Publications

(upcoming) Diversity of symptom phenotypes in SARS-CoV-2 community infections observed in multiple large datasets

Published in (under review at Nature), available on Arxiv, 2021

We apply several cutting-edge unsupervised machine learning techniques to four large and diverse datasets of SARS-CoV-2 positive cases. We explore differences in symptomatic presentation across different ages, and find key differences in the symptomatic presentation of cases at the extremes of age across all datasets.\nPaper submitted to Nature.

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Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic

Published in Philosophical Transactions of the Royal Society B, 2021

Early results from our contact tracing analyses from early in the SARS-CoV-2 pandemic. Published as part of a special issue containing the evidence base used to support the UK goverments response to the SARS-CoV-2 pandemic.

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

Published in Infectious Disease Modelling, 2020

Motivated by the ongoing response to COVID-19, we provide a toolkit of statistical and mathematical models beyond the simple SIR-type differential equation models for analysing the early stages of an outbreak and assessing interventions.

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Martyn Fyles

Publications

(upcoming) Diversity of symptom phenotypes in SARS-CoV-2 community infections observed in multiple large datasets

Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic

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