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André T. J. Alves
Researcher at Federal University of Rio de Janeiro
Publications - 5
Citations - 31
André T. J. Alves is an academic researcher from Federal University of Rio de Janeiro. The author has contributed to research in topics: Population & Disease. The author has an hindex of 2, co-authored 3 publications receiving 21 citations. Previous affiliations of André T. J. Alves include Coordenadoria de Aperfeiçoamento de Pessoal de Nível Superior.
Papers
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Exploring spatial patterns in the associations between local AIDS incidence and socioeconomic and demographic variables in the state of Rio de Janeiro, Brazil.
TL;DR: Geographically Weighted Poisson Regression (GWPR) explores spatial varying impacts of these factors across the study area focusing attention on local variations in ecological associations and finds the effects of predictors on AIDS incidence are not constant across the state.
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The acquired immunodeficiency syndrome in the State of Rio de Janeiro, Brazil: a spatio-temporal analysis of cases reported in the period 2001-2010
TL;DR: Investigation of the dynamic, spatial distribution of notified AIDS cases in the State of Rio de Janeiro, Brazil, between 2001 and 2010 found that municipalities with high incidence are likely to be close to other municipalities with similarly high incidence and, conversely, municipalities with low incidence arelikely to be surrounded by municipalities withLow incidence.
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Symptom-based clusters of hospitalized patients with severe acute respiratory illness by SARS-CoV-2 in Brazil
Letícia Martins Raposo,Gabriela R F Abreu,Felipe Borges de Medeiros Cardoso,André T. J. Alves,P. T. C. R. Rosa,Flávio Fonseca Nobre +5 more
TL;DR: In this article , the authors identified three distinct COVID-19 clusters based on the symptoms presented by patients with severe acute respiratory illness by SARS-CoV-2, but without distinction in their prevalence in the Brazilian regions.
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Mobility and Dissemination of COVID-19 in Portugal: Correlations and Estimates from Google's Mobility Data
TL;DR: In this article , a multiple linear regression with a time moving window was used to predict the spread of the coronavirus disease 2019 (COVID-19) in mainland Portugal.
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Spatial Analysis of the Sociodemographic Characteristics, Comorbidities, Hospitalization, Signs, and Symptoms Among Hospitalized Coronavirus Disease 2019 Cases in the State of Rio De Janeiro, Brazil
TL;DR: In this paper, the profile of hospitalized COVID-19 cases and the eventual clusters of similar areas, using geographic information systems, were investigated using secondary data, and a significant global spatial auto correlation was found in 28% of the variables.