Work

Development and validation of a clinical prediction tool for non-receipt of updated COVID-19 vaccines

Year: 2025
Type: article
Study design: Observational Study
Abstract: Vaccination with updated COVID-19 vaccines is important to maintain protection against circulating SARS-CoV-2 variants. We developed and validated a prediction model for non-receipt of updated COVID-19 vaccines at Kaiser Permanente Southern California. Of 3,287,287 adults, 20.2 % received 2023–2024 COVID-19 vaccine. We assessed the association of 15 variables available in electronic health records with non-receipt of 2023–2024 updated COVID-19 vaccine. The cohort was split into development and validation samples. Performance of the 15-variable model in the development sample was moderate, with a scaled Brier score of 35.6 %, R 2 of 29.3 %, C-statistic of 0.882, discrimination slope of 0.354, and calibration slope of 1; performance was similar for the validation sample and simplified 6-variable and 2-variable models. The strongest predictors were prior non-receipt of bivalent COVID-19 vaccine or influenza vaccine. These results suggest that a simple model using variables available to healthcare providers can be optimized to guide intervention strategies for updated COVID-19 vaccines.
Source: Vaccine
Language: English
Subfield: Health
Open Access status: hybrid
Estimated APC paid: $3,620
OpenAlex ID: W4409369926
FWCI: 2.233
Cites: 19
Cited by: 2
Related to: 10