Author: Lin, D.; Gu, Y.; Zeng, D.; Janes, H.; Gilbert, P.
Title: Evaluating Vaccine Efficacy Against SARS-CoV-2 Infection Cord-id: mxkfuya4 Document date: 2021_4_17
ID: mxkfuya4
Snippet: Although interim results from several large placebo-controlled phase 3 trials demonstrated high vaccine efficacy (VE) against symptomatic COVID-19, it is unknown how effective the vaccines are in preventing people from becoming asymptomatically infected and potentially spreading the virus unwittingly. It is more difficult to evaluate VE against SARS-CoV-2 infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between two antibody or RT
Document: Although interim results from several large placebo-controlled phase 3 trials demonstrated high vaccine efficacy (VE) against symptomatic COVID-19, it is unknown how effective the vaccines are in preventing people from becoming asymptomatically infected and potentially spreading the virus unwittingly. It is more difficult to evaluate VE against SARS-CoV-2 infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between two antibody or RT-PCR tests. Additional challenges arise as community transmission changes over time and as participants are vaccinated on different dates because of staggered enrollment or crossover before the end of the study. Here, we provide valid and efficient statistical methods for estimating potentially waning VE against SARS-CoV-2 infection with blood or nasal samples under time-varying community transmission, staggered enrollment, and blinded or unblinded crossover. We demonstrate the usefulness of the proposed methods through numerical studies mimicking the BNT162b2 phase 3 trial and the Prevent COVID U study. In addition, we assess how crossover and the frequency of diagnostic tests affect the precision of VE estimates.
Search related documents:
Co phrase search for related documents- actual trial and logistic regression: 1
- additional challenge and logistic regression: 1
- log hazard and logistic regression: 1, 2, 3
- log hazard ratio and logistic regression: 1, 2, 3
- log likelihood and logistic regression: 1, 2
- log likelihood and long period: 1, 2
- logistic regression and long period: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
- logistic regression and long time period: 1, 2
Co phrase search for related documents, hyperlinks ordered by date