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dc.contributor.author
Aparicio, Juan Pablo  
dc.contributor.author
Castillo Chavez, Carlos  
dc.date.available
2019-03-08T19:54:25Z  
dc.date.issued
2009-04  
dc.identifier.citation
Aparicio, Juan Pablo; Castillo Chavez, Carlos; Mathematical modelling of tuberculosis epidemics; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 6; 2; 4-2009; 209-237  
dc.identifier.issn
1547-1063  
dc.identifier.uri
http://hdl.handle.net/11336/71276  
dc.description.abstract
The strengths and limitations of using homogeneous mixing and heterogeneous mixing epidemic models are explored in the context of the transmission dynamics of tuberculosis. The focus is on three types of models: a standard incidence homogeneous mixing model, a non-homogeneous mixing model that incorporates 'household' contacts, and an age-structured model. The models are parameterized using demographic and epidemiological data and the patterns generated from these models are compared. Furthermore, the effects of population growth, stochasticity, clustering of contacts, and age structure on disease dynamics are explored. This framework is used to asses the possible causes for the observed historical decline of tuberculosis notifications.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Institute of Mathematical Sciences  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Demography  
dc.subject
Non-Autonomous Systems  
dc.subject
Stochastic Models  
dc.subject
Tuberculosis  
dc.subject.classification
Matemática Pura  
dc.subject.classification
Matemáticas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Mathematical modelling of tuberculosis epidemics  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-01-23T18:56:11Z  
dc.journal.volume
6  
dc.journal.number
2  
dc.journal.pagination
209-237  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Springfield  
dc.description.fil
Fil: Aparicio, Juan Pablo. Universidad Metropolitana San Juan; Puerto Rico. Universidad Nacional de Salta; Argentina  
dc.description.fil
Fil: Castillo Chavez, Carlos. Arizona State University. School Of Human Evolution And Social Change; Estados Unidos. Mathematical, Computational and Modeling Sciences Center; Estados Unidos. Santa Fe Institute; Estados Unidos  
dc.journal.title
Mathematical Biosciences And Engineering  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.3934/mbe.2009.6.209  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/www.aimsciences.org/article/doi/10.3934/mbe.2009.6.209