title: Travel patterns in China.
abstract: The spread of infectious disease epidemics is mediated by human travel. Yet human mobility patterns vary substantially between countries and regions. Quantifying the frequency of travel and length of journeys in well-defined population is therefore critical for predicting the likely speed and pattern of spread of emerging infectious diseases, such as a new influenza pandemic. Here we present the results of a large population survey undertaken in 2007 in two areas of China: Shenzhen city in Guangdong province, and Huangshan city in Anhui province. In each area, 10,000 randomly selected individuals were interviewed, and data on regular and occasional journeys collected. Travel behaviour was examined as a function of age, sex, economic status and home location. Women and children were generally found to travel shorter distances than men. Travel patterns in the economically developed Shenzhen region are shown to resemble those in developed and economically advanced middle income countries with a significant fraction of the population commuting over distances in excess of 50 km. Conversely, in the less developed rural region of Anhui, travel was much more local, with very few journeys over 30 km. Travel patterns in both populations were well-fitted by a gravity model with a lognormal kernel function. The results provide the first quantitative information on human travel patterns in modern China, and suggest that a pandemic emerging in a less developed area of rural China might spread geographically sufficiently slowly for containment to be feasible, while spatial spread in the more economically developed areas might be expected to be much more rapid, making containment more difficult.
authors.affiliation: MRC Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom. t.garske@imperial.ac.uk
authors.forename: Tini
authors.initials: T
authors.lastname: Garske
authors.forename: Hongjie
authors.initials: H
authors.lastname: Yu
authors.forename: Zhibin
authors.initials: Z
authors.lastname: Peng
authors.forename: Min
authors.initials: M
authors.lastname: Ye
authors.forename: Hang
authors.initials: H
authors.lastname: Zhou
authors.forename: Xiaowen
authors.initials: X
authors.lastname: Cheng
authors.forename: Jiabing
authors.initials: J
authors.lastname: Wu
authors.forename: Neil
authors.initials: N
authors.lastname: Ferguson
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D002681:China / Q000453:epidemiology; D003141:Communicable Diseases / Q000453:epidemiology / Q000635:transmission; D005191:Family Characteristics; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D009790:Occupations / Q000706:statistics & numerical data; D012424:Rural Population / Q000706:statistics & numerical data; D012574:Schools / Q000706:statistics & numerical data; D014186:Transportation / Q000706:statistics & numerical data; D014195:Travel / Q000706:statistics & numerical data*; D017132:Workplace / Q000706:statistics & numerical data; D055815:Young Adult