States show significant and increasing underascertainment over Omicron.

Reported cases capture less than 18% of infections in all 7 states under study.

Infections and Rt temporally align with major subvariant transitions (22B and 22E).

Estimates are robust to variations in the shedding profile and transmission timing.

Reconstructing the course of the COVID-19 pandemic through estimating incident infections is important for assessing disease burden and characterizing transmission dynamics. While wastewater concentration data have been used to estimate infections in localized pre-Omicron studies, a scalable approach that estimates variant-specific shedding rates and that accounts for underreporting remains underdeveloped. To this end, we develop a multi-source approach to retrospectively estimate daily COVID-19 infections in U.S. states during the Omicron era. Our approach integrates wastewater and seroprevalence surveillance data to improve infection estimates during the Delta-Omicron transition period. These refined estimates, along with wastewater concentration data adjusted for limited coverage, are used to calculate variant-specific shedding rates, which inform daily infection estimates going forward. While case-based estimates tend to exhibit striking volatility, these infection estimates show more stable and interpretable patterns that closely align with Omicron subvariant transitions. Moreover, we directly quantify the degree of underreporting, showing the extent that reported cases significantly underestimate disease burden in a sample of seven U.S. states. In these states, case reports capture less than a quarter of total infections, leaving the vast majority unaccounted for in official reports. Finally, we estimate time-varying effective reproduction numbers and growth rates to provide a more accurate and timely picture of transmission dynamics over the Omicron era in U.S. states.

Viral shedding

Disease burden

Reporting rate

Transmission dynamics

© 2026 The Authors. Published by Elsevier B.V.