Impacts of relaxed mask policies on COVID-19 epidemics: A modeling study in South Korea

Background: The COVID-19 pandemic led to widespread use of non-pharmaceutical interventions (NPIs), including mask mandates. Although many studies have examined COVID-19 policies, there is a lack of research on the impact of mask mandate relaxation in South Korea. Retrospective analyses of this topic are essential to inform optimized policy responses in future pandemics. Methods: We used a discrete-time, age-structured Susceptible–Exposed–Infectious–Vaccinated–Recovered (SEIVR) compartmental model to simulate COVID-19 transmission in South Korea and conducted counterfactual analyses to assess the impact of five major mask policy adjustment points (PAPs). The model estimated changes in confirmed cases, severe cases, and deaths under counterfactual scenarios in which mask mandates were relaxed 2 weeks earlier or later than they were in reality. Analyses were stratified by age group to evaluate differential effects. Results: Changes in Rt (effective reproduction number) following mask policy relaxations were modest across all five PAPs. While some policy shifts were followed by slight increases or decreases in Rt, none led to uncontrolled epidemic growth. Counterfactual simulations showed that advancing mask relaxation by 2 weeks could have led to significantly more confirmed cases, with increases of up to 29.5% in children and 25.2% in older adults, compared to the observed timeline. Conversely, delaying relaxation reduced case numbers across all age groups. The timing of relaxation, especially when Rt was low, appeared to play a more critical role than population immunity in determining transmission outcomes. A positive association was observed between higher Rt at the time of relaxation and increased case counts, whereas immunity levels did not show a consistent correlation. Conclusions: The timing of mask mandate relaxation substantially influenced short-term COVID-19 transmission dynamics. Real-time indicators such as Rt were more predictive of outcomes than estimated immunity levels, suggesting their utility for informing policy adjustments. Counterfactual evidence underscores that premature relaxation could disproportionately impact vulnerable populations. Policymakers should incorporate transmission dynamics, age-specific vulnerability, and timing considerations into future pandemic response strategies. Clinical trial number : Not applicable.