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[Preprint]. 2022 Nov 18:2022.11.18.22282514.
doi: 10.1101/2022.11.18.22282514.

Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study

Nicolò Gozzi  1 , Matteo Chinazzi  2 , Natalie E Dean  3 , Ira M Longini Jr  4 , M Elizabeth Halloran  5   6 , Nicola Perra  7   2 , Alessandro Vespignani  2
Affiliations

Estimating the impact of COVID-19 vaccine allocation inequities: a modeling study

Nicolò Gozzi et al. medRxiv. .

Update in

Abstract

Access to COVID-19 vaccines on the global scale has been drastically impacted by structural socio-economic inequities. Here, we develop a data-driven, age-stratified epidemic model to evaluate the effects of COVID-19 vaccine inequities in twenty lower middle and low income countries (LMIC) sampled from all WHO regions. We focus on the first critical months of vaccine distribution and administration, exploring counterfactual scenarios where we assume the same per capita daily vaccination rate reported in selected high income countries. We estimate that, in this high vaccine availability scenario, more than 50% of deaths (min-max range: [56% - 99%]) that occurred in the analyzed countries could have been averted. We further consider a scenario where LMIC had similarly early access to vaccine doses as high income countries; even without increasing the number of doses, we estimate an important fraction of deaths (min-max range: [7% - 73%]) could have been averted. In the absence of equitable allocation, the model suggests that considerable additional non-pharmaceutical interventions would have been required to offset the lack of vaccines (min-max range: [15% - 75%]). Overall, our results quantify the negative impacts of vaccines inequities and call for amplified global efforts to provide better access to vaccine programs in low and lower middle income countries.

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Figures

Figure 1:
Figure 1:. Vaccine inequities.
A) Total number of doses administered per 100 people in different income groups as of October 1, 2021. B) Scatter plot of % of a country’s population who is fully vaccinated versus their Human Development Index (HDI). The color of dots indicates the country’s income group while size is proportional to the cost of vaccinating 40% of the population as a percentage of current healthcare spending. C) Density plot of the date of first COVID-19 vaccination across different country income groups. D) Evolution in the share of doses administered monthly across country income groups (left hand), and evolution of monthly booster doses share (right hand).
Figure 2:
Figure 2:. Counterfactual scenarios - Deaths averted if countries had US-equivalent vaccination rate.
A) Countries modeled, their WHO region, and the percentage of fully vaccinated individuals there as of October 1, 2021. B) Deaths averted expressed as a percentage with respect to the actual vaccination rollout (median and interquartile range), assuming per capita vaccination rates equivalent to the United States. The median absolute number of deaths averted is reported above the inter-quartile range.
Figure 3:
Figure 3:. Counterfactual scenarios - Deaths averted if countries had US-equivalent vaccination start date.
Deaths averted expressed as a percentage with respect to the actual vaccination rollout (median and interquartile range), assuming United States start date of December 14, 2020. The median absolute number of deaths averted is reported above the inter-quartile range.
Figure 4:
Figure 4:. The role of NPIs.
A) Additional NPIs, put in place for four months, needed to match the deaths averted that the vaccination rate of the US would have allowed. B) For three countries we show the contour plots of the percentage of deaths averted (median %) with stricter and/or longer NPIs, relative to the actual vaccination baseline. Percentage of deaths averted achieved by a US-equivalent vaccination rate is plotted as reference (red dashed line).
See this image and copyright information in PMC

References

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