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Combination of Spatial Clustering Methods Using Weighted Average Voting for Spatial Epidemiology

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Fuzzy Information Processing (NAFIPS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 831))

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Abstract

The methods of spatial clustering analyze the phenomenon under study, identifying the significant and not significant clusters, which when used individually do not exactly reflect the reality of the phenomenon studied. However, with the combination of the methods it becomes possible to obtain better results. The objective of this work was to perform a combination of methods of spatial clustering, by using weighted average voting rule, for identification of municipalities in the state of Paraiba more vulnerable to the dengue fever. For methodology application, dengue fever cases in the state of Paraiba-Brazil in the year of 2011 were used. The spatial Scan statistic, Getis-Ord, Besag-Newell methods combined by the weighted average voting rule were used in order to obtain a final map with the classification of each municipality according to “priority municipalities”, “transition municipalities” (which can become priority or not) and “non-priority”. This method allowed the visualization of the spatial distribution of the dengue fever in all municipalities of Paraiba, allowing to identify vulnerable municipalities to the dengue fever. The levels of priority can help managers for decisions concerning the specific characteristics of each municipality.

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Acknowledgments

This project is partially supported by CAPES. It is also partially supported by grants 308250/2015-0 of the National Council for Scientific and Technological Development (CNPq) and is related to the National Institute of Science and Technology Medicine Assisted by Scientific Computing (465586/2014-4) also supported by CNPq.

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Authors and Affiliations

  1. Federal University of Paraíba, João Pessoa, Brazil

    Laisa Ribeiro de Sá, José Carlos da Silva Melo, Jordana de Almeida Nogueira & Ronei Marcos de Moraes

Authors
  1. Laisa Ribeiro de Sá
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  2. José Carlos da Silva Melo
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  3. Jordana de Almeida Nogueira
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  4. Ronei Marcos de Moraes
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Corresponding author

Correspondence to Laisa Ribeiro de Sá .

Editor information

Editors and Affiliations

  1. Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Guilherme A. Barreto

  2. Department of Statistics & Applied Mathematics, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Ricardo Coelho

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de Sá, L.R., da Silva Melo, J.C., de Almeida Nogueira, J., de Moraes, R.M. (2018). Combination of Spatial Clustering Methods Using Weighted Average Voting for Spatial Epidemiology. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-95312-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95311-3

  • Online ISBN: 978-3-319-95312-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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