Analyzing Country-Level Vaccination Rates and Determinants of Practical Capacity to Administer COVID-19 Vaccines
Sharika J. Hegde, Max T.M. Ng, Marcos Rios, Hani S. Mahmassani, Ying, Chen, Karen Smilowitz

TL;DR
This paper analyzes country-level COVID-19 vaccination rates using a queuing model and machine learning to identify key determinants like infrastructure, collaboration, and demographics affecting vaccination capacity worldwide.
Contribution
It introduces a novel queuing framework to quantify practical vaccination capacity and combines regression and interpretable machine learning to identify critical factors influencing vaccination rates.
Findings
Participation in multi-governmental collaborations improves vaccination capacity.
Enhanced transportation infrastructure correlates with higher vaccination rates.
Low-income countries benefit from investments in healthcare infrastructure and accessibility.
Abstract
The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Global vaccination levels, however, remain a key concern in preventing the emergence of new strains and minimizing the impact of the pandemic's disruption of daily life. In this paper, country-level vaccination rates are analyzed through a queuing framework to extract service rates that represent the practical capacity of a country to administer vaccines. These rates are further characterized through regression and interpretable machine learning methods with country-level demographic, governmental, and socio-economic variates. Model results show that participation in multi-governmental collaborations such as COVAX may improve the ability to vaccinate. Similarly, improved transportation and accessibility variates such as roads per area for…
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Taxonomy
TopicsVaccine Coverage and Hesitancy · COVID-19 epidemiological studies · Global Maternal and Child Health
Methodstravel james
