A dynamic analysis of tuberculosis dissemination to improve control and surveillance

Autores
Zorzenon dos Santos, Rita M.; Amador, Ana; de Souza, Wayner V.; de Albuquerque, Maria Fatima P. M.; Ponce Dawson, Silvina Martha; Ruffino-Netto, Antonio; Zárate-Bladés, Carlos R.; Silva, Celio L.
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes. © 2010 Zorzenon dos Santos et al.
Fil: Zorzenon dos Santos, Rita M.. Universidade Federal de Pernambuco; Brasil
Fil: Amador, Ana. Universidade Federal de Pernambuco; Brasil. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: de Souza, Wayner V.. Fundación Oswaldo Cruz; Brasil
Fil: de Albuquerque, Maria Fatima P. M.. Universidade Federal de Pernambuco; Brasil. Fundación Oswaldo Cruz; Brasil
Fil: Ponce Dawson, Silvina Martha. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Ruffino-Netto, Antonio. Universidade de Sao Paulo; Brasil
Fil: Zárate-Bladés, Carlos R.. Universidade de Sao Paulo; Brasil
Fil: Silva, Celio L.. Universidade de Sao Paulo; Brasil
Materia
Tuberculosis
Analisis espacio-temporal
Diseminacion de enfermedades contagiosas
Percolacion
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/78303
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/78303
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A dynamic analysis of tuberculosis dissemination to improve control and surveillanceZorzenon dos Santos, Rita M.Amador, Anade Souza, Wayner V.de Albuquerque, Maria Fatima P. M.Ponce Dawson, Silvina MarthaRuffino-Netto, AntonioZárate-Bladés, Carlos R.Silva, Celio L.TuberculosisAnalisis espacio-temporalDiseminacion de enfermedades contagiosasPercolacionhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes. © 2010 Zorzenon dos Santos et al.Fil: Zorzenon dos Santos, Rita M.. Universidade Federal de Pernambuco; BrasilFil: Amador, Ana. Universidade Federal de Pernambuco; Brasil. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: de Souza, Wayner V.. Fundación Oswaldo Cruz; BrasilFil: de Albuquerque, Maria Fatima P. M.. Universidade Federal de Pernambuco; Brasil. Fundación Oswaldo Cruz; BrasilFil: Ponce Dawson, Silvina Martha. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Ruffino-Netto, Antonio. Universidade de Sao Paulo; BrasilFil: Zárate-Bladés, Carlos R.. Universidade de Sao Paulo; BrasilFil: Silva, Celio L.. Universidade de Sao Paulo; BrasilPublic Library of Science2010-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/78303Zorzenon dos Santos, Rita M.; Amador, Ana; de Souza, Wayner V.; de Albuquerque, Maria Fatima P. M.; Ponce Dawson, Silvina Martha; et al.; A dynamic analysis of tuberculosis dissemination to improve control and surveillance; Public Library of Science; Plos One; 5; 11; 11-2010; 141401-1414091932-6203CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0014140info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0014140info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:24:17Zoai:ri.conicet.gov.ar:11336/78303instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:24:17.591CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A dynamic analysis of tuberculosis dissemination to improve control and surveillance
title A dynamic analysis of tuberculosis dissemination to improve control and surveillance
spellingShingle A dynamic analysis of tuberculosis dissemination to improve control and surveillance
Zorzenon dos Santos, Rita M.
Tuberculosis
Analisis espacio-temporal
Diseminacion de enfermedades contagiosas
Percolacion
title_short A dynamic analysis of tuberculosis dissemination to improve control and surveillance
title_full A dynamic analysis of tuberculosis dissemination to improve control and surveillance
title_fullStr A dynamic analysis of tuberculosis dissemination to improve control and surveillance
title_full_unstemmed A dynamic analysis of tuberculosis dissemination to improve control and surveillance
title_sort A dynamic analysis of tuberculosis dissemination to improve control and surveillance
dc.creator.none.fl_str_mv Zorzenon dos Santos, Rita M.
Amador, Ana
de Souza, Wayner V.
de Albuquerque, Maria Fatima P. M.
Ponce Dawson, Silvina Martha
Ruffino-Netto, Antonio
Zárate-Bladés, Carlos R.
Silva, Celio L.
author Zorzenon dos Santos, Rita M.
author_facet Zorzenon dos Santos, Rita M.
Amador, Ana
de Souza, Wayner V.
de Albuquerque, Maria Fatima P. M.
Ponce Dawson, Silvina Martha
Ruffino-Netto, Antonio
Zárate-Bladés, Carlos R.
Silva, Celio L.
author_role author
author2 Amador, Ana
de Souza, Wayner V.
de Albuquerque, Maria Fatima P. M.
Ponce Dawson, Silvina Martha
Ruffino-Netto, Antonio
Zárate-Bladés, Carlos R.
Silva, Celio L.
author2_role author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Tuberculosis
Analisis espacio-temporal
Diseminacion de enfermedades contagiosas
Percolacion
topic Tuberculosis
Analisis espacio-temporal
Diseminacion de enfermedades contagiosas
Percolacion
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes. © 2010 Zorzenon dos Santos et al.
Fil: Zorzenon dos Santos, Rita M.. Universidade Federal de Pernambuco; Brasil
Fil: Amador, Ana. Universidade Federal de Pernambuco; Brasil. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: de Souza, Wayner V.. Fundación Oswaldo Cruz; Brasil
Fil: de Albuquerque, Maria Fatima P. M.. Universidade Federal de Pernambuco; Brasil. Fundación Oswaldo Cruz; Brasil
Fil: Ponce Dawson, Silvina Martha. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Ruffino-Netto, Antonio. Universidade de Sao Paulo; Brasil
Fil: Zárate-Bladés, Carlos R.. Universidade de Sao Paulo; Brasil
Fil: Silva, Celio L.. Universidade de Sao Paulo; Brasil
description Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes. © 2010 Zorzenon dos Santos et al.
publishDate 2010
dc.date.none.fl_str_mv 2010-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/78303
Zorzenon dos Santos, Rita M.; Amador, Ana; de Souza, Wayner V.; de Albuquerque, Maria Fatima P. M.; Ponce Dawson, Silvina Martha; et al.; A dynamic analysis of tuberculosis dissemination to improve control and surveillance; Public Library of Science; Plos One; 5; 11; 11-2010; 141401-141409
1932-6203
CONICET Digital
CONICET
url http://hdl.handle.net/11336/78303
identifier_str_mv Zorzenon dos Santos, Rita M.; Amador, Ana; de Souza, Wayner V.; de Albuquerque, Maria Fatima P. M.; Ponce Dawson, Silvina Martha; et al.; A dynamic analysis of tuberculosis dissemination to improve control and surveillance; Public Library of Science; Plos One; 5; 11; 11-2010; 141401-141409
1932-6203
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0014140
info:eu-repo/semantics/altIdentifier/doi/10.1371/journal.pone.0014140
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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