title: GIS prediction model of malaria transmission in Jiangsu province.
abstract: OBJECTIVE
  To perform GIS spatial analysis on malaria transmission patterns in Jiangsu after setting up a malaria database and developing GIS model of malaria transmission in Jiangsu province.
  
  
  METHODS
  The epidemiological GIS database of malaria in Jiangsu province was established using ArcView 3.0a software. The climate data covering Jiangsu province and its peripheral area were extracted from the FAOCLIM database, the total growing degree days (TGDD) for Plasmodium vivax were calculated, and spatial distribution for TGDD was analyzed by ArcVeiw 3.0a.
  
  
  RESULTS
  The predicted malaria distribution map based on TGDD was created, which showed that the transmission of malaria decreased gradually from west to east, which can be divided into three belts according to the degree of transmission. The 14-year mean morbidity distribution map of malaria in Jiangsu showed that the middle and west parts of Jiangsu is the most serious endemic area. The morbidity in the areas along the Taihu valley, such as Suzhou, Wuxi and Changzhou, as well as Nantong and a few of northern counties are the lowest. The morbidity of other places is at the middle level. The 14-year mean morbidity distribution map of malaria is correlated with predicted malaria distribution map for TGDD.
  
  
  CONCLUSIONS
  It is possible to monitor the malaria transmission by GIS predicted model based on TGDD.
authors.affiliation: Jiangsu Institute of Parasitic Diseases, Wuxi 214064, China.
authors.forename: Guojing
authors.initials: G
authors.lastname: Yang
authors.forename: Xiaonong
authors.initials: X
authors.lastname: Zhou
authors.forename: J B
authors.initials: JB
authors.lastname: Malone
authors.forename: J C
authors.initials: JC
authors.lastname: McCarroll
authors.forename: Tianping
authors.initials: T
authors.lastname: Wang
authors.forename: Jianxiang
authors.initials: J
authors.lastname: Liu
authors.forename: Qi
authors.initials: Q
authors.lastname: Gao
authors.forename: Xiaoping
authors.initials: X
authors.lastname: Zhang
authors.forename: Qingbiao
authors.initials: Q
authors.lastname: Hong
authors.forename: Leping
authors.initials: L
authors.lastname: Sun
mesh_terms: D002681:China / Q000453:epidemiology; D016206:Databases, Bibliographic; D040362:Geographic Information Systems; D006801:Humans; D008288:Malaria / Q000453:epidemiology / Q000635:transmission*; D008954:Models, Biological