ORB International Uses Innovative Sampling to Improve Research Design 8 months ago


Access to accurate and up-to-date census data is essential to quality survey implementation
, but many low- and middle-income countries (LMICs) do not maintain up-to-date census data. One in four LMICs has not updated its census data in the last ten years, and marginalized communities, displaced, refugees, and nomadic populations are often left out of government accounting, leading to inaccurate sampling frames. 
 

To address this, we use GridSample: a gridded population survey sampling tool, which creates gridded population estimates in grids as small as a city block. While it starts with census counts, the approach integrates satellite and geographic information system (GIS) data layers, such as roads, land cover type, topography – using areal weighting, machine learning, or other geostatistical methods. ORB uses this approach to produce geographical units with approximately the same population in each unit (roughly 1200 people) and a maximum area of 5km by 5km. 

As a result, we are able to systematically sample in countries with old census frames and reach peripheral zones, such in peri-urban areas (the fastest growing populations in the Global South) and vulnerable populations on a consistent basis. In particular, working in regions with large displaced populations due to active Violent Extremist Organizations necessitates changing sampling frames to accommodate mass population shifts; GridSample allows us to better estimate total displacement, to sample from these populations, and reach more marginalized communities in sentiment analysis work.  

ORB began using GridSample in 2019 and has integrated the tool into its survey design for projects across the Sahel, in Mauritania, Burkina Faso, Nigeria, Niger, Cameroon, Senegal, Mali, and Sudan.


About ORB 

ORB International is a small business operating in 116 countries around the world providing monitoring and evaluation, nationally representative surveys, rapid assessments and specialized research in complex environments. Utilizing a data-centric and quality-first model, our primary focus is mixed-methods social and political research including the topics of counter-violent-extremism, governance, and working with vulnerable populations. 

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