all the cases reported in mainland china from 1994 through 1998 were obtained from the national notifiable disease surveillance system ( nndss ) . nndss is supported by a special monitoring network and produces these data annually according to county , a political subdivision of a province , which usually contains several townships and has a population of 500,000 persons . because the number of cases was small and varied yearly in each county , we used the mean number of hfrs cases from each county from 1994 to 1998 . all hfrs cases were coded according to geographic area ( geo - coded ) and matched to the corresponding polygon and its label point on a digital map of china by using the software arcgis 9.1 ( esri inc . , the study was limited to the rural areas of the country and areas with population density < 1,000/km , to capture most , if not all , of the patients infected with hntv . demographic data at the county level were obtained from the 1995 and 2000 censuses . to overcome difficulties due to changes in administrative boundaries , the vector map of the demographic data was converted to a raster map of the population with a 1-km grid ( 12 ) . based on the 1995 and 2000 maps for the population and the map of the administrative units , the average population of each county was calculated . remote sensing information was used to generate a digital elevation model ( dem ) with a 1:100,000 scale . the elevation data obtained from dem was transferred into a raster map with a 1-km grid ( 12 ) . based on dem and the map of the administrative units , the average elevation of each county was calculated . counties were then classified into 8 levels ( meters above sea level ) : < 100 , 101200 , 201500 , 5011,000 , 1,0011,500 , 1,5012,000 , 2,0013,000 , and > 3,000 . the ndvi was derived by the national satellite meteorological center in china by using advanced , high - resolution radiometer ( avhrr ) images . monthly and annual ndvi in 1998 were calculated by using erdas imagine 8.7 ( leica geosystems geospatial imaging , llc . , counties were classified according to 4 ndvi levels : < 0.1 , 0.1010.2 , 0.2010.3 , and > 0.3 . the annual precipitation data were based on the average of the cumulative annual precipitation in china from 1994 to 1998 , obtained from 700 weather stations ( 12 ) . the inverse distance weighting ( idw ) method was applied to interpolate and generate its raster map for annual precipitation with a 1-km grid ( 13,14 ) . annual precipitation values were divided into 4 levels : < 400 , 401800 , 8011,200 , and > 1,200 mm . these levels corresponded to arid , semiarid , semihumid , and humid areas , respectively . air temperature data were obtained from 700 weather stations through the country from 1970 to 2001 ( 12 ) . the idw method was applied to interpolate and generate its raster map with a 1-km grid . the average daily temperature of each county was added to derive the annual cumulative air temperature , and it was divided into 5 temperature ranges : < 1,600c , 1,600c3,399c , 3,400c4,499c , 4,500c7,999c , and > 8,000c . these levels represent frigid - temperate , mid - temperature zone , warm - temperate , semitropical , and tropical zones , respectively . lst data at county level were also obtained from the monthly avhrr 1998 data ( 12 ) . lst values were divided into 5 levels : < 28c , 28c31c , 32c34c , 3537c , and > 37c . the soil types in the map were grouped into 12 categories , i.e. , argosols , semiluvisols , caliche soils , arid soils , desert soils , skeletol primitive soils , semihydromorphic soils , hydromorphic soils , saline soils , anthrosols , alpine soils , and ferralisols . these categories are based on the classification and codes of soil in china ( 12 ) . the types of land use in the map were categorized as paddy land , irrigated land / nonirrigated farmland , timber forest land , orchard land , sparse woods , bush , prairie and grassland , hilly / mountainous grassland , desert ( desert , gobi , cold desert ) , wetland , saline - alkali land , and bare land ( 12 ) . the timber forest land is used to produce timber for building and furniture ; orchard land produces fruits and raw materials for industry or for beverages and medicines , for example . the gobi is a large desert region of southeast mongolia and northern china , which consists mainly of series of shallow alkaline basins . bush has been defined as land covered with dense vegetation or undergrowth . to process the data for landscape elements at county level , we overlaid the map of administrative units on the raster map of each landscape element . the average elevation , ndvi , air temperature , lst , precipitation , area proportions with different type of soils , and land use were then calculated for each county by using arcgis 9 . the average annual hfrs incidence of each county was calculated as well . through the linkage of the 6-digit county geo - code , the incidence of hfrs at county level was displayed on the base map with administrative boundaries and then converted to a raster map , which was overlaid on the thematic maps of the landscape elements . hfrs incidence was also calculated for each category of the landscape elements by overlaying maps of hfrs with the different thematic maps . for example , elevation was divided into 8 levels and then displayed on the map of elevation for the whole country . according to the area proportions of each level of elevation , the population and the number of hfrs cases at the county level were displayed as hfrs incidence data at each elevation level were then obtained . univariate analysis (  ) was used to compare hfrs incidence across the different levels of each landscape element , including elevation , ndvi , precipitation , annual cumulative air temperature , and lstl ; odds ratios ( ors ) were obtained by comparing the hfrs incidence of different categories of the landscape elements . to determine the associations between hfrs and soil type as well as land use , univariate logistic analysis was conducted , and ors were computed by comparing counties where hfrs was found with non - hfrs  endemic counties . through gis , different thematic maps were also generated to facilitate graphic and spatial visualization of hfrs occurrence at the county level in china and geographic distribution of the different landscape elements ( 15 ) . the dependent variable was whether hfrs occurs ; independent variables were landscape elements ( elevation , ndvi , precipitation , annual cumulative temperature and lst , type of soil , and land use ) . backward stepwise selection was performed with the criterion of p>0.05.the possible interaction between individual elements was considered . condition indexes and variance decomposition proportions were used to test colinearity among the independent variables and identify the sources of colinearity . when the condition index was > 30 , the independent variables had strong colinearity . if a large condition index is associated with variables that have variance decomposition proportions > 0.5 , these variables may be causing colinearity problems ( 16 ) . all the cases reported in mainland china from 1994 through 1998 were obtained from the national notifiable disease surveillance system ( nndss ) . nndss is supported by a special monitoring network and produces these data annually according to county , a political subdivision of a province , which usually contains several townships and has a population of 500,000 persons . because the number of cases was small and varied yearly in each county , we used the mean number of hfrs cases from each county from 1994 to 1998 . all hfrs cases were coded according to geographic area ( geo - coded ) and matched to the corresponding polygon and its label point on a digital map of china by using the software arcgis 9.1 ( esri inc . , the study was limited to the rural areas of the country and areas with population density < 1,000/km , to capture most , if not all , of the patients infected with hntv . demographic data at the county level were obtained from the 1995 and 2000 censuses . to overcome difficulties due to changes in administrative boundaries , the vector map of the demographic data was converted to a raster map of the population with a 1-km grid ( 12 ) . based on the 1995 and 2000 maps for the population and the map of the administrative units , the average population of each county was calculated . remote sensing information was used to generate a digital elevation model ( dem ) with a 1:100,000 scale . the elevation data obtained from dem was transferred into a raster map with a 1-km grid ( 12 ) . based on dem and the map of the administrative units , the average elevation of each county was calculated . counties were then classified into 8 levels ( meters above sea level ) : < 100 , 101200 , 201500 , 5011,000 , 1,0011,500 , 1,5012,000 , 2,0013,000 , and > 3,000 . the ndvi was derived by the national satellite meteorological center in china by using advanced , high - resolution radiometer ( avhrr ) images . monthly and annual ndvi in 1998 were calculated by using erdas imagine 8.7 ( leica geosystems geospatial imaging , llc . , counties were classified according to 4 ndvi levels : < 0.1 , 0.1010.2 , 0.2010.3 , and > 0.3 . the annual precipitation data were based on the average of the cumulative annual precipitation in china from 1994 to 1998 , obtained from 700 weather stations ( 12 ) . the inverse distance weighting ( idw ) method was applied to interpolate and generate its raster map for annual precipitation with a 1-km grid ( 13,14 ) . annual precipitation values were divided into 4 levels : < 400 , 401800 , 8011,200 , and > 1,200 mm . these levels corresponded to arid , semiarid , semihumid , and humid areas , respectively . air temperature data were obtained from 700 weather stations through the country from 1970 to 2001 ( 12 ) . the idw method was applied to interpolate and generate its raster map with a 1-km grid . the average daily temperature of each county was added to derive the annual cumulative air temperature , and it was divided into 5 temperature ranges : < 1,600c , 1,600c3,399c , 3,400c4,499c , 4,500c7,999c , and > 8,000c . these levels represent frigid - temperate , mid - temperature zone , warm - temperate , semitropical , and tropical zones , respectively . lst data at county level were also obtained from the monthly avhrr 1998 data ( 12 ) . lst values were divided into 5 levels : < 28c , 28c31c , 32c34c , 3537c , and > 37c . the soil types in the map were grouped into 12 categories , i.e. , argosols , semiluvisols , caliche soils , arid soils , desert soils , skeletol primitive soils , semihydromorphic soils , hydromorphic soils , saline soils , anthrosols , alpine soils , and ferralisols . these categories are based on the classification and codes of soil in china ( 12 ) . the types of land use in the map were categorized as paddy land , irrigated land / nonirrigated farmland , timber forest land , orchard land , sparse woods , bush , prairie and grassland , hilly / mountainous grassland , desert ( desert , gobi , cold desert ) , wetland , saline - alkali land , and bare land ( 12 ) . the timber forest land is used to produce timber for building and furniture ; orchard land produces fruits and raw materials for industry or for beverages and medicines , for example . the gobi is a large desert region of southeast mongolia and northern china , which consists mainly of series of shallow alkaline basins . to process the data for landscape elements at county level , we overlaid the map of administrative units on the raster map of each landscape element . the average elevation , ndvi , air temperature , lst , precipitation , area proportions with different type of soils , and land use were then calculated for each county by using arcgis 9 . the average annual hfrs incidence of each county was calculated as well . through the linkage of the 6-digit county geo - code , the incidence of hfrs at county level was displayed on the base map with administrative boundaries and then converted to a raster map , which was overlaid on the thematic maps of the landscape elements . hfrs incidence was also calculated for each category of the landscape elements by overlaying maps of hfrs with the different thematic maps . for example , elevation was divided into 8 levels and then displayed on the map of elevation for the whole country . according to the area proportions of each level of elevation , the population and the number of hfrs cases at the county level were displayed as hfrs incidence data at each elevation level were then obtained . univariate analysis (  ) was used to compare hfrs incidence across the different levels of each landscape element , including elevation , ndvi , precipitation , annual cumulative air temperature , and lstl ; odds ratios ( ors ) were obtained by comparing the hfrs incidence of different categories of the landscape elements . to determine the associations between hfrs and soil type as well as land use , univariate logistic analysis was conducted , and ors were computed by comparing counties where hfrs was found with non - hfrs  endemic counties . through gis , different thematic maps were also generated to facilitate graphic and spatial visualization of hfrs occurrence at the county level in china and geographic distribution of the different landscape elements ( 15 ) . the dependent variable was whether hfrs occurs ; independent variables were landscape elements ( elevation , ndvi , precipitation , annual cumulative temperature and lst , type of soil , and land use ) . backward stepwise selection was performed with the criterion of p>0.05.the possible interaction between individual elements was considered . condition indexes and variance decomposition proportions were used to test colinearity among the independent variables and identify the sources of colinearity . when the condition index was > 30 , the independent variables had strong colinearity . if a large condition index is associated with variables that have variance decomposition proportions > 0.5 , these variables may be causing colinearity problems ( 16 ) . the average hfrs incidence of each county in mainland china is displayed in figure 2 , with an overlaid map of a. agarius capture points ( 17 ) . the top 6 incidence rates were 20.3 , 18.9 , 8.2 , 7.7 , 5.0 , and 4.6/100,000 population in heilongjiang , shandong , zhejiang , hunan , hebei , and hubei provinces , respectively . . only xingjiang , tibet autonomous regions , and qinghai province never reported any hfrs cases figure 1 . topographic map of the people s republic of china , showing relationship between elevation and incidence of hemorrhagic fever with renal syndrome ( hfrs ) . geographic distribution of incidence of hemorrhagic fever with renal syndrome ( hfrs ) in the people s republic of china and relationship with capture points of apodemus agrarius . hfrs incidence significantly declined as elevation increased (  for trend test , p<0.001 ; spearman correlation test r = 0.466 , p<0.01 ) . the highest incidence ( 7.3/100,000 population ) was observed in areas with elevation of 100200 m. no cases were reported in areas > 3,000 m except in 3 counties of gansu province ( xiahe , diebu , and zhuoni ) . approximately 86.4% hfrs cases occurred in areas with 0500 m elevation in the eastern part of china and the sichuan basin ( figure 2 ) . hfrs incidence was 34 higher in areas with an ndvi 0.10.3 than in areas with ndvi < 0.1 ( table 1 ) . there were significant differences in hfrs incidence in regard to ndvi ( df = 3 , p<0.001 ) . however , the peak incidence of 4.6/100,000 population was observed at an ndvi level of 0.20.3 . * hfrs , hemorrhagic fever with renal syndrome ; ci , confidence interval ; ndvi , normalized difference vegetation index . p value of each landscape element ; others are p value of subdivision analyses . the highest hfrs incidence of 6.4/100,000 occurred in the semihumid areas , where precipitation levels are 400800 mm . no cases were reported from the arid areas , where the precipitation was < 200 mm . the difference in hfrs incidence was statistically significant among different precipitation level ( df = 4 , p<0.001 ) . the frigid - temperate zone , with annual cumulative temperature of < 1600c , had the highest hfrs incidence at 10.2/100,000 . this was followed by the warm zone ( 3,4004,500c ) and semitropical ( 4,500c8,000c ) zones with hfrs incidences of 8.0 and 2.6 per 100,000 , respectively . among different cumulative temperature zone , there was also a significant difference in hfrs incidence regarding lst ( df = 4 , p<0.001 ) . the incidence dropped when the lst value increased to 2834c and increased again to 4.7/100,000 when lst levels reached 3437c ( table 1 ) . as to the soil types , the univariate logistic regression analysis showed that anthrosols , alfisol , and semihydromorphic soils , which are good for cultivation , had higher risk for hfrs prevalence . all other soils seemed to be less likely to harbor the disease agent ( table 2 ) . * hfrs , hemorrhagic fever with renal syndrome ; or , odds ratio ; ci , confidence interval . the univariate logistic regression analysis also showed that land for agriculture use , including paddy land , irrigated farmland , nonirrigated farmland , and orchard land , were the landscape elements with high risk for hfrs . other types of land use , except for timber forest land and wetland , were protective against the disease ( table 3 ) . * or , multivariate logistic regression analysis indicated that elevation , ndvi , precipitation , and annual cumulative temperature were significantly associated with hfrs incidence . semihydromorphic soils ( or = 1.53 ) , timber forest land ( or = 2.04 ) , and orchard land ( or = 1.97 ) were risk factors for hfrs incidence ( table 4 ) . * hfrs , hemorrhagic fever with renal syndrome ; nvdi , normalized difference vegetation index ; or , odds ratio ; ci , confidence interval . in the early 1990s , the spatial distribution of hfrs and its variation regarding to geographic and meteorologic features were well described in china , based on a national investigation ( 18 ) . however , because of the limitation of technique used in the analyses of that study , the hfrs distribution and related environmental factors could be neither displayed at the county level nor visualized on a digital map . recently , we used gis - based spatial analysis to elucidate temporal and spatial distribution of hfrs and to highlight geographic areas with a substantially high incidence of the disease ( 12 ) . the results indicated that the application of gis , together with spatial statistical techniques , provides ways to quantify explicit hfrs and to further identify environmental factors responsible for the increasing disease risk . in the current study , we combined a landscape epidemiologic approach with gis and remote sensing techniques to increase our understanding of hfrs and its relationship with landscape elements in china . htnv and seov , the major causative agents of hfrs in mainland china , are associated with 2 distinct rodent hosts , i.e. , a. agrarius and r. norvegicus , respectively . the former thrives in rural areas , while the latter is an anthropophilic urban species . htnv- and seov - related hfrs cases should be differentiated to explore the association between hfrs incidence and landscape elements because each rodent species has its own breeding sites with special landscape attributes . unfortunately , in china , the reported hfrs cases are not distinguished by causative hv . since the rodent host ( a. agrarius ) of htnv usually lives in rural areas , large cities and counties with population density > 1,000/km were excluded from the analyses to remove most , if not all , hfrs cases caused by seov and to restrict the study to mainly htnv - type infections . the reason for the increased risk for hfrs in regions with lower elevation is not clear ; population density and human activities are likely explanations . population density remarkably increases as elevation decreases and most likely facilitates transmission of hv from rodent hosts to human , subsequently leading to increases in hfrs incidence . hfrs incidence was highest in the frigid - temperate zone , mostly in northeastern china , followed by incidence in the warm - temperate zone . the findings of a previous study on rodent surveillance supported our hypothesis , which suggested that the density as well as htnv infection rate of a. agarius in temperate zones was much higher than those in other areas ( 8) . economic activities are probable reasons for higher hfrs in the areas of particular soil type and land use . in china , semihydromorphic soil is the major cultivated soil type , usually used for growing wheat , corn , and other crops , which can provide adequate food for rodent hosts and subsequently lead to increase rodent density . forest workers and farmers had more chances to come into contact with contaminated urine and feces of rodents infected with htnv . an investigation conducted on various land types showed that the highest trap - success rate of apodemus rodents in the country was 28.9% in heihe county . the county has 38% timber forestland , 16% nonirrigated farmland , and 3% wetland ( h. chen , pers . although analyses are still preliminary , the findings can be helpful for generating hypothesis for further investigation . for better analyses , the human and rodent hfrs surveillance in china , including discrimination of hfrs cases due to different hvs , should be enhanced .
hemorrhagic fever with renal syndrome ( hfrs ) is an important public health problem in the people s republic of china , accounting for 90% of human cases reported globally . in this study , a landscape epidemiologic approach , combined with geographic information system and remote sensing techniques , was applied to increase our understanding of hfrs due to hantaan virus and its relationship with landscape elements in china . 
 the landscape elements considered were elevation , normalized difference vegetation index ( ndvi ) , precipitation , annual cumulative air temperature , land surface temperature , soil type , and land use . 
 multivariate logistic regression analysis showed that hfrs incidence was remarkably associated with elevation , ndvi , precipitation , annual cumulative air temperature , semihydromorphic soils , timber forests , and orchards . 
 these findings have important applications for targeting hfrs interventions in mainland china .