output
20182022
most citedUsing statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example

60 citations

9 papers

q-bio.PE2022★ 12 cited

Approximating quasi-stationary behaviour in network-based SIS dynamics

Christopher E. Overton, Robert R. Wilkinson, Adedapo Loyinmi +2

Deterministic approximations to stochastic Susceptible-Infectious-Susceptible models typically predict a stable endemic steady-state when above threshold. This can be hard to relat…

q-bio.PE2022★ 10 cited

Novel methods for estimating the instantaneous and overall COVID-19 case fatality risk among care home residents in England

Christopher E. Overton, Luke Webb, Uma Datta +10

The COVID-19 pandemic has had high mortality rates in the elderly and frail worldwide, particularly in care homes. This is driven by the difficulty of isolating care homes from the…

stat.AP2022★ 10 cited

Bridging disconnected networks of first and second lines of biologic therapies in rheumatoid arthritis with registry data: Bayesian evidence synthesis with target trial emulation

Sylwia Bujkiewicz, Janharpreet Singh, Lorna Wheaton +4

Objective: We aim to utilise real world data in evidence synthesis to optimise an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis in order to allo…

q-bio.PE2021★ 23 cited

EpiBeds: Data informed modelling of the COVID-19 hospital burden in England

Christopher E. Overton, Lorenzo Pellis, Helena B. Stage +9

The first year of the COVID-19 pandemic put considerable strain on the national healthcare system in England. In order to predict the effect of the local epidemic on hospital capac…

cs.LG2021★ 42 cited

A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers

Bill Cassidy, Neil D. Reeves, Joseph M. Pappachan +4

This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance. The system uses a cr…

q-bio.PE2020★ 60 cited

Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example

Christopher E. Overton, Helena B. Stage, Shazaad Ahmad +16

During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and desig…

cs.DL2020★ 34 cited

Towards a Framework for the Design, Implementation and Reporting of Methodology Scoping Reviews

Glen P. Martin, David Jenkins, Lucy Bull +10

Background: In view of the growth of published papers, there is an increasing need for studies that summarise scientific research. An increasingly common review is a 'Methodology s…

math.NA2018★ 39 cited

A Convex Geodesic Selective Model for Image Segmentation

Michael Roberts, Ke Chen, Klaus L. Irion

Selective segmentation is an important application of image processing. In contrast to global segmentation in which all objects are segmented, selective segmentation is used to iso…

math.NA2018★ 4 cited

Multigrid Algorithm Based on Hybrid Smoothers for Variational and Selective Segmentation Models

Michael Roberts, Ke Chen, Klaus L. Irion

Automatic segmentation of an image to identify all meaningful parts is one of the most challenging as well as useful tasks in a number of application areas. This is widely studied.…