Christopher Overton -- Investigating how the epidemic phase biases the severity risk of observed cases
|Starts:||14:00 22 Nov 2021|
|Ends:||15:00 22 Nov 2021|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
Join us for this seminar by Chris Overton (Manchester) as part of the North West Seminar Series in Mathematical Biology and Data Sciences. Details of the full series can be found here https://www.cms.livjm.ac.uk/APMSeminar/
The talk will be hosted on zoom, please contact email@example.com or firstname.lastname@example.org for the zoom link, or sign up to the mailing list.
Abstract: Monitoring the risk of severe outcomes during an infectious disease outbreak is important for informing the public health response. However, it has recently been shown that using case-severity fluctuates with the phase of the epidemic: case-severity increases during phases of epidemic growth and decreases during phases of epidemic decline. This leads to unbiased estimators of case-severity being biased estimators of the underlying infection-severity. Using a simple epidemic model, we investigate this epidemic phase bias. We prove the existence and direction of this bias, and analyse the performance of a method that attempts to correct for this bias. This bias has led to challenges during the COVID-19 pandemic. Here, researchers have attempted to compare the infection-severity risk of different SARS-CoV-2 variants. However, these attempts are skewed by the epidemic phase bias. Applying the model to a COVID-19 inspired scenario, we show that the epidemic phase bias could lead to at least a 50\% higher case-severity risk in a growing variant relative to a declining variant, regardless of any underlying change in infection-severity, which would skew any relative risk estimates. By raising awareness of this bias and the correction methods, future research should be able to address this challenge when comparing different variants of a pathogen.
To subscribe to the mailing list for this event series, please send an e-mail with the phrase “subscribe math-lifesci-seminar” in the message body to email@example.com
Role: Postdoctoral researcher
Organisation: University of Manchester
Travel and Contact Information