Vulnerability Predictors of Post-Vaccine SARS-CoV-2 Infection and Disease-Empirical Evidence from a Large Population-Based Italian Platform

Autor: Giovanni Corrao, Matteo Franchi, Danilo Cereda, Francesco Bortolan, Olivia Leoni, Catia Rosanna Borriello, Petra Giulia Della Valle, Marcello Tirani, Giovanni Pavesi, Antonio Barone, Michele Ercolanoni, Jose Jara, Massimo Galli, Guido Bertolaso
Přispěvatelé: Corrao, G, Franchi, M, Cereda, D, Bortolan, F, Leoni, O, Borriello, C, Della Valle, P, Tirani, M, Pavesi, G, Barone, A, Ercolanoni, M, Jara, J, Galli, M, Bertolaso, G
Rok vydání: 2022
Předmět:
Zdroj: Vaccines; Volume 10; Issue 6; Pages: 845
ISSN: 2076-393X
Popis: We aimed to identify individual features associated with increased risk of post-vaccine SARS-CoV-2 infection and severe COVID-19 illness. We performed a nested case–control study based on 5,350,295 citizens from Lombardy, Italy, aged ≥ 12 years who received a complete anti-COVID-19 vaccination from 17 January 2021 to 31 July 2021, and followed from 14 days after vaccine completion to 11 November 2021. Overall, 17,996 infections and 3023 severe illness cases occurred. For each case, controls were 1:1 (infection cases) or 1:10 (severe illness cases) matched for municipality of residence and date of vaccination completion. The association between selected predictors (sex, age, previous occurrence of SARS-CoV-2 infection, type of vaccine received, number of previous contacts with the Regional Health Service (RHS), and the presence of 59 diseases) and outcomes was assessed by using multivariable conditional logistic regression models. Sex, age, previous SARS-CoV-2 infection, type of vaccine and number of contacts with the RHS were associated with the risk of infection and severe illness. Moreover, higher odds of infection and severe illness were significantly associated with 14 and 34 diseases, respectively, among those investigated. These results can be helpful to clinicians and policy makers for prioritizing interventions.
Databáze: OpenAIRE