Assessing Interventions against Coronavirus Disease 2019 (COVID-19) in Osaka, Japan: A Modeling Study.
Assessing Interventions against Coronavirus Disease 2019 (COVID-19) in Osaka, Japan: A Modeling Study.
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DOI：
10.3390/jcm10061256
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发表时间：
2021-03-18
影响因子：
3.9
通讯作者：
Nishiura H
中科院分区：
文献类型：
--
作者：
Nakajo K;Nishiura H
实时估计冠状病毒病（COVID-19）的有效繁殖数R(t)是一项持续的挑战。R(t)反映了基于现成的发病数据的流行病动态，对规划和实施公共卫生和社会措施很有用。在本研究中，我们提出了一种计算COVID-19的R(t)的方法，并将该方法应用于2020年2月至9月大阪府的疫情。我们使用发病日期估计R(t)作为感染时间的函数。大阪的疫情在第一波和第二波分别于4月2日和7月26日左右得到控制。R(t)在任何单一干预后都没有急剧下降。然而，当多种干预措施联合使用时，第一波和第二波R(t)的相对降低分别为70%和51%。虽然第二波疫情在没有宣布紧急状态的情况下得到了控制，但我们的模型比较表明，依靠单一干预措施不足以使R(t) < 1。COVID-19大流行的结果继续依赖于政治领导，迅速设计和实施能够广泛和适当地减少接触的综合干预措施。
Estimation of the effective reproduction number, R(t), of coronavirus disease (COVID-19) in real-time is a continuing challenge. R(t) reflects the epidemic dynamics based on readily available illness onset data, and is useful for the planning and implementation of public health and social measures. In the present study, we proposed a method for computing the R(t) of COVID-19, and applied this method to the epidemic in Osaka prefecture from February to September 2020. We estimated R(t) as a function of the time of infection using the date of illness onset. The epidemic in Osaka came under control around 2 April during the first wave, and 26 July during the second wave. R(t) did not decline drastically following any single intervention. However, when multiple interventions were combined, the relative reductions in R(t) during the first and second waves were 70% and 51%, respectively. Although the second wave was brought under control without declaring a state of emergency, our model comparison indicated that relying on a single intervention would not be sufficient to reduce R(t) < 1. The outcome of the COVID-19 pandemic continues to rely on political leadership to swiftly design and implement combined interventions capable of broadly and appropriately reducing contacts.
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