A new proof-of-concept system is harnessing new techniques to detect and track COVID-19 transmission in hospitals.
A team of scientists from the University of Manchester has created the system which combines the movement and interaction of staff and patients with genomic sequencing of the virus to help signpost how to improve patient pathways, staff movement, and to reduce risk.
The system can identify hotspots within hospitals where patients and staff had likely been in contact and shared similar or identical variants of the virus.
The results have been published in the journal eLife.
Infection control implications
The collaboration between Manchester scientists, clinical staff, and hospital executives collected data between March and June 2020 across five hospitals in North West England. Through the application of genomic sequencing to the throat and nasal swabs of 173 healthcare workers and patients, the team took advantage of the natural genetic changes in the virus to understand how closely related samples were from different staff and patients affected by the virus.
If the COVID-19 genome from one affected individual appears almost identical to that of another, this shows they share a common, nearby source of infection. The team combined this information with data on patient and staff movement can identify where and when clusters of infection occur.
Identification using genomic sequencing methods can take at least a week to complete, but the team’s process can be completed in 48 hours, an approach which they say is in a position to be scaled up at pace.
Dr Jamie Ellingford from The University of Manchester said: “The methods applied in this study to completely characterise what the virus looks like in each sample goes above and beyond routine testing strategies. And that can enable identification of areas of hospitals where outbreaks are occurring and help alert infection control teams.”
A potential limitation to the approach is two individuals can share a similar variant by chance, rather than as a result of interrelated infections. The team tackled this issue by sequencing the virus in people collected from the Emergency Department of over 30 hospital sites.
Using this data the team was able to identify clusters of individuals who shared viruses more genetically similar than would be expected by chance.
Dr Ellingford said: “It is extremely important to understand the effectiveness of infection control methods if we are to reduce and prevent SARS-CoV-2 transmission in hospital. While vaccines may reduce risk to individuals in hospital, the risk of infection will still exist, and infection control is strongly needed to ensure patient and staff safety.
“We think, however, an important tool in the infection control armoury is viral genome sequencing, which offers a realistic possibility to track and identify root-causes of hospital-acquired transmissions. It is able to alert us to individuals who have been in contact during a given period and share genetically similar viral samples. And that can lead to targeted interventions and ultimately prevent avoidable harm to vulnerable individuals who acquire COVID-19 in hospital.”
Graeme Black, Professor of Genetics and Ophthalmology at the University of Manchester, added: “Once hospitals have identified clusters there are a range of measures they can take to make them safe. With this information hospital managers can, for example, evaluate existing infection control practices and easily check which ones are working most effectively. The use of PPE could also be adapted according to where a cluster might be.
“But we also suggest these data support the widespread adoption of screening strategies for healthcare workers who may be pre-symptomatic or asymptomatic shedders of SARS-CoV-2 who are important contributors to SARSCoV-2 outbreaks.
“We also think that developing methods to more accurately track movement could be useful in hospital to extend the characterisation of contacts between individuals and to understand the accuracy of the assumptions enforced in this study.”