Inferring variant-specific effective reproduction numbers from combined case and sequencing data
- 1Department of Applied Mathematics, University of Washington, Seattle, WA, USA
- 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- 3Howard Hughes Medical Institute, Seattle, WA, USA
Abstract
Accurately estimating relative transmission rates of SARS-CoV-2 variants remains a scientific and public health priority. Recent studies have used the sample proportions of different variants from genetic sequence data to describe variant frequency dynamics and relative transmission rates, but frequencies alone cannot capture the rich epidemiological behavior of SARS-CoV-2. Here, we extend methods for inferring the effective reproduction number of an epidemic using confirmed case data to jointly estimate variant-specific effective reproduction numbers and frequencies of co-circulating variants using cases and sequences across states in the United States from January 2021 to March 2022. Our method can be used to infer structured relationships between effective reproduction numbers across time series, allowing us to estimate fixed variant-specific growth advantages. We use this model to estimate the effective reproduction number of SARS-CoV-2 variants of concern and variants of interest in the United States, and to estimate consistent growth advantages of particular variants across different locations.
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BibTeX
@article{figgins2026inferring,
title = {{Inferring variant-specific effective reproduction numbers from combined case and sequencing data}},
author = {Marlin D Figgins and Trevor Bedford},
journal = {eLife},
year = {2026},
month = jul,
doi = {10.7554/elife.104802.2},
url = {https://doi.org/10.7554/elife.104802.2},
note = {CC BY},
}
RIS
TY - JOUR
TI - Inferring variant-specific effective reproduction numbers from combined case and sequencing data
AU - Marlin D Figgins
AU - Trevor Bedford
PY - 2026
DA - 2026/07/09
JO - eLife
DO - 10.7554/elife.104802.2
UR - https://doi.org/10.7554/elife.104802.2
AB - Accurately estimating relative transmission rates of SARS-CoV-2 variants remains a scientific and public health priority. Recent studies have used the sample proportions of different variants from genetic sequence data to describe variant frequency dynamics and relative transmission rates, but frequencies alone cannot capture the rich epidemiological behavior of SARS-CoV-2. Here, we extend methods for inferring the effective reproduction number of an epidemic using confirmed case data to jointly estimate variant-specific effective reproduction numbers and frequencies of co-circulating variants using cases and sequences across states in the United States from January 2021 to March 2022. Our method can be used to infer structured relationships between effective reproduction numbers across time series, allowing us to estimate fixed variant-specific growth advantages. We use this model to estimate the effective reproduction number of SARS-CoV-2 variants of concern and variants of interest in the United States, and to estimate consistent growth advantages of particular variants across different locations.
SN - 2050-084X
ER -