Study On Influence Of Environmental Changes On Hemorrhagic Fever With Renal Syndrome In Changsha City

Hemorrhagic fever with renal syndrome (HFRS), caused by Hantaviruses (HV), is characterized by fever, acute renal dysfunction and hemorrhage manifestations, which is serious harm to human health. It is one of the key infectious diseases harming people’s health and safety with wide distribution, high incidence and complicated type of endemic areas in China’s mainland. Combined with GIS, RS, rodent animal hosts and environmental factors data, we establish accurate mathematical model that can correctly forecast the range and strength of HFRS epidemic to take appropriate control measures and to provide a scientific basis for public health department at all levels.Study on Changsha City and Chenzhou City, we collect and organize the data of disease surveillance, rodent animal hosts, remote sensing image and meteorological conditions. Using main technology of GIS and RS, methods of mathematical statistics, we study the the influence of environmental changes on HFRS transmission. The content and results of this study are as follows:(1) Delay-dependent analysis:Correlation calculation between environmental factors and HFRS series by delay-dependent analysis. Rearward movement environment series1to6months and doing correlation calculation. Get delay-dependent period of defferent environmental factors and HFRS incidence, through discussion, to analyze the reasons.(2) Multiple environment variable ARIMAX model:Take farmland NDVI and rodent density as input variables, HFRS incidence series as response variable, doing the delay-dependent analysis and fitting, forecasting the model, with Changsha Ctiy as an example. The results show that the ARIMAX model can better fit the HFRS incidence and accurate forecast the number of infected at a short period. Take NDVI, rodent density, average temperature, precipitation (all in months) as input variables, HFRS incidence series as response variable, doing the delay-dependent analysis and determine the optimal model with which variables by ARIMAX model. While fitting and forecasting the model. The results showed that, ARIMAX(0,1,2) with NDVI, rodent density, average temperature and precipitation series which residuals autocorrelation and partial autocorrelation does not exist has a better fitting effect, and close the incidence trend.(3) Soil humidity Extraction and influence of HFRS:Value of Temperature-Vegetation Dryness Index (TVDI) are extracted by MODIS remote sensing image, which can retrieved soil humidity. Overlay the patients coordinate and TVDI classification map, the results show that the cases point focus on areas of high TVDI value which is dry regions with low soil humidity. This article based on GIS, RS and adding environment variable to study the spread rule of HFRS, adequately consider the geospatial characteristics and environmental impact of HFRS, quantificationally study the spatial and temporal characteristics and relationship between environmental factors and HFRS. The results are important in the clear understanding of the prevalence of HFR. The method and means was provided for future similar epidemics study by this study.