SrasV1, Ncbi, Merge, bibRecord, 001959

Epidemic modeling in complex realities.

Identifieur interne : 001959 ( Ncbi/Merge ); précédent : 001958; suivant : 001960

Epidemic modeling in complex realities.

Auteurs : Vittoria Colizza [États-Unis] ; Marc Barthélemy ; Alain Barrat ; Alessandro Vespignani

Source :

Comptes rendus biologies [ 1631-0691 ] ; 2007.

RBID : pubmed:17502293

Descripteurs français

KwdFr :
- Europe (épidémiologie), Facteurs socioéconomiques, Humains, Peste (mortalité), Peste (épidémiologie), Population, Santé mondiale, Syndrome respiratoire aigu sévère (épidémiologie), Virus du SRAS, Voyage, Épidémiologie ().
MESH :
- mortalité : Peste.
- épidémiologie : Europe, Peste, Syndrome respiratoire aigu sévère.
- Facteurs socioéconomiques, Humains, Population, Santé mondiale, Virus du SRAS, Voyage, Épidémiologie.

English descriptors

KwdEn :
- Epidemiology (statistics & numerical data), Europe (epidemiology), Global Health, Humans, Plague (epidemiology), Plague (mortality), Population, SARS Virus, Severe Acute Respiratory Syndrome (epidemiology), Socioeconomic Factors, Travel.
MESH :
- geographic , epidemiology : Europe.
- epidemiology : Plague, Severe Acute Respiratory Syndrome.
- mortality : Plague.
- statistics & numerical data : Epidemiology.
- Global Health, Humans, Population, SARS Virus, Socioeconomic Factors, Travel.

Abstract

In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.

DOI: 10.1016/j.crvi.2007.02.014
PubMed: 17502293

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pubmed:17502293

Le document en format XML

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<term>Plague (epidemiology)</term>
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<term>Peste (mortalité)</term>
<term>Peste (épidémiologie)</term>
<term>Population</term>
<term>Santé mondiale</term>
<term>Syndrome respiratoire aigu sévère (épidémiologie)</term>
<term>Virus du SRAS</term>
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<term>Épidémiologie ()</term>
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<front><div type="abstract" xml:lang="en">In our global world, the increasing complexity of social relations and transport infrastructures are key factors in the spread of epidemics. In recent years, the increasing availability of computer power has enabled both to obtain reliable data allowing one to quantify the complexity of the networks on which epidemics may propagate and to envision computational tools able to tackle the analysis of such propagation phenomena. These advances have put in evidence the limits of homogeneous assumptions and simple spatial diffusion approaches, and stimulated the inclusion of complex features and heterogeneities relevant in the description of epidemic diffusion. In this paper, we review recent progresses that integrate complex systems and networks analysis with epidemic modelling and focus on the impact of the various complex features of real systems on the dynamics of epidemic spreading.</div>
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Epidemic modeling in complex realities.

Epidemic modeling in complex realities.

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

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Pour générer des pages wiki