Optimal spatial evaluation of a pro rata vaccine distribution rule for COVID-19

Abstract

The COVID-19 Vaccines Global Access (COVAX) is a World Health Organization (WHO) initiative that aims for an equitable access of 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 jurisdictions’ relative population size. Utilizing economic—epidemiological modeling, we benchmark the performance of this pro rata 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 pro rata strategy. The pro rata 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 behavioral and epidemiological uncertainty diminishing the performance of the optimal allocation, it generally outperforms the pro rata vaccine distribution rule.

Model-informed health and socio-economic benefits of enhancing global equity and access to Covid-19 vaccines

“…Giving more vaccines to LMI countries, we would have experienced fewer cases and death globally ( cases globally), but herd immunity would have not been achieved in HI countries ( cases in MLI nations but in HI nations). This is in agreement with the results presented in 26 , 27 . Interestingly, the number of deaths in the GEA scenario with the current access to vaccines is fully comparable with the one computed in the analysis by Moore et al 26 , even if the model and its calibration are different.…”

“…We first analyzed how a redistribution of the current amount of vaccines would affect the pandemic evolution, in line with previous studies 26 , 27 . We found that, independently from the equity in access, the current access to vaccines is insufficient to stop the pandemic.…”

“…Vaccine hesitancy could be considered by adding a class of subjects who do not want to get vaccinated and by modeling the related socio-cultural dynamics 62 , 63 . Finally, from the viewpoint of the control policy, also the vaccination rates could be adjusted in time to optimally govern the pandemic 27 in accordance with prescribed targets. These new approaches address the issue that controlling outbreaks by herd immunity may be an elusive goal with Covid-19, because protections could last briefly (especially in older people), or if escape mutants emerge.…”

“…This modeling approach is reasonably predictive for infectious diseases that are transmitted among humans 25 . A few works specifically investigated the effect of different Covid-19 vaccine allocation strategies via a modeling approach 26 , 27 . In particular, Moore et al 26 analyzes the effect of equally redistributing the vaccine doses administrated during the year 2021, while 27 studies the advantage of using an infection-dependent allocation strategy of the vaccines with respect to a constant one.…”