Optimal control of the spatial allocation of COVID-19 vaccines: Italy as a case study

Author:

Lemaitre Joseph ChadiORCID,Pasetto DamianoORCID,Zanon MarioORCID,Bertuzzo EnricoORCID,Mari LorenzoORCID,Miccoli StefanoORCID,Casagrandi RenatoORCID,Gatto MarinoORCID,Rinaldo Andrea

Abstract

While campaigns of vaccination against SARS-CoV-2 are underway across the world, communities face the challenge of a fair and effective distribution of a limited supply of doses. Current vaccine allocation strategies are based on criteria such as age or risk. In the light of strong spatial heterogeneities in disease history and transmission, we explore spatial allocation strategies as a complement to existing approaches. Given the practical constraints and complex epidemiological dynamics, designing effective vaccination strategies at a country scale is an intricate task. We propose a novel optimal control framework to derive the best possible vaccine allocation for given disease transmission projections and constraints on vaccine supply and distribution logistics. As a proof-of-concept, we couple our framework with an existing spatially explicit compartmental COVID-19 model tailored to the Italian geographic and epidemiological context. We optimize the vaccine allocation on scenarios of unfolding disease transmission across the 107 provinces of Italy, from January to April 2021. For each scenario, the optimal solution significantly outperforms alternative strategies that prioritize provinces based on incidence, population distribution, or prevalence of susceptibles. Our results suggest that the complex interplay between the mobility network and the spatial heterogeneities implies highly non-trivial prioritization strategies for effective vaccination campaigns. Our work demonstrates the potential of optimal control for complex and heterogeneous epidemiological landscapes at country, and possibly global, scales.

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Fondazione Cassa di Risparmio di Padova e Rovigo

Special Integrative Fund for Research

Università Ca’ Foscari di Venezia

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics

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