Predictive modelling of the effectiveness of vaccines against COVID-19 in Bogotá: Methodological innovation involving different variants and computational optimisation efficiency

Journal article

The uncertainty associated with the future of viruses such as SARS-CoV-2 poses a challenge to public health officials because of its implications for welfare, economics and population health. In this document, we develop an age-stratified epidemiological-mathematical model to predict various health outcomes, considering the effectiveness of COVID-19 vaccines. The analytical model proposed and developed for this research is based on the approach constructed by the COVID-19 International Modelling Consortium. Following this approach, this paper innovates at the frontier of knowledge by including the various variants of SARS-CoV-2 in the Consortium model. Furthermore, for the first time in international literature, a complete compilation of the formal mathematical development of this entire quantitative model is presented. Our model accurately fits the observed historical data of new infections, cumulative mortality, symptomatic infections, hospitalisations, and Intensive Care Units admissions, capturing the waves of contagion that have occurred in Bogotá, Colombia. In turn, the prognosis obtained indicates a considerable decrease in the incidence and lethality caused by SARS-CoV-2 under current conditions, thus evidencing the effectiveness of vaccines against infection, hospitalisation, and death. This model enables the evaluation of different scenarios in response to changes in the dynamics of this infectious disease, providing information to policymakers for real-world evidence-based decision-making.

Authors: Espinosa, O; White, L; Bejarano, V; Aguas, R; Rincón, D

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Elsevier
• Journal: Heliyon
• Volume: 10
• Issue: 21
• Pages: e39725
• Publication date: 2024-10-23
• DOI: 10.1016/j.heliyon.2024.e39725
• EISSN: 2405-8440
• ISSN: 2405-8440
• Pmid: 39559218
• Language: English
• Keywords: Real-world Evidence; Vaccines; Covid-19; Predictive Modelling; Mathematical Epidemiology; Public Health; Effectiveness