Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil.
Rio de Janeiro, Brazil, experienced a severe dengue fever epidemic in 2008. This was the worst epidemic ever, characterized by a sharp increase in case-fatality rate, mainly among younger individuals. A combination of factors, such as climate, mosquito abundance, buildup of the susceptible populatio...
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ftdoajarticles:oai:doaj.org/article:1020ec8672da44568a12568cf7713113 2023-05-15T15:16:53+02:00 Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. Nildimar Alves Honório Rita Maria Ribeiro Nogueira Cláudia Torres Codeço Marilia Sá Carvalho Oswaldo Gonçalves Cruz Mônica de Avelar Figueiredo Mafra Magalhães Josélio Maria Galvão de Araújo Eliane Saraiva Machado de Araújo Marcelo Quintela Gomes Luciane Silva Pinheiro Célio da Silva Pinel Ricardo Lourenço-de-Oliveira 2009-11-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0000545 https://doaj.org/article/1020ec8672da44568a12568cf7713113 EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC2768822?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0000545 https://doaj.org/article/1020ec8672da44568a12568cf7713113 PLoS Neglected Tropical Diseases, Vol 3, Iss 11, p e545 (2009) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2009 ftdoajarticles https://doi.org/10.1371/journal.pntd.0000545 2022-12-31T13:34:20Z Rio de Janeiro, Brazil, experienced a severe dengue fever epidemic in 2008. This was the worst epidemic ever, characterized by a sharp increase in case-fatality rate, mainly among younger individuals. A combination of factors, such as climate, mosquito abundance, buildup of the susceptible population, or viral evolution, could explain the severity of this epidemic. The main objective of this study is to model the spatial patterns of dengue seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro. As blood sampling coincided with the peak of dengue transmission, we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance. We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model (GAM).Three neighborhoods were investigated: a central urban neighborhood, and two isolated areas characterized as a slum and a suburban area. Weekly mosquito collections started in September 2006 and continued until March 2008. In each study area, 40 adult traps and 40 egg traps were installed in a random sample of premises, and two infestation indexes calculated: mean adult density and mean egg density. Sera from individuals living in the three neighborhoods were collected before the 2008 epidemic (July through November 2007) and during the epidemic (February through April 2008). Sera were tested for DENV-reactive IgM, IgG, Nested RT-PCR, and Real Time RT-PCR. From the before-after epidemics paired data, we described seroprevalence, recent dengue infections (asymptomatic or not), and seroconversion. Recent dengue infection varied from 1.3% to 14.1% among study areas. The highest IgM seropositivity occurred in the slum, where mosquito abundance was the lowest, but household conditions were the best for promoting contact between hosts and vectors. By fitting spatial GAM we found dengue seroprevalence hotspots located at the entrances of the two isolated communities, which are commercial ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Gam ENVELOPE(-57.955,-57.955,-61.923,-61.923) PLoS Neglected Tropical Diseases 3 11 e545 |
institution |
Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Nildimar Alves Honório Rita Maria Ribeiro Nogueira Cláudia Torres Codeço Marilia Sá Carvalho Oswaldo Gonçalves Cruz Mônica de Avelar Figueiredo Mafra Magalhães Josélio Maria Galvão de Araújo Eliane Saraiva Machado de Araújo Marcelo Quintela Gomes Luciane Silva Pinheiro Célio da Silva Pinel Ricardo Lourenço-de-Oliveira Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Rio de Janeiro, Brazil, experienced a severe dengue fever epidemic in 2008. This was the worst epidemic ever, characterized by a sharp increase in case-fatality rate, mainly among younger individuals. A combination of factors, such as climate, mosquito abundance, buildup of the susceptible population, or viral evolution, could explain the severity of this epidemic. The main objective of this study is to model the spatial patterns of dengue seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro. As blood sampling coincided with the peak of dengue transmission, we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance. We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model (GAM).Three neighborhoods were investigated: a central urban neighborhood, and two isolated areas characterized as a slum and a suburban area. Weekly mosquito collections started in September 2006 and continued until March 2008. In each study area, 40 adult traps and 40 egg traps were installed in a random sample of premises, and two infestation indexes calculated: mean adult density and mean egg density. Sera from individuals living in the three neighborhoods were collected before the 2008 epidemic (July through November 2007) and during the epidemic (February through April 2008). Sera were tested for DENV-reactive IgM, IgG, Nested RT-PCR, and Real Time RT-PCR. From the before-after epidemics paired data, we described seroprevalence, recent dengue infections (asymptomatic or not), and seroconversion. Recent dengue infection varied from 1.3% to 14.1% among study areas. The highest IgM seropositivity occurred in the slum, where mosquito abundance was the lowest, but household conditions were the best for promoting contact between hosts and vectors. By fitting spatial GAM we found dengue seroprevalence hotspots located at the entrances of the two isolated communities, which are commercial ... |
format |
Article in Journal/Newspaper |
author |
Nildimar Alves Honório Rita Maria Ribeiro Nogueira Cláudia Torres Codeço Marilia Sá Carvalho Oswaldo Gonçalves Cruz Mônica de Avelar Figueiredo Mafra Magalhães Josélio Maria Galvão de Araújo Eliane Saraiva Machado de Araújo Marcelo Quintela Gomes Luciane Silva Pinheiro Célio da Silva Pinel Ricardo Lourenço-de-Oliveira |
author_facet |
Nildimar Alves Honório Rita Maria Ribeiro Nogueira Cláudia Torres Codeço Marilia Sá Carvalho Oswaldo Gonçalves Cruz Mônica de Avelar Figueiredo Mafra Magalhães Josélio Maria Galvão de Araújo Eliane Saraiva Machado de Araújo Marcelo Quintela Gomes Luciane Silva Pinheiro Célio da Silva Pinel Ricardo Lourenço-de-Oliveira |
author_sort |
Nildimar Alves Honório |
title |
Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. |
title_short |
Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. |
title_full |
Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. |
title_fullStr |
Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. |
title_full_unstemmed |
Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil. |
title_sort |
spatial evaluation and modeling of dengue seroprevalence and vector density in rio de janeiro, brazil. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2009 |
url |
https://doi.org/10.1371/journal.pntd.0000545 https://doaj.org/article/1020ec8672da44568a12568cf7713113 |
long_lat |
ENVELOPE(-57.955,-57.955,-61.923,-61.923) |
geographic |
Arctic Gam |
geographic_facet |
Arctic Gam |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 3, Iss 11, p e545 (2009) |
op_relation |
http://europepmc.org/articles/PMC2768822?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0000545 https://doaj.org/article/1020ec8672da44568a12568cf7713113 |
op_doi |
https://doi.org/10.1371/journal.pntd.0000545 |
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PLoS Neglected Tropical Diseases |
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3 |
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11 |
container_start_page |
e545 |
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