ArticleEcological modelling2018
The intrinsic vulnerability of networks to epidemics.
Article in Ecological modelling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Food availability leads to more connected contact networks among peridomestic zoonotic reservoir hosts.Royal Society open science · 2023Article
- The role of social structure and dynamics in the maintenance of endemic disease.Behavioral ecology and sociobiology · 2021Review
- Landscape simplification shapes pathogen prevalence in plant-pollinator networks.Ecology letters · 2020Article
- Identification of critical airports for controlling global infectious disease outbreaks: Stress-tests focusing in Europe.Journal of air transport management · 2020Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Contact networks are convenient models to investigate epidemics, with nodes and links representing potential hosts and infection pathways, respectively. The outcomes of outbreak simulations on networks are driven both by the underlying epidemic model, and by the networks' structural properties, so that the same pathogen can generate different epidemic dynamics on different networks. Here we ask whether there are general properties that make a contact network intrinsically vulnerable to epidemics (that is, regardless of specific epidemiological parameters). By conducting simulations on a large set of modelled networks, we show that, when a broad range of network topologies is taken into account, the effect of specific network properties on outbreak magnitude is stronger than that of fundamental pathogen features such as transmission rate, infection duration, and immunization ability. Then, by focusing on a large set of real world networks of the same type (potential contacts between field voles,
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