PROJECT SUMMARY/ABSTRACT
Despite the success of the unprecedented COVID-19 vaccine rollout in the U.S., vaccine hesitancy is evident,
partly due to safety concerns about severe adverse events (SAEs) surrounding the novel technology of mRNA
COVID-19 vaccines and reports of blood clots following receipt of the Janssen COVID-19 vaccine. While
rigorous safety monitoring may help support COVID-19 vaccination, it is methodologically challenging to
thoroughly evaluate the safety of the two-dose mRNA COVID-19 vaccines and the one-dose Janssen COVID-
19 vaccine. Existing approaches can produce false positive and false negative signals when 1) risk windows
after vaccination are incorrectly specified, 2) a constant risk of SAEs during the risk window is wrongly
assumed, 3) factors that may influence receipt of the second dose of mRNA COVID-19 vaccines are not
accounted for, and 4) the nature of the risk of SAEs during potential overlapping risk windows of the first and
second doses of mRNA COVID-19 vaccines is not assessed.
In response to the FOA, PA-18-873, this proposal addresses the specific objective: “creation/evaluation of
statistical methodologies for analyzing data on vaccine safety, including data available from existing data
sources such as passive reporting systems or healthcare databases.” We propose to develop novel statistical
models to properly measure the risk of new COVID-19 vaccines by allowing the risk level to vary during
unknown risk windows and using a data-driven approach to define these risk windows. We will also create a
new metric for measuring the risk of SAEs considering both the risk level and the length of the risk window,
address the potential overlap of risk windows of two doses, and employ a propensity score model approach to
account for factors that may influence receipt of the second dose of mRNA COVID-19 vaccines. We will
establish these novel approaches to evaluate COVID-19 vaccine safety and will apply them to existing data
from members of Kaiser Permanente Southern California, a large, racially, and socio-economically diverse
population.
Through this research, we will detect SAEs of concern, better inform the public and policymakers about the
safety of COVID-19 vaccines, and generate vaccine safety information that may be helpful for clinicians to
deliver appropriate care to those at risk.