This research introduces a model that integrates a logistic approach to alcohol consumption to delve into the effect of alcohol consumption on the advancement of hepatitis C infection, evaluates th...

Explore the article collection: Behavioural Epidemiology. Published in Mathematics in Medical and Life Sciences.

During the COVID-19 pandemic, Aotearoa followed an elimination strategy followed by a mitigation strategy, which saw high success and kept health impact low. However, there were inequities in healt...

This study explored relationships between exhaustion and disengagement among health sciences undergraduates at the Medical University of Gdańsk, using the Oldenburg Burnout Inventory (OLBI). We ass...

This paper is part of a special issue on Behavioural Epidemiology.Historically, responses to health-related emergencies (whether public health, veterinary health or plant health related) have expos...

Hearing loss is a growing public health concern, affecting millions and contributing to impaired communication, social isolation, and reduced quality of life. As a hidden condition, hearing loss is...

The primary objective of this study was to integrate several robust statistical techniques to address specific challenges inherent to the analysis of a large, multidimensional clinical dataset char...

Computing and data science have permeated diverse fields of knowledge in recent decades. In biology the change has been especially noticeable, as very large data sets are revising how science is do...

Accurate epidemic prediction is vital for public health interventions. Traditional models like the Susceptible-Infected-Recovered (SIR) model offer mechanistic insights but struggle with complex ep...

The mean curvature model is one of the efficient higher-order models for image denoising, and its Euler-Lagrange equation is a fourth-order nonlinear equation which makes the development of efficie...

Explore the article collection: Behavioural Epidemiology. Published in Mathematics in Medical and Life Sciences.

The COVID-19 pandemic underscored the importance of mass testing to mitigate the spread of the virus. This study presents mass-testing strategies developed through machine learning models, which pr...

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Estimating the exposure time to single infectious pathogens and the associated incubation period, based on symptom onset data, is crucial for identifying infection sources and implementing public h...

During the COVID-19 pandemic, universities experienced unique challenges, and current research has used mathematical models that leveraged model parameters calibrated to local contexts, such as hos...

During cancer invasion cells penetrate into healthy tissues by migrating through sub-cellular or sub-nuclear constrictions in the basal membrane or the extracellular matrix. Current therapies to co...

We describe a novel procedure for Bayesian cutpoint simulation in ordered probit models. Our approach capitalizes upon a series of auxiliary binary probit models implied by the ordinal probit to cr...

Published in MAA Convergence (Vol. 22, No. 1, 2025)

This paper is part of a special issue on Behavioural Epidemiology.In many epidemiological and ecological contexts, there is a trade-off between infections and interactions. This arises because the ...

Spatiotemporal correlations between meteo-inputs and wind-solar outputs in an optimal regional scale are inevitable in the evolution of robust models that are reliable in mid-term prediction time h...

Similarity fractal dimensions may predict clinical outcomes of Varithena treatment for superficial varicose veins of the great saphenous vein. Eight patients with symptomatic varicose veins receive...

Similarity fractal dimensions may predict clinical outcomes of Varithena treatment for superficial varicose veins of the great saphenous vein. Eight patients with symptomatic varicose veins receive...