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Age-Stratified COVID-19 Spread Analysis and Vaccination: A Multitype Random Network Approach
Xianhao Chen1, Guangyu Zhu1, Lan Zhang2
1Department of Electrical and Computer EngineeringUniversity of Florida Gainesville FL 32611 USA.
IEEE Transactions on Network Science and Engineering
|July 5, 2022
Summary
Prioritizing COVID-19 vaccination depends on the reproduction number. High transmission requires vaccinating the elderly, while low transmission benefits from targeting younger adults to reduce mortality and hospitalizations.
Area of Science:
- Epidemiology
- Network Theory
- Mathematical Modeling
Background:
- COVID-19 severity and mortality increase with age.
- Age-stratified modeling is crucial for reducing COVID-19 hospitalizations and deaths.
- Complex contact networks influence disease spread.
Purpose of the Study:
- To develop an age-stratified epidemic model for COVID-19 dynamics.
- To propose an effective age-stratified vaccination strategy.
- To analyze the impact of vaccination prioritization on mortality and hospitalizations.
Main Methods:
- Developed an age-stratified SEAHIR (susceptible-exposed-asymptomatic-hospitalized-infectious-removed) model.
- Extended the standard SEIR compartmental model.
- Utilized network theory to model COVID-19 spread in complex networks with general degree distributions.
Main Results:
- Derived key epidemiological metrics from the SEAHIR model.
- Determined that vaccination prioritization strategy effectiveness is contingent on the reproduction number (R0).
- Identified that elderly prioritization is optimal only when R0 is high.
Conclusions:
- When R0 is low due to interventions like masking, prioritizing high-transmission groups (adults 20-39) is most effective.
- Age-based vaccination strategies significantly impact COVID-19 outcomes.
- Findings offer recommendations for optimizing age-based COVID-19 vaccination prioritization.
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