Determinants and Predictors of Dengue Infection in Mexico
A national serosurvey was conducted in Mexico from March to October 1986 to identify predictors of dengue transmission and target areas at high risk of severe annual epidemics. A total of 3,408 households in 70 localities with populations less than 50,000 were randomly sampled, and serology was obta...
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Veröffentlicht in: | American journal of epidemiology 1991-06, Vol.133 (11), p.1168-1178 |
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description | A national serosurvey was conducted in Mexico from March to October 1986 to identify predictors of dengue transmission and target areas at high risk of severe annual epidemics. A total of 3,408 households in 70 localities with populations less than 50,000 were randomly sampled, and serology was obtained from one subject under age 25 years in each household. When comparing exposure and infection frequenctes across the 70 communities, the authors found that median temperature during the rainy season was the stron9est predictor of dengue infection, with an adjusted fourfold risk in the comparison of 30°C with 17°C. High temperatures increase vector efficiency by reducing the period of viral replication in mosquitoes. The proportion of houses in a community with larva on the premises was significantly associated with the community proportion infected (odds ratio (OR)adjas = 1 .9; 95% confidence interval (C1) 1.4–2.5), as was the proportion of households with uncovered water containers present (ORadj = 1.9; 95% Cl 1.4–2.7). Because these factors have effects beyond the individual household and subjects infected from them create a risk for other subjects, both analyses of effects and organization of control efforts must be at the community level. A predictive model was constructed using the community level risk factors to classify communities as being at high, medium, or low risk of experiencing an epidemic; 57% of these communities were correctly classified using this model. |
doi_str_mv | 10.1093/oxfordjournals.aje.a115829 |
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Rebecca ; Mann, Miguel Angel Vaca ; Dantes, Hector Gomez ; Aquino, Maria Luisa Zarate ; Longini, Ira M. ; Amor, Jaime Sepulveda</creator><creatorcontrib>Koopman, James S. ; Prevots, D. Rebecca ; Mann, Miguel Angel Vaca ; Dantes, Hector Gomez ; Aquino, Maria Luisa Zarate ; Longini, Ira M. ; Amor, Jaime Sepulveda</creatorcontrib><description>A national serosurvey was conducted in Mexico from March to October 1986 to identify predictors of dengue transmission and target areas at high risk of severe annual epidemics. A total of 3,408 households in 70 localities with populations less than 50,000 were randomly sampled, and serology was obtained from one subject under age 25 years in each household. When comparing exposure and infection frequenctes across the 70 communities, the authors found that median temperature during the rainy season was the stron9est predictor of dengue infection, with an adjusted fourfold risk in the comparison of 30°C with 17°C. High temperatures increase vector efficiency by reducing the period of viral replication in mosquitoes. The proportion of houses in a community with larva on the premises was significantly associated with the community proportion infected (odds ratio (OR)adjas = 1 .9; 95% confidence interval (C1) 1.4–2.5), as was the proportion of households with uncovered water containers present (ORadj = 1.9; 95% Cl 1.4–2.7). Because these factors have effects beyond the individual household and subjects infected from them create a risk for other subjects, both analyses of effects and organization of control efforts must be at the community level. A predictive model was constructed using the community level risk factors to classify communities as being at high, medium, or low risk of experiencing an epidemic; 57% of these communities were correctly classified using this model.</description><identifier>ISSN: 0002-9262</identifier><identifier>EISSN: 1476-6256</identifier><identifier>DOI: 10.1093/oxfordjournals.aje.a115829</identifier><identifier>PMID: 2035520</identifier><identifier>CODEN: AJEPAS</identifier><language>eng</language><publisher>Cary, NC: Oxford University Press</publisher><subject>Adult ; Aedes - isolation & purification ; Animals ; Arboviroses ; Biological and medical sciences ; dengue ; Dengue - epidemiology ; Dengue - immunology ; Dengue - transmission ; Dengue fevers ; Ecology ; Human viral diseases ; Humans ; Infectious diseases ; Larva - isolation & purification ; Medical sciences ; Mexico - epidemiology ; Odds Ratio ; Random Allocation ; Risk Factors ; Seasons ; seroepidemiologic methods ; Temperature ; Tropical medicine ; Tropical viral diseases ; Viral diseases</subject><ispartof>American journal of epidemiology, 1991-06, Vol.133 (11), p.1168-1178</ispartof><rights>1991 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c507t-340fca483c59b219f15e50e2cdb580d57ce99a77bc19bb16239b1018708e04d03</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27869,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19773100$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/2035520$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Koopman, James S.</creatorcontrib><creatorcontrib>Prevots, D. Rebecca</creatorcontrib><creatorcontrib>Mann, Miguel Angel Vaca</creatorcontrib><creatorcontrib>Dantes, Hector Gomez</creatorcontrib><creatorcontrib>Aquino, Maria Luisa Zarate</creatorcontrib><creatorcontrib>Longini, Ira M.</creatorcontrib><creatorcontrib>Amor, Jaime Sepulveda</creatorcontrib><title>Determinants and Predictors of Dengue Infection in Mexico</title><title>American journal of epidemiology</title><addtitle>Am J Epidemiol</addtitle><description>A national serosurvey was conducted in Mexico from March to October 1986 to identify predictors of dengue transmission and target areas at high risk of severe annual epidemics. A total of 3,408 households in 70 localities with populations less than 50,000 were randomly sampled, and serology was obtained from one subject under age 25 years in each household. When comparing exposure and infection frequenctes across the 70 communities, the authors found that median temperature during the rainy season was the stron9est predictor of dengue infection, with an adjusted fourfold risk in the comparison of 30°C with 17°C. High temperatures increase vector efficiency by reducing the period of viral replication in mosquitoes. The proportion of houses in a community with larva on the premises was significantly associated with the community proportion infected (odds ratio (OR)adjas = 1 .9; 95% confidence interval (C1) 1.4–2.5), as was the proportion of households with uncovered water containers present (ORadj = 1.9; 95% Cl 1.4–2.7). Because these factors have effects beyond the individual household and subjects infected from them create a risk for other subjects, both analyses of effects and organization of control efforts must be at the community level. A predictive model was constructed using the community level risk factors to classify communities as being at high, medium, or low risk of experiencing an epidemic; 57% of these communities were correctly classified using this model.</description><subject>Adult</subject><subject>Aedes - isolation & purification</subject><subject>Animals</subject><subject>Arboviroses</subject><subject>Biological and medical sciences</subject><subject>dengue</subject><subject>Dengue - epidemiology</subject><subject>Dengue - immunology</subject><subject>Dengue - transmission</subject><subject>Dengue fevers</subject><subject>Ecology</subject><subject>Human viral diseases</subject><subject>Humans</subject><subject>Infectious diseases</subject><subject>Larva - isolation & purification</subject><subject>Medical sciences</subject><subject>Mexico - epidemiology</subject><subject>Odds Ratio</subject><subject>Random Allocation</subject><subject>Risk Factors</subject><subject>Seasons</subject><subject>seroepidemiologic methods</subject><subject>Temperature</subject><subject>Tropical medicine</subject><subject>Tropical viral diseases</subject><subject>Viral diseases</subject><issn>0002-9262</issn><issn>1476-6256</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1991</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>K30</sourceid><recordid>eNqFkUGP0zAQhS0EWsouPwEpAi23lBk7tmNuqLvQlYpgJZAQF8txJiiltRc7kcq_J1XDIrhwmsP7Zt7oPcaeIywRjHgVD11M7TaOKbhdXrotLR2irLl5wBZYaVUqLtVDtgAAXhqu-GP2JOctAKKRcMbOOAgpOSyYuaKB0r4PLgy5cKEtPiZqez_ElIvYFVcUvo1U3ISO_NDHUPSheE-H3scL9qib3OnpPM_Z57fXn1brcvPh3c3qzab0EvRQigo676paeGkajqZDSRKI-7aRNbRSezLGad14NE2DigvTIGCtoSaoWhDn7OXp7l2KP0bKg9332dNu5wLFMdsapK6Uwv-CKI1CDXwCX_wD_o7SogClZGW0nqjXJ8qnmHOizt6lfu_ST4tgjzXYv2uwUw12rmFafjZbjM2e2vvVOfdJv5x1l73bdckF3-c_DscHEI5ceeL6PNDhXnfpu1VaaGnXX77aSuhbuREruxa_AJPXo40</recordid><startdate>19910601</startdate><enddate>19910601</enddate><creator>Koopman, James S.</creator><creator>Prevots, D. Rebecca</creator><creator>Mann, Miguel Angel Vaca</creator><creator>Dantes, Hector Gomez</creator><creator>Aquino, Maria Luisa Zarate</creator><creator>Longini, Ira M.</creator><creator>Amor, Jaime Sepulveda</creator><general>Oxford University Press</general><general>School of Hygiene and Public Health of the Johns Hopkins University</general><scope>BSCLL</scope><scope>IQODW</scope><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>HVZBN</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope><scope>7U9</scope><scope>H94</scope><scope>7X8</scope></search><sort><creationdate>19910601</creationdate><title>Determinants and Predictors of Dengue Infection in Mexico</title><author>Koopman, James S. ; Prevots, D. 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Rebecca</au><au>Mann, Miguel Angel Vaca</au><au>Dantes, Hector Gomez</au><au>Aquino, Maria Luisa Zarate</au><au>Longini, Ira M.</au><au>Amor, Jaime Sepulveda</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Determinants and Predictors of Dengue Infection in Mexico</atitle><jtitle>American journal of epidemiology</jtitle><addtitle>Am J Epidemiol</addtitle><date>1991-06-01</date><risdate>1991</risdate><volume>133</volume><issue>11</issue><spage>1168</spage><epage>1178</epage><pages>1168-1178</pages><issn>0002-9262</issn><eissn>1476-6256</eissn><coden>AJEPAS</coden><abstract>A national serosurvey was conducted in Mexico from March to October 1986 to identify predictors of dengue transmission and target areas at high risk of severe annual epidemics. A total of 3,408 households in 70 localities with populations less than 50,000 were randomly sampled, and serology was obtained from one subject under age 25 years in each household. When comparing exposure and infection frequenctes across the 70 communities, the authors found that median temperature during the rainy season was the stron9est predictor of dengue infection, with an adjusted fourfold risk in the comparison of 30°C with 17°C. High temperatures increase vector efficiency by reducing the period of viral replication in mosquitoes. The proportion of houses in a community with larva on the premises was significantly associated with the community proportion infected (odds ratio (OR)adjas = 1 .9; 95% confidence interval (C1) 1.4–2.5), as was the proportion of households with uncovered water containers present (ORadj = 1.9; 95% Cl 1.4–2.7). Because these factors have effects beyond the individual household and subjects infected from them create a risk for other subjects, both analyses of effects and organization of control efforts must be at the community level. A predictive model was constructed using the community level risk factors to classify communities as being at high, medium, or low risk of experiencing an epidemic; 57% of these communities were correctly classified using this model.</abstract><cop>Cary, NC</cop><pub>Oxford University Press</pub><pmid>2035520</pmid><doi>10.1093/oxfordjournals.aje.a115829</doi><tpages>11</tpages></addata></record> |
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subjects | Adult Aedes - isolation & purification Animals Arboviroses Biological and medical sciences dengue Dengue - epidemiology Dengue - immunology Dengue - transmission Dengue fevers Ecology Human viral diseases Humans Infectious diseases Larva - isolation & purification Medical sciences Mexico - epidemiology Odds Ratio Random Allocation Risk Factors Seasons seroepidemiologic methods Temperature Tropical medicine Tropical viral diseases Viral diseases |
title | Determinants and Predictors of Dengue Infection in Mexico |
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