Distribution and Risk Factors of 2009 Pandemic Influenza A (H1N1) in Mainland China

Fang, Li-Qun; Wang, Li-Ping; de Vlas, Sake J.; Liang, Song; Tong, Shi-Lu; Li, Yan-Li; Li, Ya-Pin; Qian, Quan; Yang, Hong; Zhou, Mai-Geng; Wang, Xiao-Feng; Richardus, Jan Hendrik; Ma, Jia-Qi; Cao, Wu-Chun

To assess the association between the invasion of pandemic influenza and different means of domestic travel, we performed a survival analysis (Cox analysis) of the time delay of the first confirmed case for each affected county, considering unaffected counties as right-censored. The time delay of the first confirmed case was defined as the duration (in days) since May 9, 2009, the date of the first confirmed case in mainland China. Domestic travel was expressed using 4 variables: distance (from the midpoint of each county) to the nearest civil airport and whether or not a county was intersected by national highways, freeways, or railways. This information was obtained from the National Bureau of Statistics of China (9, 15) . Spatial analyses were used to extract data on these variables in ArcGIS 9.2 (ESRI Inc.). Since population density is also linked to human activities and may facilitate influenza transmission (16, 17) and since density of medical facilities could be linked to patient reporting, we adjusted for the effects of these variables. In this study, the population density for each county was obtained from the National Bureau of Statistics of China (9, 15) , and the densities of medical facilities were based on the CISDCP, including all reporting sectors for notifiable infectious diseases, comprising provincial, prefectural, and county centers for disease control and prevention and provincial, prefectural, and county hospitals and township clinics. Hazard ratios and their 95% confidence intervals and P values were estimated using maximum likelihood methods. Hazard ratios for the continuous variables were calculated for the following units: distance to the nearest airport (in 50-km increments), population density (in 1,000 persons per km 2 ), and density of medical facilities (in number of reporting sectors for pandemic influenza per 10,000 persons).