Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018

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...

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Autores principales:	Yongbin Wang, Chunjie Xu, Shengkui Zhang, Zhende Wang, Ying Zhu, Juxiang Yuan
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Human Brucellosis Brucellosis Incidence Autoregressive Integrated Moving Average (ARIMA) ARIMA Method Mean Absolute Percentage Error (MAPE) Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3d7e7f02ef69499187a75822ecc76457
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spelling	oai:doaj.org-article:3d7e7f02ef69499187a75822ecc764572021-12-02T15:08:15ZTemporal trends analysis of human brucellosis incidence in mainland China from 2004 to 201810.1038/s41598-018-33165-92045-2322https://doaj.org/article/3d7e7f02ef69499187a75822ecc764572018-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-33165-9https://doaj.org/toc/2045-2322Abstract 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.Yongbin WangChunjie XuShengkui ZhangZhende WangYing ZhuJuxiang YuanNature PortfolioarticleHuman BrucellosisBrucellosis IncidenceAutoregressive Integrated Moving Average (ARIMA)ARIMA MethodMean Absolute Percentage Error (MAPE)MedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-11 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Human Brucellosis Brucellosis Incidence Autoregressive Integrated Moving Average (ARIMA) ARIMA Method Mean Absolute Percentage Error (MAPE) Medicine R Science Q
spellingShingle	Human Brucellosis Brucellosis Incidence Autoregressive Integrated Moving Average (ARIMA) ARIMA Method Mean Absolute Percentage Error (MAPE) Medicine R Science Q Yongbin Wang Chunjie Xu Shengkui Zhang Zhende Wang Ying Zhu Juxiang Yuan Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018
description	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.
format	article
author	Yongbin Wang Chunjie Xu Shengkui Zhang Zhende Wang Ying Zhu Juxiang Yuan
author_facet	Yongbin Wang Chunjie Xu Shengkui Zhang Zhende Wang Ying Zhu Juxiang Yuan
author_sort	Yongbin Wang
title	Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018
title_short	Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018
title_full	Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018
title_fullStr	Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018
title_full_unstemmed	Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018
title_sort	temporal trends analysis of human brucellosis incidence in mainland china from 2004 to 2018
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/3d7e7f02ef69499187a75822ecc76457
work_keys_str_mv	AT yongbinwang temporaltrendsanalysisofhumanbrucellosisincidenceinmainlandchinafrom2004to2018 AT chunjiexu temporaltrendsanalysisofhumanbrucellosisincidenceinmainlandchinafrom2004to2018 AT shengkuizhang temporaltrendsanalysisofhumanbrucellosisincidenceinmainlandchinafrom2004to2018 AT zhendewang temporaltrendsanalysisofhumanbrucellosisincidenceinmainlandchinafrom2004to2018 AT yingzhu temporaltrendsanalysisofhumanbrucellosisincidenceinmainlandchinafrom2004to2018 AT juxiangyuan temporaltrendsanalysisofhumanbrucellosisincidenceinmainlandchinafrom2004to2018
_version_	1718388180420395008

Temporal trends analysis of human brucellosis incidence in mainland China from 2004 to 2018

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