Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: an application to the Italian scenario

TL;DR

This paper develops an optimized control framework using an age-structured SIR model to plan COVID-19 vaccination campaigns, aiming to minimize infections, deaths, and hospitalizations efficiently, demonstrated through Italian data.

Contribution

It introduces a novel optimal control approach for multiage vaccination strategies within a detailed COVID-19 model, tailored to real-world data and specific health goals.

Findings

The framework effectively identifies optimal vaccination priorities.

Numerical simulations align with Italian COVID-19 data.

The approach reduces infections and hospitalizations efficiently.

Abstract

In the context of SARS-CoV-2 pandemic, mathematical modelling has played a fundamental role for making forecasts, simulating scenarios and evaluating the impact of preventive political, social and pharmaceutical measures. Optimal control theory can be a useful tool based on solid mathematical bases to plan the vaccination campaign in the direction of eradicating the pandemic as fast as possible. The aim of this work is to explore the optimal prioritisation order for planning vaccination campaigns able to achieve specific goals, as the reduction of the amount of infected, deceased and hospitalized in a fixed time frame, among age classes. For this purpose, we introduce an age stratified SIR-like epidemic compartmental model settled in an abstract framework for modelling two-doses vaccination campaigns and conceived with the description of COVID19 disease. Overall, we formalize an optimal control framework adopting the model as state problem by acting on the administrations of vaccine-doses. An extensive campaign of numerical tests, featured in the Italian scenario and calibrated on available data from Dipartimento di Protezione Civile Italiana, shows that the presented framework can be a valuable tool to support the planning of vaccination campaigns minimizing specific goals.