论文标题
同时估计有效复制数量和COVID-19的检测率
Simultaneous estimation of the effective reproducing number and the detection rate of COVID-19
论文作者
论文摘要
估计$ r $（有效繁殖数量）的主要困难是，大多数Covid-19感染的病例是轻度或无症状的，因此很难确定感染的真实数量。本文估计$ r $的每日变化和使用贝叶斯型号同时更改检测率。使用合成数据的分析表明，我们的模型正确估计$ r $，并检测到检测率的短期冲击。然后，我们将模型应用于来自几个国家的数据，以评估公共医疗措施的有效性。我们的分析重点是日本，该日本采用适度的措施来保持“社会距离”。结果表明趋势下降，现在$ r $变为$ 1 $。尽管我们的分析是初步的，但这可能表明，适度的政策仍然可以防止Covid-19的流行。
A major difficulty to estimate $R$ (the effective reproducing number) of COVID-19 is that most cases of COVID-19 infection are mild or asymptomatic, therefore true number of infection is difficult to determine. This paper estimates the daily change of $R$ and the detection rate simultaneously using a Bayesian model. The analysis using synthesized data shows that our model correctly estimates $R$ and detects a short-term shock of the detection rate. Then, we apply our model to data from several countries to evaluate the effectiveness of public healthcare measures. Our analysis focuses Japan, which employs a moderate measure to keep "social distance". The result indicates a downward trend and now $R$ becomes below $1$. Although our analysis is preliminary, this may suggest that a moderate policy still can prevent epidemic of COVID-19.
