2077. Utility of a Real-Time Spatiotemporal Mapping Surveillance System in Detection of Healthcare-Associated Acute Respiratory Viral Infection Clusters in a Tertiary Healthcare Institution

Abstract

Abstract Background Transition to endemic COVID-19 has been associated with a rise in community respiratory viral infections (ARIs) with a corresponding increase in healthcare-associated ARIs (HA-ARIs) (Figure 1). 4D-Disease Outbreak Surveillance System (4D-DOSS) is a real-time spatiotemporal mapping surveillance system being developed to detect healthcare-associated infection clusters. We aimed to assess 4D-DOSS’s utility in detection of HA-ARI clusters. Methods 4D-DOSS is a system that integrates and maps clinical, laboratory and patient movement data onto a digital twin of the hospital’s physical space. In addition to a virtual mapping replica of Singapore General Hospital, a 2000-bedded tertiary hospital in Singapore, it constitutes detailed healthcare cloud architecture and surveillance algorithms. Respiratory specimens from inpatients with ARI symptoms are tested for 16 human respiratory viral pathogens via a respiratory virus multiplex PCR (RV16) panel. HA-ARI constitutes first positive sample beyond the maximum incubation period of the corresponding virus (from admission date). Earlier positive test is categorized as community-associated ARI (CA-ARI). Two or more patients with spatial temporal overlap of three-days or less, during the infectious period (7-days) of an index patient are deemed a HA-ARI cluster. Results Incidence of HA-ARI, as per 10,000 patient-days was 7.4 pre-COVID-19 pandemic (Jan 2018 to Dec 2019), 1.5 during pandemic (Jan 2020 to Dec 2022) and 6.4 during transition to endemicity (Jan 2023 – April 2023). Between September 2018 and December 2018, one influenza cluster of ten inpatients (Nov 2018) was identified in the proof-of-concept version of 4D-DOSS. There were four HA-ARI clusters during the Jan 2020-Dec 2022 COVID-19 pandemic phase. 19 HA-ARI clusters were identified between Jan 2023-April 2023. Conclusion 4D-DOSS can detect HA-ARI clusters and has potential to trigger an alert-response process for more effective infection prevention. It enables study of infectious disease transmission kinetics in real-time. Disclosures Sean Whiteley, BSc (IT), Axomem: Board Member|Axomem: Fees received for service and software licenses Maybelle Auw, MBBS, Axomem: Work for company that received fees for service and licensing