Estimating the generation time for SARS-CoV-2 transmission using household data in the United States, December 2021 – May 2023

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Abstract

Background

Generation time, representing the interval between infection events in primary and secondary cases, is important for understanding disease transmission dynamics including predicting the effective reproduction number (Rt), which informs public health decisions. While previous estimates of SARS-CoV-2 generation times have been reported for early Omicron variants, there is a lack of data for subsequent sub-variants, such as XBB.

Methods

We estimated SARS-CoV-2 generation times using data from the Respiratory Virus Transmission Network – Sentinel (RVTN-S) household transmission study conducted across seven U.S. sites from December 2021 to May 2023. The study spanned three Omicron sub-periods dominated by the sub-variants BA.1/2, BA.4/5, and XBB. We employed a Susceptible-Exposed-Infectious-Recovered (SEIR) model with a Bayesian data augmentation method that imputes unobserved infection times of cases to estimate the generation time.

Findings

The estimated mean generation time for the overall Omicron period was 3.5 days (95% credible interval, CrI: 3.3-3.7). During the sub-periods, the estimated mean generation times were 3.8 days (95% CrI: 3.4-4.2) for BA.1/2, 3.5 days (95% CrI: 3.3-3.8) for BA.4/5, and 3.5 days (95% CrI: 3.1-3.9) for XBB.

Interpretation

Our study provides estimates of generation times for the Omicron variant, including the sub-variants BA.1/2, BA.4/5, and XBB. These up-to-date estimates specifically address the gap in knowledge regarding these sub-variants and are consistent with earlier studies. They enhance our understanding of SARS-CoV-2 transmission dynamics by aiding in the prediction of Rt, offering insights for improving COVID-19 modeling and public health strategies.

Funding

Centers for Disease Control and Prevention, and National Center for Advancing Translational Sciences.

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