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Volume 17
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10.3390/v17040473
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Article

Initial Establishment of Warning Model for Epidemic Intensity of Norovirus GII Associated with Acute Gastroenteritis in Beijing Based on Synthetic Index Method

by
Taoli Han
1,
Yan Gao
1,
Shiyao Zhang
1,
Yang Jiao
1,
Jianhong Zhao
1,
Jiaxin Zhao
1,
Yujie Liu
1,
Kuankuan Liu
1,
Pan Lu
1,
Ru Fan
1,
Yuqi Zhang
1,
Xingmei Ren
1,
Mengnan Wang
1,
Zhiyong Gao
2,
Wenjing Li
1,
Beibei Li
1,
Tongyue Su
3 and
Lingli Sun
1,*
1
Beijing Chaoyang Center for Disease Control and Prevention, Beijing 100021, China
2
Beijing Center for Disease Control and Prevention, Beijing 100013, China
3
School of Public Health, Hebei University, Baoding 071000, China
*
Author to whom correspondence should be addressed.
Viruses 2025, 17(4), 473; https://doi.org/10.3390/v17040473
Submission received: 8 February 2025 / Revised: 14 March 2025 / Accepted: 22 March 2025 / Published: 26 March 2025
(This article belongs to the Special Issue Human Norovirus 2024)
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Abstract

At present, there is no research that classifies the epidemic intensity of acute gastroenteritis (AGE) caused by Norovirus (NoV) GII combined cases and environmental surveillance data at the same time. With reference to the experience of the epidemiological-level classification of infectious disease and the actual epidemiological status of NoV AGE in Chaoyang District, Beijing, China, the epidemic intensity of NoV GII was divided into five grades with increasing intensity from grade 1 to grade 5, which corresponds to non-epidemic risk, general risk, moderate risk, high risk, and ultra-high risk, respectively. If the synthetic index of two consecutive monitoring weeks in the epidemic season of 2023–2024 exceeds a certain threshold, an early warning for the corresponding epidemic intensity will be issued and recommendations on the corresponding control measures will be given. This study established and quantified the criteria for the epidemic intensity of AGE caused by NoV GII based on case surveillance data and environmental surveillance data. It provides a reference for other methods to carry out relevant studies in the future. However, mathematical models cannot completely replace skilled experience. Therefore, when making decisions with early warning models in practice, it is necessary to refer to the opinions of professional and experienced experts to avoid the bias of the early warning model from affecting strategy judgment.
Keywords: synthetic index method; norovirus; acute gastroenteritis; wastewater surveillance; average temperatures synthetic index method; norovirus; acute gastroenteritis; wastewater surveillance; average temperatures

Share and Cite

MDPI and ACS Style

Han, T.; Gao, Y.; Zhang, S.; Jiao, Y.; Zhao, J.; Zhao, J.; Liu, Y.; Liu, K.; Lu, P.; Fan, R.; et al. Initial Establishment of Warning Model for Epidemic Intensity of Norovirus GII Associated with Acute Gastroenteritis in Beijing Based on Synthetic Index Method. Viruses 2025, 17, 473. https://doi.org/10.3390/v17040473

AMA Style

Han T, Gao Y, Zhang S, Jiao Y, Zhao J, Zhao J, Liu Y, Liu K, Lu P, Fan R, et al. Initial Establishment of Warning Model for Epidemic Intensity of Norovirus GII Associated with Acute Gastroenteritis in Beijing Based on Synthetic Index Method. Viruses. 2025; 17(4):473. https://doi.org/10.3390/v17040473

Chicago/Turabian Style

Han, Taoli, Yan Gao, Shiyao Zhang, Yang Jiao, Jianhong Zhao, Jiaxin Zhao, Yujie Liu, Kuankuan Liu, Pan Lu, Ru Fan, and et al. 2025. "Initial Establishment of Warning Model for Epidemic Intensity of Norovirus GII Associated with Acute Gastroenteritis in Beijing Based on Synthetic Index Method" Viruses 17, no. 4: 473. https://doi.org/10.3390/v17040473

APA Style

Han, T., Gao, Y., Zhang, S., Jiao, Y., Zhao, J., Zhao, J., Liu, Y., Liu, K., Lu, P., Fan, R., Zhang, Y., Ren, X., Wang, M., Gao, Z., Li, W., Li, B., Su, T., & Sun, L. (2025). Initial Establishment of Warning Model for Epidemic Intensity of Norovirus GII Associated with Acute Gastroenteritis in Beijing Based on Synthetic Index Method. Viruses, 17(4), 473. https://doi.org/10.3390/v17040473

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