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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

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Published on: July 4, 2007

A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries.

Madjid Tavana^1,2, Kannan Govindan³, Arash Khalili Nasr⁴

¹Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, PA 19141 USA.

Annals of Operations Research

|June 8, 2021

Summary

Developing countries can optimize COVID-19 vaccine distribution using a mathematical model. This approach prioritizes vulnerable populations and ensures equitable allocation, crucial for economic recovery and pandemic control.

Keywords:

COVID-19 Coronavirus vaccine Equitable distribution Location-inventory problem Mixed-integer linear programming model Vaccine supply chain

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Production of Near-Infrared Sensitive, Core-Shell Vaccine Delivery Platform

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Published on: October 20, 2020

Area of Science:

Public Health
Operations Research
Epidemiology

Background:

Developing countries face challenges in controlling COVID-19 spread and achieving economic recovery.
Equitable vaccine distribution is critical for pandemic mitigation and economic rebound.
Vaccination is the most effective strategy against COVID-19, necessitating careful planning in resource-limited settings.

Purpose of the Study:

To develop a mathematical model for equitable COVID-19 vaccine distribution in developing countries.
To address practical considerations in vaccine allocation, including storage, shortages, and population heterogeneity.
To optimize vaccine deployment for vulnerable groups and ensure efficient resource utilization.

Main Methods:

A mixed-integer linear programming model was formulated.
The model incorporates vaccine categories (cold, very cold, ultra-cold) and their specific storage requirements.
Assumptions include future storage, shortage management, budget constraints, manufacturer selection, order allocation, time-dependent capacities, and population grouping.

Main Results:

The study demonstrates the efficiency and effectiveness of the proposed mathematical programming approach.
The model provides a framework for rationalizing vaccine allocation processes in developing countries.
Real-world data validated the practical applicability of the developed model.

Conclusions:

The mathematical model offers a robust solution for equitable COVID-19 vaccine distribution in developing nations.
Prioritizing vulnerable populations and optimizing allocation are key to successful vaccination campaigns.
This approach supports both public health goals and economic recovery efforts.