Epidemiological data relevant to HPAI H5N1 outbreaks in poultry were provided by the Avian Influenza Control Center, Department of Livestock Development (DLD, Bangkok, Thailand), a unit in charge of surveillance and monitoring of avian influenza (AI) in poultry. Since January 2004, DLD has been recording information on all poultry outbreaks confirmed by a diagnostic test. Tests were carried out by diagnostic laboratories on sick or dead poultry or cloacal samples using reverse-transcriptase polymerase chain reaction and virus isolation [22] . We restricted the study to outbreaks in chickens and ducks which occurred during the second wave of HPAI because at that point both the passive and active components of the surveillance system were fully implemented to detect the disease. The data included records of 1 717 laboratory-confirmed cases (flocks of affected poultry) dating from 3 July 2004 to 5 May 2005. The background susceptible population was calculated for each subdistrict based on the poultry census data that DLD collected during the X-ray survey of February 2005. This was used to model the relative risk. We computed several anthropogenic factors to investigate the role of humans in disease spread since poultry product trading activities operate at different geographic scales. To take into account these different commercial activities, we built anthropogenic indicators based on the road network and human population settlements. Using the 2004 human population census database of the Thailand Department of Provincial Administration 3 , we calculated the human population density in subdistricts to study its association with the relative risk of HPAI, previous papers having found differing results regarding the effect of human population density on HPAI [8, 24] . In addition, we computed the distance from the subdistrict to major cities (defined as having a population of 100 000 or more). We believed that major cities may have played a role in disease spread due to the intensity of poultry trade in the areas surrounding them. Information on the road network (primary and secondary roads, highways) was obtained from the Ministry of Transport, Bangkok, Thailand. This information made it possible to compute the road density per subdistrict (grouping primary and secondary roads) which was taken as an indicator of the intensity of the local trade of poultry products within a subdistrict. We suspected that highways played a role not only in the long-distance spread of the virus through the dispersal of infected materials, but also in the short-distance spread to subdistricts located in their vicinity. Therefore, we introduced the distance of a subdistrict to the closest highway as an explanatory variable. Finally, we computed the distance to the closest highway junction, which was assumed to function as a ''dissemination node'' for the HPAI virus. We assumed that if the virus was transported mainly through the road network, the subdistricts located close to a highway junction were more likely to come in contact with the virus than those located further away. To take into account environmental risk factors, we used topographic data (altitude, hydrology) which were obtained from the 1996 digital database of the Thailand Environment Research Institute 4 (Bangkok). Research has shown that rice-cropping intensity is a relevant risk factor in Thailand and other Asian countries [9] . Therefore, we included maps of rice-cropping intensity based on MODIS sensor images processed from satellite-based mapping algorithms developed by Xiao et al. [30] . Using data from the DLD poultry census, we also estimated for each subdistrict the density of animals and households raising poultry for different types of poultry: native chickens, fighting cocks, broiler and layer chickens, free-grazing ducks, and broiler and layer ducks.