Search

Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models. [ABSTRACT FROM AUTHOR]

To what extent did the Covid-19 pandemic affect the tools, priorities and organisation of cultural policies? And did the pandemic enhance the digital aspect of these policies? This paper compares pandemic cultural policy measures in seven European countries to answer these questions. The countries all installed a plurality of mitigating measures, combining grants and subsidies, compensation of lost income, income support and financial flexibility, creating a tendency towards cultural policy turning into economic policy, fiscal policy, and labour market policy. Cultural policies have not been fundamentally challenged by the pandemic, in the sense that it has affected the essential political tools, divisions of labour, or core goals. The responses have confirmed an existing policy structure or enhanced existing developments. The importance of a state-centred or a federalist cultural policy system has not been challenged in a substantial way. Secondly there is little evidence to show a general acceleration of national digital cultural policies. [ABSTRACT FROM AUTHOR]

Global energy consumption is growing rapidly, with the frequency and intensity of extreme events constantly increasing, posing a long-term threat to power supply and consumption. Therefore, analyzing the spatiotemporal characteristics of electricity consumption and quantitatively assessing the impact of extreme events on electricity consumption are of great significance. Based on fine-grained electricity consumption data from Europe for the years 2019–2022, this paper employs a data mining perspective and four methods including Z-score, Isolation Forest, Local Outlier Factor, and Autoencoder to detect abnormal electricity consumption during extreme events. Additionally, it combines indicators such as elastic loss, vulnerability, and duration to measure the impact of extreme events on electricity consumption. It is found that low temperatures could lead to abrupt changes in electricity consumption, with Northern Europe being more significantly affected by low temperatures. The COVID-19 pandemic had the most significant impact on electricity consumption in Europe, with the middle part of Europe being the hardest hit during the first wave of the pandemic. Electricity anomalies during the pandemic period were related to national pandemic control policies and exhibited some lag. High temperatures persisted for a longer duration in the middle part of Europe. [ABSTRACT FROM AUTHOR]

This paper investigates how restriction policies have impacted elderly self-assessed health (SAH) in Europe during the pandemic, and how the Covid-19 infection interacts with policy stringency to modulate the SAH deterioration. Using the Survey of Health, Aging and Retirement in Europe (SHARE) between October 2019 and August 2021, including 9,034 adults aged 50 years and above, alongside with a stringency index from the Oxford's Coronavirus Government Response Tracker (OxCGRT), we design both an adjusted probit model and a recursive bivariate probit model to test for endogeneity of Covid-19 infection. Estimations results show a bell curve between stringency and SAH degradation: a deleterious effect of restrictions at low levels of stringency up to a tipping point after which more stringent policies become protective. Covid-19 infection moderates this association. Depending on individuals' initial health, the effect of restrictions is uneven: highly stringent policies become damaging for individuals most likely to enter a vulnerabilization path, for whom the bell curve is thus inverted. Overall, this study shows clear patterns of association between policy stringency and perceived health among older Europeans, and highlights the potential trade-off between targeting as many people as possible, those in poor health or those on the edge of vulnerability. • The association between policy stringency and SAH degradation is a bell curve. • Strict restrictions only affect the SAH of people likely to become vulnerable. • Covid-19 infection moderates the deterioration of SAH caused by policy stringency. • The recursive bivariate probit model controls for endogeneity in infection. [ABSTRACT FROM AUTHOR]

Although Covid-19 was not the first pandemic, it was unique in the scale and intensity with which societies responded. Countries reacted differently to the threat posed by the new virus. The public health crisis affected European societies in many ways. It also influenced the way the media portrayed vaccines and discussed factors related to vaccine hesitancy. Europeans differed in their risk perceptions, attitudes towards vaccines and vaccine uptake. In European countries, Covid-19-related discourses were at the centre of media attention for many months. This paper reports on a media analysis which revealed significant differences as well as some similarities in the media debates in different countries. The study focused on seven European countries and considered two dimensions of comparison: between the pre-Covid period and the beginning of the Covid pandemic period, and between countries. The rich methodological approach, including linguistics, semantic field analysis and discourse analysis of mainstream news media, allowed the authors to explore the set of meanings related to vaccination that might influence actors' agency. This approach led the authors to redefine vaccine hesitancy in terms of characteristics of the "society in the situation" rather than the psychological profile of individuals. We argue that vaccine hesitancy can be understood in terms of agency and temporality. This dilemma of choice that transforms the present into an irreversible past and must be taken in relation to an uncertain future, is particularly acute under the pressure of urgency and when someone's health is at stake. As such, it is linked to how vaccine meaning is co-produced within public discourses. • Vaccine hesitancy is co-produced by media discourses. • Covid-19 caused a shift in European vaccine discourses. • Discursive shift from prevention (future) to effective vaccine distribution (now). • Vaccine hesitancy is mediated through temporal structures in agents' orientation. [ABSTRACT FROM AUTHOR]