Weekly HVAC Filter Surveillance of Respiratory Viruses in University Settings: Linking Viral Loads to Airborne Viral Concentrations and Infection Risk

ZHOUYUAN WANG, Liang Zhao, Irene Xagoraraki, Kaisen Lin, Michigan State University

     Abstract Number: 127
     Working Group: Bioaerosols

Abstract
As COVID-19 transitions from a pandemic to an endemic disease, monitoring its presence in public spaces remains essential for effective public health management. Traditional clinical testing is increasingly limited by reduced participation and underreporting due to widespread home testing, highlighting the need for complementary surveillance tools, especially in high-occupancy indoor environments such as university buildings. Our previous study evaluated the potential of HVAC filters for SARS-CoV-2 detection through monthly dust collection and RT-ddPCR analysis. SARS-CoV-2 RNA was detected in 28-86% of pre-filter and 17-50% of final filter samples across different air handling units (AHUs), with significant variation among AHUs.

To capture community transmission trends with higher time resolution, we implemented weekly sampling between February and March 2025 and expanded detection targets to include other respiratory viruses, such as Influenza A. During this period, we concurrently monitored room occupancy and HVAC operational parameters (supply, return, and outdoor airflow rates) to evaluate their influence on viral loads on filters. Furthermore, we aim to estimate the fraction of virus-laden particles released by infected individuals that are captured by HVAC filters, considering particle deposition on indoor surfaces. This will enable estimation of time-averaged airborne viral concentrations and allow infection risk assessment through quantitative microbial risk assessment (QMRA).

Overall, our findings demonstrate that HVAC filter-based surveillance is a practical, non-invasive strategy for ongoing respiratory virus monitoring in non-healthcare settings. By leveraging existing building infrastructure, this approach supports data-driven public health responses during the endemic phase of COVID-19 and beyond.