{"title":"基于小学缺课人数的疫情时空分析——以2009年甲型H1N1流感大流行为例","authors":"Yusuke Kataoka, Yasushi Asami, K. Kohriyama","doi":"10.5638/THAGIS.20.149","DOIUrl":null,"url":null,"abstract":"This study aims to determine a spatial trend in epidemics by developing an epidemic model using the numbers of elementary school absentees and by conducting a spatio-temporal analysis of the pandemic influenza A H1N1 that occurred in 2009. We model an epidemic considering situations in multiple areas by applying the SIR model. We also set unknown parameters of infectious risks with regard to each inner and outer area and the traffic flow between areas. The parameters are estimated using the numbers of influenza-infected absentees from elementary schools in Sendai City and the numbers of trips, which were acquired through a person trip survey data. This analysis shows that the relationship of the infection risks with the each inner and outer school zone and that the effect of traffic flow between school zones on the infection risk increases roughly in proportion to traffic flow.","PeriodicalId":177070,"journal":{"name":"Theory and Applications of GIS","volume":"62 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatio-temporal analysis of an epidemic on the basis of the numbers of elementary school absentees: —The case of the pandemic influenza A H1N1 in 2009—\",\"authors\":\"Yusuke Kataoka, Yasushi Asami, K. Kohriyama\",\"doi\":\"10.5638/THAGIS.20.149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to determine a spatial trend in epidemics by developing an epidemic model using the numbers of elementary school absentees and by conducting a spatio-temporal analysis of the pandemic influenza A H1N1 that occurred in 2009. We model an epidemic considering situations in multiple areas by applying the SIR model. We also set unknown parameters of infectious risks with regard to each inner and outer area and the traffic flow between areas. The parameters are estimated using the numbers of influenza-infected absentees from elementary schools in Sendai City and the numbers of trips, which were acquired through a person trip survey data. This analysis shows that the relationship of the infection risks with the each inner and outer school zone and that the effect of traffic flow between school zones on the infection risk increases roughly in proportion to traffic flow.\",\"PeriodicalId\":177070,\"journal\":{\"name\":\"Theory and Applications of GIS\",\"volume\":\"62 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory and Applications of GIS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5638/THAGIS.20.149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory and Applications of GIS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5638/THAGIS.20.149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatio-temporal analysis of an epidemic on the basis of the numbers of elementary school absentees: —The case of the pandemic influenza A H1N1 in 2009—
This study aims to determine a spatial trend in epidemics by developing an epidemic model using the numbers of elementary school absentees and by conducting a spatio-temporal analysis of the pandemic influenza A H1N1 that occurred in 2009. We model an epidemic considering situations in multiple areas by applying the SIR model. We also set unknown parameters of infectious risks with regard to each inner and outer area and the traffic flow between areas. The parameters are estimated using the numbers of influenza-infected absentees from elementary schools in Sendai City and the numbers of trips, which were acquired through a person trip survey data. This analysis shows that the relationship of the infection risks with the each inner and outer school zone and that the effect of traffic flow between school zones on the infection risk increases roughly in proportion to traffic flow.