ArticleScientific reports2018
Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.
- Dynamic Modeling of Prevention and Control ofTransboundary and emerging diseases · 2025Pooled it
- Spatiotemporal dynamics, clustering, and ARIMA-based short-term prediction of human brucellosis in Xinjiang, China.BMC infectious diseases · 2026Article
- Prevalence and spatial distribution characteristics of human brucellosis in Ningxia from 2010 to 2024.PLoS neglected tropical diseases · 2026Article
- 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
- Prediction analysis of human brucellosis cases in Ili Kazakh Autonomous Prefecture Xinjiang China based on time series.Scientific reports · 2025Article
- Spatiotemporal epidemiology of brucellosis in Iran from 2009 to 2018: A mixed ecological study.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2025Article
- Using ARIMA and ETS models for forecasting water level changes for sustainable environmental management.Scientific reports · 2024Article
- Analysis and forecasting of syphilis trends in mainland China based on hybrid time series models.Epidemiology and infection · 2024Article
- Spatial-temporal drivers and incidence heterogeneity of hemorrhagic fever with renal syndrome transmission in Shandong Province, China, 2016-2022.BMC public health · 2024Article
- Trend analysis and prediction of gonorrhea in mainland China based on a hybrid time series model.BMC infectious diseases · 2024Article
- Epidemiological characteristics and spatio-temporal analysis of brucellosis in Shandong province, 2015-2021.BMC infectious diseases · 2023Article
- Driving role of climatic and socioenvironmental factors on human brucellosis in China: machine-learning-based predictive analyses.Infectious diseases of poverty · 2023Article
- The research on TBATS and ELM models for prediction of human brucellosis cases in mainland China: a time series study.BMC infectious diseases · 2022Article
- Beneficial influence of single-stage posterior surgery for the treatment of lumbar brucella spondylitis combined with spondylolisthesis.Scientific reports · 2022Article
- Forecasting adversities of COVID-19 waves in India using intelligent computing.Innovations in systems and software engineering · 2022Article
- Zoonoses as Important Causes of Hospital Admissions: A 15-Year Study in Portugal.Portuguese journal of public health · 2022Article
- Spatiotemporal Pattern Evolution and Driving Factors of Brucellosis in China, 2003-2019.International journal of environmental research and public health · 2022Article
- Applying SARIMA, ETS, and hybrid models for prediction of tuberculosis incidence rate in Taiwan.PeerJ · 2022Article
- Predictive analysis of the number of human brucellosis cases in Xinjiang, China.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the re-emergence of brucellosis in mainland China since the mid-1990s, an increasing threat to public health tends to become even more violent, advanced warning plays a pivotal role in the control of brucellosis. However, a model integrating the autoregressive integrated moving average (ARIMA) with Error-Trend-Seasonal (ETS) methods remains unexplored in the epidemiological prediction. The hybrid ARIMA-ETS model based on discrete wavelet transform was hence constructed to assess the epidemics of human brucellosis from January 2004 to February 2018 in mainland China. The preferred hybrid model including the best-performing ARIMA method for approximation-forecasting and the best-fitting ETS approach for detail-forecasting is evidently superior to the standard ARIMA and ETS techniques in both three in-sample simulating and out-of-sample forecasting horizons in terms of the minimum performance indices of the root mean square error, mean absolute error, mean error rate and mean absolute percentage error. Whereafter, an ahead prediction from March to December in 2018 displays a dropping trend compared to the preceding years. But being still present, in various trends, in the present or future. This hybrid model can be highlighted in predicting the temporal trends of human brucellosis, which may act as the potential for far-reaching implications for prevention and control of this disease.
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