Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da FIOCRUZ (ARCA) |
Texto Completo: | https://www.arca.fiocruz.br/handle/icict/59413 |
Resumo: | Department of Epidemiology and Public Health. Swiss Tropical and Public Health Institute. Basel, Switzerland / University of Basel. Basel, Switzerland. |
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Karagiannis-Voules, Dimitrios-AlexiosScholte, Ronaldo Guilherme CarvalhoGuimarães, Luiz H.Utzinger, JürgVounatsou, Penelope2023-07-05T12:33:54Z2023-07-05T12:33:54Z2013KARAGIANNIS-VOULES, Dimitrios-Alexios et al. Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil. PLOS Neglected Tropical Diseases, v. 7, n. 5, p. 1-13, e2213, 2013.1935-2735https://www.arca.fiocruz.br/handle/icict/5941310.1371/journal.pntd.0002213engPublic Library of ScienceBayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleDepartment of Epidemiology and Public Health. Swiss Tropical and Public Health Institute. Basel, Switzerland / University of Basel. Basel, Switzerland.Department of Epidemiology and Public Health. Swiss Tropical and Public Health Institute. Basel, Switzerland / University of Basel. Basel, Switzerland / Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brazil.Universidade Federal da Bahia. Complexo Hospitalar Universitário Prof. Edgard Santos. Serviço de Imunologia. Salvador, BA, Brazil.Department of Epidemiology and Public Health. Swiss Tropical and Public Health Institute. Basel, Switzerland / University of Basel. Basel, Switzerland.Department of Epidemiology and Public Health. Swiss Tropical and Public Health Institute. Basel, Switzerland / University of Basel. Basel, Switzerland.Background: Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries. Methodology: We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010). Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis. Principal findings: For both types of leishmaniasis, precipitation and socioeconomic proxies were identified as important risk factors. The predicted number of cases in 2010 were 30,189 (standard deviation [SD]: 7,676) for cutaneous leishmaniasis and 4,889 (SD: 288) for visceral leishmaniasis. Our risk maps predicted the highest numbers of infected people in the states of Minas Gerais and Pará for visceral and cutaneous leishmaniasis, respectively. Conclusions/significance: Our spatially explicit, high-resolution incidence maps identified priority areas where leishmaniasis control efforts should be targeted with the ultimate goal to reduce disease incidence.LeishmaniasisEndemicLeishmaniasis incidenceRisk factorsinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZORIGINALpntd.0002213 1..13.pdfpntd.0002213 1..13.pdfapplication/pdf1330806https://www.arca.fiocruz.br/bitstream/icict/59413/2/pntd.0002213%201..13.pdf594cc44f1468f728e830fdf61852760dMD52LICENSElicense.txttext/plain1748https://www.arca.fiocruz.br/bitstream/icict/59413/1/license.txt8a4605be74aa9ea9d79846c1fba20a33MD51icict/594132023-07-05 23:37:55.67oai:www.arca.fiocruz.br:icict/59413Tk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=Repositório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352023-07-06T02:37:55Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false |
dc.title.en_US.fl_str_mv |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
title |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
spellingShingle |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil Karagiannis-Voules, Dimitrios-Alexios Leishmaniasis Endemic Leishmaniasis incidence Risk factors |
title_short |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
title_full |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
title_fullStr |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
title_full_unstemmed |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
title_sort |
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil |
author |
Karagiannis-Voules, Dimitrios-Alexios |
author_facet |
Karagiannis-Voules, Dimitrios-Alexios Scholte, Ronaldo Guilherme Carvalho Guimarães, Luiz H. Utzinger, Jürg Vounatsou, Penelope |
author_role |
author |
author2 |
Scholte, Ronaldo Guilherme Carvalho Guimarães, Luiz H. Utzinger, Jürg Vounatsou, Penelope |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Karagiannis-Voules, Dimitrios-Alexios Scholte, Ronaldo Guilherme Carvalho Guimarães, Luiz H. Utzinger, Jürg Vounatsou, Penelope |
dc.subject.en.none.fl_str_mv |
Leishmaniasis Endemic Leishmaniasis incidence Risk factors |
topic |
Leishmaniasis Endemic Leishmaniasis incidence Risk factors |
description |
Department of Epidemiology and Public Health. Swiss Tropical and Public Health Institute. Basel, Switzerland / University of Basel. Basel, Switzerland. |
publishDate |
2013 |
dc.date.issued.fl_str_mv |
2013 |
dc.date.accessioned.fl_str_mv |
2023-07-05T12:33:54Z |
dc.date.available.fl_str_mv |
2023-07-05T12:33:54Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
KARAGIANNIS-VOULES, Dimitrios-Alexios et al. Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil. PLOS Neglected Tropical Diseases, v. 7, n. 5, p. 1-13, e2213, 2013. |
dc.identifier.uri.fl_str_mv |
https://www.arca.fiocruz.br/handle/icict/59413 |
dc.identifier.issn.en_US.fl_str_mv |
1935-2735 |
dc.identifier.doi.none.fl_str_mv |
10.1371/journal.pntd.0002213 |
identifier_str_mv |
KARAGIANNIS-VOULES, Dimitrios-Alexios et al. Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil. PLOS Neglected Tropical Diseases, v. 7, n. 5, p. 1-13, e2213, 2013. 1935-2735 10.1371/journal.pntd.0002213 |
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https://www.arca.fiocruz.br/handle/icict/59413 |
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eng |
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eng |
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Public Library of Science |
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Public Library of Science |
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