A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic

no code implementations • Environment International 2023 • Guangquan Li, Hubert Denise, Peter Diggle, Jasmine Grimsley, Chris Holmes, Daniel James, Radka Jersakova, Callum Mole, George Nicholson, Camila Rangel Smith, Sylvia Richardson, William Rowe, Barry Rowlingson, Fatemeh Torabi, Matthew J. Wade, Marta Blangiardo

Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time.

Epidemiology

A large-scale and PCR-referenced vocal audio dataset for COVID-19

1 code implementation • 15 Dec 2022 • Jobie Budd, Kieran Baker, Emma Karoune, Harry Coppock, Selina Patel, Ana Tendero Cañadas, Alexander Titcomb, Richard Payne, David Hurley, Sabrina Egglestone, Lorraine Butler, Jonathon Mellor, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Radka Jersakova, Rachel A. McKendry, Peter Diggle, Sylvia Richardson, Björn W. Schuller, Steven Gilmour, Davide Pigoli, Stephen Roberts, Josef Packham, Tracey Thornley, Chris Holmes

The UK COVID-19 Vocal Audio Dataset represents the largest collection of SARS-CoV-2 PCR-referenced audio recordings to date.

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers

1 code implementation • 15 Dec 2022 • Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven Gilmour, Stephen Roberts, Chris Holmes

Recent work has reported that AI classifiers trained on audio recordings can accurately predict severe acute respiratory syndrome coronavirus 2 (SARSCoV2) infection status.

Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19

no code implementations • 15 Dec 2022 • Davide Pigoli, Kieran Baker, Jobie Budd, Lorraine Butler, Harry Coppock, Sabrina Egglestone, Steven G. Gilmour, Chris Holmes, David Hurley, Radka Jersakova, Ivan Kiskin, Vasiliki Koutra, Jonathon Mellor, George Nicholson, Joe Packham, Selina Patel, Richard Payne, Stephen J. Roberts, Björn W. Schuller, Ana Tendero-Cañadas, Tracey Thornley, Alexander Titcomb

Since early in the coronavirus disease 2019 (COVID-19) pandemic, there has been interest in using artificial intelligence methods to predict COVID-19 infection status based on vocal audio signals, for example cough recordings.

Inferring proximity from Bluetooth Low Energy RSSI with Unscented Kalman Smoothers

no code implementations • 9 Jul 2020 • Tom Lovett, Mark Briers, Marcos Charalambides, Radka Jersakova, James Lomax, Chris Holmes

The Covid-19 pandemic has resulted in a variety of approaches for managing infection outbreaks in international populations.