Spatiotemporal Heterogeneity Analysis of Haemorrhagic Fever with Renal Syndrome in Anqiu City, China, 2000-2014

Background: The purpose of this study was to explore the dynamics of the occurrence of haemorrhagic fever with renal syndrome (HFRS) and find the potential spatiotemporal factors leading to the incidence of HFRS in Anqiu City. Methods: Monthly reported cases of HFRS and climatic data for 2000–2014 in Anqiu City were obtained. An autoregressive integrated moving average (ARIMA) model was used to fit the HFRS incidence prediction model and predict the epidemic trend in Anqiu City. Multiple linear regression method was used to analyze the temporal relationship between HFRS incidence and meteorological factors during the study period. Results: Spatial analysis results indicated that the annualized average incidence at the town level ranged from 2.18 to 6.09 per 100, 000 among 14 towns, and the western towns in Anqiu City exhibited high endemic levels during the study periods. With high validity, the optimal ARIMA (0, 1, 1) × (0, 1, 1)12 model could be used to predict the HFRS incidence in Anqiu City in 2014. The monthly trend in HFRS incidence was negatively associated with temperature and precipitation and positively associated with average wind speed. Multiple linear regression models showed that precipitation and relative wind speed were key climatic factors contributing to the transmission of HFRS. Conclusions: This study provides evidence that the ARIMA model can be used to fit the fluctuations in HFRS frequency in Anqiu City. Our findings add to the knowledge of the role played by climate factors in HFRS transmission in Anqiu City and can assist local health authorities in the development/refinement of a better strategy to prevent HFRS transmission.