Spatio-Temporal Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014
Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might a...
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| description | Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease. |
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The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0167836</identifier><identifier>PMID: 28030550</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Biology and Life Sciences ; China - epidemiology ; Cities ; Cluster Analysis ; Clustering ; Computer and Information Sciences ; Correlation analysis ; Data processing ; Disease control ; Disease Outbreaks - statistics & numerical data ; Earth Sciences ; Ecological monitoring ; Economics ; Epidemics ; Fever ; Hemorrhage ; Hemorrhagic fever with renal syndrome ; Hemorrhagic Fever with Renal Syndrome - epidemiology ; Heterogeneity ; Human population density ; Human populations ; Humans ; Humidity ; Incidence ; Infectious diseases ; Kidneys ; Laboratories ; Medicine and Health Sciences ; Outbreaks ; People and Places ; Population (statistical) ; Population density ; Remote sensing ; Research methodology ; Seasons ; Socioeconomics ; Spatial analysis ; Spatial distribution ; Spatio-Temporal Analysis ; Statistical analysis ; Statistics ; Studies</subject><ispartof>PloS one, 2016-12, Vol.11 (12), p.e0167836-e0167836</ispartof><rights>2016 Ge et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. 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Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014</title><author>Ge, Liang ; Zhao, Youlin ; Zhou, Kui ; Mu, Xiangming ; Yu, Haibo ; Wang, Yongfeng ; Wang, Ning ; Fan, Hong ; Guo, Liqiang ; Huo, XiXiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c559t-a6e387444bc1377f99951a9d6ebf082efdd1ac9c9309d9537e00e46e40331cae3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Biology and Life Sciences</topic><topic>China - epidemiology</topic><topic>Cities</topic><topic>Cluster Analysis</topic><topic>Clustering</topic><topic>Computer and Information Sciences</topic><topic>Correlation analysis</topic><topic>Data processing</topic><topic>Disease control</topic><topic>Disease Outbreaks - statistics & numerical data</topic><topic>Earth Sciences</topic><topic>Ecological 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titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ge, Liang</au><au>Zhao, Youlin</au><au>Zhou, Kui</au><au>Mu, Xiangming</au><au>Yu, Haibo</au><au>Wang, Yongfeng</au><au>Wang, Ning</au><au>Fan, Hong</au><au>Guo, Liqiang</au><au>Huo, XiXiang</au><au>de la Torre, Juan C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio-Temporal Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2016-12-01</date><risdate>2016</risdate><volume>11</volume><issue>12</issue><spage>e0167836</spage><epage>e0167836</epage><pages>e0167836-e0167836</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28030550</pmid><doi>10.1371/journal.pone.0167836</doi><oa>free_for_read</oa></addata></record> |
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| ispartof | PloS one, 2016-12, Vol.11 (12), p.e0167836-e0167836 |
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| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Biology and Life Sciences China - epidemiology Cities Cluster Analysis Clustering Computer and Information Sciences Correlation analysis Data processing Disease control Disease Outbreaks - statistics & numerical data Earth Sciences Ecological monitoring Economics Epidemics Fever Hemorrhage Hemorrhagic fever with renal syndrome Hemorrhagic Fever with Renal Syndrome - epidemiology Heterogeneity Human population density Human populations Humans Humidity Incidence Infectious diseases Kidneys Laboratories Medicine and Health Sciences Outbreaks People and Places Population (statistical) Population density Remote sensing Research methodology Seasons Socioeconomics Spatial analysis Spatial distribution Spatio-Temporal Analysis Statistical analysis Statistics Studies |
| title | Spatio-Temporal Pattern and Influencing Factors of Hemorrhagic Fever with Renal Syndrome (HFRS) in Hubei Province (China) between 2005 and 2014 |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T10%3A14%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatio-Temporal%20Pattern%20and%20Influencing%20Factors%20of%20Hemorrhagic%20Fever%20with%20Renal%20Syndrome%20(HFRS)%20in%20Hubei%20Province%20(China)%20between%202005%20and%202014&rft.jtitle=PloS%20one&rft.au=Ge,%20Liang&rft.date=2016-12-01&rft.volume=11&rft.issue=12&rft.spage=e0167836&rft.epage=e0167836&rft.pages=e0167836-e0167836&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0167836&rft_dat=%3Cproquest_plos_%3E1859484996%3C/proquest_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1853732159&rft_id=info:pmid/28030550&rft_doaj_id=oai_doaj_org_article_68d345da90b24ba1900d293b26c2e855&rfr_iscdi=true |