ArticleEpidemiology and infection2025
Spatio-temporal clustering and meteorological factors influencing HFRS incidence in mainland China, 2004-2021.
Article in Epidemiology and infection, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Article
- Epidemiological characteristics and spatiotemporal heterogeneity of hemorrhagic fever with renal syndrome in the Jiaodong Peninsula region, China, 2019-2025.Frontiers in public health · 2026Article
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4 authors.
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Abstract
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.
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