With the spread of the novel coronavirus disease 2019 (COVID-19) around the world, the estimation of the incubation period of COVID-19 has become a hot issue. Based on the doubly interval-censored data model, we assume that the incubation period follows lognormal and Gamma distribution, and estimate the parameters of the incubation period of COVID-19 by adopting the maximum likelihood estimation, expectation maximization algorithm and a newly proposed algorithm (expectation mostly conditional maximization algorithm, referred as ECIMM). The main innovation of this paper lies in two aspects: Firstly, we regard the sample data of the incubation period as the doubly interval-censored data without unnecessary data simplification to improve the accuracy and credibility of the results; secondly, our new ECIMM algorithm enjoys better convergence and universality compared with others. With the framework of this paper, we conclude that 14-day quarantine period can largely interrupt the transmission of COVID-19, however, people who need specially monitoring should be isolated for about 20 days for the sake of safety. The results provide some suggestions for the prevention and control of COVID-19. The newly proposed ECIMM algorithm can also be used to deal with the doubly interval-censored data model appearing in various fields.

随着新型冠状病毒病 2019 (COVID-19) 在全球范围内的传播，对 COVID-19 潜伏期的估计已成为热点问题。基于双区间删失数据模型，我们假设潜伏期服从对数正态分布和 Gamma 分布，采用最大似然估计、期望最大化算法和新提出的算法估计 COVID-19 的潜伏期参数（期望大多是条件最大化算法，简称ECIMM）。本文的主要创新点在于两个方面：一是我们将潜伏期的样本数据作为双区间截尾数据，没有进行不必要的数据简化，以提高结果的准确性和可信度；其次，与其他算法相比，我们的新 ECIMM 算法具有更好的收敛性和普遍性。在本文的框架下，我们得出结论，14 天的隔离期可以在很大程度上阻断 COVID-19 的传播，但是为了安全起见，需要特别监控的人应该隔离 20 天左右。研究结果为COVID-19的防控提供了一些建议。新提出的ECIMM算法也可用于处理出现在各个领域的双区间删失数据模型。研究结果为COVID-19的防控提供了一些建议。新提出的ECIMM算法也可用于处理出现在各个领域的双区间删失数据模型。研究结果为COVID-19的防控提供了一些建议。新提出的ECIMM算法也可用于处理出现在各个领域的双区间删失数据模型。