Abstract
BackgroundGetting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist. This study aimed to test an alternative method using freely available aerial imagery.MethodsA gridded map and random selection method was used to select households for interviews. A hundred numbered of points were put along the edges of an updated map of Maroua. Then two numbers were randomly draw at a time and a line was drawn between those two numbers. A lot of different kinds of shapes of different sizes obtained were numbered. Ten shapes were randomly draw and the one selected were considered as ‘neighbourhoods’. A grid of 30 m × 30 m was drawn over each and then numbered. 202 grids considered here as households were randomly selected from the ten neighbourhoods for interviews.ResultsOut of 202 households visited, only 4 were found to be something other than a house. In addition, 30 sampled households (14.85%) were abandoned or the occupants had relocated elsewhere. This method resulted in an accuracy level of 72%, its advantage is the ability to generate efficient random sample at relatively low cost as well the time required.ConclusionsThe method proposed in this study was efficient and cost-effective when compared to the infield generation of a household inventory or Global Positioning System (GPS) tracking of households. It can then be used by researchers in low-incomes countries where funding for research is a challenge. However, this method needs to train the investigators on how to use the GPS.
Highlights
Getting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist
The objective of this paper is to propose an alternative method of surveys which is inexpensive and simple using Google Earth and Geographical Information System data as an alternative to some outdated data
Study site This study was carried out from july to october 2014 in the Maroua towns which is the biggest town in the Diamare Division of the Far North Region of Cameroon
Summary
Getting a random household sample during a survey can be expensive and very difficult especially in urban area and non-specialist. Urban population in Cameroon was reported at 54.94% in 2016, according to the World Bank collection of development indicators, compiled from officially recognised sources. It appears that cities become the living environment of more than half of the world population. Ngom Vougat et al Int J Health Geogr (2019) 18:22 and cultural rules. They have contributed to the development of a new set of roles for health care systems and the evolution of demand models for health and other resources within and between cities. The challenge for researchers is to analyse the complex relationships between urbanisation and health, to explore new health challenges under conditions of pervasive urbanisation, to identify universal commonalities and local specificities in the urban experience of health, in the context of globalisation and to recognise the growing interdependencies between far-flung cities [3]
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