Bibliographic Details
| Title: |
Estimating vaccine efficacy during open-label follow-up of COVID-19 vaccine trials based on population-level surveillance data |
| Authors: |
Mia Moore, Yifan Zhu, Ian Hirsch, Tom White, Robert C. Reiner, Ryan M. Barber, David Pigott, James K. Collins, Serena Santoni, Magdalena E. Sobieszczyk, Holly Janes |
| Source: |
Epidemics, Vol 47, Iss , Pp 100768- (2024) |
| Publisher Information: |
Elsevier, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Infectious and parasitic diseases |
| Subject Terms: |
Clinical trial design, Randomized controlled trial, Vaccine, Counterfactual, Infectious and parasitic diseases, RC109-216 |
| More Details: |
While rapid development and roll out of COVID-19 vaccines is necessary in a pandemic, the process limits the ability of clinical trials to assess longer-term vaccine efficacy. We leveraged COVID-19 surveillance data in the U.S. to evaluate vaccine efficacy in U.S. Government-funded COVID-19 vaccine efficacy trials with a three-step estimation process. First, we used a compartmental epidemiological model informed by county-level surveillance data, a “population model”, to estimate SARS-CoV-2 incidence among the unvaccinated. Second, a “cohort model” was used to adjust the population SARS-CoV-2 incidence to the vaccine trial cohort, taking into account individual participant characteristics and the difference between SARS-CoV-2 infection and COVID-19 disease. Third, we fit a regression model estimating the offset between the cohort-model-based COVID-19 incidence in the unvaccinated with the placebo-group COVID-19 incidence in the trial during blinded follow-up. Counterfactual placebo COVID-19 incidence was estimated during open-label follow-up by adjusting the cohort-model-based incidence rate by the estimated offset. Vaccine efficacy during open-label follow-up was estimated by contrasting the vaccine group COVID-19 incidence with the counterfactual placebo COVID-19 incidence. We documented good performance of the methodology in a simulation study. We also applied the methodology to estimate vaccine efficacy for the two-dose AZD1222 COVID-19 vaccine using data from the phase 3 U.S. trial (ClinicalTrials.gov # NCT04516746). We estimated AZD1222 vaccine efficacy of 59.1% (95% uncertainty interval (UI): 40.4%–74.3%) in April, 2021 (mean 106 days post-second dose), which reduced to 35.7% (95% UI: 15.0%–51.7%) in July, 2021 (mean 198 days post-second-dose). We developed and evaluated a methodology for estimating longer-term vaccine efficacy. This methodology could be applied to estimating counterfactual placebo incidence for future placebo-controlled vaccine efficacy trials of emerging pathogens with early termination of blinded follow-up, to active-controlled or uncontrolled COVID-19 vaccine efficacy trials, and to other clinical endpoints influenced by vaccination. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1755-4365 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S175543652400029X; https://doaj.org/toc/1755-4365 |
| DOI: |
10.1016/j.epidem.2024.100768 |
| Access URL: |
https://doaj.org/article/0c1184e721274b25b668765f603565a2 |
| Accession Number: |
edsdoj.0c1184e721274b25b668765f603565a2 |
| Database: |
Directory of Open Access Journals |
