Assessing Inequities in COVID-19 Vaccine Roll-Out Strategy Programs: A Cross-Country Study Using a Machine Learning Approach

23 Pages Posted: 3 Sep 2021

See all articles by Merhdad Kazemi

Merhdad Kazemi

York University

Nicola Luigi Bragazzi

University of Parma

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC); University of Toronto

Date Written: August 31, 2021

Abstract

Background: After the start of the COVID-19 pandemic and its spread across the world, countries have adopted containment measures to stop its transmission, limit fatalities and relieve hospitals from strain and overwhelming imposed by the virus. Many countries implemented social distancing and lockdown strategies that negatively impacted their economies and the psychological wellbeing of their citizens, even though they contributed to saving lives. Recently approved and available, COVID-19 vaccines can provide a really viable and sustainable option for controlling the pandemic. However, their uptake represents a global challenge, due to vaccine hesitancy logistic-organizational hurdles that have made its distribution stagnant in several developed countries despite several appeal by the media, policy- and decision-makers, and community leaders. Vaccine distribution is a concern also in developing countries, where there is scarcity of doses.

Objective: To set up a metric to assess vaccination uptake and identify national socio-economic factors influencing this indicator.

Methods: We conducted a cross-country study. We first estimated the vaccination uptake rate across countries by fitting a logistic model to reported daily case numbers. Using the uptake rate, we estimated the vaccine roll-out index. Next, we used Random Forest, an “off-the-shelf” machine learning algorithm, to study the association between vaccination uptake rate and socio-economic factors.

Results: We found that the mean vaccine roll-out index is 0.016 (standard deviation 0.016), with a range between 0.0001 (Haiti) and 0.0829 (Mongolia). The top four factors associated with vaccine roll-out index are the median per capita income, human development index, percentage of individuals who have used the internet in the last three months, and health expenditure per capita.

Conclusion: The still ongoing COVID-19 pandemic has shed light on the chronic inequality in global health systems. The disparity in vaccine adoption across low- and high-income countries is a global public health challenge. We must pave the way for a universal access to vaccines and other approved treatments, regardless of demographic structures and underlying health conditions. Income disparity remains, instead, an important cause of vaccine inequity, and the tendency toward "vaccine nationalism" and “vaccine apartheid” restricts the functioning of the global vaccine allocation framework and, thus, the ending of the pandemic. Stronger mechanisms are needed to foster countries' political willingness to promote vaccine and drug access equity in a globalized society, where future pandemics and other global health rises can be anticipated.

Note: Funding: This research is funded by NSERC Undergraduate Student Research Award and Canada's International Development Research Centre (IDRC) (Grant No. 109559-001)

Declaration of Interests: None to declare.

Suggested Citation

Kazemi, Merhdad and Bragazzi, Nicola Luigi and Kong, Jude Dzevela, Assessing Inequities in COVID-19 Vaccine Roll-Out Strategy Programs: A Cross-Country Study Using a Machine Learning Approach (August 31, 2021). Available at SSRN: https://ssrn.com/abstract=3914835 or http://dx.doi.org/10.2139/ssrn.3914835

Merhdad Kazemi

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Jude Dzevela Kong

Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC) ( email )

University of Toronto
Toronto, Ontario M5R 0A3
Canada

University of Toronto ( email )

105 St George Street
Toronto, Ontario M5S 3G8
Canada

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