Evaluating vaccine allocation strategies using simulation-assisted causal modelling

TL;DR

This paper introduces a simulation-assisted causal model to evaluate and compare age-dependent COVID-19 vaccine allocation strategies, demonstrating its effectiveness and adaptability for future pandemics.

Contribution

It develops a modular, data-driven model combining infection simulation and causal inference to assess vaccine strategies, including retrospective analysis and future pandemic scenarios.

Findings

Israel's vaccine strategy was highly effective.

Prioritizing elderly reduces severe cases most.

Targeting middle-aged groups reduces infections effectively.

Abstract

Early on during a pandemic, vaccine availability is limited, requiring prioritisation of different population groups. Evaluating vaccine allocation is therefore a crucial element of pandemics response. In the present work, we develop a model to retrospectively evaluate age-dependent counterfactual vaccine allocation strategies against the COVID-19 pandemic. To estimate the effect of allocation on the expected severe-case incidence, we employ a simulation-assisted causal modelling approach which combines a compartmental infection-dynamics simulation, a coarse-grained, data-driven causal model and literature estimates for immunity waning. We compare Israel's implemented vaccine allocation strategy in 2021 to counterfactual strategies such as no prioritisation, prioritisation of younger age groups or a strict risk-ranked approach; we find that Israel's implemented strategy was indeed highly effective. We also study the marginal impact of increasing vaccine uptake for a given age group and find that increasing vaccinations in the elderly is most effective at preventing severe cases, whereas additional vaccinations for middle-aged groups reduce infections most effectively. Due to its modular structure, our model can easily be adapted to study future pandemics. We demonstrate this flexibility by investigating vaccine allocation strategies for a pandemic with characteristics of the Spanish Flu. Our approach thus helps evaluate vaccination strategies under the complex interplay of core epidemic factors, including age-dependent risk profiles, immunity waning, vaccine availability and spreading rates.