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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| creator | Honório, Nildimar Alves Nogueira, Rita Maria Ribeiro Codeço, Cláudia Torres Carvalho, Marilia Sá Cruz, Oswaldo Gonçalves Magalhães, Mônica de Avelar Figueiredo Mafra de Araújo, Josélio Maria Galvão de Araújo, Eliane Saraiva Machado Gomes, Marcelo Quintela Pinheiro, Luciane Silva da Silva Pinel, Célio Lourenço-de-Oliveira, Ricardo |
| 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 activity areas with high human movement. No association between recent dengue infection and household's high mosquito abundance was observed in this sample.
This study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence, recent dengue infection, and vector density. In conclusion, the variation in spatial seroprevalence patterns inside the neighborhoods, with signif |
| doi_str_mv | 10.1371/journal.pntd.0000545 |
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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 activity areas with high human movement. No association between recent dengue infection and household's high mosquito abundance was observed in this sample.
This study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence, recent dengue infection, and vector density. In conclusion, the variation in spatial seroprevalence patterns inside the neighborhoods, with significantly higher risk patches close to the areas with large human movement, suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro. Surveillance guidelines should be further discussed, considering these findings, particularly the spatial patterns for both human and mosquito populations.</description><identifier>ISSN: 1935-2735</identifier><identifier>ISSN: 1935-2727</identifier><identifier>EISSN: 1935-2735</identifier><identifier>DOI: 10.1371/journal.pntd.0000545</identifier><identifier>PMID: 19901983</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Adult ; Aedes - physiology ; Aedes aegypti ; Aged ; Animals ; Antibodies, Viral - blood ; Antibodies, Viral - immunology ; Brazil - epidemiology ; Child ; Child, Preschool ; Dengue - epidemiology ; Dengue - immunology ; Dengue - transmission ; Dengue - virology ; Dengue virus ; Dengue Virus - genetics ; Dengue Virus - immunology ; Dengue Virus - isolation & purification ; Ecology ; Fatalities ; Fever ; Households ; Humans ; Infant ; Insect Vectors - physiology ; Male ; Middle Aged ; Models, Biological ; Mosquitoes ; Population Density ; Public Health and Epidemiology ; Seroepidemiologic Studies ; Socioeconomic Factors ; Tropical diseases ; Virology ; Young Adult</subject><ispartof>PLoS neglected tropical diseases, 2009-11, Vol.3 (11), p.e545-545</ispartof><rights>2009 Honorio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Honório NA, Nogueira RMR, Codeço CT, Carvalho MS, Cruz OG, et al. (2009) Spatial Evaluation and Modeling of Dengue Seroprevalence and Vector Density in Rio de Janeiro, Brazil. PLoS Negl Trop Dis 3(11): e545. doi:10.1371/journal.pntd.0000545</rights><rights>Honorio et al. 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c622t-8b66b09a7da8e286a72a3635df56804f84b0b8467447bf133066a4cc99aa2aa83</citedby><cites>FETCH-LOGICAL-c622t-8b66b09a7da8e286a72a3635df56804f84b0b8467447bf133066a4cc99aa2aa83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768822/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768822/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19901983$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Gubler, Duane</contributor><creatorcontrib>Honório, Nildimar Alves</creatorcontrib><creatorcontrib>Nogueira, Rita Maria Ribeiro</creatorcontrib><creatorcontrib>Codeço, Cláudia Torres</creatorcontrib><creatorcontrib>Carvalho, Marilia Sá</creatorcontrib><creatorcontrib>Cruz, Oswaldo Gonçalves</creatorcontrib><creatorcontrib>Magalhães, Mônica de Avelar Figueiredo Mafra</creatorcontrib><creatorcontrib>de Araújo, Josélio Maria Galvão</creatorcontrib><creatorcontrib>de Araújo, Eliane Saraiva Machado</creatorcontrib><creatorcontrib>Gomes, Marcelo Quintela</creatorcontrib><creatorcontrib>Pinheiro, Luciane Silva</creatorcontrib><creatorcontrib>da Silva Pinel, Célio</creatorcontrib><creatorcontrib>Lourenço-de-Oliveira, Ricardo</creatorcontrib><title>Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil</title><title>PLoS neglected tropical diseases</title><addtitle>PLoS Negl Trop Dis</addtitle><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 activity areas with high human movement. No association between recent dengue infection and household's high mosquito abundance was observed in this sample.
This study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence, recent dengue infection, and vector density. In conclusion, the variation in spatial seroprevalence patterns inside the neighborhoods, with significantly higher risk patches close to the areas with large human movement, suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro. Surveillance guidelines should be further discussed, considering these findings, particularly the spatial patterns for both human and mosquito populations.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aedes - physiology</subject><subject>Aedes aegypti</subject><subject>Aged</subject><subject>Animals</subject><subject>Antibodies, Viral - blood</subject><subject>Antibodies, Viral - immunology</subject><subject>Brazil - epidemiology</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>Dengue - epidemiology</subject><subject>Dengue - immunology</subject><subject>Dengue - transmission</subject><subject>Dengue - virology</subject><subject>Dengue virus</subject><subject>Dengue Virus - genetics</subject><subject>Dengue Virus - immunology</subject><subject>Dengue Virus - isolation & purification</subject><subject>Ecology</subject><subject>Fatalities</subject><subject>Fever</subject><subject>Households</subject><subject>Humans</subject><subject>Infant</subject><subject>Insect Vectors - physiology</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Biological</subject><subject>Mosquitoes</subject><subject>Population Density</subject><subject>Public Health and Epidemiology</subject><subject>Seroepidemiologic Studies</subject><subject>Socioeconomic Factors</subject><subject>Tropical diseases</subject><subject>Virology</subject><subject>Young Adult</subject><issn>1935-2735</issn><issn>1935-2727</issn><issn>1935-2735</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNp9kltrFDEUxwdRbF39BqIBQV_cNbfJ5UXQeqsUBC_P4Uwms6Zkk20ys1A_vdnuqK2IeUhOkt_5nwunaR4SvCJMkhfnacoRwmobx36F62p5e6s5Jpq1SypZe_uafdTcK-W8IrpV5G5zRLTGRCt23LgvWxg9BOR2EKZqpogg9miTehd8XKM0oDcurieHistpm_eci9ZdUTtnx5RR72Lx4yXyEX32qV7RR4jO5_Qcvc7ww4f7zZ0BQnEP5nPRfHv39uvJh-XZp_enJ6_OllZQOi5VJ0SHNcgelKNKgKTABGv7oRUK80HxDneKC8m57AbCGBYCuLVaA1AAxRbN44PuNqRi5g4VQ6hSWGsp20qcHog-wbnZZr-BfGkSeHP1kPLaQB69Dc4QTLGzSkjaA-c1AyC07naQkjBSoy-al3O0qdu43ro4Zgg3RG_-RP_drNPOUCmUorQKPJsFcrqYXBnNxhfrQqjdS1MxkvF9kWRPPv0vSQmXmApdwSd_gf_uAj9QNqdSsht-J02w2U_XLy-zny4zT1d1e3S94D9O8zixn4ATzKg</recordid><startdate>20091101</startdate><enddate>20091101</enddate><creator>Honório, Nildimar Alves</creator><creator>Nogueira, Rita Maria Ribeiro</creator><creator>Codeço, Cláudia Torres</creator><creator>Carvalho, Marilia Sá</creator><creator>Cruz, Oswaldo Gonçalves</creator><creator>Magalhães, Mônica de Avelar Figueiredo Mafra</creator><creator>de Araújo, Josélio Maria Galvão</creator><creator>de Araújo, Eliane Saraiva Machado</creator><creator>Gomes, Marcelo Quintela</creator><creator>Pinheiro, Luciane Silva</creator><creator>da Silva Pinel, Célio</creator><creator>Lourenço-de-Oliveira, Ricardo</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7SS</scope><scope>7T2</scope><scope>7T7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>H95</scope><scope>H97</scope><scope>K9.</scope><scope>L.G</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20091101</creationdate><title>Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil</title><author>Honório, Nildimar Alves ; Nogueira, Rita Maria Ribeiro ; Codeço, Cláudia Torres ; Carvalho, Marilia Sá ; Cruz, Oswaldo Gonçalves ; Magalhães, Mônica de Avelar Figueiredo Mafra ; de Araújo, Josélio Maria Galvão ; de Araújo, Eliane Saraiva Machado ; Gomes, Marcelo Quintela ; Pinheiro, Luciane Silva ; da Silva Pinel, Célio ; Lourenço-de-Oliveira, Ricardo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c622t-8b66b09a7da8e286a72a3635df56804f84b0b8467447bf133066a4cc99aa2aa83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Aedes - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS neglected tropical diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Honório, Nildimar Alves</au><au>Nogueira, Rita Maria Ribeiro</au><au>Codeço, Cláudia Torres</au><au>Carvalho, Marilia Sá</au><au>Cruz, Oswaldo Gonçalves</au><au>Magalhães, Mônica de Avelar Figueiredo Mafra</au><au>de Araújo, Josélio Maria Galvão</au><au>de Araújo, Eliane Saraiva Machado</au><au>Gomes, Marcelo Quintela</au><au>Pinheiro, Luciane Silva</au><au>da Silva Pinel, Célio</au><au>Lourenço-de-Oliveira, Ricardo</au><au>Gubler, Duane</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil</atitle><jtitle>PLoS neglected tropical diseases</jtitle><addtitle>PLoS Negl Trop Dis</addtitle><date>2009-11-01</date><risdate>2009</risdate><volume>3</volume><issue>11</issue><spage>e545</spage><epage>545</epage><pages>e545-545</pages><issn>1935-2735</issn><issn>1935-2727</issn><eissn>1935-2735</eissn><abstract>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 activity areas with high human movement. No association between recent dengue infection and household's high mosquito abundance was observed in this sample.
This study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence, recent dengue infection, and vector density. In conclusion, the variation in spatial seroprevalence patterns inside the neighborhoods, with significantly higher risk patches close to the areas with large human movement, suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro. Surveillance guidelines should be further discussed, considering these findings, particularly the spatial patterns for both human and mosquito populations.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>19901983</pmid><doi>10.1371/journal.pntd.0000545</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1935-2735 |
| ispartof | PLoS neglected tropical diseases, 2009-11, Vol.3 (11), p.e545-545 |
| issn | 1935-2735 1935-2727 1935-2735 |
| language | eng |
| recordid | cdi_plos_journals_1288099775 |
| source | Public Library of Science (PLoS) Journals Open Access; MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; PubMed Central Open Access |
| subjects | Adolescent Adult Aedes - physiology Aedes aegypti Aged Animals Antibodies, Viral - blood Antibodies, Viral - immunology Brazil - epidemiology Child Child, Preschool Dengue - epidemiology Dengue - immunology Dengue - transmission Dengue - virology Dengue virus Dengue Virus - genetics Dengue Virus - immunology Dengue Virus - isolation & purification Ecology Fatalities Fever Households Humans Infant Insect Vectors - physiology Male Middle Aged Models, Biological Mosquitoes Population Density Public Health and Epidemiology Seroepidemiologic Studies Socioeconomic Factors Tropical diseases Virology Young Adult |
| title | Spatial evaluation and modeling of Dengue seroprevalence and vector density in Rio de Janeiro, Brazil |
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