Ms. Maureen Canning1, Dr Marion A Kainer1
1Western Health, Sunshine, Australia
Biography:
Dr. Kainer is the head of Infectious Diseases at Western Health. She is an infectious diseases physician and healthcare epidemiologist. She trained as an Epidemic Intelligence Service officer at the Centers for Disease Control and Prevention (CDC) in the hospital infections program and subsequently was the director of the Healthcare Associated Infections and Antimicrobial Resistance Program at the Tennessee Department of Health (TDH). She led the 2012 fungal meningitis outbreak investigation at TDH and was named Tennessean of the Year. She was honored by the Obama White House as a Champion of Change for Prevention and Public Health in 2013.
Abstract:
Introduction
Understanding the relative burden and preventability of various healthcare associated infections (HAI) is essential for evidence-based resource allocation. Since the pandemic, our health service has reported healthcare-associated COVID (HA-COVID) infection to the VICNISS Coordinating Centre for healthcare associated infection surveillance (VICNISS). HA-COVID has a 30-day mortality of 10.6%. Universal masking, improving ventilation/cleaning air, and early identification of COVID patients can reduce HA-COVID.
We reported the following HAIs to VICNISS: infections following hip, knee or colorectal surgery, hysterectomy and Caesarean sections; central line associated blood stream infections (in intensive care units); facility-wide Staphylococcus aureus bacteraemia; and Clostridioides difficile infection.
We sought to understand the relative burden of HA-COVID compared to other HAIs reported to VICNISS.
Methods
We extracted numerator data on HAIs submitted to VICNISS by reporting campus and quarter from January 2020 to March 2024. Because data on some HAIs were not captured for some quarters (due to surveillance protocols or exemptions), we imputed missing numerator data using campus specific rates for HAIs using available data since 2020. We calculated the expected number of HAIs since January 2020 or January 2022 if surveillance were continuous. Continuous HA-COVID data was available through May 2024. The proportion of HA-COVID was calculated by dividing HA-COVID by the sum of HA-COVID plus other HAIs.
Results
Assuming ongoing continuous surveillance, HA-COVID represents 63% of all HAIs (from January 2020) and 73% (from January 2022).
Conclusion
HA-COVID accounts for the vast majority of all HAIs. Surveillance and prevention of HA-COVID should be prioritized.