Abstract:
:The serial interval is the time between symptom onsets in an infector-infectee pair. The generation time, also known as the generation interval, is the time between infection events in an infector-infectee pair. The serial interval and the generation time are key parameters for assessing the dynamics of a disease. A number of scientific papers reported information pertaining to the serial interval and/or generation time for COVID-19. OBJECTIVE:Conduct a review of available evidence to advise on appropriate parameter values for serial interval and generation time in national COVID-19 transmission models for Ireland and on methodological issues relating to those parameters. METHODS:We conducted a rapid review of the literature covering the period 1 January 2020 and 21 August 2020, following predefined eligibility criteria. Forty scientific papers met our inclusion criteria and were included in the review. RESULTS:The mean of the serial interval ranged from 3.03 to 7.6 days, based on 38 estimates, and the median from 1.0 to 6.0 days (based on 15 estimates). Only three estimates were provided for the mean of the generation time. These ranged from 3.95 to 5.20 days. One estimate of 5.0 days was provided for the median of the generation time. DISCUSSION:Estimates of the serial interval and the generation time are very dependent on the specific factors that apply at the time that the data are collected, including the level of social contact. Consequently, the estimates may not be entirely relevant to other environments. Therefore, local estimates should be obtained as soon as possible. Careful consideration should be given to the methodology that is used. Real-time estimations of the serial interval/generation time, allowing for variations over time, may provide more accurate estimates of reproduction numbers than using conventionally fixed serial interval/generation time distributions.
journal_name
BMJ Openjournal_title
BMJ openauthors
Griffin J,Casey M,Collins Á,Hunt K,McEvoy D,Byrne A,McAloon C,Barber A,Lane EA,More Sdoi
10.1136/bmjopen-2020-040263subject
Has Abstractpub_date
2020-11-23 00:00:00pages
e040263issue
11issn
2044-6055pii
bmjopen-2020-040263journal_volume
10pub_type
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