In this study, HFRS data were obtained from China CDC and ECDC, while monthly meteorological data and GDP were extracted from the National Bureau of Statistics of China website. Descriptive epidemiology, time series decomposition, and spatial autocorrelation analyses were employed to evaluate HFRS incidence patterns. A spatial panel data model was used to estimate the effects of meteorological and socio-economic variables on HFRS incidence. The average annual incidence rate of HFRS was 0.90/100000 in China, compared to 29.3/100000 in Finland. The incidence level in China was comparable to that in Belgium and the EU/EEA (excluding the UK), the high-incidence age group was 45–64 years, which was similar to Finland and the EU/EEA. HFRS in China exhibited marked seasonality. Three north-eastern provinces, Shaanxi, Shandong, and Jiangxi reported higher incidence rates. After adjusting for spatial individual effects and spatial autocorrelation, HFRS incidence was negatively associated with precipitation during the same period, per capita GDP showed no significant effect on HFRS incidence. Continued surveillance and prevention of HFRS remain necessary in China, particularly in Shaanxi. Additional disease prevention and control efforts should be directed towards individuals aged 45–64 years during the high-risk period from October to December.

Given the growing importance of the wine industry in the United States, wine special interests are on the rise. Data shows that campaign contributions from the wine industry to officials running for state offices have increased over time. Given this reality, one can expect wine excise tax to remain low in states that receive higher campaign contributions. In addition, there are theoretical and empirical reasons to believe that these tax rates are interdependent based on Tiebout competition and yardstick competition. Based on this reasoning, one can hypothesize wine excise tax rates to be spatially dependent. In this study, I test this hypothesis using state-level campaign contributions data from the National Institute on Money in State Politics and Distilled Spirits Council of the United States, Inc. and find that there is strong statistical evidence of spatial dependence between state wine excise tax rates. (JEL Classifications: C12, C23, H71)