Our approach

This website explains how Call Detail Records (CDR) can be leveraged for improving the understanding of population mobility in low- and middle-income countries, in the context of the COVID-19 pandemic.

Throughout this platform you will find resources that explain the key stages in the analysis of CDR data, and information that sets a standard for the CDR aggregates to be produced, and the mobility indicators that can be derived from the aggregates, to support decision makers within the ongoing COVID-19 pandemic.


Flowminder has designed a series of aggregates and indicators to represent all dimensions of mobility and with the following considerations as a priority:

  1. They should not be excessively computationally intensive to produce, even in settings with scarce compute resources,

  2. They are fully anonymous and contain no information about individual subscribers, ensuring that the privacy of subscribers is maintained at all times, and

  3. They are robust to sparse tower distribution and to infrequent phone usage (the aggregates have been developed with the assumption that most subscribers will not have a record associated with them every day, or even once every few days), both of which are common in low-and middle-income countries.

With these considerations in mind, we have produced the set of CDR aggregates and indicators presented on this website (along with code, methods and guidelines), which we believe extract relevant mobility information from CDRs in low-and middle-income countries, in a privacy-conscious and robust manner.

Flowminder will expand its set of indicators for other types of mobile operator data during and after the pandemic.

Our approach in details

Several key stages are required to convert raw CDR data into actionable insights. Read about the process here.

Anonymised and aggregated mobile operator data is a key data source to understand mobility patterns of populations. Read more here.