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Development and delivery of a real-time hospital-onset COVID-19 surveillance system using network analysis

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posted on 2023-06-10, 01:18 authored by James Richard Price, Siddharth Mookerjee, Eleonora Dyakova, Ashleigh Myall, Wendy Leung, Andrea Yeong Weiße, Yeeshika Shersing, Eimear Therese Brannigan, Tracey Galletly, David Muir, Paul Randell, Frances Davies, Frances Bolt, Mauricio Barahona, Jonathan Ashley Otter, Alison H Holmes
Background Understanding nosocomial acquisition, outbreaks, and transmission chains in real time will be fundamental to ensuring infection-prevention measures are effective in controlling coronavirus disease 2019 (COVID-19) in healthcare. We report the design and implementation of a hospital-onset COVID-19 infection (HOCI) surveillance system for an acute healthcare setting to target prevention interventions. Methods The study took place in a large teaching hospital group in London, United Kingdom. All patients tested for SARS-CoV-2 between 4 March and 14 April 2020 were included. Utilizing data routinely collected through electronic healthcare systems we developed a novel surveillance system for determining and reporting HOCI incidence and providing real-time network analysis. We provided daily reports on incidence and trends over time to support HOCI investigation and generated geotemporal reports using network analysis to interrogate admission pathways for common epidemiological links to infer transmission chains. By working with stakeholders the reports were co-designed for end users. Results Real-time surveillance reports revealed changing rates of HOCI throughout the course of the COVID-19 epidemic, key wards fueling probable transmission events, HOCIs overrepresented in particular specialties managing high-risk patients, the importance of integrating analysis of individual prior pathways, and the value of co-design in producing data visualization. Our surveillance system can effectively support national surveillance. Conclusions Through early analysis of the novel surveillance system we have provided a description of HOCI rates and trends over time using real-time shifting denominator data. We demonstrate the importance of including the analysis of patient pathways and networks in characterizing risk of transmission and targeting infection-control interventions.

History

Publication status

  • Published

File Version

  • Published version

Journal

Clinical Infectious Diseases

ISSN

1058-4838

Publisher

Oxford University Press

Issue

1

Volume

72

Page range

82-89

Event location

United States

Department affiliated with

  • BSMS Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2021-10-05

First Open Access (FOA) Date

2021-10-05

First Compliant Deposit (FCD) Date

2021-10-05

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