Nosocomial transmission of SARS-CoV-2

Lead Research Organisation: London Sch of Hygiene and Trop Medicine
Department Name: Epidemiology and Population Health

Abstract

SARS-CoV-2 spreads in many different types of environments including within healthcare settings. Understanding how much transmission happens in hospitals or in the community will aid our ability to control ongoing spread, as well as to improve interventions. By knowing what factors make certain hospitals hotspots of transmission we can limit spread by targeting these factors in particular. Within this project we will use mathematical and statistical techniques to harness the UK wide data on hospital cases to understand how important transission of SARS-CoV-2 in hospitals was to the first "wave" of COVID-19 in the UK and what we could do in the face of any future resurgence.

Technical Summary

There is increasing evidence that the novel coronavirus (SARS-CoV-2) can spread within healthcare settings. Quantifying the relative contribution of this environment to wider transmission will aid in intervention design and control of SARS-CoV-2. In this project we aim to combine statistical and mathematical modelling, with UK wide situational reports, an individual patient level database, and Trust level information, to determine the likely contribution of nosocomial transmission to the UK COVID-19 epidemic.

Our project consists of three parts. Firstly, we will determine the contribution of nosocomial transmission by using combinations of samples from data-driven distributions to estimate the number of missed SARS-CoV-2 infections, adjusting total hospitalised COVID-19 case numbers to account for "nosocomial acquired, community onset" cases. We will also quantify the number of COVID-19 cases due to onward transmission from undetected nosocomial transmission. Secondly, we will use multilevel Poisson regression models to determine the important factors that contribute to the observed heterogeneity in nosocomial transmission between Trusts. Thirdly, we will combine the above insights to estimate the impact of interventions: from the number of undetected cases and knowledge of the natural history of COVID-19 we can estimate the likely effect of quarantine for discharged patients or screening on (re-) admission. Such information will provide key evidence to inform the use of additional interventions in the event of future resurgences.
 
Description Member of SPI-M: reporting back analysis on
Geographic Reach National 
Policy Influence Type Membership of a guideline committee
 
Description Collaboration on nosocomial transmission of SARS-CoV-2 
Organisation Lancaster University
Country United Kingdom 
Sector Academic/University 
PI Contribution Worked together on English data to explore levels of nosocomial transmission of SARS-CoV-2 - I developed models to determine the missed nosocomial cases
Collaborator Contribution Worked together on English data to explore levels of nosocomial transmission of SARS-CoV-2 - data sharing from PHE as well as analysis input
Impact Nosocomial COVID grant (MR/V028456/1) with co-supervision of a reseach assistant for a year and 4 publications.
Start Year 2020
 
Description Collaboration on nosocomial transmission of SARS-CoV-2 
Organisation Public Health England
Department Antimicrobial Resistance and Healthcare-Associated Infections Reference Unit
Country United Kingdom 
Sector Public 
PI Contribution Worked together on English data to explore levels of nosocomial transmission of SARS-CoV-2 - I developed models to determine the missed nosocomial cases
Collaborator Contribution Worked together on English data to explore levels of nosocomial transmission of SARS-CoV-2 - data sharing from PHE as well as analysis input
Impact Nosocomial COVID grant (MR/V028456/1) with co-supervision of a reseach assistant for a year and 4 publications.
Start Year 2020
 
Description Collaboration on nosocomial transmission of SARS-CoV-2 
Organisation University of Oxford
Department Nuffield Department of Medicine
Country United Kingdom 
Sector Academic/University 
PI Contribution Worked together on English data to explore levels of nosocomial transmission of SARS-CoV-2 - I developed models to determine the missed nosocomial cases
Collaborator Contribution Worked together on English data to explore levels of nosocomial transmission of SARS-CoV-2 - data sharing from PHE as well as analysis input
Impact Nosocomial COVID grant (MR/V028456/1) with co-supervision of a reseach assistant for a year and 4 publications.
Start Year 2020
 
Description Patient and public engagment 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Zoom presentation and discussion session with general public on the contribution of transmission in hospital settings to the COVID-19 pandemic
Year(s) Of Engagement Activity 2021