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

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.

Spatial Distributions of Diarrheal Cases in Relation to Housing Conditions in Informal Settlements: A Cross-Sectional Study in Abidjan, Côte d’Ivoire

“…Construction materials and the spatial disposition of cooking spaces were consistently associated with higher risks of diarrhea, even accounting for access to basic sanitation and hygiene amenities, continuity of water services, and socioeconomic status. These results corroborate previous findings regarding spatial predictors of diarrhea in Côte d’Ivoire [ 17 ], suggesting that housing conditions may play an important role in mediating contamination pathways that cause diarrhea.…”

“…Building on our recent research [ 17 , 18 ] and on previous environmental health studies in SSA [ 9 , 13 ], this study argues for a holistic approach to the prevention of diarrheal diseases that, beyond WASH services, also addresses the physical environment and the spatial characteristics of poverty [ 19 ]. Our starting point was the assumption that inadequate dwelling conditions hamper the potential health benefits expected from WASH interventions, which can be indirectly measured by the risk of diarrhea [ 20 ].…”

Environmental determinants of access to shared sanitation in informal settlements: a cross-sectional study in Abidjan and Nairobi

“…There are aspects related to the specific settlement’s morphology that are associated with the perceived safety in accessing those facilities, and this may have significant health implications. These findings resonate with a recent ecological study conducted in Côte d’Ivoire, which showed that specific landscape features related to dense, deprived settlements were a more accurate predictor of diarrhea in Ivorian urban areas than the sole availability of sanitation services [ 62 ]. In fact, although the availability of sanitation services represents a theoretical improvement, in practice, the health benefits of these improved services may be null if the targeted populations do not feel safe to use them.…”

Examining African contributions to global health: Reflections on knowledge circulation and innovation

“…The latter remain amongst the main causes of death worldwide, especially in Africa (GBD 2018;Diarrhoeal Disease Collaborators, 2018), and can be used as a proxy indicator of the quality of access to WASH services (Clasen et al, 2014). The study uses readily available open access data and combines quantitative spatial analyses conducted at different geographic scales, and thus relies on ecological analyses at city scale and cross-sectional household surveys at neighbourhood scale (Pessoa Colombo et al, 2022).…”