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Sigmae

e-ISSN: 2317-0840


Vol. 12 Issue 3 (2023) / Applied Statistics

Spatial Analysis of dengue cases in the state of Paraíba, Brazil: an application with RIE

Samara Rilda Sousa Bezerra Ricardo Sandes Ehlers Mateus Santos Peixoto Maria Izabel de Andrade Araújo Tiago Almeida de Oliveira Diogo Francisco Rossoni

Author information

Samara Rilda Sousa Bezerra

ORCID not informed.
  • samaujp@yahoo.com.br
  • Programa de Interinstitucional Pós-Graduação em Estatística (PIPGEs) - UFSCAR/USP, São Carlos/SP
  • Biography not informed.

Author information

Ricardo Sandes Ehlers

ORCID not informed.
  • ehlers@icmc.usp.br
  • Universidade Federal de São Carlos - UFSCAR/USP
  • Biography not informed.

Author information

Mateus Santos Peixoto

ORCID not informed.
  • mateus_peixoto12@hotmail.com
  • Programa de Pós-Graduação em Estatística e Experimentação Agropecuária - UFLA, Lavras/MG
  • Biography not informed.

Author information

Maria Izabel de Andrade Araújo

ORCID not informed.
  • yzabelfor@hotmail.com
  • UniFatice - Centro Universitário (Polo de Campina Grande - PB), Paranavaí/PR
  • Biography not informed.

Author information

Tiago Almeida de Oliveira

ORCID not informed.

Author information

Diogo Francisco Rossoni

ORCID not informed.
  • dfrossoni@uem.br
  • Programa de Pós-Graduação em Bioestatística (PBE) - UEM, Maringá/PB
  • Biography not informed.

Published in fevereiro 21, 2024 https://10.29327/2537114.12.3-25

Abstract

This research presents an analysis of the dissemination of dengue, transmitted by Aedes aegypti, commonly known as the dengue mosquito. The study highlights the global increase in cases over the years, with a significant rise in Brazil, specifically in Paraíba. The research aims to analyze the distribution of reported dengue cases in the years 2015 and 2022 in the State of Paraíba using spatial statistical methods, considering socioeconomic and environmental factors. Moran indices were used to test spatial dependence, and maps such as Box Map, Lisa Map, and Moran Map were employed to visualize spatial associations. A Spatial Autoregressive (SAR) regression model was applied to assess the influence of independent variables on the Spatial Incidence Ratio (SIR). The results suggest spatial autocorrelation in the SIR and highlight the significance of the variables (Municipal Human Development Index and Per Capita Income) in the SAR 4 model

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Paper information

History

  • Received: 30/09/2023
  • Published: 21/02/2024