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Article: Effects of geographic scale on population factors in acute disease diffusion analysis
Title | Effects of geographic scale on population factors in acute disease diffusion analysis |
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Authors | |
Issue Date | 2015 |
Citation | Journal of Acute Disease, 2015, v. 4 n. 4, p. 287-291 How to Cite? |
Abstract | Objective 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 Identifier | http://hdl.handle.net/10722/225001 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Lai, PC | - |
dc.contributor.author | Chow, CB | - |
dc.contributor.author | Wong, FHT | - |
dc.contributor.author | Kwong, KH | - |
dc.contributor.author | Liu, SH | - |
dc.contributor.author | Tong, WK | - |
dc.contributor.author | Cheung, WK | - |
dc.contributor.author | Wong, WL | - |
dc.contributor.author | Kwan, YW | - |
dc.date.accessioned | 2016-04-18T03:35:14Z | - |
dc.date.available | 2016-04-18T03:35:14Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Journal of Acute Disease, 2015, v. 4 n. 4, p. 287-291 | - |
dc.identifier.uri | http://hdl.handle.net/10722/225001 | - |
dc.description.abstract | Objective 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.language | eng | - |
dc.relation.ispartof | Journal of Acute Disease | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | Effects of geographic scale on population factors in acute disease diffusion analysis | - |
dc.type | Article | - |
dc.identifier.email | Lai, PC: pclai@hku.hk | - |
dc.identifier.email | Cheung, WK: alessi@hku.hk | - |
dc.identifier.authority | Lai, PC=rp00565 | - |
dc.identifier.authority | Cheung, WK=rp01590 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1016/j.joad.2015.06.006 | - |
dc.identifier.hkuros | 257646 | - |
dc.identifier.isi | WOS:000215278600006 | - |