Serial Intervals and Case Isolation Delays for Coronavirus Disease 2019: A Systematic Review and Meta-Analysis.

Abstract

BackgroundEstimates of the serial interval distribution contribute to our understanding of the transmission dynamics of coronavirus disease 2019 (COVID-19). Here, we aimed to summarize the existing evidence on serial interval distributions and delays in case isolation for COVID-19.MethodsWe conducted a systematic review of the published literature and preprints in PubMed on two epidemiological parameters namely serial intervals and delay intervals relating to isolation of cases for COVID-19 until 22 October, 2020 following predefined eligibility criteria. We assessed the variation in these parameter estimates by correlation and regression analysis.ResultsOf 103 unique studies identified on serial intervals of COVID-19, 56 were included providing 129 estimates and of 451 unique studies on isolation delays, 18 studies were included providing 74 estimates. Serial interval estimates varied from 1.0 to 9.9 days, while case isolation delays varied from 1.0 to 12.5 days which were associated with spatial, methodological and temporal factors. In mainland China, the pooled mean serial interval was 6.2 (range, 5.1-7.8) days before the epidemic peak and reduced to 4.9 (range, 1.9-6.5) days after the epidemic peak. Similarly, the pooled mean isolation delay related intervals were 6.0 (range, 2.9-12.5) days and 2.4 (range, 2.0-2.7) days before and after the epidemic peak, respectively. There was a positive association between serial interval and case isolation delay.ConclusionsTemporal factors, such as different control measures and case isolation in particular led to shorter serial interval estimates over time. Correcting transmissibility estimates for these time-varying distributions could aid mitigation efforts.