The National Bureau of Statistics and the United Nations Children Fund have signed a Memorandum of Understanding for the Conduct of Multiple Indicator Cluster Survey and the National Immunisation Coverage Survey.
The pact will enable the NBS to conduct survey that focuses on issues such as health, education, child protection, water and sanitation, amongst others.
The data to be generated from the survey are also expected to serve as a major source of information for the 2030 Sustainable Development Agenda.
The Statistician-General of the Federation, Dr Yemi Kale, said the survey would enable policymakers track Nigeria’s attainment or otherwise of the Sustainable Development Goals.
Kale said the pact underscored the strong working relationship between the two agencies.
He described UNICEF as one of the NBS’ closest working partners, adding that under his watch, the NBS had collaborated with UNICEF to conduct more than 10 separate statistical activities.
The NBS boss said, “As the principal agency responsible for the production and management of social data in the country, we are keen on providing the public, government and policymakers useful and reliable statistics to be used for designing and implementing developmental interventions and programs across the country.
“The implementation of the SDGs is already in full swing across the country; programmes and interventions are being designed and implemented to address several areas identified under the SDG framework.
“Simultaneously, policies and programmes are being monitored and evaluated; lessons are also being learnt as to what interventions work and those not working.
“All these efforts require sound, reliable and timely data, and this is what the MICS exercise gives us.”
The NBS boss said each round of MICS has come with significant improvements and innovations, either in terms of the design of the survey, the methodology applied or the data collection method.
He expressed strong belief that this round would not be different as it would experience the most significant improvement in terms of data quality and utilisation of the results.
