2021/03/03 by David Benkeser, Iván Díaz, Benkeser, David +3
Mathematics · Medicine · Social Sciences · #Advanced Causal Inference Techniques #FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #SARS-CoV-2 and COVID-19 Research #Statistics Theory (math.ST) #Vaccine Coverage and Hesitancy
paper · pdf · doi:10.48550/arxiv.2103.02643
openalex publication_date 2021/03/03 · openalex created_date 2021/03/15 · openalex updated_date 2026/07/28
Combating the SARS-CoV2 pandemic will require the fast development of effective preventive vaccines. Regulatory agencies may open accelerated approval pathways for vaccines if an immunological marker can be established as a mediator of a vaccine's protection. A rich source of information for identifying such correlates are large-scale efficacy trials of COVID-19 vaccines, where immune responses are measured subject to a case-cohort sampling design. We propose two approaches to estimation of mediation parameters in the context of case-cohort sampling designs. We establish the theoretical large-sample efficiency of our proposed estimators and evaluate them in a realistic simulation to understand whether they can be employed in the analysis of COVID-19 vaccine efficacy trials.