- Data applicability: primarily, the research must transform data to insights that could improve humanitarian action and policymaking. This process depends on aligning and linking the analysis with key real facts.
- Data availability: it's important to observe technological penetration in the communities of interest and as this data is held by the private sector, the type of subscribers generating the data being analysed and their communication habits.
- Data distribution: data may not be be distributed homogeneously in the region being considered thus introducing a bias that should be considered when interpreting comparative metrics. In order to exploit data analytics for humanitarian action and maximise utility for decision-making, one must also triangulate with ‘ground truth data’ and contextual knowledge to truthfully characterize social phenomena measured with mobile phone data.
Using Mobile Phone Activity For Disaster Management
Using the 2009 Tabasco Floods in Mexico as a Test Case
- Gathering socio-economic information on shocks between 2009 and 2010 in Mexico (news, surveys, Government records, civil protection action summaries, etc.)
- Gathering phone data statistics to measure data usefulness and identify potential data sources to generate a pool of data to help interpretate trends
- The telecom’s clients form a representative sample of the Tabasco population compared to census data in 2009.
- The mobile phone data contains accurate signals which identify and locate abnormal patterns when a flooding of this magnitude occurs (see ‘How Mobile Data Analysis Works’ section, below).
- Changes in the maximum peak in the volume of calls serve to identify the main affected area. To validate this result, LANDSAT data from NASA was used to obtain a segmentation of the flooded areas covering the interval of time of our phone data. Additionally, news and reports were used to confirm the floods.
- The civil protection warning may not be an effective way to raise people’s awareness in the case of flooding. Here we observed the synchronization of trends in people’s activities (data-deduced human behavior variable) with the rainfall levels during the floods (external fact variable) and the alerts triggered by civil protection warnings (objective human action variable). This strategy allowed us to hypothesize a lack of awareness of the population during the days of maximum precipitations. There was no discernable impact as a direct result of the civil protection alert, which is a useful indication of the utility of some diffusion strategies promoting early response in the case of a possible disaster for a specific region.
HOW MOBILE DATA ANALYSIS WORKSCommunication activity is determined by the number of phone calls made by each user while communicating from a given location, identified by the nearest telecom carrier antenna. By looking at the set of antennas that serve users through time, we can create mobility network maps from individual trajectories that depict the flow of people moving across a region.And by studying spatial and temporal variables, we were able to estimate population distribution, identify critical areas and observe abnormal temporal patterns that might be used to predict events.