Journal ArticleDOI
Predicting the Spread of COVID-19 in Italy using Machine Learning: Do Socio-Economic Factors Matter?
TLDR
In this paper, the authors exploit the provincial variability of COVID-19 cases registered in Italy to select the territorial predictors of the pandemic, and apply machine learning to isolate, among 77 potential predictors, those that minimize the out-of-sample prediction error.About:
This article is published in Structural Change and Economic Dynamics.The article was published on 2021-03-01. It has received 20 citations till now.read more
Citations
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Journal ArticleDOI
International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors.
Elza Bontempi,Mario Coccia +1 more
TL;DR: In this paper, a case study on 107 provinces of Italy, one of the first countries to experience a rapid increase in confirmed cases and deaths, showed that total import and export of provinces has a high association with confirmed cases over time (average r ≥ 0.78, p-value <.001).
Journal ArticleDOI
Does regional integration improve economic resilience? Evidence from urban agglomerations in China
TL;DR: In this article , the authors considered urban agglomeration planning as a quasi-natural experiment of regional integration and use a difference-in-differences method to explore the effect of region integration on economic resilience.
Journal ArticleDOI
Mobility in times of pandemics: evidence on the spread of Covid19 in Italy's labour market areas
TL;DR: In this article, the authors investigate the interplay between the local spread of COVID-19 and patterns of individual mobility within and across self-contained geographical areas, and explore how individual mobility plays different roles in LMAs hosting industrial districts.
Journal ArticleDOI
Exploring the spatio-temporal evolution of economic resilience in Chinese cities during the COVID-19 crise
TL;DR: Based on economic resilience measured from undesired economic output, the economic resilience of Chinese cities in 2020 was analyzed using GIS to characterize the spatio-temporal evolution of globality and local interactions as discussed by the authors .
Journal ArticleDOI
Spatiotemporal Dynamic of COVID-19 Diffusion in China: A Dynamic Spatial Autoregressive Model Analysis
TL;DR: China’s policies for controlling the spread of the epidemic, specifically with respect to limiting inter-city mobility and implementing intra-city travel restrictions (social isolation), were most effective in reducing the viral transmission of COVID-19.
References
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Book
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
TL;DR: In this paper, the authors describe the important ideas in these areas in a common conceptual framework, and the emphasis is on concepts rather than mathematics, with a liberal use of color graphics.
Journal ArticleDOI
Regularization and variable selection via the elastic net
Hui Zou,Trevor Hastie +1 more
TL;DR: It is shown that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation, and an algorithm called LARS‐EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lamba.
Journal ArticleDOI
Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe.
Seth Flaxman,Swapnil Mishra,Axel Gandy,H. Juliette T. Unwin,Thomas A. Mellan,Helen Coupland,Charles Whittaker,Harrison Zhu,Tresnia Berah,Jeffrey W. Eaton,Melodie Monod,Azra C. Ghani,Christl A. Donnelly,Christl A. Donnelly,Steven Riley,Michaela A. C. Vollmer,Neil M. Ferguson,Lucy C Okell,Samir Bhatt +18 more
TL;DR: The results show that major non-pharmaceutical interventions and lockdown in particular have had a large effect on reducing transmission and continued intervention should be considered to keep transmission of SARS-CoV-2 under control.
BookDOI
Statistical Learning with Sparsity: The Lasso and Generalizations
TL;DR: Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data and extract useful and reproducible patterns from big datasets.
Journal ArticleDOI
School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review.
Russell M Viner,Simon Russell,Helen Croker,Jessica Packer,Joseph L Ward,Claire Stansfield,Oliver T Mytton,Chris Bonell,Robert Booy +8 more
TL;DR: Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that combinations of social distancing measures should be considered.
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Moayyad Shawaqfah,Fares Almomani +1 more