Predicting Geographical Human Risk of West Nile Virus — Saskatchewan, 2003 and 2007
Objectives: To detail the use of a model to predict areas of low, medium, and high risk of West Nile virus (WNV) in humans in both 2003 and 2007 in the province of Saskatchewan. To identify consistent high-risk areas from year to year as well as important environmental variables within those high-ri...
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Veröffentlicht in: | Canadian journal of public health 2009-09, Vol.100 (5), p.344-348 |
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description | Objectives: To detail the use of a model to predict areas of low, medium, and high risk of West Nile virus (WNV) in humans in both 2003 and 2007 in the province of Saskatchewan. To identify consistent high-risk areas from year to year as well as important environmental variables within those high-risk areas. Methods: The number of laboratory-confirmed WNV individuals was obtained from Saskatchewan Health by rural municipality. The population at risk was obtained from Statistics Canada by rural municipality. Climate and habitat variables were incorporated into a discriminant analysis model with the production of risk maps as an end product. Results: The discriminant analysis models had testing classification accuracies of 67% in 2003 and 44% in 2007. Climate and habitat variables remained important in all models while some habitat variables were less important in 2007. Risk maps from historically trained 2007 model revealed a southwest to northeast decreasing trend of risk. Conclusion: The models could be useful for indicating areas of high risk on a year-to-year basis or based on historical data. High-risk regions are characterized by less rainfall in June and July followed by higher temperatures in July and August with less vegetation and water coverage than low-risk regions. Objectifs : Expliquer l'utilisation d'un modèle de prévision des secteurs à risque modéré, moyen et élevé pour les humains de contracter le virus du Nil occidental (VNO) en 2003 et en 2007 dans la province de la Saskatchewan. Déterminer les secteurs à risque uniformément élevé d'une année à l'autre, ainsi que les variables environnementales importantes dans les secteurs à risque élevé. Méthode : Nous avons obtenu auprès du ministère de la Santé de la Saskatchewan le nombre de cas séropositifs pour le VNO confirmés en laboratoire, par municipalité rurale. Statistique Canada nous a fourni le nombre de personnes à risque par municipalité rurale. Des variables climatiques et d'habitat ont été intégrées dans un modèle d'analyse discriminante afin de produire des cartes du risque. Résultats : Les modèles d'analyse discriminante étaient exacts à 67 % en 2003 et à 44 % en 2007. Les variables climatiques et d'habitat sont demeurées importantes dans tous les modèles, mais certaines variables d'habitat avaient moins d'importance en 2007. Les cartes du risque produites à partir du modèle chronologique de 2007 montrent que le risque a eu tendance à diminuer en allant du Sud-Ouest vers le Nord-Est |
doi_str_mv | 10.1007/BF03405266 |
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To identify consistent high-risk areas from year to year as well as important environmental variables within those high-risk areas. Methods: The number of laboratory-confirmed WNV individuals was obtained from Saskatchewan Health by rural municipality. The population at risk was obtained from Statistics Canada by rural municipality. Climate and habitat variables were incorporated into a discriminant analysis model with the production of risk maps as an end product. Results: The discriminant analysis models had testing classification accuracies of 67% in 2003 and 44% in 2007. Climate and habitat variables remained important in all models while some habitat variables were less important in 2007. Risk maps from historically trained 2007 model revealed a southwest to northeast decreasing trend of risk. Conclusion: The models could be useful for indicating areas of high risk on a year-to-year basis or based on historical data. High-risk regions are characterized by less rainfall in June and July followed by higher temperatures in July and August with less vegetation and water coverage than low-risk regions. Objectifs : Expliquer l'utilisation d'un modèle de prévision des secteurs à risque modéré, moyen et élevé pour les humains de contracter le virus du Nil occidental (VNO) en 2003 et en 2007 dans la province de la Saskatchewan. Déterminer les secteurs à risque uniformément élevé d'une année à l'autre, ainsi que les variables environnementales importantes dans les secteurs à risque élevé. Méthode : Nous avons obtenu auprès du ministère de la Santé de la Saskatchewan le nombre de cas séropositifs pour le VNO confirmés en laboratoire, par municipalité rurale. Statistique Canada nous a fourni le nombre de personnes à risque par municipalité rurale. Des variables climatiques et d'habitat ont été intégrées dans un modèle d'analyse discriminante afin de produire des cartes du risque. Résultats : Les modèles d'analyse discriminante étaient exacts à 67 % en 2003 et à 44 % en 2007. Les variables climatiques et d'habitat sont demeurées importantes dans tous les modèles, mais certaines variables d'habitat avaient moins d'importance en 2007. Les cartes du risque produites à partir du modèle chronologique de 2007 montrent que le risque a eu tendance à diminuer en allant du Sud-Ouest vers le Nord-Est. Conclusion : Ces modèles pourraient être utiles pour indiquer les secteurs à risque élevé d'une année à l'autre ou selon des données historiques. Les régions à risque élevé se caractérisent par une pluviosité relativement faible en juin et en juillet suivie de hausses de la température en juillet et en août, avec une couverture végétale et hydrique plus limitée que dans les régions à risque modéré.</description><identifier>ISSN: 0008-4263</identifier><identifier>EISSN: 1920-7476</identifier><identifier>DOI: 10.1007/BF03405266</identifier><identifier>PMID: 19994734</identifier><identifier>CODEN: CJPEA4</identifier><language>eng</language><publisher>Cham: Canadian Public Health Association</publisher><subject>2003 AD ; 2007 AD ; Accuracy ; Animals ; Arboviral encephalitis ; Arboviroses ; Behavior ; Biological and medical sciences ; Classification ; Data sampling ; Datasets ; Discriminant analysis ; Disease ; Disease models ; Disease Outbreaks ; Disease risk ; Environmental conditions ; Geography ; Health surveillance ; Human viral diseases ; Humans ; Infections ; Infectious diseases ; Medical sciences ; Medicine ; Medicine & Public Health ; Miscellaneous ; Modeling ; Models, Theoretical ; Mosquitoes ; Multivariate Analysis ; Population Surveillance ; Principal components analysis ; Public Health ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; QUANTITATIVE RESEARCH ; Remote sensing ; Risk Assessment ; Risk Factors ; Saskatchewan - epidemiology ; Social aspects ; Temperature ; Tropical viral diseases ; Viral diseases ; Viruses ; West Nile fever ; West Nile Fever - epidemiology ; West Nile Fever - transmission ; West Nile virus ; Wetlands ; Zoonoses - epidemiology</subject><ispartof>Canadian journal of public health, 2009-09, Vol.100 (5), p.344-348</ispartof><rights>Canadian Public Health Association, 2009 © Association canadienne de santé publique, 2009</rights><rights>The Canadian Public Health Association 2009</rights><rights>2015 INIST-CNRS</rights><rights>COPYRIGHT 2009 Springer</rights><rights>Copyright Canadian Public Health Association Sep/Oct 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c661t-b0c0dfc59cb5e17aec517564fb12276e98cd2100fb48b9f4f1d93895951cbf713</citedby><cites>FETCH-LOGICAL-c661t-b0c0dfc59cb5e17aec517564fb12276e98cd2100fb48b9f4f1d93895951cbf713</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/41995288$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/41995288$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,727,780,784,803,885,27924,27925,41488,42557,51319,53791,53793,58017,58250</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22177139$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19994734$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Epp, Tasha Y.</creatorcontrib><creatorcontrib>Waldner, Cheryl L.</creatorcontrib><creatorcontrib>Berke, Olaf</creatorcontrib><title>Predicting Geographical Human Risk of West Nile Virus — Saskatchewan, 2003 and 2007</title><title>Canadian journal of public health</title><addtitle>Can J Public Health</addtitle><addtitle>Can J Public Health</addtitle><description>Objectives: To detail the use of a model to predict areas of low, medium, and high risk of West Nile virus (WNV) in humans in both 2003 and 2007 in the province of Saskatchewan. To identify consistent high-risk areas from year to year as well as important environmental variables within those high-risk areas. Methods: The number of laboratory-confirmed WNV individuals was obtained from Saskatchewan Health by rural municipality. The population at risk was obtained from Statistics Canada by rural municipality. Climate and habitat variables were incorporated into a discriminant analysis model with the production of risk maps as an end product. Results: The discriminant analysis models had testing classification accuracies of 67% in 2003 and 44% in 2007. Climate and habitat variables remained important in all models while some habitat variables were less important in 2007. Risk maps from historically trained 2007 model revealed a southwest to northeast decreasing trend of risk. Conclusion: The models could be useful for indicating areas of high risk on a year-to-year basis or based on historical data. High-risk regions are characterized by less rainfall in June and July followed by higher temperatures in July and August with less vegetation and water coverage than low-risk regions. Objectifs : Expliquer l'utilisation d'un modèle de prévision des secteurs à risque modéré, moyen et élevé pour les humains de contracter le virus du Nil occidental (VNO) en 2003 et en 2007 dans la province de la Saskatchewan. Déterminer les secteurs à risque uniformément élevé d'une année à l'autre, ainsi que les variables environnementales importantes dans les secteurs à risque élevé. Méthode : Nous avons obtenu auprès du ministère de la Santé de la Saskatchewan le nombre de cas séropositifs pour le VNO confirmés en laboratoire, par municipalité rurale. Statistique Canada nous a fourni le nombre de personnes à risque par municipalité rurale. Des variables climatiques et d'habitat ont été intégrées dans un modèle d'analyse discriminante afin de produire des cartes du risque. Résultats : Les modèles d'analyse discriminante étaient exacts à 67 % en 2003 et à 44 % en 2007. Les variables climatiques et d'habitat sont demeurées importantes dans tous les modèles, mais certaines variables d'habitat avaient moins d'importance en 2007. Les cartes du risque produites à partir du modèle chronologique de 2007 montrent que le risque a eu tendance à diminuer en allant du Sud-Ouest vers le Nord-Est. Conclusion : Ces modèles pourraient être utiles pour indiquer les secteurs à risque élevé d'une année à l'autre ou selon des données historiques. Les régions à risque élevé se caractérisent par une pluviosité relativement faible en juin et en juillet suivie de hausses de la température en juillet et en août, avec une couverture végétale et hydrique plus limitée que dans les régions à risque modéré.</description><subject>2003 AD</subject><subject>2007 AD</subject><subject>Accuracy</subject><subject>Animals</subject><subject>Arboviral encephalitis</subject><subject>Arboviroses</subject><subject>Behavior</subject><subject>Biological and medical sciences</subject><subject>Classification</subject><subject>Data sampling</subject><subject>Datasets</subject><subject>Discriminant analysis</subject><subject>Disease</subject><subject>Disease models</subject><subject>Disease Outbreaks</subject><subject>Disease risk</subject><subject>Environmental conditions</subject><subject>Geography</subject><subject>Health surveillance</subject><subject>Human viral diseases</subject><subject>Humans</subject><subject>Infections</subject><subject>Infectious diseases</subject><subject>Medical sciences</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Miscellaneous</subject><subject>Modeling</subject><subject>Models, Theoretical</subject><subject>Mosquitoes</subject><subject>Multivariate Analysis</subject><subject>Population Surveillance</subject><subject>Principal components analysis</subject><subject>Public Health</subject><subject>Public health. Hygiene</subject><subject>Public health. Hygiene-occupational medicine</subject><subject>QUANTITATIVE RESEARCH</subject><subject>Remote sensing</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Saskatchewan - epidemiology</subject><subject>Social aspects</subject><subject>Temperature</subject><subject>Tropical viral diseases</subject><subject>Viral diseases</subject><subject>Viruses</subject><subject>West Nile fever</subject><subject>West Nile Fever - epidemiology</subject><subject>West Nile Fever - transmission</subject><subject>West Nile virus</subject><subject>Wetlands</subject><subject>Zoonoses - epidemiology</subject><issn>0008-4263</issn><issn>1920-7476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpt0stu1DAUBuAIgehQ2LAHWZWoxCXFlySON5VKRS9SVRClsLQcx854mrGndsJlx0PwhDwJHmU0M5FGWSSWv_zOOTlJ8hzBIwQhff_hDJIM5rgoHiQTxDBMaUaLh8kEQlimGS7IXvIkhFlcEkLJ42QPMcYySrJJcvvZq9rIztgGnCvXeLGYGilacNHPhQVfTLgDToPvKnTg2rQKfDO-D-Dfn7_gRoQ70cmp-insO4BjOBC2Xj7Qp8kjLdqgnq3u-8nt2cevpxfp1afzy9OTq1QWBerSCkpYa5kzWeUKUaFkjmheZLpCGNNCsVLWOJaoq6ysmM40qhkpWc5yJCtNEdlPjofcRV_NVS2V7bxo-cKbufC_uROGj3esmfLG_eAFo4TCZcDBKsC7-z4WyWeu9zZ-M8dkWQnNyojSATWiVdxY7WKWbJRVMdJZpWNf-AlGCJMiJ-UmdOTlwtzzbXS0A8WrVnMjd6a-Hr0QTad-dY3oQ-CXN9dje7hlp0q03TS4tu-Ms2EM3wxQeheCV3rdOwT5crj4Zrgifrnd7Q1dTVMEr1ZAhDhD2gsrTVg7jBGNP41F93ZwIW7ZRvlN13ce-2LQs9A5v07L4rE5LkvyH8656Ik</recordid><startdate>20090901</startdate><enddate>20090901</enddate><creator>Epp, Tasha Y.</creator><creator>Waldner, Cheryl L.</creator><creator>Berke, Olaf</creator><general>Canadian Public Health Association</general><general>Springer International Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>0-V</scope><scope>3V.</scope><scope>4S-</scope><scope>4U-</scope><scope>7QP</scope><scope>7QR</scope><scope>7RV</scope><scope>7T2</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>88J</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FQ</scope><scope>8FV</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AN0</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DPSOV</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>KC-</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2L</scope><scope>M2O</scope><scope>M2R</scope><scope>M3G</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope><scope>5PM</scope></search><sort><creationdate>20090901</creationdate><title>Predicting Geographical Human Risk of West Nile Virus — Saskatchewan, 2003 and 2007</title><author>Epp, Tasha Y. ; Waldner, Cheryl L. ; Berke, Olaf</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c661t-b0c0dfc59cb5e17aec517564fb12276e98cd2100fb48b9f4f1d93895951cbf713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>2003 AD</topic><topic>2007 AD</topic><topic>Accuracy</topic><topic>Animals</topic><topic>Arboviral encephalitis</topic><topic>Arboviroses</topic><topic>Behavior</topic><topic>Biological and medical sciences</topic><topic>Classification</topic><topic>Data sampling</topic><topic>Datasets</topic><topic>Discriminant analysis</topic><topic>Disease</topic><topic>Disease models</topic><topic>Disease Outbreaks</topic><topic>Disease risk</topic><topic>Environmental conditions</topic><topic>Geography</topic><topic>Health surveillance</topic><topic>Human viral diseases</topic><topic>Humans</topic><topic>Infections</topic><topic>Infectious diseases</topic><topic>Medical sciences</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Miscellaneous</topic><topic>Modeling</topic><topic>Models, Theoretical</topic><topic>Mosquitoes</topic><topic>Multivariate Analysis</topic><topic>Population Surveillance</topic><topic>Principal components analysis</topic><topic>Public Health</topic><topic>Public health. Hygiene</topic><topic>Public health. Hygiene-occupational medicine</topic><topic>QUANTITATIVE RESEARCH</topic><topic>Remote sensing</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>Saskatchewan - epidemiology</topic><topic>Social aspects</topic><topic>Temperature</topic><topic>Tropical viral diseases</topic><topic>Viral diseases</topic><topic>Viruses</topic><topic>West Nile fever</topic><topic>West Nile Fever - epidemiology</topic><topic>West Nile Fever - transmission</topic><topic>West Nile virus</topic><topic>Wetlands</topic><topic>Zoonoses - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Epp, Tasha Y.</creatorcontrib><creatorcontrib>Waldner, Cheryl L.</creatorcontrib><creatorcontrib>Berke, Olaf</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE 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health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Epp, Tasha Y.</au><au>Waldner, Cheryl L.</au><au>Berke, Olaf</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting Geographical Human Risk of West Nile Virus — Saskatchewan, 2003 and 2007</atitle><jtitle>Canadian journal of public health</jtitle><stitle>Can J Public Health</stitle><addtitle>Can J Public Health</addtitle><date>2009-09-01</date><risdate>2009</risdate><volume>100</volume><issue>5</issue><spage>344</spage><epage>348</epage><pages>344-348</pages><issn>0008-4263</issn><eissn>1920-7476</eissn><coden>CJPEA4</coden><abstract>Objectives: To detail the use of a model to predict areas of low, medium, and high risk of West Nile virus (WNV) in humans in both 2003 and 2007 in the province of Saskatchewan. To identify consistent high-risk areas from year to year as well as important environmental variables within those high-risk areas. Methods: The number of laboratory-confirmed WNV individuals was obtained from Saskatchewan Health by rural municipality. The population at risk was obtained from Statistics Canada by rural municipality. Climate and habitat variables were incorporated into a discriminant analysis model with the production of risk maps as an end product. Results: The discriminant analysis models had testing classification accuracies of 67% in 2003 and 44% in 2007. Climate and habitat variables remained important in all models while some habitat variables were less important in 2007. Risk maps from historically trained 2007 model revealed a southwest to northeast decreasing trend of risk. Conclusion: The models could be useful for indicating areas of high risk on a year-to-year basis or based on historical data. High-risk regions are characterized by less rainfall in June and July followed by higher temperatures in July and August with less vegetation and water coverage than low-risk regions. Objectifs : Expliquer l'utilisation d'un modèle de prévision des secteurs à risque modéré, moyen et élevé pour les humains de contracter le virus du Nil occidental (VNO) en 2003 et en 2007 dans la province de la Saskatchewan. Déterminer les secteurs à risque uniformément élevé d'une année à l'autre, ainsi que les variables environnementales importantes dans les secteurs à risque élevé. Méthode : Nous avons obtenu auprès du ministère de la Santé de la Saskatchewan le nombre de cas séropositifs pour le VNO confirmés en laboratoire, par municipalité rurale. Statistique Canada nous a fourni le nombre de personnes à risque par municipalité rurale. Des variables climatiques et d'habitat ont été intégrées dans un modèle d'analyse discriminante afin de produire des cartes du risque. Résultats : Les modèles d'analyse discriminante étaient exacts à 67 % en 2003 et à 44 % en 2007. Les variables climatiques et d'habitat sont demeurées importantes dans tous les modèles, mais certaines variables d'habitat avaient moins d'importance en 2007. Les cartes du risque produites à partir du modèle chronologique de 2007 montrent que le risque a eu tendance à diminuer en allant du Sud-Ouest vers le Nord-Est. Conclusion : Ces modèles pourraient être utiles pour indiquer les secteurs à risque élevé d'une année à l'autre ou selon des données historiques. Les régions à risque élevé se caractérisent par une pluviosité relativement faible en juin et en juillet suivie de hausses de la température en juillet et en août, avec une couverture végétale et hydrique plus limitée que dans les régions à risque modéré.</abstract><cop>Cham</cop><pub>Canadian Public Health Association</pub><pmid>19994734</pmid><doi>10.1007/BF03405266</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0008-4263 |
ispartof | Canadian journal of public health, 2009-09, Vol.100 (5), p.344-348 |
issn | 0008-4263 1920-7476 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6973701 |
source | MEDLINE; JSTOR Archive Collection A-Z Listing; EZB-FREE-00999 freely available EZB journals; PubMed Central; SpringerLink Journals - AutoHoldings |
subjects | 2003 AD 2007 AD Accuracy Animals Arboviral encephalitis Arboviroses Behavior Biological and medical sciences Classification Data sampling Datasets Discriminant analysis Disease Disease models Disease Outbreaks Disease risk Environmental conditions Geography Health surveillance Human viral diseases Humans Infections Infectious diseases Medical sciences Medicine Medicine & Public Health Miscellaneous Modeling Models, Theoretical Mosquitoes Multivariate Analysis Population Surveillance Principal components analysis Public Health Public health. Hygiene Public health. Hygiene-occupational medicine QUANTITATIVE RESEARCH Remote sensing Risk Assessment Risk Factors Saskatchewan - epidemiology Social aspects Temperature Tropical viral diseases Viral diseases Viruses West Nile fever West Nile Fever - epidemiology West Nile Fever - transmission West Nile virus Wetlands Zoonoses - epidemiology |
title | Predicting Geographical Human Risk of West Nile Virus — Saskatchewan, 2003 and 2007 |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T07%3A20%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Predicting%20Geographical%20Human%20Risk%20of%20West%20Nile%20Virus%20%E2%80%94%20Saskatchewan,%202003%20and%202007&rft.jtitle=Canadian%20journal%20of%20public%20health&rft.au=Epp,%20Tasha%20Y.&rft.date=2009-09-01&rft.volume=100&rft.issue=5&rft.spage=344&rft.epage=348&rft.pages=344-348&rft.issn=0008-4263&rft.eissn=1920-7476&rft.coden=CJPEA4&rft_id=info:doi/10.1007/BF03405266&rft_dat=%3Cgale_pubme%3EA211236538%3C/gale_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=232007748&rft_id=info:pmid/19994734&rft_galeid=A211236538&rft_jstor_id=41995288&rfr_iscdi=true |