Department of Biostatistics, University of Florida, Gainesville, FL, USA.
Department of Statistics, University of Georgia, Athens, GA, USA.
BMC Infect Dis. 2023 Jun 26;23(1):429. doi: 10.1186/s12879-023-08407-5.
The serial interval is the period of time between symptom onset in the primary case and symptom onset in the secondary case. Understanding the serial interval is important for determining transmission dynamics of infectious diseases like COVID-19, including the reproduction number and secondary attack rates, which could influence control measures. Early meta-analyses of COVID-19 reported serial intervals of 5.2 days (95% CI: 4.9-5.5) for the original wild-type variant and 5.2 days (95% CI: 4.87-5.47) for Alpha variant. The serial interval has been shown to decrease over the course of an epidemic for other respiratory diseases, which may be due to accumulating viral mutations and implementation of more effective nonpharmaceutical interventions. We therefore aggregated the literature to estimate serial intervals for Delta and Omicron variants.
This study followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A systematic literature search was conducted of PubMed, Scopus, Cochrane Library, ScienceDirect, and preprint server medRxiv for articles published from April 4, 2021, through May 23, 2023. Search terms were: ("serial interval" or "generation time"), ("Omicron" or "Delta"), and ("SARS-CoV-2" or "COVID-19"). Meta-analyses were done for Delta and Omicron variants using a restricted maximum-likelihood estimator model with a random effect for each study. Pooled average estimates and 95% confidence intervals (95% CI) are reported.
There were 46,648 primary/secondary case pairs included for the meta-analysis of Delta and 18,324 for Omicron. Mean serial interval for included studies ranged from 2.3-5.8 days for Delta and 2.1-4.8 days for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4-4.3) (20 studies) and Omicron was 3.2 days (95% CI: 2.9-3.5) (20 studies). Mean estimated serial interval for BA.1 was 3.3 days (95% CI: 2.8-3.7) (11 studies), BA.2 was 2.9 days (95% CI: 2.7-3.1) (six studies), and BA.5 was 2.3 days (95% CI: 1.6-3.1) (three studies).
Serial interval estimates for Delta and Omicron were shorter than ancestral SARS-CoV-2 variants. More recent Omicron subvariants had even shorter serial intervals suggesting serial intervals may be shortening over time. This suggests more rapid transmission from one generation of cases to the next, consistent with the observed faster growth dynamic of these variants compared to their ancestors. Additional changes to the serial interval may occur as SARS-CoV-2 continues to circulate and evolve. Changes to population immunity (due to infection and/or vaccination) may further modify it.
序列间隔是指主要病例发病与次要病例发病之间的时间间隔。了解序列间隔对于确定 COVID-19 等传染病的传播动态非常重要，包括繁殖数和二次攻击率，这可能会影响控制措施。对 COVID-19 的早期荟萃分析报告原始野生型变异的序列间隔为 5.2 天（95%CI：4.9-5.5），Alpha 变异的序列间隔为 5.2 天（95%CI：4.87-5.47）。已经表明，对于其他呼吸道疾病，随着疫情的发展，序列间隔会缩短，这可能是由于病毒突变的积累和更有效的非药物干预措施的实施。因此，我们汇总了文献，以估计 Delta 和 Omicron 变体的序列间隔。
本研究遵循系统评价和荟萃分析的首选报告项目指南。从 2021 年 4 月 4 日至 2023 年 5 月 23 日，对 PubMed、Scopus、Cochrane 图书馆、ScienceDirect 和预印本服务器 medRxiv 进行了系统文献检索，以查找发表的文章。检索词为：("serial interval" 或 "generation time")、("Omicron" 或 "Delta") 和 ("SARS-CoV-2" 或 "COVID-19")。使用具有每个研究的随机效应的限制最大似然估计模型对 Delta 和 Omicron 变体进行荟萃分析。报告了汇总的平均估计值和 95%置信区间（95%CI）。
共有 46648 对原发性/继发性病例纳入 Delta 的荟萃分析，18324 对 Omicron 纳入。纳入研究的平均序列间隔范围为 Delta 的 2.3-5.8 天和 Omicron 的 2.1-4.8 天。Delta 的汇总平均序列间隔为 3.9 天（95%CI：3.4-4.3）（20 项研究），Omicron 为 3.2 天（95%CI：2.9-3.5）（20 项研究）。BA.1 的估计平均序列间隔为 3.3 天（95%CI：2.8-3.7）（11 项研究），BA.2 为 2.9 天（95%CI：2.7-3.1）（6 项研究），BA.5 为 2.3 天（95%CI：1.6-3.1）（3 项研究）。
Delta 和 Omicron 的序列间隔估计值短于原始 SARS-CoV-2 变体。最近的 Omicron 亚变体的序列间隔更短，这表明序列间隔可能随着时间的推移而缩短。这表明从一代病例到下一代的传播速度更快，与这些变体与它们的祖先相比更快的增长动态一致。随着 SARS-CoV-2 的继续传播和演变，序列间隔可能会发生其他变化。由于感染和/或疫苗接种而导致的人群免疫力的变化可能会进一步改变它。
