Transmission of severe acute respiratory syndrome in dynamical small-world networks.
Identifieur interne : 004F97 ( Main/Exploration ); précédent : 004F96; suivant : 004F98Transmission of severe acute respiratory syndrome in dynamical small-world networks.
Auteurs : Naoki Masuda [Japon] ; Norio Konno ; Kazuyuki AiharaSource :
- Physical review. E, Statistical, nonlinear, and soft matter physics [ 1539-3755 ] ; 2004.
Descripteurs français
- KwdFr :
- Contrôle des maladies contagieuses (), Flambées de maladies, Humains, Modèles biologiques, Modèles de hasards proportionnels, Simulation numérique, Syndrome respiratoire aigu sévère (), Syndrome respiratoire aigu sévère (transmission), Syndrome respiratoire aigu sévère (épidémiologie), Écosystème, Évaluation des risques ().
- MESH :
English descriptors
- KwdEn :
- Communicable Disease Control (methods), Computer Simulation, Disease Outbreaks, Ecosystem, Humans, Models, Biological, Proportional Hazards Models, Risk Assessment (methods), Severe Acute Respiratory Syndrome (epidemiology), Severe Acute Respiratory Syndrome (prevention & control), Severe Acute Respiratory Syndrome (transmission).
- MESH :
- epidemiology : Severe Acute Respiratory Syndrome.
- methods : Communicable Disease Control, Risk Assessment.
- prevention & control : Severe Acute Respiratory Syndrome.
- transmission : Severe Acute Respiratory Syndrome.
- Computer Simulation, Disease Outbreaks, Ecosystem, Humans, Models, Biological, Proportional Hazards Models.
Abstract
The outbreak of severe acute respiratory syndrome (SARS) is still threatening the world because of a possible resurgence. In the current situation that effective medical treatments such as antiviral drugs are not discovered yet, dynamical features of the epidemics should be clarified for establishing strategies for tracing, quarantine, isolation, and regulating social behavior of the public at appropriate costs. Here we propose a network model for SARS epidemics and discuss why superspreaders emerged and why SARS spread especially in hospitals, which were key factors of the recent outbreak. We suggest that superspreaders are biologically contagious patients, and they may amplify the spreads by going to potentially contagious places such as hospitals. To avoid mass transmission in hospitals, it may be a good measure to treat suspected cases without hospitalizing them. Finally, we indicate that SARS probably propagates in small-world networks associated with human contacts and that the biological nature of individuals and social group properties are factors more important than the heterogeneous rates of social contacts among individuals. This is in marked contrast with epidemics of sexually transmitted diseases or computer viruses to which scale-free network models often apply.
DOI: 10.1103/PhysRevE.69.031917
PubMed: 15089332
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">The outbreak of severe acute respiratory syndrome (SARS) is still threatening the world because of a possible resurgence. In the current situation that effective medical treatments such as antiviral drugs are not discovered yet, dynamical features of the epidemics should be clarified for establishing strategies for tracing, quarantine, isolation, and regulating social behavior of the public at appropriate costs. Here we propose a network model for SARS epidemics and discuss why superspreaders emerged and why SARS spread especially in hospitals, which were key factors of the recent outbreak. We suggest that superspreaders are biologically contagious patients, and they may amplify the spreads by going to potentially contagious places such as hospitals. To avoid mass transmission in hospitals, it may be a good measure to treat suspected cases without hospitalizing them. Finally, we indicate that SARS probably propagates in small-world networks associated with human contacts and that the biological nature of individuals and social group properties are factors more important than the heterogeneous rates of social contacts among individuals. This is in marked contrast with epidemics of sexually transmitted diseases or computer viruses to which scale-free network models often apply.</div>
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