Development and Delivery of a Real-time Hospital-onset COVID-19 Surveillance System Using Network Analysis. (7th July 2020) - Price, James Richard; Mookerjee, Siddharth; Dyakova, Eleonora; Myall, Ashleigh; Leung, Wendy; Weiße, Andrea Yeong; Shersing, Yeeshika; Brannigan, Eimear Therese; Galletly, Tracey; Muir, David; Randell, Paul; Davies, Frances; et al.
Abstract: 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. Abstract : We implemented a novel surveillance system to reveal the epidemiology of hospital-onset COVID-19 infections over time. Hospital-wide patient pathways need to be taken into account to effectively inform infection-prevention practices. Local surveillance systems can effectively support national surveillance methods.