Networks and the Epidemiology of Infectious Disease
By Leon Danon, Ashley P. Ford, Thomas A. House, Chris P. Jewell, M. Keeling, Gareth O. Roberts, Joshua V. Ross, Matthew C. Vernon. Interdisciplinary Perspectives on Infectious Diseases, 2010
488 citations recorded by the source corpus.
The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review the growing body of research concerning the spread of infectious diseases on networks, focusing on the interplay between network theory and epidemiology. The review is split into four main sections, which examine: the types of network relevant to epidemiology; the multitude of ways these networks can be characterised; the statistical methods that can be applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network. Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible. Instead, we provide a personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights. As such, considerable importance is placed on analytical approaches and statistical methods which are both rapidly expanding fields. Throughout this review we restrict our attention to epidemiological issues.
Subfields: Modeling and Simulation, Public Health, Environmental and Occupational Health, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/bd261f99eacd424cebcedc80dd322638623ed223
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Citations in the corpus
- Knowledge transfer in smart tourism destinations: Analyzing the effects of a network structure (2015, methodology): “For what concerns our cases we can use an epidemiological modelling approach (Danon et al., 2011; LópezPintado, 2008).”
- Mathematical models to characterize early epidemic growth: A Review (2016, unknown): “For a comprehensive review of network epidemic modeling methods, we point the reader to [70].”
- Modeling infectious disease dynamics in the complex landscape of global health (2015, unknown): “Increasing sophistication of contact network models (42), together with data on epidemiological contacts, creates opportunities for understanding and controlling transmission at a fundamental level (43) and opens up the possibility of independent study of relevant social factors (10).”
- Impacts of climate change on plant diseases—opinions and trends (2012, background): “…consensus that prediction and management of climate change effects on plant health are complicated by interactions between globalization, shifts in climate, pollution and increasing numbers of invasive plants, pests and pathogens (Mistretta 2002; DesprezLoustau et al. 2007a; Danon et al. 2011; Fig.”