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

Int J Environ Res Public Health. 2022 Jun 23;19(13):7677. doi: 10.3390/ijerph19137677.

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.

Keywords: African cities; Cote d’Ivoire; diarrhoea; landscape ecology; open-source software; urban planning.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child
  • Child, Preschool
  • Cote d'Ivoire / epidemiology
  • Diarrhea* / epidemiology
  • Humans
  • Sanitation*
  • Socioeconomic Factors
  • Water

Substances

  • Water

Grants and funding

This research was funded by the Swiss National Science Foundation, grant number CRSII5_183577, and the APC was funded by École Polytechnique Fédérale de Lausanne.