ArticleOne health (Amsterdam, Netherlands)2022
Driving effect of multiplex factors on human brucellosis in high incidence region, implication for brucellosis based on one health concept.
Article in One health (Amsterdam, Netherlands), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 21 citations in OpenAlex.
- Predicting the incidence of syphilis in China using Baidu search index and an ARIMAX model.BMC infectious diseases · 2026Article
- Spatiotemporal dynamics, clustering, and ARIMA-based short-term prediction of human brucellosis in Xinjiang, China.BMC infectious diseases · 2026Article
- Spatiotemporal heterogeneity and influencing factors of hepatitis B in China: a 17-year national surveillance analysis.BMC public health · 2026Article
- Spatiotemporal dynamics and environmental factors of human brucellosis in mainland China, 2004-2022.BMC infectious diseases · 2026Article
- Seroprevalence and Associated Risk Factors of Brucellosis in Backyard Dairy Cattle in the Western Buffer Zone of Chitwan National Park, Nepal.Veterinary medicine and science · 2026Article
- Climate sensitivity is widely but unevenly spread across zoonotic diseases.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Spatiotemporal trends and ecological determinants of human brucellosis among 31 provinces in mainland China, 2004-2021: a Bayesian spatiotemporal modeling study.BMC public health · 2025Article
- Multiscale environmental drivers of human brucellosis transmission in Xinjiang: A spatiotemporal analysis integrating GAM and MaxEnt modeling (2015-2023).PLoS neglected tropical diseases · 2025Article
- Enhancing public health surveillance: SARIMAX model incorporating Baidu search index for HCV prediction in China.BMC medical research methodology · 2025Article
- Changing trends in human brucellosis in pastoral and agricultural China, 2004-2019: a Joinpoint regression analysis.BMC infectious diseases · 2025Article
- Risk effects of environmental factors on human brucellosis in Aksu Prefecture, Xinjiang, China, 2014-2023.Scientific reports · 2025Article
- Spatiotemporal risk of human brucellosis under intensification of livestock keeping based on machine learning techniques in Shaanxi, China.Epidemiology and infection · 2024Article
- Risk effects of meteorological factors on human brucellosis in Jilin province, China, 2005-2019.Heliyon · 2024Article
- Asymmetric Effects of Weather-Integrated Human Brucellosis Forecasting System Using a New Nonlinear Autoregressive Distributed Lag Model.Transboundary and emerging diseases · 2024Article
- Exploring the influence of environmental indicators and forecasting influenza incidence using ARIMAX models.Frontiers in public health · 2024Article
- Joint extremes in precipitation and infectious disease in the USA: A bivariate POT study.One health (Amsterdam, Netherlands) · 2023Article
- Socioeconomic, meteorological factors and spatiotemporal distribution of human brucellosis in China between 2004 and 2019-A study based on spatial panel model.PLoS neglected tropical diseases · 2023Article
- An Epidemiological Study of Brucellosis in Different Animal Species from the Al-Qassim Region, Saudi Arabia.Vaccines · 2023Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brucellosis is a typical zoonosis driven by various risk factors, including environmental ones. The present study aimed to explore the driving effect of environmental factors on human brucellosis in a high incidence rate area, which provides understanding and implications in mitigating disease transmission risk in a multi-system between the human-animal-environment interface for preventing and controlling brucellosis based on the One Health concept. Based on the monthly time series data of human brucellosis and environmental variables, a Seasonal Autoregressive Integrated Moving Average Model with explanatory variables (SARIMAX) was applied to assess the association between environmental indicators and human brucellosis incidence (IHB). The results indicated distinct seasonal fluctuation during the study duration, tending to climb from April to August. Atmospheric pressure, precipitation, relative humidity, mean temperature, sunshine duration, and normalized difference vegetation index significantly drive IHB. Moreover, the well-fitting and predicting capability were performed and assessed in the optimal model was the SARIMAX (0,1,1) (0,1,1)
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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.