COVID-19 in Scottish care homes: A metapopulation model of spread among residents and staff.

The movement of populations between locations and activities can result in complex transmission dynamics, posing significant challenges in controlling infectious diseases like COVID-19. Notably, networks of care homes create an ecosystem where staff and visitor movement acts as a vector for disease transmission, contributing to the heightened risk for their vulnerable communities. Care homes in the UK were disproportionately affected by the first wave of the COVID-19 pandemic, accounting for almost half of COVID-19 deaths during the period of 6th March - 15th June 2020 and so there is a pressing need to explore modelling approaches suitable for such systems.

Modelling norovirus dynamics within oysters emphasises potential food safety issues associated with current testing & depuration protocols.

Norovirus is a significant global cause of viral gastroenteritis, with raw oyster consumption often linked to such outbreaks due to their filter-feeding in harvest waters. National water quality and depuration/relaying times are often classified using Escherichia coli, a poor proxy for norovirus levels in shellfish. The current norovirus assay is limited to only the digestive tracts of oysters, meaning the total norovirus load of an oyster may differ from reported results.

Expected goals in football: Improving model performance and demonstrating value.

Recently, football has seen the creation of various novel, ubiquitous metrics used throughout clubs' analytics departments. These can influence many of their day-to-day operations ranging from financial decisions on player transfers, to evaluation of team performance. At the forefront of this scientific movement is the metric expected goals, a measure which allows analysts to quantify how likely a given shot is to result in a goal however, xG models have not until this point considered using important features, e.

One model to rule them all? Modelling approaches across OneHealth for human, animal and plant epidemics.

One hundred years after the 1918 influenza outbreak, are we ready for the next pandemic? This paper addresses the need to identify and develop collaborative, interdisciplinary and cross-sectoral approaches to modelling of infectious diseases including the fields of not only human and veterinary medicine, but also plant epidemiology. Firstly, the paper explains the concepts on which the most common epidemiological modelling approaches are based, namely the division of a host population into susceptible, infected and removed (SIR) classes and the proportionality of the infection rate to the size of the susceptible and infected populations. It then demonstrates how these simple concepts have been developed into a vast and successful modelling framework that has been used in predicting and controlling disease outbreaks for over 100 years.

A model for estimating pathogen variability in shellfish and predicting minimum depuration times.

Norovirus is a major cause of viral gastroenteritis, with shellfish consumption being identified as one potential norovirus entry point into the human population. Minimising shellfish norovirus levels is therefore important for both the consumer's protection and the shellfish industry's reputation. One method used to reduce microbiological risks in shellfish is depuration; however, this process also presents additional costs to industry.