Environmental Variations And The Spatial-temporal Distribution Of Hemorrhagic Fever With Renal Syndrome

Hemorrhagic fever with renal syndrome (HFRS) is a natural focal disease, characterized with fever, hemorrhagic manifestations and acute renal dysfunction. HFRS is widely transmitted from rodents to humans through touching saliva, urine or excreta of infected rodents. China is of the highest incidence of HFRS in the world, although HFRS incidence has decreased obviously in recent years in our country, the HFRS infections and deaths were still the most serious in the world.In this study, we analyzed HFRS case data together with environmental data from the Dongting Lake district and Chenzhou city during 2005-2010. Geographic Information System(GIS)、Remote Sensing(RS).. Principal component analysis、polynomial distributed lag (PDL) models and Ecological Niche Models(ENMs) were used to analyze the spatio-temporal distribution of HFRS cases, and to investigate the HFRS risk areas and seasonal variations of risk areas; and to explore the quantitative relationship between HFRS transmission and environmental variables, forecasted the prevalent trend of HFRS transmission. The content and results were as follows:(1) The spatio-temporal distribution of HFRS. On time scale, HFRS incidence of Dongting Lake district was high in Spring and Winter (from November to next January), but lower between August to October; the HFRS incidence of Chenzhou was stable over study period. Monthly HFRS cases revealed that HFRS incidence was high in November to January, low in July and August. On spatial scale, the low incidence of HFRS incidence always occurred far away from the Dongting Lake whereas the high incidence always focused on the southeast and southwest of the Dongting Lake. HFRS cases of Chenzhou mainly concentrated in northwest (Yongxing county, Guiyang county and Linwu county) and city center. HFRS cases few occurred in southeast (Guidong county and Rucheng county).(2) The results of ENMs. A comparison of the four models indicated that low-risk areas of HFRS incidence always occurred far away from the Dongting Lake whereas the high risk areas always focused on the southeast and northwest of the Dongting Lake. The results of MaxEnt resulted to be more consistent with the actual case distribution in 2010. Time-specific MaxEnt showed that risk areas that varied across seasons, were smaller in March, May and August, high in June, July and October to December.(3) The results of PDL model, we analyzed the relationship between HFRS cases and environmental variations (natural factors and socioeconomic factors) in Chenzhou. PDL model was produced to explore the potential influence of environmental variables on HFRS transmission. Results showed that HFRS incidence was affected by not only the natural factors but also the socioeconomic factors. Models based on both natural variables and social variables showed better performance (R2= 0.857) than models based on only natural variables (R2 0.656).PDL model based on lagged environmental variables well fitted and predicted HFRS incidence in Chenzhou.(4) Relationships between HFRS and environmental risk factors. NDVI was the main factor associated with the HFRS case distribution of Dongting Lake district followed by land use, DEM, and the landscape slope. The PDL model showed HFRS incidence was positively correlated with rodent density,rainfall and relative humidity, negatively correlated with GDP and urbanization rate in Chenzhou.