Comparing statistical methods for detecting and estimating waning efficacy of rotavirus vaccines in developing countries

• Authors: Michael Haber, Emory University; Jacqueline E Tate, Centers for Disease Control and Prevention, Atlanta; Benjamin Lopman, Emory University; Wenrui Qi, Emory University; Kylie EC Ainslie, Imperial College, London; Umesh D Parashar, Centers for Disease Control and Prevention, Atlanta
• Journal Title: HUMAN VACCINES & IMMUNOTHERAPEUTICS
• Volume: Volume 17, Number 11
• Publisher: TAYLOR & FRANCIS INC | 2021-10-08, Pages 4632-4635
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1080/21645515.2021.1968738
• Subjects: Biology, Biostatistics; Health Sciences, Epidemiology
• Keywords: Science & Technology; Life Sciences & Biomedicine; Biotechnology & Applied Microbiology; Immunology; waning vaccine efficacy; rotavirus vaccine; hazard of infection; Cox regression model; agent-based simulations

Abstract

Introduction: Vaccination has significantly reduced morbidity and mortality resulting from rotavirus infection worldwide. However, rotavirus vaccine efficacy (VE) appears to wane over the first 2 years since vaccination, particularly in developing countries. Statistical methods for detecting VE waning and estimating its rate have been used in a few studies, but comparisons of methods for evaluating VE waning have not yet been performed. In this work we present and compare three methods–Durham’s method, Tian’s method, and time-dependent covariate (TDC) method–based on generalizations of the Cox proportional hazard model. Methods: We developed a new stochastic agent-based simulation model to generate data from a hypothetical rotavirus vaccine trial where the protective efficacy of the vaccine may vary over time. Input parameters to the simulation model were obtained from studies on rotavirus infections in four developing countries. We applied each of the methods to four simulated datasets and compared the type-1 error probabilities and the powers of the resulting statistical tests. We also compared estimated and true values of VE over time. Results: Durham’s method had the highest power of detecting true VE waning of the three methods. This method also provided quite accurate estimates of VE in each period and of the per-period drop in VE. Conclusions: Durham’s method is somewhat more powerful than the other two Cox proportional hazards model-based methods for detecting VE waning and provides more information about the temporal behavior of VE.