title: Modelling input-output flows of severe acute respiratory syndrome in mainland China.
abstract: BACKGROUND
  Severe acute respiratory syndrome (SARS) originated in China in 2002, and it spread to 26 provinces in mainland China and 32 countries across five continents in a matter of months. This outbreak resulted in 774 deaths. However, the spatial features and potential determinants of SARS input-output flows remain unclear.
  
  
  METHODS
  We used an adjusted spatial interaction model to examine the spatial effects and potential factors associated with SARS input-output flows.
  
  
  RESULTS
  The presence of origin-based spatial dependence positively affected SARS input-output flows from the neighbours of the origin regions. Two components of the input-output flows, migrant and hospitalization flows, exhibited distinctive features. The origin-based and destination-based spatial dependence positively affected migrant flows (i.e., due to those seeking jobs) from the neighbours of origin and destination locations. Similarly, the destination-based spatial dependence also positively affected hospitalization flows (i.e., due to those seeking treatment) from the neighbours of destination regions. However, the origin-to-destination based spatial dependence negatively affected hospitalisation flows from the neighbours of origin-to-destination regions. The direct effects accounted for 78% of the SARS input-output flows, which was 3.56-fold greater than the indirect effects. Differences in regional income drove the SARS input-output flows. Therefore, urban income had a positive effect, whereas rural income had a negative effect. Total interregional flows increased by 3.54% with a 1% increase in urban income, and intraregional flows increased by 8.35%. In contrast, the total interregional flows decreased by 3.38% with a 1% increase in rural income, and intraregional flows declined by 2.29%. Railway capacity, per person gross domestic product (PGDP), urban rate and the law of distance decay also affected the input-output flows.
  
  
  CONCLUSIONS
  Our results confirm that the SARS input-output flows presented significant geographic spatial heterogeneity and spatial effects. Income differences were the major cause of the flows between pairs of regions. Railway capacity, PGDP, and urban rate also played important roles. These findings provide valuable information for the Chinese government to control the future spread of nationwide epidemics.
authors.affiliation: LREIS, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. wangli@lreis.ac.cn.|University of Chinese Academy of Sciences, Beijing, 100049, China. wangli@lreis.ac.cn.
authors.forename: Li
authors.initials: L
authors.lastname: Wang
authors.affiliation: LREIS, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. wangjf@Lreis.ac.cn.|Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Jiangsu, China. wangjf@Lreis.ac.cn.|Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Jiangsu, China. wangjf@Lreis.ac.cn.
authors.forename: Jinfeng
authors.initials: J
authors.lastname: Wang
authors.affiliation: LREIS, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. xucd@lreis.ac.cn.|Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Jiangsu, China. xucd@lreis.ac.cn.
authors.forename: Chengdong
authors.initials: C
authors.lastname: Xu
authors.affiliation: LREIS, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. liutj@lreis.ac.cn.|University of Chinese Academy of Sciences, Beijing, 100049, China. liutj@lreis.ac.cn.
authors.forename: Tiejun
authors.initials: T
authors.lastname: Liu
mesh_terms: D002681:China / Q000453:epidemiology; D004196:Disease Outbreaks; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D007182:Income / Q000706:statistics & numerical data; D008962:Models, Theoretical; D012307:Risk Factors; D045169:Severe Acute Respiratory Syndrome / Q000453:epidemiology*; D062206:Spatial Analysis; D014171:Transients and Migrants / Q000706:statistics & numerical data