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20202023
most citedUsing statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example

60 citations · 85 across the 4 of their papers we have counts for

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Showing q-bio.PEShow all

5 papers · 1 filter

q-bio.PE2023

Calculation of Epidemic First Passage and Peak Time Probability Distributions

Jacob Curran-Sebastian, Lorenzo Pellis, Ian Hall +1

Understanding the timing of the peak of a disease outbreak forms an important part of epidemic forecasting. In many cases, such information is essential for planning increased hosp…

q-bio.PE2022★ 2 cited

Modelling the impact of repeat asymptomatic testing policies for staff on SARS-CoV-2 transmission potential

Carl A Whitfield, University of Manchester COVID-19 Modelling Group, Ian Hall

Repeat asymptomatic testing in order to identify and quarantine infectious individuals has become a widely-used intervention to control SARS-CoV-2 transmission. In some workplaces,…

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…

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…

q-bio.PE2020

Challenges in control of Covid-19: short doubling time and long delay to effect of interventions

Lorenzo Pellis, Francesca Scarabel, Helena B. Stage +14

Early assessments of the spreading rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but more reliable…