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Defining and Estimating Outcomes Directly Averted by a Vaccination Program when Rollout Occurs Over Time.

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This study clarifies how to accurately measure vaccine effectiveness, defining "directly averted" deaths and showing it’s a lower bound for total deaths prevented. It also identifies biases in common estimation methods for vaccine impact.

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cumulative incidence differencedirect impactoverall impactvaccine-averted outcomes

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Estimating deaths averted by COVID-19 vaccination is crucial.
  • Previous studies often focused on "directly averted" deaths, potentially underestimating overall impact.
  • Accurate measurement of vaccine effectiveness is vital for public health policy.

Purpose of the Study:

  • To define and quantify outcomes "directly averted" by vaccination, considering vaccinated individuals only.
  • To develop an unbiased estimator for this causal estimand in randomized controlled trials (RCTs).
  • To analyze the bias of existing estimators, like the "hazard difference" method.

Main Methods:

  • Causal inference framework to define "directly averted" outcomes.
  • Development of an unbiased estimator for a one-stage RCT.
  • Simulation studies to compare the proposed estimator with the "hazard difference" estimator.
  • Exploration of estimands and estimators for "avertible outcomes".

Main Results:

  • The "directly averted" outcome estimand serves as a lower bound for total averted outcomes when indirect effects are non-negative.
  • The "hazard difference" estimator is biased in RCTs if vaccination has a non-null effect due to "depletion of susceptibles".
  • Bias in the "hazard difference" estimator is small for averted deaths with low infection-fatality rates but can be large for averted infections with high reproduction numbers.

Conclusions:

  • The proposed causal estimand provides a more accurate measure of vaccination impact on vaccinated individuals.
  • Awareness of "depletion of susceptibles" is necessary for unbiased estimation of vaccine effectiveness.
  • Further research is needed to apply these causal methods in observational studies.