Impact of vaccination against severe COVID-19 in the French population aged 50 years and above: a retrospective population-based study.

BACKGROUND: Given the widespread implementation of COVID-19 vaccination to mitigate the pandemic from the end of 2020, it is important to retrospectively evaluate its impact, in particular by quantifying the number of severe outcomes prevented through vaccination. METHODS: We estimated the number of hospitalizations, intensive care unit (ICU) admissions and deaths directly averted by vaccination in France, in people aged ≥ 50 years, from December 2020 to March 2022, based on (1) the number of observed events, (2) vaccination coverage, and (3) vaccine effectiveness. We accounted for the effect of primary vaccination and the first booster dose, the circulating variants, the age groups, and the waning of vaccine-induced protection over time. RESULTS: An estimated 480,150 (95% CI: 260,072-582,516) hospitalizations, 132,156 (50,409-157,767) ICU admissions and 125,376 (53,792-152,037) deaths were directly averted by vaccination in people aged ≥ 50 years, which corresponds to a reduction of 63.2% (48.2-67.6), 68.7% (45.6-72.4) and 62.7% (41.9-67.1) respectively, compared to what would have been expected without vaccination over the study period. An estimated 5852 (2285-6853) deaths were directly averted among the 50-59 years old, 16,837 (6568-19,473) among the 60-69 years old, 32,136 (13,651-36,758) among the 70-79 years old and 70,551 (31,288-88,953) among the ≥ 80 years old. CONCLUSIONS: The vaccination campaign in France considerably reduced COVID-19 morbidity and mortality, as well as stress on the healthcare system.

Application of Machine Learning Prediction of Individual SARS-CoV-2 Vaccination and Infection Status to the French Serosurveillance Survey From March 2020 to 2022: Cross-Sectional Study.

BACKGROUND: The seroprevalence of SARS-CoV-2 infection in the French population was estimated with a representative, repeated cross-sectional survey based on residual sera from routine blood testing. These data contained no information on infection or vaccination status, thus limiting the ability to detail changes observed in the immunity level of the population over time. OBJECTIVE: Our aim is to predict the infected or vaccinated status of individuals in the French serosurveillance survey based only on the results of serological assays. Reference data on longitudinal serological profiles of seronegative, infected, and vaccinated individuals from another French cohort were used to build the predictive model. METHODS: A model of individual vaccination or infection status with respect to SARS-CoV-2 obtained from a machine learning procedure was proposed based on 3 complementary serological assays. This model was applied to the French nationwide serosurveillance survey from March 2020 to March 2022 to estimate the proportions of the population that were negative, infected, vaccinated, or infected and vaccinated. RESULTS: From February 2021 to March 2022, the estimated percentage of infected and unvaccinated individuals in France increased from 7.5% to 16.8%. During this period, the estimated percentage increased from 3.6% to 45.2% for vaccinated and uninfected individuals and from 2.1% to 29.1% for vaccinated and infected individuals. The decrease in the seronegative population can be largely attributed to vaccination. CONCLUSIONS: Combining results from the serosurveillance survey with more complete data from another longitudinal cohort completes the information retrieved from serosurveillance while keeping its protocol simple and easy to implement.