IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0262473.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0262473
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0262473&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0262473?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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).
    3. Bauhoff, Sebastian & Busch, Jonah, 2020. "Does deforestation increase malaria prevalence? Evidence from satellite data and health surveys," World Development, Elsevier, vol. 127(C).
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guangdong Li & Chuanglin Fang & Yingjie Li & Zhenbo Wang & Siao Sun & Sanwei He & Wei Qi & Chao Bao & Haitao Ma & Yupeng Fan & Yuxue Feng & Xiaoping Liu, 2022. "Global impacts of future urban expansion on terrestrial vertebrate diversity," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Laxmi D. Bhatta & Sunita Chaudhary & Anju Pandit & Himlal Baral & Partha J. Das & Nigel E. Stork, 2016. "Ecosystem Service Changes and Livelihood Impacts in the Maguri-Motapung Wetlands of Assam, India," Land, MDPI, vol. 5(2), pages 1-14, June.
    3. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    4. Rob Hyndman & Heather Booth & Farah Yasmeen, 2013. "Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.
    5. Nahapetyan Yervand, 2019. "The benefits of the Velvet Revolution in Armenia: Estimation of the short-term economic gains using deep neural networks," Central European Economic Journal, Sciendo, vol. 6(53), pages 286-303, January.
    6. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
    7. McLennan, D. & Sharma, R., 2012. "The Delivering Ecological Services Index (DESI)," Working papers 119, Rimisp Latin American Center for Rural Development.
    8. Caviedes, Julián & Ibarra, José Tomás & Calvet-Mir, Laura & Álvarez-Fernández, Santiago & Junqueira, André Braga, 2024. "Indigenous and local knowledge on social-ecological changes is positively associated with livelihood resilience in a Globally Important Agricultural Heritage System," Agricultural Systems, Elsevier, vol. 216(C).
    9. Maeda, Eduardo Eiji & Clark, Barnaby J.F. & Pellikka, Petri & Siljander, Mika, 2010. "Modelling agricultural expansion in Kenya's Eastern Arc Mountains biodiversity hotspot," Agricultural Systems, Elsevier, vol. 103(9), pages 609-620, November.
    10. Dombi, József & Jónás, Tamás & Tóth, Zsuzsanna Eszter, 2018. "Modeling and long-term forecasting demand in spare parts logistics businesses," International Journal of Production Economics, Elsevier, vol. 201(C), pages 1-17.
    11. Jaiswal, Sreeja & Balietti, Anca & Schäffer, Daniel, 2023. "Environmental Protection and Labor Market Composition," Working Papers 0736, University of Heidelberg, Department of Economics.
    12. Amita Gajewar & Gagan Bansal, 2016. "Revenue Forecasting for Enterprise Products," Papers 1701.06624, arXiv.org.
    13. Tao XIONG & Chongguang LI & Yukun BAO, 2017. "An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(3), pages 136-148.
    14. Chomitz, Kenneth M. & Thomas, Timothy S. & Brandão, Antônio Salazar P., 2005. "The economic and environmental impact of trade in forest reserve obligations: a simulation analysis of options for dealing with habitat heterogeneity," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 43(4), January.
    15. Pieter van der Spek & Chris Verhoef, 2014. "Balancing Time‐to‐Market and Quality in Embedded Systems," Systems Engineering, John Wiley & Sons, vol. 17(2), pages 166-192, June.
    16. Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
    17. Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011. "Optimal combination forecasts for hierarchical time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
    18. Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
    19. Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2015. "Forecasting the price of gold," Applied Economics, Taylor & Francis Journals, vol. 47(39), pages 4141-4152, August.
    20. Thomas Horvath & Peter Huber & Ulrike Huemer & Helmut Mahringer & Philipp Piribauer & Mark Sommer & Stefan Weingärtner, 2022. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2021 bis 2028," WIFO Studies, WIFO, number 70720.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0262473. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.