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2939. Multi-feature SEIR model for epidemic analysis and vaccine prioritization
Invited abstract in session WC-15: COVID-19 (2), stream OR in Health Services (ORAHS).
Wednesday, 12:30-14:00Room: 18 (building: 116)
Authors (first author is the speaker)
| 1. | Hoda Bidkhori
|
| George Mason University |
Abstract
The SEIR model has become a valuable tool for studying infectious disease dynamics and predicting the spread of diseases, particularly concerning the COVID pandemic. However, existing models often oversimplify population characteristics and fail to account for differences in disease sensitivity and social contact rates that can vary significantly among individuals.
To address these limitations, we have developed a new multi-feature SEIR model that considers the heterogeneity of health conditions (disease sensitivity) and social activity levels (contact rates) among populations affected by infectious diseases. Our model has been validated using data from the Centers for Disease Control and Prevention on COVID cases in Allegheny County.
In addition, we have used our multi-feature SEIR model to propose and evaluate different vaccine prioritization strategies tailored to the characteristics of heterogeneous populations. We have formulated optimization problems to determine effective vaccine distribution strategies. We have designed extensive numerical simulations to compare vaccine distribution strategies in different scenarios.
Keywords
- Health Care
- Optimization Modeling
- Algorithms
Status: accepted
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