ArticleFrontiers in public health2025
Spatial-temporal evolution patterns of influenza incidence in plateau regions from 2009 to 2023.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Spatial-temporal epidemiological characteristics of influenza and its correlation with meteorological factors in Gansu province based on 24 solar terms.BMC public health · 2026Article
- Spatiotemporal patterns and incidence trends of other infectious diarrhea in Qinghai Province, 2009-2023: a surveillance-based analysis.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study used (Geographic Information System) GIS technology to analyze the spatiotemporal distribution of influenza incidence in Qinghai from 2009 to 2023, based on influenza surveillance data. Methods: This study first accessed the influenza data sets of Qinghai Province from 2009 to 2023 through the Chinese Infectious Disease Surveillance System. Subsequently, trend charts of influenza incidence in each city and prefecture were employed to illustrate the trends of influenza incidence during the period from 2009 to 2023. To explore the risks of influenza incidence in different counties and districts, methods including spatial autocorrelation, cluster analysis, hotspot analysis, Gravity center shift model, and standard deviation ellipse were utilized. Results: The study showed that the incidence of influenza showed significant fluctuations, with marked spikes in 2019 and 2023. Spatial autocorrelation analysis revealed significant positive autocorrelation in 2015, 2017-2019, and 2022-2023 (Moran's Conclusion: The prominent spatiotemporal heterogeneity of influenza incidence in Qinghai Province indicates the need to develop differentiated and precise influenza prevention and control strategies in different regions to address the changing trends of influenza epidemics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.