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Susceptibility to Resurgent COVID-19 Outbreaks Following Vaccine Rollouts: A Modeling Study
Georgios Neofotistos1, Mattia Angeli1, Marios Mattheakis1
1Harvard J. A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Viruses
|October 27, 2022
Summary
The Susceptible-Asymptomatic-Infected-Vaccinated-Removed (SAIVR) model predicts COVID-19 resurgence. Vaccination coverage and waning immunity significantly influence epidemic patterns, impacting public health strategies.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- The COVID-19 pandemic highlighted the need for advanced epidemiological models.
- Existing Susceptible-Infectious-Removed (SIR) models lack compartments for asymptomatic and vaccinated individuals.
Purpose of the Study:
- To analyze the effectiveness of COVID-19 vaccine rollouts.
- To assess susceptibility to resurgent epidemics under various conditions.
- To explore the impact of vaccination coverage, importation, and SARS-CoV-2 variants.
Main Methods:
- Utilized the novel Susceptible-Asymptomatic-Infected-Vaccinated-Removed (SAIVR) compartmental model.
- Employed numerical solutions to simulate epidemic dynamics.
- Incorporated parameters reflecting SARS-CoV-2 epidemiological characteristics and immunity waning.
Main Results:
- Demonstrated that vaccination coverage and immunity waning dictate resurgent epidemic patterns (surges vs. endemic).
- Showcased the model's ability to replicate observed COVID-19 trends in highly vaccinated populations.
- Identified key factors influencing vaccine rollout effectiveness and epidemic susceptibility.
Conclusions:
- The SAIVR model provides valuable insights into COVID-19 dynamics post-vaccination.
- Understanding the interplay of vaccination and immunity waning is crucial for managing future epidemics.
- Findings inform public health policies for effective vaccine strategies and epidemic control.
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