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The fewer, the better fare: Can the loss of vegetation in the Cerrado drive the increase in dengue fever cases infection?

Author

Listed:
  • Arlindo Ananias Pereira da Silva
  • Adriano Roberto Franquelino
  • Paulo Eduardo Teodoro
  • Rafael Montanari
  • Glaucia Amorim Faria
  • Cristóvão Henrique Ribeiro da Silva
  • Dayane Bortoloto da Silva
  • Walter Aparecido Ribeiro Júnior
  • Franciele Muchalak
  • Kassia Maria Cruz Souza
  • Marcos Henrique Prudencio da Silva
  • Larissa Pereira Ribeiro Teodoro

Abstract

Several studies have reported the relationship of deforestation with increased incidence of infectious diseases, mainly due to the deregulation caused in these environments. The purpose of this study was to answer the following questions: a) is increased loss of vegetation related to dengue cases in the Brazilian Cerrado? b) how do different regions of the tropical savanna biome present distinct patterns for total dengue cases and vegetation loss? c) what is the projection of a future scenario of deforestation and an increased number of dengue cases in 2030? Thus, this study aimed to assess the relationship between loss of native vegetation in the Cerrado and dengue infection. In this paper, we quantify the entire deforested area and dengue infection cases from 2001 to 2019. For data analyses, we used Poisson generalized linear model, descriptive statistics, cluster analysis, non-parametric statistics, and autoregressive integrated moving average (ARIMA) models to predict loss of vegetation and fever dengue cases for the next decade. Cluster analysis revealed the formation of four clusters among the states. Our results showed significant increases in loss of native vegetation in all states, with the exception of Piauí. As for dengue cases, there were increases in the states of Minas Gerais, São Paulo, and Mato Grosso. Based on projections for 2030, Minas Gerais will register about 4,000 dengue cases per 100,000 inhabitants, São Paulo 750 dengue cases per 100,000 inhabitants, and Mato Grosso 500 dengue cases per 100,000 inhabitants. To reduce these projections, Brazil will need to control deforestation and implement public health, environmental and social policies, requiring a joint effort from all spheres of society.

Suggested Citation

  • Arlindo Ananias Pereira da Silva & Adriano Roberto Franquelino & Paulo Eduardo Teodoro & Rafael Montanari & Glaucia Amorim Faria & Cristóvão Henrique Ribeiro da Silva & Dayane Bortoloto da Silva & Wal, 2022. "The fewer, the better fare: Can the loss of vegetation in the Cerrado drive the increase in dengue fever cases infection?," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-16, January.
    • Handle: RePEc:plo:pone00:0262473
    DOI: 10.1371/journal.pone.0262473
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    References listed on IDEAS

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    1. Bauhoff, Sebastian & Busch, Jonah, 2020. "Does deforestation increase malaria prevalence? Evidence from satellite data and health surveys," World Development, Elsevier, vol. 127(C).
    2. H. S. Grantham & A. Duncan & T. D. Evans & K. R. Jones & H. L. Beyer & R. Schuster & J. Walston & J. C. Ray & J. G. Robinson & M. Callow & T. Clements & H. M. Costa & A. DeGemmis & P. R. Elsen & J. Er, 2020. "Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    3. Norman Myers & Russell A. Mittermeier & Cristina G. Mittermeier & Gustavo A. B. da Fonseca & Jennifer Kent, 2000. "Biodiversity hotspots for conservation priorities," Nature, Nature, vol. 403(6772), pages 853-858, February.
    4. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
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