The Spatial-temporal Research Of Hemorrhagic Fever With Renal Syndrome In Shaoyang,2005-2010

Hemorrhagic fever with renal syndrome (HFRS), also called epidemic hemorrhagic fever (EHF), is caused by a group of hantaviruses, characterized by fever, acute renal dysfunction and hemorrhage manifestations. HFRS is a rodent-borne viral disease, and rats are the major animal reservoir. HFRS is a serious public health threat in China with wide distribution, high fatality and high incidence in adults. Human cases in China account for 90% of the total global reported cases. Since the first HFRS case was detected in 1963, Shaoyang has become one of the most severe endemic areas in Hunan Province, with more than 3000 infections for a several years in the eighties. The distribution, transmission and popular of HFRS are influenced by environmental factors, including in geographic landscape, climate and human activities.In this paper, data on HFRS cases and environmental variables in Shaoyang were collected. Time-lag relationship analysis, models and logistic regression models were used to analyze the spatio-temporal distribution of HFRS cases, and to explore the temporal trends and spatial infection risk of HFRS and its relationship with environmental variables. The content and results were as follows:(1) The spatio-temporal distribution of HFRS. On time scale, HFRS incidence in Shaoyang was high from November to next May, but lower between June to October. On spatial scale, HFRS cases concentrated in municipal districts and surrounding cities (Shaodong county, Xinshao county and Shaoyang county). HFRS cases few occurred in Longhui county, xinning county and Chengbu Miao Autonomous County.(2) Simulation and prediction of prevalent trend of HFRS. Results of time lag correlation analysis showed that monthly HFRS incidence correlated with temperature lagged 2 month, rainfall lagged 4 month, NDVI lagged 2 month and distance from the water lagged 1 month. Models based on both natural variables and social variables showed better performance (R2= 0.682744, AIC=318.3953).(3) Prediction of the transmission risks of HFRS. Results of multivariate logistic regression showed that the risk of HFRS was mainly high in north-east of Shaoyang, low in north and south west.(4) Relationships between HFRS and environmental risk factors. Results of univariate logistic regression models and ARIMAX models showed that HFRS incidence positively correlated with mean annual temperature, negatively correlated with annual accumulative precipitation, elevation and mean annul NDVI.In this study, we effectively explored the spatio-temporal distribution of HFRS cases, forecast the prevalent trend of HFRS transmission, and revealed the transmission pattern based on HFRS cases, providing theoretical basis for the prevention and control of HFRS. At the same time, our study firstly combined ARIMAX model with logistic regression model to predict the spatio-temporal occurrence risk of HFRS, which helps in understanding the spatio-temporal transmission rule of HFRS. Our study also provided reference for the investigations of HFRS and other similar infectious diseases in different areas.