. 287-291 How to Cite?
AbstractObjective To explore socio-demographic data of the population as proxies for risk factors in disease transmission modeling at different geographic scales. Methods Patient records of confirmed H1N1 influenza were analyzed at three geographic aggregation levels together with population census statistics. Results The study confirmed that four population factors were related in different degrees to disease incidence, but the results varied according to spatial resolution. The degree of association actually decreased when data of a higher spatial resolution were used. Conclusions We concluded that variables at suitable spatial resolution may be useful in improving the predictive powers of models for disease outbreaks.
Persistent Identifierhttp://hdl.handle.net/10722/225001

 

DC FieldValueLanguage
dc.contributor.authorLai, PC-
dc.contributor.authorChow, CB-
dc.contributor.authorWong, FHT-
dc.contributor.authorKwong, KH-
dc.contributor.authorLiu, SH-
dc.contributor.authorTong, WK-
dc.contributor.authorCheung, WK-
dc.contributor.authorWong, WL-
dc.contributor.authorKwan, YW-
dc.date.accessioned2016-04-18T03:35:14Z-
dc.date.available2016-04-18T03:35:14Z-
dc.date.issued2015-
dc.identifier.citationJournal of Acute Disease, 2015, v. 4 n. 4, p. 287-291-
dc.identifier.urihttp://hdl.handle.net/10722/225001-
dc.description.abstractObjective To explore socio-demographic data of the population as proxies for risk factors in disease transmission modeling at different geographic scales. Methods Patient records of confirmed H1N1 influenza were analyzed at three geographic aggregation levels together with population census statistics. Results The study confirmed that four population factors were related in different degrees to disease incidence, but the results varied according to spatial resolution. The degree of association actually decreased when data of a higher spatial resolution were used. Conclusions We concluded that variables at suitable spatial resolution may be useful in improving the predictive powers of models for disease outbreaks.-
dc.languageeng-
dc.relation.ispartofJournal of Acute Disease-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleEffects of geographic scale on population factors in acute disease diffusion analysis-
dc.typeArticle-
dc.identifier.emailLai, PC: pclai@hku.hk-
dc.identifier.emailCheung, WK: alessi@hku.hk-
dc.identifier.authorityLai, PC=rp00565-
dc.identifier.authorityCheung, WK=rp01590-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.joad.2015.06.006-
dc.identifier.hkuros257646-

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