COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a
pandemic by the World Health Organisation (WHO) in March 2020. By mid-August 2020 …

A pervasive challenge in neuroscience is testing whether neuronal connectivity changes
over time due to specific causes, such as stimuli, events, or clinical interventions. Recent …

The novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has
rapidly spread around the world, causing serious illness and death and creating a heavy …

We employ the epidemic Renormalization Group (eRG) framework to understand, reproduce
and predict the COVID-19 pandemic diffusion across the US. The human mobility across …

This paper concerns structure learning or discovery of discrete generative models. It focuses
on Bayesian model selection and the assimilation of training data or content, with a special …

In this paper, we evaluate the effect of the state of emergency for the first wave of COVID-19
in Japan, 2020 from the viewpoint of mathematical modelling. In Japan, it was announced …

Objectives To identify differences in the clinical and epidemiologic characteristics of patients
during the first and second waves of the COVID-19 pandemic at the EsSalud Lambayeque …

Newly emerging infectious diseases, such as the coronavirus (COVID-19), create new
challenges for public healthcare systems. Before effective treatments, countering the spread …

We apply a generalized logistic growth model, with time-dependent parameters, to describe
the fatality curves of the COVID-19 disease for several countries that exhibit multiple waves …

This technical report describes the dynamic causal modelling of mitigated epidemiological
outcomes during the COVID-9 coronavirus outbreak in 2020. Dynamic causal modelling is a …