A random sampling strategy based on geographical coordinates of private households was used to select in each household one adult (greater than or equal to 18 years old), living at least six months in the neighbourhood. To select a random sample a sampling frame was needed, i.e., a complete list of all residents at least 18 years old who lived in each unit for at least 6 months. Given the lack of this type of sampling frame, an alternative sampling frame was developed based on the geographical coordinates of private households in each urban unit, combining GIS and statistical software.
Nonclassical households (hospitals, orphanages, military, etc.) and homeless were not included in this study. The urban planning team identified the geographical coordinates corresponding to households, providing the centroid of the polygons which is supposed to represent a building or a detached house. However, the spatial visualization shows roofs which may represent a household or a set of households, for example, a building with 7 floors with 2 households per floor. In the last case, we repeated the corresponding geographical coordinate 14 times. Field workers were needed to complete this exhaustive field work in order to provide a more realistic list of households in each area. This list was exported to SPSS statistical software and a random sample was generated for each area.
