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dc.contributor.authorRosa-Freitas, Maria Goreties_ES
dc.contributor.authorSchreiber, Kathleen Ves_ES
dc.contributor.authorTsouris, Pantelises_ES
dc.contributor.authorWeimann, Ellem Tatiani de Souzaes_ES
dc.contributor.authorLuitgards-Moura, José Franciscoes_ES
dc.date.accessioned2015
dc.date.available2015
dc.date.issued2006es_ES
dc.identifier.citationRosa-Freitas, Maria Goreti,Schreiber, Kathleen V,Tsouris, Pantelis,Weimann, Ellem Tatiani de Souza,Luitgards-Moura, José Francisco (2006) Associations between dengue and combinations of weather factors in a city in the Brazilian Amazon. Rev Panam Salud Publica;20(4) 256-267,oct. 2006. Retrieved from http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S1020-49892006000900006&lng=pt&nrm=iso&tlng=enen_US
dc.identifier.urihttp://www.scielosp.org/scielo.php?script=sci_arttext&pid=S1020-49892006000900006&lng=pt&nrm=iso&tlng=enes_ES
dc.identifier.urihttps://iris.paho.org/handle/10665.2/7919
dc.format.extentmapes_ES
dc.format.extenttabes_ES
dc.relation.ispartofseriesRev Panam Salud Publica;20(4),oct. 2006es_ES
dc.subjectDenguees_ES
dc.subjectSaúde da População Urbanapt_BR
dc.subjectTempo (Meteorologia)es_ES
dc.subjectBrasilpt_BR
dc.titleAssociations between dengue and combinations of weather factors in a city in the Brazilian Amazonen_US
dc.typeJournal articlesen_US
dc.rights.holderPan American Health Organizationen_US
dc.description.notesOBJECTIVES: Dengue has become the most important endemic disease in Brazil. The Amazonian state of Roraima has one of the highest incidence rates of dengue in the country. The objective of this study was to determine whether significant temporal relationships exist between the number of reported dengue cases and short-term climate measures for the city of Boa Vista, the capital of Roraima. If such relationships exist, that suggests that it may be possible to predict dengue case numbers based on antecedent climate, thus helping develop a climate-based dengue early-warning system for Boa Vista. METHODS: Seasonal Pearson product-moment correlations were developed between 3-week running averages of daily numbers of reported dengue cases for September 1998-December 2001 and certain meteorological variables (thermal, hydroclimatic, wind, atmospheric pressure, and humidity) up to 25 weeks before. Two-sample t tests were also applied to test for statistically significant differences between samples of daily dengue cases with above-average values and samples with below-average values for three-variable meteorological combinations. These multivariate combinations consisted of the three climate measures that together explained the greatest portion of the variance in the number of dengue cases for the particular season. RESULTS: The strength of the individual averaged correlations varied from weak to moderate. The correlations differed according to the period of the year, the particular climatic variable, and the lag period between the climate indicator and the number of dengue cases. The seasonal correlations in our study showed far stronger relationships than had daily, full-year measures reported in previous studies. Two-sample t tests of multivariate meteorological combinations of atmospheric pressure, wind, and humidity values showed statistically significant differences in the number of reported dengue cases. CONCLUSIONS: Relationships between...(AU)en_US


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