Human Mobility and Population Density in
In the SDG sphere, the first condition for impactful measuring is to have detailed information about a country’s population through census, which remains a challenge in many contexts, usually being time-consuming and expensive. A census can only be conducted once every few years at best and some countries, especially those experiencing conflict or political instability, have not been able to conduct a census in decades. Moreover, a census will yield a solid estimate of population size, structure, and distribution at one point in time, but will not provide a reliable picture of changes happening in real time.
Having an estimate of human mobility patterns and trends that reflect the temporal and geographical dimensions is an invaluable step to provide new insights for effective public policies. In this context, using Big Data, and in particular Call Detail Records (CDR), can be an effective methodology to shed new light on demographic features that have a wide range of implications for development policies and programmes.
Data-Pop is contributing to the implementation of innovative approaches towards this end.
Together with UNFPA and the National Bureau of Statistics we launched a project in the Maldives, a nation of half million people dispersed over more than 1,000 islands, where the last demographic count took place in 2014. The migration rate, both of foreign workers and people moving towards the greater Male’ area, is expected to increase in the coming decades. The main goal of this pilot is to explore new methodologies to produce high quality statistics of these trends in the capital city of Male’, with the possibility to scale to the rest of the country.
To analyse population density and movement patterns, our partners at FBK developed a prototype that leverages the use of Call Detail Records (CDRs) and new data analytics techniques by utilizing the temporal dynamics derived from mobile data, while preserving the anonymity of mobile phone users.
This allowed to conduct specific analysis that revealed interesting insights on the population of Male’, such as:
Malé’s population density according to the time of the day, based on mobile phone data.
There is a great potential for scaling the analysis and comparing it to the national official census, eventually feeding this information into evidence-based policy towards reaching SDGs.