Modeling a High-Uptake Booster Scenario on the COVID-19 Burden and Healthcare Costs in New York City

Background: Uptake of the COVID-19 bivalent booster vaccination among eligible residents of New York City (NYC) has been modest and declining. Assessing the impact of improved population-level booster coverage with bivalent vaccines in NYC can help inform investment towards vaccination and potential cost-savings.Methods: We calibrated an agent-based model of disease transmission to confirmed and probable cases of COVID-19 in NYC, and simulated it to projected outcomes under two scenarios. In the base case scenario, we assumed that vaccination continued with the average daily rate administered during December 2022. In the counterfactual scenario, we modeled a high-uptake scenario between January 1, 2023 and March 31, 2023 that increased bivalent coverage in NYC to match the age-specific influenza vaccine coverage of the 2020-2021 season. Vaccination rate outside the campaign duration remained the same as the base case scenario.Findings: Compared to the base case, the high-uptake scenario averted 160,977 (95% Credible Interval [CrI]: 145,599–177,675) cases, and prevented 4,348 (95% CrI: 3,906–4,799) hospitalizations between January 1 through the end of June 2023. This results in net savings of $527.0 (95% CrI: 472.6–577.1) million in direct healthcare costs. We estimated that the high-uptake scenario would avert 125,268 (95% CrI: 113,043–138,646) days of student absenteeism from schools due to COVID-19 illness.Interpretation: Our results illustrate the continued benefits of COVID-19 vaccines in preventing severe health outcomes, averting healthcare costs, and maintaining educational continuity in NYC.Funding: A.P. and M.C.F. acknowledge support from NSF RAPID grant 2138192. S.M.M. acknowledges support by the Canadian Institutes of Health Research [OV4 – 170643, COVID-19 Rapid Research] and the Natural Sciences and Engineering Research Council of Canada, Emerging Infectious Disease Modelling, MfPH grant. A.P.G. acknowledges support from the NIH grant R01 AI151176, NSF Expeditions grant 1918784, The Commonwealth Fund, and The Notsew Orm Sands Foundation.Declaration of Interest: Authors declare that they have no competing interests.