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Using Open-Access Data to Explore Relations between Urban Landscapes and Diarrhoeal Diseases in Côte d’Ivoire

Author

Listed:
  • Vitor Pessoa Colombo

    (School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland)

  • Jérôme Chenal

    (School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland)

  • Brama Koné

    (Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan 01 BP 1303, Côte d’Ivoire)

  • Martí Bosch

    (School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland)

  • Jürg Utzinger

    (Swiss Tropical and Public Health Institute, 4123 Allschwil, Switzerland
    University of Basel, 4001 Basel, Switzerland)

Abstract

Unlike water and sanitation infrastructures or socio-economic indicators, landscape features are seldomly considered as predictors of diarrhoea. In contexts of rapid urbanisation and changes in the physical environment, urban planners and public health managers could benefit from a deeper understanding of the relationship between landscape patterns and health outcomes. We conducted an ecological analysis based on a large ensemble of open-access data to identify specific landscape features associated with diarrhoea. Designed as a proof-of-concept study, our research focused on Côte d’Ivoire. This analysis aimed to (i) build a framework strictly based on open-access data and open-source software to investigate diarrhoea risk factors originating from the physical environment and (ii) understand whether different types and forms of urban settlements are associated with different prevalence rates of diarrhoea. We advanced landscape patterns as variables of exposure and tested their association with the prevalence of diarrhoea among children under the age of five years through multiple regression models. A specific urban landscape pattern was significantly associated with diarrhoea. We conclude that, while the improvement of water, sanitation, and hygiene infrastructures is crucial to prevent diarrhoeal diseases, the health benefits of such improvements may be hampered if the overall physical environment remains precarious.

Suggested Citation

  • Vitor Pessoa Colombo & Jérôme Chenal & Brama Koné & Martí Bosch & Jürg Utzinger, 2022. "Using Open-Access Data to Explore Relations between Urban Landscapes and Diarrhoeal Diseases in Côte d’Ivoire," IJERPH, MDPI, vol. 19(13), pages 1-20, June.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7677-:d:845811
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    References listed on IDEAS

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    1. repec:rre:publsh:v:37:y:2007:i:1:p:5-27 is not listed on IDEAS
    2. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
    3. Max Grazier G'Sell & Stefan Wager & Alexandra Chouldechova & Robert Tibshirani, 2016. "Sequential selection procedures and false discovery rate control," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 423-444, March.
    4. Bosch, Martí & Chenal, Jérôme & Joost, Stéphane, 2019. "Addressing urban sprawl from the complexity sciences," MPRA Paper 93489, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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