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. 2023 Jan;95(1):e28269.
doi: 10.1002/jmv.28269. Epub 2022 Nov 12.

Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study

Junyu He  1   2 , Yanding Wang  3   4 , Xianyu Wei  4   5 , Hailong Sun  4 , Yuanyong Xu  4 , Wenwu Yin  6 , Yong Wang  3   4   5 , Wenyi Zhang  3   4   5
Affiliations

Spatial-temporal dynamics and time series prediction of HFRS in mainland China: A long-term retrospective study

Junyu He et al. J Med Virol. 2023 Jan.

Erratum in

Abstract

Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China. The current study aims to characterize the spatial-temporal dynamics of HFRS in mainland China during a long-term period (1950-2018). A total of 1 665 431 cases of HFRS were reported with an average annual incidence of 54.22 cases/100 000 individuals during 1950-2018. The joint regression model was used to define the global trend of the HFRS cases with an increasing-decreasing-slightly increasing-decreasing-slightly increasing trend during the 68 years. Then spatial correlation analysis and wavelet cluster analysis were used to identify four types of clusters of HFRS cases located in central and northeastern China. Lastly, the prophet model outperforms auto-regressive integrated moving average model in the HFRS modeling. Our findings will help reduce the knowledge gap on the transmission dynamics and distribution patterns of the HFRS in mainland China and facilitate to take effective preventive and control measures for the high-risk epidemic area.

Keywords: HFRS; prediction; spatial autocorrelation; wavelet cluster analysis.

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References

REFERENCES

    1. Liang W, Gu X, Li X, et al. Mapping the epidemic changes and risks of hemorrhagic fever with renal syndrome in Shaanxi province, China, 2005-2016. Sci Rep. 2018;8(1):749. doi:10.1038/s41598-017-18819-4
    1. Xiao H, Tian HY, Gao LD, et al. Animal reservoir, natural and socioeconomic variations and the transmission of hemorrhagic fever with renal syndrome in chenzhou, China, 2006-2010. PLoS Neglected Trop Dis. 2014;8(1):e2615. doi:10.1371/journal.pntd.0002615
    1. He J, Christakos G, Zhang W, Wang Y. A Space-Time study of hemorrhagic fever with renal syndrome (HFRS) and its climatic associations in heilongjiang province, China. Front Appl Math Stat. 2017;3:16. doi:10.3389/fams.2017.00016
    1. He J, Wang Y, Mu D, et al. The impacts of climatic factors and vegetation on hemorrhagic fever with renal syndrome transmission in China: a study of 109 counties. Int J Environ Res Public Health. 2019;16(18):3434. doi:10.3390/ijerph16183434
    1. He J, Christakos G, Wu J, et al. Probabilistic logic analysis of the highly heterogeneous spatiotemporal HFRS incidence distribution in Heilongjiang province (China) during 2005-2013. PLoS Neglected Trop Dis. 2019;13(1):e0007091. doi:10.1371/journal.pntd.0007091

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