Meta-analysis of the SARS-CoV-2 serial interval and the impact of parameter uncertainty on the COVID-19 reproduction number

Abstract

The serial interval of an infectious disease, commonly interpreted as the time between onset of symptoms in sequentially infected individuals within a chain of transmission, is a key epidemiological quantity involved in estimating the reproduction number. The serial interval is closely related to other key quantities, including the incubation period, the generation interval (the time between sequential infections) and time delays between infection and the observations associated with monitoring an outbreak such as confirmed cases, hospital admissions and deaths. Estimates of these quantities are often based on small data sets from early contact tracing and are subject to considerable uncertainty, which is especially true for early COVID-19 data. In this paper we estimate these key quantities in the context of COVID-19 for the UK, including a meta-analysis of early estimates of the serial interval. We estimate distributions for the serial interval with a mean 5.6 (95% CrI 5.1–6.2) and SD 4.2 (95% CrI 3.9–4.6) days (empirical distribution), the generation interval with a mean 4.8 (95% CrI 4.3–5.41) and SD 1.7 (95% CrI 1.0–2.6) days (fitted gamma distribution), and the incubation period with a mean 5.5 (95% CrI 5.1–5.8) and SD 4.9 (95% CrI 4.5–5.3) days (fitted log normal distribution). We quantify the impact of the uncertainty surrounding the serial interval, generation interval, incubation period and time delays, on the subsequent estimation of the reproduction number, when pragmatic and more formal approaches are taken. These estimates place empirical bounds on the estimates of most relevant model parameters and are expected to contribute to modelling COVID-19 transmission.

Epidemiology and transmission characteristics of early COVID-19 cases, 20 January–19 March 2020, in Bavaria, Germany

“…This corresponds with two other studies [30,31], but is lower than in a systematic review [32]. The serial interval is also dependent on the effectiveness of interventions, such as timing of isolation, and thus, may be changing over time [32,33]. The mean serial interval is almost one day shorter than the mean overall incubation period (4.6 days) but equal to the mean incubation period for cases coming from Austria (3.7 days).…”

“…Out of 53 pairs of index and secondary cases, we estimated a mean serial interval of 3.9 days. This corresponds with two other studies [30,31], but is lower than in a systematic review [32]. The serial interval is also dependent on the effectiveness of interventions, such as timing of isolation, and thus, may be changing over time [32,33].…”

Analysis of severe outcomes associated with the SARS-CoV-2 Variant of Concern 202012/01 in England using ICNARC Case Mix Programme and QResearch databases

“…The characteristics and outcomes of patients infected with VOC B.1.1.7 are not yet known. Early analyses, of mortality linked to diagnostic data, have suggested that infection with VOC B.1.1.7 may be associated with a higher risk of mortality compared with infection with other virus variants 7,8,9,10,11,12 . However, these analyses had either limited adjustment for key patient characteristics thought to be associated with COVID-19 outcomes, or did not consider effects on critical care admission or outcome.…”

Second wave mortality among patients hospitalised for COVID-19 in Sweden: a nationwide observational cohort study

“…It is also possible that the increase in mortality during the second half of 2020 was caused by mutations of the SARS-CoV-2 virus. The SARS-CoV-2 virus variant of concern (B.1.1.7), which was first detected in the United Kingdom has been associated with an enhanced mortality among out-patients with SARS-CoV-2 infection [19,20]. However, as virus variants of concern occurred only sporadically in Sweden before January 2021 [21], they were most likely not involved in the increased second wave mortality that was noted in this study.…”