ArticleScientific reports2025
Spatiotemporal distribution and ecological factors of disease burden in Inner Mongolia's working age population with brucellosis from 2015 to 2020.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Spatiotemporal dynamics and environmental factors of human brucellosis in mainland China, 2004-2022.BMC infectious diseases · 2026Article
- Spatiotemporal distribution characteristics and disease burden of human brucellosis in Inner Mongolia Autonomous Region, 2014-2023.Frontiers in public health · 2026Article
- Interactions between brucellosis and environmental factors: spatiotemporal epidemiology from Xinjiang, China.BMC public health · 2025Article
- Protocol for a randomized controlled trial on the impact of a health action process approach model-based mobile health intervention via WeChat on health behaviors of brucellosis patients.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Brucellosis is a major public health problem globally, with cases concentrated in working-age populations, but there are few studies on the disease burden of brucellosis in working-age populations. This study estimated the disease burden and spatiotemporal distribution characteristics of brucellosis in Inner Mongolia's working-age population from 2015 to 2020 and explored the ecological influences on its disease burden. Spatiotemporal Bayesian modeling was utilized; thus, the spatiotemporal variation pattern of disease burden of brucellosis was analyzed. Using the geographically weighted regression analysis (GWR), the study explored the ecological influencing factors of the burden of brucellosis in the working-age population. Bayan Nur in Inner Mongolia exhibited a low risk of disease burden of brucellosis, but the risk of disease burden of brucellosis has fast increasing speed from 2015 to 2020 there. A considerably high number of slaughtered fattened sheep and goats (β: 0.008734-0.008752, P < 0.05), number of health beds (β: - 0.005591 to 0.005579, P < 0.05), and high rainfall (β: 0.015433-0.015439, P < 0.05) are ecological influences on the disease burden of brucellosis in the working-age population of Inner Mongolia. In the prevention and control of brucellosis, the goverment commonly focus on regions with a high disease burden, and it is equally important which those regions where the increase of disease burden is fast but its disease burden is not high. High number of slaughtered fattened sheep and goats, high rainfall, and a low number of health beds are ecological influences on the disease burden of brucellosis among the working-age population. Combined with our ecological influencing factors, we can take prevention and control measures in advance for the working-age population in areas with a fast rising rate of the disease burden of brucellosis.
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.