Study population and setting
Authors compiled a database of 1,407 Covid-19 “transmission pairs” where information on who infected whom (infector to infectee) could be constructed from publicly available data on 9,120 confirmed cases in 27 provinces and 264 health commissions in China. Cases from Hubei province were excluded as chains of transmission were harder to reconstruct. Analysis was restricted to the 677 pairs for which dates of symptom onset and their social relationships were available. Infectors reported symptom onset between January 9 to February 13, 2020 during which key interventions were implemented. The authors estimated the time between symptom onset of the infector and symptom onset of the infectee (the serial interval) over three time periods: i) January 9 to 22 or “pre-peak”; ii) January 23 to 29 or “peak-week”; and iii) January 30 to February 13 or “post-peak”. They also estimated the serial interval over time using a rolling average. Authors then explored whether changes in the serial interval could be explained by factors including age, sex, social relationships, or non-pharmaceutical interventions (NPIs) and the potential impact of changing serial intervals over the course of the epidemic on estimates of transmissibility (Rt or the reproduction number).
Summary of Main Findings
Authors estimated that the serial interval shortened over the course of the epidemic from 7.8 days (95% credible interval: 7.0 – 8.6) pre-peak to 5.1 days (95% CrI: 4.6 – 5.7) during the peak, and 2.6 days (95% CrI: 1.9 – 3.2) post-peak. This decline was also observed when the serial interval was estimated over a rolling time window and when stratified by age, sex, and social relationship. Authors found that the delay from SARS-COV-2 confirmation to isolation was the primary driver and could explain 51.5% of the variability in the observed serial interval duration. For each day of early isolation, the serial interval decreased on average by 0.7 days. NPI strategies and population immunity explained an additional 15-20% of variability. Authors found that using a fixed serial interval distribution in analyses led to mis-estimation of Rt and potentially underestimation early in the pandemic.
Authors used a large number of transmission pairs (677 pairs) for which detailed epidemiological information was available to estimate the serial interval over multiple time points and explicitly excluded data from Hubei province which was deemed less reliable. Authors estimated the serial interval using non-overlapping and rolling average time-windows and found the same declining trend in the serial interval over time.
While authors consider a large number of transmission pairs, some epidemiological data may be limited by recall bias e.g. date of symptom onset. Additional unknown factors aside from time to isolation, NPIs or population immunity could have resulted in the reduction of the serial interval. Additionally, the effect of other NPIs and population immunity could not be disentangled.
Authors demonstrate that rapid case isolation can be an effective NPI. They additionally show that the serial interval is not a fixed interval as is often assumed and can be impacted significantly by non-pharmaceutical interventions. The use of “effective” serial intervals in analyses may provide better estimates of the reproduction number.
This review was posted on: 13 October 2020