Objectives: Year-to-year variation in respiratory viruses may result in lower attack rates than expected. We aimed to illustrate the impact of year-to-year variation in attack rates on the likelihood of demonstrating vaccine efficacy (VE).
Study design and setting: We considered an individually randomized maternal vaccine trial against respiratory syncytial virus (RSV)-associated hospitalizations. For 10 RSV-associated hospitalizations per 1,000 infants, sample size to have 80% power for true VE of 50% and 70% was 9,846 and 4,424 participants. We reported power to show VE for varying attack rates, selected to reflect realistic year-to-year variation using observational studies. Eight scenarios including varying number of countries and seasons were developed to assess the influence of these trial parameters.
Results: Including up to three seasons decreased the width of the interquartile range for power. Including more seasons concentrated statistical power closer to 80%. Least powered trials had higher statistical power with more seasons. In all scenarios, at least half of the trials had <80% power. For three-season trials, increasing the sample size by 10% reduced the percentage of underpowered trials to less than one-quarter of trials.
Conclusion: Year-to-year variation in RSV attack rates should be accounted for during trial design. Mitigation strategies include recruiting over more seasons, or adaptive trial designs.
Keywords: Attack rate; Incidence; RSV; Sample size; Seasonality; Statistical power.
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