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COVID-19 vaccination policies under uncertain transmission characteristics using stochastic programming
Krishna Reddy Gujjula1, Jiangyue Gong1, Brittany Segundo1
1Wm Michael Barnes '64 Department of Industrial & Systems Engineering, Texas A&M University, College Station, Texas, United States of America.
Plos One
|July 22, 2022
Summary
This study introduces a new method for optimal COVID-19 vaccination policies in diverse populations. It determines the minimum vaccinations needed to control outbreaks reliably, even with limited vaccine supplies.
Area of Science:
- Epidemiology
- Public Health
- Mathematical Modeling
Background:
- Controlling infectious disease outbreaks like COVID-19 requires effective vaccination strategies.
- Heterogeneous populations and uncertainties in disease parameters complicate optimal vaccine allocation.
- Stochastic programming offers a framework for decision-making under uncertainty.
Purpose of the Study:
- To develop a novel stochastic programming methodology for optimal vaccination policies in multi-community settings.
- To identify the minimum vaccination coverage required to achieve a desired level of outbreak control (reproduction number < 1) with a specified reliability.
- To account for uncertainties in vaccine efficacy, age-specific susceptibility/infectivity, household structures, and social interactions.
Main Methods:
- Developed a stochastic programming model to optimize vaccination strategies.
- Incorporated key uncertainties: vaccine efficacy, age-related transmission, household composition, and human interaction patterns.
- Applied the methodology to a computational study of neighboring U.S. counties, considering vaccine availability.
Main Results:
- Identified minimum vaccination percentages necessary for outbreak control in each community based on reliability levels.
- Demonstrated the model's capability to facilitate vaccine sharing among counties facing limited supplies.
- Highlighted the importance of tailored vaccination policies for heterogeneous populations.
Conclusions:
- The developed methodology provides a robust decision-making tool for public health agencies.
- It aids in the efficient allocation of limited vaccines to control epidemics under uncertainty.
- Optimized vaccination policies are crucial for managing infectious diseases in diverse populations.
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