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Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018.
Sci Rep. 2018 10 26; 8(1):15901.SR

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.

Authors+Show Affiliations

School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P. R. China.School of Public Health, Capital Medical University, Beijing, 100069, P. R. China.School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P. R. China.School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P. R. China.School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P. R. China.School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, P. R. China. yuanjx@ncst.edu.cn.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

30367079

Citation

Wang, Yongbin, et al. "Temporal Trends Analysis of Human Brucellosis Incidence in Mainland China From 2004 to 2018." Scientific Reports, vol. 8, no. 1, 2018, p. 15901.
Wang Y, Xu C, Zhang S, et al. Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018. Sci Rep. 2018;8(1):15901.
Wang, Y., Xu, C., Zhang, S., Wang, Z., Zhu, Y., & Yuan, J. (2018). Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018. Scientific Reports, 8(1), 15901. https://doi.org/10.1038/s41598-018-33165-9
Wang Y, et al. Temporal Trends Analysis of Human Brucellosis Incidence in Mainland China From 2004 to 2018. Sci Rep. 2018 10 26;8(1):15901. PubMed PMID: 30367079.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018. AU - Wang,Yongbin, AU - Xu,Chunjie, AU - Zhang,Shengkui, AU - Wang,Zhende, AU - Zhu,Ying, AU - Yuan,Juxiang, Y1 - 2018/10/26/ PY - 2018/05/29/received PY - 2018/09/20/accepted PY - 2018/10/28/entrez PY - 2018/10/28/pubmed PY - 2019/10/30/medline SP - 15901 EP - 15901 JF - Scientific reports JO - Sci Rep VL - 8 IS - 1 N2 - 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. SN - 2045-2322 UR - https://www.unboundmedicine.com/medline/citation/30367079/Temporal_trends_analysis_of_human_brucellosis_incidence_in_mainland_China_from_2004_to_2018_ L2 - http://dx.doi.org/10.1038/s41598-018-33165-9 DB - PRIME DP - Unbound Medicine ER -