Impact of a Data-Informed Universal Masking Policy on Hospital-Acquired COVID-19, Influenza, and RSV Infections in King County, Washington: A Controlled Interrupted Time-Series Analysis

Abstract

Hospital-acquired respiratory viral infections (HAIs), including COVID-19, influenza, and respiratory syncytial virus (RSV), contribute to increased patient morbidity and healthcare burden. Universal masking has been shown to reduce respiratory virus transmission in healthcare settings, but masking mandates have fallen out of favor in the years following the COVID-19 pandemic. In response, the Northwest Healthcare Response Network (NWHRN) created a data-informed masking policy that “turns on” when respiratory virus transmission risk is high, and “off” when transmission risk is low. This study evaluated the impact of this data-informed hospital masking policy on HAIs in King County, Washington. We conducted a controlled interrupted time series analysis (CITS) using hospitalization data from the Washington Respiratory Virus Hospitalization Surveillance Network (RESP-NET) during the 2024–2025 respiratory virus season. The masking policy was activated on November 23, 2024, when emergency department visits for COVID-19, influenza, or RSV exceeded a predefined alert threshold. Hospital-acquired infections were compared with community-acquired infections (CAIs), which served as a control group. Among 3,374 laboratory-confirmed COVID-19, influenza, and RSV hospitalizations, 168 were classified as HAIs. No significant immediate change in the HAI-to-CAI ratio was observed following policy implementation (RR = 0.98, 95% CI: 0.31–3.08). The weekly HAI-to-CAI ratio declined by 9% per week after implementation compared to the pre-intervention period, although this decrease was not statistically significant (95% CI: 0.72–1.13). Although inconclusive, our findings suggest that data-informed masking policies may mitigate respiratory virus transmission in healthcare settings while minimizing the need for prolonged masking mandates. Further evaluation of this policy using data from multiple seasons and larger geographic areas is warranted to further assess its effectiveness.