Predictive Analysis of Socio-Spatial Disparities of Childhood Diarrhea in Yaoundé (Cameroon)
Antoine Banza-Nsungu, United Nations Population Fund (UNFPA)
The application uses data from a sample survey (sample of 20 sectors of residence from 105 in total) conducted among 3,034 households in Yaoundé. These data were integrated into the GIS and transformed into grids, which allows the application of spatial autocorrelation test and predictive analysis of the distribution of infant diarrhea in different urban residential areas (logistic regression ARCGIS). The indicator of the standard of living of households was constructed from a combination of the amount of economic value of goods available, luxury accommodation and state of the surrounding housing. The application evaluates the effect of this indicator on the risk of occurrence of childhood diarrhea in the previous 15 days. The application shows a breakdown of diarrhea indicating a real health problem in poor neighborhoods. It emerges as a 'spatial polarization' between these neighborhoods and residential areas.