A Two-Phase Stochastic Dynamic Model for COVID-19 Mid-Term Policy Recommendations in Greece: A Pathway towards Mass...

Area of Science:

• Epidemiology and Public Health
• Mathematical Modeling
• Infectious Disease Dynamics

Background:

• Greece implemented a second nationwide lockdown in November 2020 to control the SARS-CoV-2 pandemic.
• Mass vaccination began in January 2021, necessitating continued non-pharmaceutical interventions (NPIs).
• The study aims to balance public health with socio-economic costs during the COVID-19 pandemic.

Purpose of the Study:

• To evaluate the effectiveness of different non-pharmaceutical intervention strategies during the second wave of COVID-19 in Greece.
• To assess the impact of vaccination rates on disease transmission and outcomes in the post-vaccination phase.
• To model and compare various COVID-19 mitigation scenarios.

Main Methods:

• Development of a two-phase stochastic dynamic network compartmental model (SEIR and SVEIR).
• Assessment of three distinct scenarios for the pre-vaccination phase (baseline, semi-lockdown, rolling lockdown).
• Evaluation of three scenarios with varying vaccination rates for the post-vaccination phase.

Main Results:

• The 'semi-lockdown' scenario in the first phase resulted in 5.7% fewer expected fatalities compared to a 'rolling lockdown'.
• The second phase outcomes are highly dependent on vaccine supply and high vaccination uptake.
• Model simulations provide insights into optimizing public health interventions.

Conclusions:

• A 'semi-lockdown' approach with targeted NPIs is more effective than stringent, rolling lockdowns for mitigating COVID-19.
• Successful COVID-19 control requires a combination of vaccination and sustained NPIs.
• Vaccine availability and uptake are critical determinants of pandemic control post-vaccination.