Seasonal rainfall variability, the incidence of hemorrhagic fever with renal syndrome, and prediction of the disease in low-lying areas of China.
To investigate determinants of hemorrhagic fever with renal syndrome (HFRS) in low-lying areas of China, the authors studied Chuigang and Wanggang communities in Anhui Province. These adjacent farming communities have a population of about 100,000. Data were collected from the two communities in 1961-1977 and from Yingshang County in 1983-1995; information covered the incidence of HFRS, amount of precipitation, differences in the water level of the Huai River, density of Apodemus agrarius, autumn crop production, and areas of inundated farmland. Correlation and multiple linear regression analyses were used to estimate the relation between seasonal rainfall, density of mice, occupational factors, and occurrence of the disease. Associations were observed between the incidence of HFRS and the amount of precipitation, the water level of the Huai River, and the areas of inundated farmland in Chuigang community. The smaller the water-level difference, the less farmland was inundated and the higher the incidence of HFRS. In Wanggang community, the density of A. agrarius (r1=0.63, p=0.02), the water-level difference in the Huai River (r2=-0.81, p=0.007), and crop production (r3=0.96, p=0.005) were correlated with the incidence of HFRS. The regression analyses based on Wanggang community suggested that these indexes could be used as predictive variables, and the results from the model were well calibrated with the actual incidence of HFRS in that community (R2=0.88, p < 0.01) and Yingshang County (R2=0.91, p < 0.01).
Department of Social and Preventive Medicine, University of Queensland, Brisbane, Australia.
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D000818:Animals; D002681:China / Q000453:epidemiology; D019353:Endemic Diseases; D005544:Forecasting; D006480:Hemorrhagic Fever with Renal Syndrome / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D051379:Mice; D011891:Rain; D012189:Retrospective Studies; D012424:Rural Population; D012621:Seasons