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Updated: Aug 6, 2025

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
The effect of mixed vaccination rollout strategy: A modelling study
Nico Stollenwerk1,2, Carlo Delfin S Estadilla1,3, Javier Mar4,5
1BCAM-Basque Center for Applied Mathematics, Bilbao, Basque Country, Spain.
Abstract:
Vaccines have measurable efficacy obtained first from vaccine trials. However, vaccine efficacy (VE) is not a static measure and long-term population studies are needed to evaluate its performance and impact. COVID-19 vaccines have been developed in record time and the currently licensed vaccines are extremely effective against severe disease with higher VE after the full immunization schedule. To assess the impact of the initial phase of the COVID-19 vaccination rollout programmes, we used an extended Susceptible - Hospitalized - Asymptomatic/mild - Recovered (SHAR) model. Vaccination models were proposed to evaluate different vaccine types: vaccine type 1 which protects against severe disease only but fails to block disease transmission, and vaccine type 2 which protects against both severe disease and infection. VE was assumed as reported by the vaccine trials incorporating the difference in efficacy between one and two doses of vaccine administration. We described the performance of the vaccine in reducing hospitalizations during a momentary scenario in the Basque Country, Spain. With a population in a mixed vaccination setting, our results have shown that reductions in hospitalized COVID-19 cases were observed five months after the vaccination rollout started, from May to June 2021. Specifically in June, a good agreement between modelling simulation and empirical data was well pronounced.
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