Conscious of the need to improve the availability of data for monitoring indicators, the National Agency for Statistics and Demography (Agence Nationale de la Statistique et de la Démographie - ANSD) is interested in the use of new data sources for the production and monitoring of data. As a promising source, mobile data is a viable alternative to traditional sources such as the national census. As part of the OPAL project pilot, ANSD is interested in estimating the population density of Senegal at the communal level through analysis of SONATEL Call Data Records (CDRs).
A study of the validity and accuracy of the indicators - as calculated from the CDRs and accessed via the OPAL platform - will be made by comparing them to the results and projections obtained from the 2013 census. As part of the implementation of this Friendly User Test (FUT) project, ANSD is supported by OPAL consultant Till Koebe, co-Founder of Knuper, through trainings and the development of a case study related to population density. This involves a calibration of the algorithm for calculating the population density from CDRs of the telco; calibrated population density approximations with weights derived from the OPAL platform will be used.
Once calibrated, mobile metadata can enrich official statistics by providing indicators on internal migration, information on the distribution of the population at the communal level while conducting more accurate and realistic projections as they capture the movements and displacements of a large part of the population.
OPAL could allow ANSD to:
A detailed explanation of the methodology of this experimental study, specifically the calibration and population projections while revisiting the current ANSD challenges in terms of treatment of migration and disaggregation of projections has been written in the report with the collaboration of the ANSD staff.
The calibrated population density algorithm will be used by other FUTs as part of their work. In addition, ANSD intends to continue collaboration in the context of a FUT on poverty analysis with the support of another consultant, Neeti Pokhriyal from the State University of New York (SUNY) at Buffalo.
The overall objective of this work is to implement an algorithm for multi-dimensional poverty mapping from mobile phone metadata on the OPAL platform, which will act as a use case for ANSD in Senegal for generating accurate and timely poverty indices at commune level. Multi-dimensional poverty maps will disaggregate poverty based on three dimensions of human development indicators – health, education and standard of living. The expected final product is to have a multi-dimensional poverty map (MPI) for Senegal for all communes and urban areas for the years 2014 and 2015. The output of the algorithm will be visualized separately on any open source software, such as QGIS.
The local stakeholders will have the capacity, through the OPAL platform, to generate poverty maps using mobile phone metadata, thus providing poverty estimates that are frequent and available at the level of communes. The maps will show the deprivations in the three dimensions of health, education and standard of living.
These poverty maps have the potential to be updated frequently, and thereby providing frequent monitoring of the progress towards the attainment of Sustainable Development Goals.
By: Fatou N’Diaye