Seroprevalence for dengue virus in a hyperendemic area and associated socioeconomic and demographic factors using a cross-sectional design and a geostatistical approach, state of São Paulo, Brazil

• Published in: BMC infectious diseases 2019-05, Vol.19 (1), p.441-441, Article 441
• Main Authors: Chiaravalloti-Neto, Francisco, da Silva, Rafael Alves, Zini, Nathalia, da Silva, Gislaine Celestino Dutra, da Silva, Natal Santos, Parra, Maisa Carla Pereira, Dibo, Margareth Regina, Estofolete, Cassia Fernanda, Fávaro, Eliane Aparecida, Dutra, Karina Rocha, Mota, Manlio Tasso Oliveira, Guimarães, Georgia Freitas, Terzian, Ana Carolina Bernardes, Blangiardo, Marta, Nogueira, Mauricio Lacerda
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Antibodies, Viral - blood; Bayesian analysis; Brazil; Brazil - epidemiology; Cohort Studies; Cross-Sectional Studies; Cross-sectional study; Demographic variables; Demographics; Demography; Dengue; Dengue - diagnosis; Dengue - epidemiology; Dengue - virology; Dengue fever; Dengue Virus - immunology; Dengue Virus - isolation & purification; Dependence; Enzyme-linked immunosorbent assay; Epidemics; Female; Fever; Geostatiscal analysis; Geostatistics; Humans; Immunoglobulin G; Incidence; Male; Middle Aged; Older people; Partial differential equations; Population; Risk Factors; Seroprevalence; Serotypes; Socioeconomic Factors; Socioeconomics; Spatial Analysis; Statistical inference; Stochasticity; Studies; Surveillance; Vector-borne diseases; Viral diseases; Viruses; West Nile virus; Young Adult
• ISSN: 1471-2334; 1471-2334
• DOI: 10.1186/s12879-019-4074-4

São José do Rio Preto is one of the cities of the state of São Paulo, Brazil, that is hyperendemic for dengue, with the presence of the four dengue serotypes. to calculate dengue seroprevalence in a neighbourhood of São José do Rio Preto and identify if socioeconomic and demographic covariates are associated with dengue seropositivity. A cohort study to evaluate dengue seroprevalence and incidence and associated factors on people aged 10 years or older, was assembled in Vila Toninho neighbourhood, São José do Rio Preto. The participant enrolment occurred from October 2015 to March 2016 (the first wave of the cohort study), when blood samples were collected for serological test (ELISA IgG anti-DENV) and questionnaires were administrated on socio-demographic variables. We evaluated the data collected in this first wave using a cross-sectional design. We considered seropositive the participants that were positive in the serological test (seronegative otherwise). We modelled the seroprevalence with a logistic regression in a geostatistical approach. The Bayesian inference was made using integrated nested Laplace approximations (INLA) coupled with the Stochastic Partial Differential Equation method (SPDE). We found 986 seropositive individuals for DENV in 1322 individuals surveyed in the study area in the first wave of the cohort study, corresponding to a seroprevalence of 74.6% (95%CI: 72.2-76.9). Between the population that said never had dengue fever, 68.4% (566/828) were dengue seropositive. Older people, non-white and living in a house (instead of in an apartment), were positively associated with dengue seropositivity. We adjusted for the other socioeconomic and demographic covariates, and accounted for residual spatial dependence between observations, which was found to present up to 800 m. Only one in four people aged 10 years or older did not have contact with any of the serotypes of dengue virus in Vila Toninho neighbourhood in São José do Rio Preto. Age, race and type of house were associated with the occurrence of the disease. The use of INLA in a geostatistical approach in a Bayesian context allowed us to take into account the spatial dependence between the observations and identify the associated covariates to dengue seroprevalence.