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Article: Spatial analysis of hemorrhagic fever with renal syndrome in China

TitleSpatial analysis of hemorrhagic fever with renal syndrome in China
Authors
Issue Date2006
Citation
BMC Infectious Diseases, 2006, v. 6, article no. 77 How to Cite?
AbstractBackground: Hemorrhagic fever with renal syndrome (HFRS) is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS)-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. Methods: Annualized average incidence at a county level was calculated using HFRS cases reported during 1994-1998 in mainland China. GIS-based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. Results: Spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's 1 = 0.5044 (p = 0.001). Spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS (p < 0.01) with maximum spatial cluster sizes of ≤ 20% and ≤ 10% of the total population, respectively. Conclusion: The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS.
Persistent Identifierhttp://hdl.handle.net/10722/296589
ISSN
2023 Impact Factor: 3.4
2023 SCImago Journal Rankings: 1.031
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFang, Liqun-
dc.contributor.authorYan, Lei-
dc.contributor.authorLiang, Song-
dc.contributor.authorde Vlas, Sake J.-
dc.contributor.authorFeng, Dan-
dc.contributor.authorHan, Xiaona-
dc.contributor.authorZhao, Wenjuan-
dc.contributor.authorXu, Bing-
dc.contributor.authorBian, Ling-
dc.contributor.authorYang, Hong-
dc.contributor.authorGong, Peng-
dc.contributor.authorRichardus, Jan Hendrik-
dc.contributor.authorCao, Wuchun-
dc.date.accessioned2021-02-25T15:16:13Z-
dc.date.available2021-02-25T15:16:13Z-
dc.date.issued2006-
dc.identifier.citationBMC Infectious Diseases, 2006, v. 6, article no. 77-
dc.identifier.issn1471-2334-
dc.identifier.urihttp://hdl.handle.net/10722/296589-
dc.description.abstractBackground: Hemorrhagic fever with renal syndrome (HFRS) is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS)-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. Methods: Annualized average incidence at a county level was calculated using HFRS cases reported during 1994-1998 in mainland China. GIS-based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. Results: Spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's 1 = 0.5044 (p = 0.001). Spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS (p < 0.01) with maximum spatial cluster sizes of ≤ 20% and ≤ 10% of the total population, respectively. Conclusion: The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS.-
dc.languageeng-
dc.relation.ispartofBMC Infectious Diseases-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleSpatial analysis of hemorrhagic fever with renal syndrome in China-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/1471-2334-6-77-
dc.identifier.pmid16638156-
dc.identifier.pmcidPMC1471792-
dc.identifier.scopuseid_2-s2.0-33646893252-
dc.identifier.volume6-
dc.identifier.spagearticle no. 77-
dc.identifier.epagearticle no. 77-
dc.identifier.eissn1471-2334-
dc.identifier.isiWOS:000237978800001-
dc.identifier.issnl1471-2334-

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