Epidemic dynamic model based evaluation of effectiveness of prevention and control strategies for COVID-19 in Ningbo
10.3760/cma.j.cn112338-20200311-00313
- VernacularTitle:基于传染病动力学模型的宁波市新型冠状病毒肺炎防控措施效果评估
- Author:
Hang HONG
1
;
Hongbo SHI
;
Haibo JIANG
;
Xiaomin GU
;
Yi CHEN
;
Keqin DING
;
Guozhang XU
Author Information
1. 宁波市疾病预防控制中心性病艾滋病预防控制所 传染病预防控制所 315010
- Keywords:
COVID-19;
Dynamic model;
Basic reproduction number;
Effectiveness of prevention and control
- From:
Chinese Journal of Epidemiology
2020;41(10):1606-1610
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To evaluate effectiveness of prevention and control strategies for COVID-19 in Ningbo by using an epidemic dynamic model.Methods:The incidence data and epidemic information of COVID-19 reported in Ningbo as of 9 March, 2020 were collected, and based on the implementation of prevention and control strategies, we developed a SEIR epidemic dynamics model. The basic and real-time reproduction numbers were calculated to evaluate effectiveness of prevention and control.Results:A total of 157 cases of COVID-19 were confirmed, without death, in Ningbo. The proportion of severe cases was 12.1 %. The mean incubation period was estimated to be (5.7±2.9) days. The mean interval from illness onset to diagnosis was (5.4±3.7) days. The mean duration from diagnosis to hospital discharge was (16.6±6.5) days. A total of 105 339 contacts had been under medical observation. The infection rates in contacts with home quarantine and centralized quarantine were 0.1 % and 0.3 %, respectively. In the confirmed cases, those who had been under medical observation before diagnoses accounted for 63.1 %. The basic reproduction number was estimated to be 4.8. With the strengthening of prevention and control measures, real-time reproduction number showed a gradual downward trend, dropping to below 1.0 on 4 February, and then continued to drop to 0.2 in mid-February. Conclusion:The effectiveness of the prevention and control measures for COVID-19 in Ningbo can be evaluated by using epidemic dynamic model to provide scientific evidence for the development of the prevention and control strategies.
