Vaccine efficacy at a point in time.

Area of Science:

• Epidemiology
• Vaccinology
• Biostatistics

Background:

• Traditional vaccine trials focus on clinical disease, not infection dynamics.
• Assessing vaccine effects on infection requires frequent sampling, which is often impractical.
• Existing methods may not accurately capture vaccine impact on infection transmission.

Purpose of the Study:

• To evaluate proxies for vaccine effects on transmission at a single time point.
• To introduce and define vaccine efficacy on prevalent infection (VEPI) and prevalent viral load (VEPVL).
• To demonstrate how these parameters can be estimated from cross-sectional or longitudinal sampling.

Main Methods:

• Developed a proportional hazards model accounting for waning vaccine efficacy, infection duration, and viral load.
• Estimated VEPI and VEPVL using regression models with repeated cross-sectional or frequent longitudinal sampling.
• Validated methods through simulation and analysis of a Phase III vaccine trial using PCR for subclinical infection detection.

Main Results:

• Prevalent vaccine efficacy measures (VEPI, VEPVL) can be estimated from point-in-time sampling.
• These proxies naturally incorporate transmission potential related to infection duration and viral load.
• The proposed methods are applicable to real-world trial data, including subclinical infections.

Conclusions:

• VEPI and VEPVL offer practical alternatives for assessing vaccine effects on infection and transmission.
• These methods enhance the utility of cross-sectional sampling in vaccine efficacy studies.
• The findings support better evaluation of vaccine impact beyond clinical endpoints.