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Mayo Clinic Proceedings: Digital Health ; 1(2):172-184, 2023.
Article in English | ScienceDirect | ID: covidwho-2320142

ABSTRACT

Objective To develop an electronic surveillance system that provides prompt in-depth situational infectious disease risk and linkage analysis for inpatients in a tertiary hospital. Patients and Methods All patients admitted to Singapore General Hospital (SGH), a 1900-bedded tertiary care hospital, are included in routine surveillance. The 3-Dimensional Disease Outbreak Surveillance System (3D-DOSS) was developed to spatiotemporally represent inpatient surveillance data on a "digital twin” of SGH and evaluated for performance in surveillance, contact tracing, and outbreak investigations. This study was conducted over a 12 month period (October 1, 2020 to September 30, 2021). Results The 3D-DOSS surveillance module identified an influenza cluster of 10 inpatients in November 2018, mapping retrospective data between September 2018 and December 2018. Seventy-six clusters of 2 or more linked patients with health care–associated Klebsiella pneumoniae carbapenemase–type carbapenemase-producing Enterobacteriaceae were detected in SGH in 2 years (2018 and 2019). The 3D-DOSS contact tracing module promptly identified 44 primary and 162 secondary inpatient contacts, after exposure to a health care worker with coronavirus disease 2019 in April 2021. For outbreak mapping, 24 patients with OXA-48 were mapped on October 22, 2020, using 3D-DOSS to determine their spatiotemporal distribution. Conclusion The integration of health care data and representation on a virtual hospital digital twin is a useful tool in an outbreak alert and response framework. Infectious disease surveillance systems, which are syndrome-based, that can access real-time data, and can incorporate movement networks, can potentially enhance health care–associated infection prevention and preparedness for disease X.

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