ArticleGeoHealth2024
Characteristics of the Spatiotemporal Distribution of Influenza Incidence and Its Driving Factors Among Residents in Mainland China From 2004 to 2018.
Article in GeoHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Modeling spatially dependent count time series data using COM-poisson INGARCH Models.PloS one · 2026Article
- Epidemiological characteristics and spatio-temporal analysis of influenza in Sichuan Province from 2015 to 2024.BMC infectious diseases · 2025Article
- Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Influenza is an acute respiratory infection that spreads rapidly and widely in densely populated areas with low vaccination coverage. The trends and drivers of the spatial and temporal dynamics of influenza incidence among residents of mainland China have not been systematically studied. This study comprehensively analyses the dynamics and spatial correlation of influenza using long-term scale data and spatial panel data. It then identifies the interactive process of socio-economic and natural elements on the incidence of influenza. The highest prevalence of influenza was found in the 0-4 years age group in mainland China (mean prevalence, 67.56/100,000). In addition, influenza in mainland China shows seasonality, with fall and winter being the periods of high incidence. Between 2014 and 2017, influenza incidence was clustered in Hubei and Anhui provinces, and the spatial clustering was statistically significant (
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