Adaptive modeling of viral diseases in bats with a focus on rabies.
Identifieur interne : 001D40 ( Ncbi/Curation ); précédent : 001D39; suivant : 001D41Adaptive modeling of viral diseases in bats with a focus on rabies.
Auteurs : Dobromir T. Dimitrov [États-Unis] ; Thomas G. Hallam ; Charles E. Rupprecht ; Gary F. MccrackenSource :
- Journal of theoretical biology [ 1095-8541 ] ; 2008.
Descripteurs français
- KwdFr :
- Animaux, Chiroptera (immunologie), Chiroptera (virologie), Dynamique des populations, Humains, Maladies virales (immunologie), Maladies virales (transmission), Modèles biologiques, Modèles immunologiques, Rage (maladie) (transmission), Réservoirs d'agents pathogènes, Simulation numérique, Virus de la rage, Zoonoses (transmission).
- MESH :
- immunologie : Chiroptera, Maladies virales.
- virologie : Chiroptera.
- transmission : Animaux, Dynamique des populations, Humains, Maladies virales, Modèles biologiques, Modèles immunologiques, Rage (maladie), Réservoirs d'agents pathogènes, Simulation numérique, Virus de la rage, Zoonoses.
English descriptors
- KwdEn :
- MESH :
- immunology : Chiroptera, Virus Diseases.
- transmission : Rabies, Virus Diseases, Zoonoses.
- virology : Chiroptera.
- Animals, Computer Simulation, Disease Reservoirs, Humans, Models, Biological, Models, Immunological, Population Dynamics, Rabies virus.
Abstract
Many emerging and reemerging viruses, such as rabies, SARS, Marburg, and Ebola have bat populations as disease reservoirs. Understanding the spillover from bats to humans and other animals, and the associated health risks requires an analysis of the disease dynamics in bat populations. Traditional compartmental epizootic models, which are relatively easy to implement and analyze, usually impose unrealistic aggregation assumptions about disease-related structure and depend on parameters that frequently are not measurable in field conditions. We propose a novel combination of computational and adaptive modeling approaches that address the maintenance of emerging diseases in bat colonies through individual (intra-host) models of the response of the host to a viral challenge. The dynamics of the individual models are used to define survival, susceptibility and transmission conditions relevant to epizootics as well as to develop and parametrize models of the disease evolution into uniform and diverse populations. Applications of the proposed approach to modeling the effects of immunological heterogeneity on the dynamics of bat rabies are presented.
DOI: 10.1016/j.jtbi.2008.08.007
PubMed: 18761020
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pubmed:18761020Le document en format XML
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<term>Models, Biological</term>
<term>Models, Immunological</term>
<term>Population Dynamics</term>
<term>Rabies (transmission)</term>
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<term>Virus Diseases (immunology)</term>
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<term>Maladies virales (transmission)</term>
<term>Modèles biologiques</term>
<term>Modèles immunologiques</term>
<term>Rage (maladie) (transmission)</term>
<term>Réservoirs d'agents pathogènes</term>
<term>Simulation numérique</term>
<term>Virus de la rage</term>
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<term>Modèles immunologiques</term>
<term>Rage (maladie)</term>
<term>Réservoirs d'agents pathogènes</term>
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<front><div type="abstract" xml:lang="en">Many emerging and reemerging viruses, such as rabies, SARS, Marburg, and Ebola have bat populations as disease reservoirs. Understanding the spillover from bats to humans and other animals, and the associated health risks requires an analysis of the disease dynamics in bat populations. Traditional compartmental epizootic models, which are relatively easy to implement and analyze, usually impose unrealistic aggregation assumptions about disease-related structure and depend on parameters that frequently are not measurable in field conditions. We propose a novel combination of computational and adaptive modeling approaches that address the maintenance of emerging diseases in bat colonies through individual (intra-host) models of the response of the host to a viral challenge. The dynamics of the individual models are used to define survival, susceptibility and transmission conditions relevant to epizootics as well as to develop and parametrize models of the disease evolution into uniform and diverse populations. Applications of the proposed approach to modeling the effects of immunological heterogeneity on the dynamics of bat rabies are presented.</div>
</front>
</TEI>
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