Am J Epidemiol. 2020 Nov 2;189(11):1421-1426. doi: 10.1093/aje/kwaa090.
Serial interval (SI), defined as the time between symptom onset in an infector and infectee pair, is commonly used to understand infectious diseases transmission. Slow progression to active disease, as well as the small percentage of individuals who will eventually develop active disease, complicate the estimation of the SI for tuberculosis (TB). In this paper, we showed via simulation studies that when there is credible information on the percentage of those who will develop TB disease following infection, a cure model, first introduced by Boag in 1949, should be used to estimate the SI for TB. This model includes a parameter in the likelihood function to account for the study population being composed of those who will have the event of interest and those who will never have the event. We estimated the SI for TB to be approximately 0.5 years for the United States and Canada (January 2002 to December 2006) and approximately 2.0 years for Brazil (March 2008 to June 2012), which might imply a higher occurrence of reinfection TB in a developing country like Brazil.
序列间隔（SI）定义为感染者和被感染者之间出现症状的时间间隔，常用于了解传染病的传播。结核病（TB）的 SI 估计较为复杂，原因在于疾病的进展较为缓慢，以及最终会发展为活动性疾病的个体比例较小。在本文中，我们通过模拟研究表明，当有可信的信息表明感染后有多少人会发展为结核病时，应该使用 Boag 于 1949 年首次提出的治愈模型来估计 TB 的 SI。该模型在似然函数中包含一个参数，用于说明研究人群由那些将发生感兴趣事件的个体和那些永远不会发生该事件的个体组成。我们估计美国和加拿大（2002 年 1 月至 2006 年 12 月）的 TB SI 约为 0.5 年，巴西（2008 年 3 月至 2012 年 6 月）的 TB SI 约为 2.0 年，这可能意味着在巴西等发展中国家，再感染性结核病的发生率更高。
