• Presenter: François Castonguay, PhD. Formerly: PhD student at the University of California, Davis (UC Davis). Currently: Public Health Analytics and Modeling Fellow in the Health Economics and Modeling Unit (HEMU), Division of Preparedness and Emerging Infections (DPEI), National Center for Emerging and Zoonotic Infectious Diseases (NCEZID), Centers for Disease Control and Prevention (CDC).

• DISCLAIMER: This presentation represents work done while I was a graduate student at UC Davis and represents my work and opinions while I was a graduate student. The findings and conclusions in the presentation are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

• Abstract: The COVID-19 Vaccines Global Access (COVAX) is a World Health Organization (WHO) initiative that aims for an equitable access to COVID-19 vaccines. Despite potential heterogeneous infection levels across a country, countries receiving allotments of vaccines may follow WHO’s allocation guidelines and distribute vaccines based on a jurisdiction’s relative population size. Utilizing economic–epidemiological modelling, we benchmark the performance of a population size-based allocation rule by comparing it to an optimal one that minimizes the economic damages and expenditures over time, including a penalty representing the social costs of deviating from the relative population strategy. The relative population rule performs better when the duration of naturally- and vaccine-acquired immunity is short, when there is population mixing, when the supply of vaccine is high, and when there is minimal heterogeneity in demographics. Despite behavioural and epidemiological uncertainty diminishing the performance of the optimal allocation, it generally outperforms the relative population rule.

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