Issues in COVID-19 research and statistical analyses (Part XVVI) January 5, 2022
With the ongoing rise in COVID-19 cases due to the Omicron variant of Sars-Cov-2, we searched for some actual studies on the change in vaccine efficacy due to Omicron exposure. In one pre-print article, Buchan et al studied 3,442 Omicron-positive cases, 9,201 Delta-positive cases, and 471,545 test-negative controls. They found that after 2 doses of COVID-19 vaccine, vaccine effectiveness against Delta infection declined steadily over time but recovered to 93% (95%CI, 92-94%) ≥7 days after receiving an mRNA vaccine for the third dose. In contrast, receipt of 2 doses of COVID-19 vaccines was not protective against Omicron. Vaccine effectiveness against Omicron was 37% (95%CI, 19-50%) ≥7 days after receiving an mRNA vaccine for the third dose, although with a wider confidence interval. Their results are from a multivariate logistic regression model. In an article published in New England Journal of Medicine, using data from Discovery Health, a South African managed care organization, Collie et al estimated the vaccine effectiveness of two doses of the BNT162b2 vaccine (i.e., full vaccination) against hospitalization for Covid-19 caused by the omicron variant by analyzing data sets that included the results of polymerasechain-reaction (PCR) assays and other admission data/medical records. They used a test-negative design and data-exclusion rules to obtain estimates of vaccine effectiveness. They described test negative case control studies in their supplementary appendix as having been deemed powerful to assess vaccinations for a range of diseases. They describe that the design specifies cases as individuals who tested positive with COVID19 and controls with a negative test. The design of the study tries to overcome selection bias of healthcare seeking behavior through selection of individuals who have both tested. At they stated, their core assumption of the test negative design is predicated on the assumption that the intervention (vaccine) has no effect on other diseases with similar symptoms. Therefore, using the test negative strategy, they used the following formula:1−odds ratio for Covid-19 hospitalization in the vaccinated population, where the odds ratio was calculated with the use of logistic regression after adjustment for confounders of age, sex, previous Covid-19 infection, surveillance week, geographic location, and the number of CDC risk factors. In this analysis, Covid-19 hospitalization was a dependent variable, and vaccination status was included as an independent variable in the model. During the proxy omicron period, they found a vaccine effectiveness of 70% (95% confidence interval [CI], 62 to