Optimal Allocation of Covid-19 Vaccines using Mathematical Modeling

Date

1-2023

Abstract

The COVID-19 pandemic that emerged in 2019 is regarded as one of the most disruptive events of the century impacting the global economic, health, agricultural, educational, and financial systems. To combat this disease, vaccines against COVID-19 have been developed, and have been in limited supply when these first became available in late 2020. Although COVID-19 vaccines have become more available worldwide today, there is an imbalance in resources among nations in the world putting underdeveloped nations at a disadvantage. Literature points out that unequal distribution of vaccines among wealthier and poorer countries continue to lead to a gap in vaccination rates that becomes alarming to low-income countries because of resource constraints.

Hence, within low-income countries such as the Philippines, optimal allocation of COVID-19 vaccines especially for resource-constrained communities is vital. Optimal allocation of vaccines would allow resources to be apportioned for other equally important aspects of pandemic response, and would create an equitable opportunity for citizens to access COVID-19 vaccines to achieve herd immunity that will eventually help in curbing the pandemic.

Using constrained optimization, this research developed a mathematical model for the optimal allocation of COVID-19 vaccines considering various constraints in supply and demand such as prioritization framework, available doses of vaccine brands, demand for vaccine in each locality, and the financial requirements for vaccination. The model was applied in Abulug, Cagayan where data was available using local data collected from their Rural Health Unit. Secondary data came from the Municipal Planning Office of Abulug, Cagayan, Department of Health, and Philippine Statistics Authority.

Results show that allocating vaccines using the model yield additional COVID-19 deaths of 14. Compared to other approaches of vaccine allocation, allocating vaccines proportionally with respect to the demand of priority groups, then distributing the vaccines proportionally with respect to the demand of localities will result to additional COVID-19 deaths of 15. On the hand, if vaccines are allocated proportionally to priority groups then distributed equally among localities, the projected additional COVID-19 deaths is 27.

It is, therefore, recommended for the Rural Health Unit to utilize the developed model in allocating vaccines per priority group per locality as it yields the least number of projected deaths as compared to other known approaches of vaccine allocation. It has to be noted, however, that the results from the model will not remain the same through time. It has to be recalibrated when there are changes in parameters such as demand, supply, budget, vaccine-related costs, COVID-19 data (e.g., fatality rate), and demographics. The model, likewise, has to be adjusted to fit the requirements of the community (or country) to which it will be applied. Nonetheless, as demonstrated in this research, the model can be used for its purpose to determine the optimal allocation of vaccines to minimize the projected number of additional COVID-19 deaths especially for resource-constrained communities.

Research directions that merit investigation include exploring other parameters to be included in the modeling process such as vaccine expiration, effect of population density, and dynamic system models. Further, it is strongly encouraged for the government to advance its interests in processes and technologies that will allow systematic, organized, and complete data collection that can be made publicly available to support research and academic undertakings in the country.

Document Type

Master Thesis

Degree

Master of Management major in Business Management

College

College of Economics and Management (CEM)

Adviser/Committee Chair

Dr. Dinah Pura T. Depositorio

Language

English

LC Subject

Distribution (Economic theory), COVID-19 vaccines, Epidemics

Location

UPLB College of Economics and Management (CEM)

Notes

Award: Best Business Research

Not available for general public.

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