ArticleChaos, solitons, and fractals2020
Assessing functional propagation patterns in COVID-19.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Exploring the correlations betweenJournal of hazardous materials advances · 2023Article
- A straightforward edge centrality concept derived from generalizing degree and strength.Scientific reports · 2022Article
- Simplifying functional network representation and interpretation through causality clustering.Scientific reports · 2021Article
- Trends in Incidence and Transmission Patterns of COVID-19 in Valencia, Spain.JAMA network open · 2021Article
- A Bayesian spatio-temporal analysis of mortality rates in Spain: application to the COVID-19 2020 outbreak.Population health metrics · 2021Article
- A minimal model of hospital patients' dynamics in COVID-19.Chaos, solitons, and fractals · 2020Article
- Travel restrictions during pandemics: A useful strategy?Chaos (Woodbury, N.Y.) · 2020Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Among the many efforts done by the scientific community to help coping with the COVID-19 pandemic, one of the most important has been the creation of models to describe its propagation, as these are expected to guide the deployment of containment and health policies. These models are commonly based on exogenous information, as e.g. mobility data, whose limitedness always compromise the reliability of obtained results. In this contribution we propose a different approach, based on extracting relationships between the evolution of the disease in different regions through information theoretical metrics. In a way similar to what is commonly done in neuroscience, propagation is understood as information transfer, and the resulting propagation patterns are represented and studied as functional networks. By applying this methodology to the dynamics of COVID-19 in several countries and regions thereof, we were able to reconstruct static and time-varying propagation graphs. We further discuss the advantages, promises and open research questions associated with this functional approach.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.