Version 1
: Received: 14 September 2024 / Approved: 16 September 2024 / Online: 16 September 2024 (14:08:44 CEST)
How to cite:
Garcia-Carretero, R.; Ordoñez-Garcia, M.; Vazquez-Gomez, O.; Belen Rodriguez-Maya, B.; Gil-Prieto, R.; Gil-de-Miguel, A. Impact and Effectiveness of COVID-19 Vaccines Using Machine Learning to Analyze a Time Series: A Population-Based Study. Preprints2024, 2024091247. https://doi.org/10.20944/preprints202409.1247.v1
Garcia-Carretero, R.; Ordoñez-Garcia, M.; Vazquez-Gomez, O.; Belen Rodriguez-Maya, B.; Gil-Prieto, R.; Gil-de-Miguel, A. Impact and Effectiveness of COVID-19 Vaccines Using Machine Learning to Analyze a Time Series: A Population-Based Study. Preprints 2024, 2024091247. https://doi.org/10.20944/preprints202409.1247.v1
Garcia-Carretero, R.; Ordoñez-Garcia, M.; Vazquez-Gomez, O.; Belen Rodriguez-Maya, B.; Gil-Prieto, R.; Gil-de-Miguel, A. Impact and Effectiveness of COVID-19 Vaccines Using Machine Learning to Analyze a Time Series: A Population-Based Study. Preprints2024, 2024091247. https://doi.org/10.20944/preprints202409.1247.v1
APA Style
Garcia-Carretero, R., Ordoñez-Garcia, M., Vazquez-Gomez, O., Belen Rodriguez-Maya, B., Gil-Prieto, R., & Gil-de-Miguel, A. (2024). Impact and Effectiveness of COVID-19 Vaccines Using Machine Learning to Analyze a Time Series: A Population-Based Study. Preprints. https://doi.org/10.20944/preprints202409.1247.v1
Chicago/Turabian Style
Garcia-Carretero, R., Ruth Gil-Prieto and Angel Gil-de-Miguel. 2024 "Impact and Effectiveness of COVID-19 Vaccines Using Machine Learning to Analyze a Time Series: A Population-Based Study" Preprints. https://doi.org/10.20944/preprints202409.1247.v1
Abstract
Background: Although confirmed cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been declining since late 2020 due to general vaccination, little research has been done regarding the impact of vaccines against SARS-CoV-2 in Spain in terms of hospitalizations and deaths. Objective: Our aim was to identify the reduction in severity and mortality of coronavirus disease 2019 (COVID-19) at a nationwide level due to vaccination. Methods: We designed a retrospective, population-based study to define waves of infection and to describe the characteristics of the hospitalized population. We also studied the rollout of vaccination and its relationship with the decline in hospitalizations and deaths. Finally, we developed two mathematical models to estimate non-vaccination scenarios using machine learning modeling (with the ElasticNet and RandomForest algorithms). The vaccination and non-vaccination scenarios were eventually compared to estimate the number of averted hospitalizations and deaths. Results: In total, 498,789 patients were included, with a global mortality of 14.3%. We identified six waves or epidemic outbreaks during the observed period. We established a strong relationship between the beginning of vaccination and the decline in both hospitalizations and deaths due to COVID-19 in all age groups. We also estimated that vaccination prevented 170,959 hospitalizations (CI 95% 77,844–264,075) and 24,546 deaths (CI 95% 2,548–46,543) in Spain between March 2021 and December 2021. We estimated a global reduction of 9.19% in total deaths during the first year of COVID-19 vaccination. Conclusions: Demographic and clinical profiles changed over the first months of the pandemic. Patients over 80 years old and other age groups obtained clinical benefit from early vaccination. The severity of COVID-19, in terms of hospitalizations and deaths, decreased due to vaccination.
Public Health and Healthcare, Health Policy and Services
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
