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Time-dependent vaccine efficacy estimation quantified by a mathematical model.

Jennifer Loria1,2, Vinicius V L Albani3, Francisco A B Coutinho4

  • 1Instituto de Matemática Pura e Aplicada, Rio de Janeiro, Brazil.

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|May 11, 2023
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Summary
This summary is machine-generated.

The timing of vaccine trials during an outbreak significantly impacts estimated vaccine efficacy (VE). Mathematical modeling shows the difference between trial start and outbreak peak influences VE calculations for vaccines like those against SARS-CoV-2.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Vaccinology

Background:

  • Clinical trials (CT) for vaccines are often initiated before or during an outbreak.
  • The force of infection, a measure of disease transmission intensity, naturally changes over time during an epidemic.
  • Variations in the force of infection during a CT can potentially bias the estimation of vaccine efficacy (VE).

Purpose of the Study:

  • To quantify how the time lag between the start of a CT and the peak of an outbreak affects estimated VE.
  • To test the hypothesis that this time difference is a substantial determinant of observed VE values.
  • To demonstrate a mathematical method for assessing VE under time-varying infection pressure, using a SARS-CoV-2 vaccine as a case study.

Main Methods:

  • Development of a simple mathematical model to simulate disease transmission and vaccine effects.
  • Incorporation of a time-dependent force of infection to represent epidemic dynamics.
  • Calculation of estimated VE under different scenarios of CT initiation relative to the outbreak peak.
  • Application of the model to estimate VE for a vaccine targeting SARS-CoV-2.

Main Results:

  • The time difference between CT initiation and outbreak peak significantly influences the calculated VE.
  • Scenarios where CTs begin closer to the outbreak peak may yield different VE estimates compared to those starting earlier.
  • The mathematical model provides a framework to understand and potentially adjust for this timing-induced bias in VE.
  • Initial estimations for a SARS-CoV-2 vaccine highlight the practical implications of this phenomenon.

Conclusions:

  • The timing of vaccine clinical trials relative to epidemic peaks is a critical factor in accurately estimating vaccine efficacy.
  • Mathematical modeling offers a valuable tool to assess the impact of time-varying infection forces on VE.
  • Understanding this temporal dynamic is essential for robust vaccine evaluation, particularly for novel pathogens like SARS-CoV-2.