Projected COVID-19 Mortality Reduction From Paxlovid Rollout

COVID-19 was the third leading cause of death in the US in 2022, and following FDA approval of Paxlovid (nirmatrelvir-ritonavir), the test-to-treat initiative became a cornerstone of the US pandemic response.¹ Paxlovid treatment requires testing and initiating medication within 5 days of symptom onset. However, the population-level impact of Paxlovid rollout has not been estimated.² The purpose of this study is to project simulated effects of Paxlovid rollout on hospitalizations and mortality and to quantify the number of COVID-19 tests and Paxlovid courses required for different levels of mortality reduction during a surge comparable to the 2022 winter Omicron wave (WOW) (December 15, 2021, to March 15, 2022).

We modeled COVID-19 hospitalization and mortality reductions associated with Paxlovid rollout as the product of (1) the proportion of eligible symptomatic patients tested within 5 days of symptom onset, (2) probability of receiving Paxlovid given eligibility, and (3) Paxlovid effectiveness against hospitalization and mortality risks. Details on quantification of number of required symptomatic tests and required Paxlovid courses are available in eMethods in Supplement 1. For sensitivity analyses, we constructed 10 models (Table) to estimate optimistic and pessimistic bounds for hospitalization and mortality reduction (models 2-3), subpopulation analyses (models 4-6), projections given increased Paxlovid uptake (models 7-8), and tests and Paxlovid courses required (models 9-10). Detailed descriptions for each model are provided in the eMethods and eTables 1-3 in Supplement 1. Institutional review board approval was not required as human participants were not involved per the Common Rule (45 CFR §46). The study followed the CHEERS reporting guideline.

We estimated that 78% of US cases that will require hospitalization are detected within 5 days of symptom onset, and that uptake of Paxlovid is 5% among eligible infected individuals. Given Paxlovid effectiveness of 67% against hospitalization and 81% against mortality, this corresponds to relative percentage reductions of COVID-19 hospitalization by 2.7% and mortality by 3.2% (Figure).

In sensitivity analyses (Table, models 2-3), COVID-19 hospitalization reductions varied between 0.5% and 7.5% and mortality reductions between 0.6% and 7.5%. However, in nursing homes, with higher uptake, we estimate hospitalization and mortality reductions at 7.7% and 9.3% (model 4). If Paxlovid uptake among eligible populations increases to 40% (model 7), we project a 21% reduction in hospitalization and 25% reduction in mortality. If Paxlovid uptake increases to 80% (model 8), we project a 42% reduction in hospitalization and 51% reduction in mortality.

At 5% Paxlovid uptake (model 1), the required number of symptomatic tests and Paxlovid courses needed during the WOW would have been 4.8 million and 2.5 million, respectively, averting 2.7% of hospitalizations and 3.2% of deaths. At 80% Paxlovid uptake (model 8), the required number of symptomatic tests and Paxlovid courses would have been 75.3 million and 39.8 million, respectively, averting 41.8% of hospitalizations and 50.5% of deaths.

In this study, we estimated that had current Paxlovid uptake been achieved in January 2022, 4.8 thousand deaths would have been averted during the WOW. Our estimates suggest that 0.7 to 75.3 million symptomatic tests and 0.4 to 39.8 million courses of Paxlovid are needed for a future Omicron-like wave.

There are limitations to this work. Our parameterization is limited by a dearth of data on Paxlovid uptake. Also, relevant parameters are likely to continue shifting over time due to reduced prescribing restrictions or potential resistance.^3,4 Nevertheless, in this rapidly changing landscape, we provide a simple, flexible framework for understanding the resource requirements and benefits associated with future expansions of the test-to-treat initiative.

Accepted for Publication: January 11, 2023.

Published: March 17, 2023. doi:10.1001/jamahealthforum.2023.0046

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2023 Khunte M et al. JAMA Health Forum.

Corresponding Author: Alyssa Bilinski, PhD, Department of Health Services, Policy, and Practice, Brown School of Public Health, 121 S Main St, Box G-S121-7, Providence, RI 02912 (alyssa_bilinski@brown.edu).

Author Contributions: Mr Khunte and Mr Kumar had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Authors Khunte and Kumar contributed equally.

Concept and design: All authors.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Khunte, Kumar.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Khunte, Kumar, Salomon.

Obtained funding: Salomon, Bilinski.

Administrative, technical, or material support: Kumar, Bilinski.

Supervision: Salomon, Bilinski.

Conflict of Interest Disclosures: None reported.

Funding/Support: All authors were supported by the Centers for Disease Control and Prevention through the Council of State and Territorial Epidemiologists (NU38OT000297-02). Dr Saloman was also supported by the National Institute on Drug Abuse (3R37DA01561217S1).

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.