Back

Combining genomic data and infection estimates to characterize the complex dynamics of SARS-CoV-2 Omicron variants in the United States

Lopes, R.; Pham, K.; Klaassen, F.; Chitwood, M. H.; Hahn, A.; Redmond, S.; Swartwood, N. A.; Salomon, J. A.; Menzies, N. A.; Cohen, T.; Grubaugh, N. D.

2023-11-08 epidemiology
10.1101/2023.11.07.23298178 medRxiv
Show abstract

SARS-CoV-2 Omicron surged as a variant of concern in late 2021. Subsequently, several distinct Omicron variants have appeared and overtaken each other. We combined variant frequencies and infection estimates from a nowcasting model for each US state to estimate variant-specific infections, attack rates, and effective reproduction numbers (Rt). BA.1 rapidly emerged, and we estimate that it infected 47.7% of the US population between late 2021 and early 2022 before it was replaced by BA.2. We estimate that BA.5, despite a slower takeoff than BA.1, infected 35.7% of the US population, persisting in circulation for nearly 6 months. Other Omicron variants - BA.2, BA.4, and XBB - together infected 30.7% of the US population. We found a positive correlation between the state-level BA.1 attack rate and social vulnerability and a negative correlation between the BA.1 and BA.2 attack rates. Our findings illustrate the complex interplay between viral evolution, population susceptibility, and social factors during the Omicron emergence in the US.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.