Selected article for: "separate analysis and virus infection"

Author: Lipsitch, Marc; Kahn, Rebecca
Title: Interpreting vaccine efficacy trial results for infection and transmission
  • Cord-id: su838uzk
  • Document date: 2021_2_28
  • ID: su838uzk
    Snippet: Randomized controlled trials (RCTs) have shown high efficacy of multiple vaccines against SARS-CoV-2 disease (COVID-19), but evidence remains scarce about vaccines’ efficacy against infection with, and ability to transmit, the virus. We describe an approach to estimate these vaccines’ effects on viral positivity, a prevalence measure which under reasonable assumptions forms a lower bound on efficacy against transmission. Specifically, we recommend separate analysis of positive tests triggere
    Document: Randomized controlled trials (RCTs) have shown high efficacy of multiple vaccines against SARS-CoV-2 disease (COVID-19), but evidence remains scarce about vaccines’ efficacy against infection with, and ability to transmit, the virus. We describe an approach to estimate these vaccines’ effects on viral positivity, a prevalence measure which under reasonable assumptions forms a lower bound on efficacy against transmission. Specifically, we recommend separate analysis of positive tests triggered by symptoms (usually the primary outcome) and cross-sectional prevalence of positive tests obtained regardless of symptoms. The odds ratio of carriage for vaccine vs. placebo provides an unbiased estimate of vaccine effectiveness against viral positivity, under certain assumptions, and we show through simulations that likely departures from these assumptions will only modestly bias this estimate. Applying this approach to published data from the RCT of the Moderna vaccine, we estimate that one dose of vaccine reduces the potential for transmission by at least 61%, possibly considerably more. We describe how these approaches can be translated into observational studies of vaccine effectiveness.

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