A bi-objective optimization model to plan vaccination campaigns

TL;DR

This paper introduces a bi-objective optimization model for planning COVID-19 vaccination campaigns, balancing effectiveness and costs, and emphasizing the strategic use of temporary vaccination centers to reach vulnerable groups.

Contribution

It presents a novel bi-objective model incorporating COVID-19 specific factors and resource management strategies for vaccination campaign planning.

Findings

The model effectively balances vaccination coverage and costs.

Temporary centers improve reach to vulnerable populations.

The approach offers multiple plans based on prioritization.

Abstract

Vaccination campaigns have saved thousands of lives, reaching the farthest places in the world. These campaigns have required substantial investments and accurate coordination between several actors within the vaccine supply chain. Despite these successful strategies, the outbreak of COVID-19 has altered the objectives and rules of undertaking vaccine campaigns. Then, it is essential to consider two new facts in planning vaccination campaigns. First, some groups of infected people by the virus are more vulnerable to severe illness. Second, the virus is exceptionally contagious; sometimes, no symptoms are apparent. Accordingly, we propose a bi-objective optimization model that allows healthcare decision-makers to design effective vaccination campaigns by considering these COVID-19 characteristics and controlling the associated costs. Careful utilization of temporary and traditional vaccination centers is crucial to creating a more robust strategy. Located in suitable places, temporary centers help increase the probability of reaching groups difficult to be vaccinated while simultaneously avoiding crowd congestion and reducing the risk of spreading infections in dispensing vaccination centers. Experiments were conducted using data from an area in Santiago, Chile. The results show the model allows us to manage the resources by providing a variety of vaccination plans according to the prioritization level of each objective.