Publication:

Socioeconomic Indicators of Dengue and Zika in Rio de Janeiro, Brazil: A Bayesian Approach

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dc.contributor.advisorPringle, Robert M.
dc.contributor.authorBarba, Patrick
dc.date.accessioned2017-07-13T14:24:19Z
dc.date.accessioned2026-09-29T22:07:04Z
dc.date.available2017-07-13T14:24:19Z
dc.date.available2026-09-29T22:07:04Z
dc.date.created2017-04-21
dc.date.issued2017-4-21
dc.description.abstractAssociating dengue incidence rates with socioeconomic and demographic indicators is vital for anticipating and understanding outbreaks of dengue and other similar arboviruses, like the Zika virus. In this paper, we explore this relationship with a Bayesian model analyzing dengue incidence from the neighborhoods of Rio de Janeiro, Brazil. We aggregate monthly dengue incidence rates into three markers: the first, alpha, characterizes dengue epidemic frequency; the second, beta, shows the average duration of an epidemic; and the third, gamma, is a proxy for maximum dengue epidemic intensity. We demonstrate that though there is a limited relationship between alpha and beta and our indicators, gamma shows a strong positive relationship with the proportion of a neighborhood’s heads of household earning less than one minimum wage. This observation adds to the evidence that low socioeconomic status is related to increased dengue incidence in urban environments. Our study’s last step is to compare these dengue indices to preliminary Zika data in order to draw early conclusions about this new virus’ transmission. Although we found inconclusive relationships between our Zika data and dengue markers, we stress that with dengue data aggregated at a smaller scale and a larger sample size of Zika cases, minor but significant variation between the two viruses will become evident.en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01r207tr93n
dc.identifier.urihttps://theses-dissertations.princeton.edu/handle/88435/dsp01r207tr93n
dc.language.isoen_USen_US
dc.titleSocioeconomic Indicators of Dengue and Zika in Rio de Janeiro, Brazil: A Bayesian Approachen_US
dc.typePrinceton University Senior Theses
dspace.entity.typePublication
pu.contributor.advisorid960045176
pu.contributor.authorid960847371
pu.date.classyear2017en_US
pu.departmentEcology and Evolutionary Biologyen_US
pu.pdf.coverpageSeniorThesisCoverPage

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