| 黄丽红,沈思鹏,余平,魏永越.基于动态基本再生数的新型冠状病毒肺炎疫情防控现状评估[J].Chinese journal of Epidemiology,2020,41(4):466-469 |
| 基于动态基本再生数的新型冠状病毒肺炎疫情防控现状评估 |
| Dynamic basic reproduction number based evaluation for current prevention and control of COVID-19 outbreak in China |
| Received:February 09, 2020 |
| DOI：10.3760/cma.j.cn112338-20200209-00080 |
| KeyWord: 新型冠状病毒肺炎 动态基本再生数 统计预测 |
| English Key Word: Coronavirus disease Dynamic basic reproduction number Statistical prediction |
| FundProject:国家自然科学青年基金（81903407） |
| Author Name | Affiliation | E-mail | | Huang Lihong | Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032, China | | | Shen Sipeng | Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China | | | Yu Ping | Jingan District Center for Disease Control and Prevention, Shanghai 200072, China | yuping@jingancdc.net | | Wei Yongyue | Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China | |
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| Abstract: |
| 目的 对全国各省份的新型冠状病毒肺炎(COVID-19)疫情防控现状进行分析,建立预测模型预估现有防控措施预期成效,为决策部门提供科学信息。方法 基于COVID-19疫情网络公开数据,估计全国、各省份以及武汉市不同时间基本再生数(R0)的动态变化R0(t),以评估在现有防控措施下,COVID-19传染速率随时间变化的趋势,预估现有防控措施的预期成效。结果 从结果稳定性考虑,选择累积确诊病例数>100例的地区进行分析,共24个省份纳入分析。在疫情初期,全国整体R0(t)不稳定,数值较大,误差也较大。随着防控措施的进一步加强,R0(t)普遍在1月下旬开始呈现下降趋势,2月始下降趋势稳定。截至数据分析日,纳入分析的24个省份中已有18个省份(75%)R0(t)降到1以下。这为有条件地开放人员流动提供了信息。结论 动态R0(t)有助于动态评估COVID-19传染速率变化情况,本次疫情防控措施已初显成效,如能继续保持,全国疫情有望短期内得到全面控制。 |
| English Abstract: |
| Objective To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision-making departments. Methods Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number R0(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time. Results For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the R0(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, R0(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the R0(t)s less than 1. The results could be used for the decision making to free population floating conditionally. Conclusions Dynamic R0(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future. |
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