Linus Bengtsson and colleagues examine the use of mobile phone positioning data to monitor population movements during disasters and outbreaks, finding that reports on population movements can be generated within twelve hours of receiving data.
Population movements following disasters can cause important increases in morbidity and mortality. Without knowledge of the locations of affected people, relief assistance is compromised. No rapid and accurate method exists to track population movements after disasters. We used position data of subscriber identity module (SIM) cards from the largest mobile phone company in Haiti (Digicel) to estimate the magnitude and trends of population movements following the Haiti 2010 earthquake and cholera outbreak.
Geographic positions of SIM cards were determined by the location of the mobile phone tower through which each SIM card connects when calling. We followed daily positions of SIM cards 42 days before the earthquake and 158 days after. To exclude inactivated SIM cards, we included only the 1.9 million SIM cards that made at least one call both pre-earthquake and during the last month of study. In Port-au-Prince there were 3.2 persons per included SIM card. We used this ratio to extrapolate from the number of moving SIM cards to the number of moving persons. Cholera outbreak analyses covered 8 days and tracked 138,560 SIM cards.
An estimated 630,000 persons (197,484 Digicel SIM cards), present in Port-au-Prince on the day of the earthquake, had left 19 days post-earthquake. Estimated net outflow of people (outflow minus inflow) corresponded to 20% of the Port-au-Prince pre-earthquake population. Geographic distribution of population movements from Port-au-Prince corresponded well with results from a large retrospective, population-based UN survey. To demonstrate feasibility of rapid estimates and to identify areas at potentially increased risk of outbreaks, we produced reports on SIM card movements from a cholera outbreak area at its immediate onset and within 12 hours of receiving data.
Every year, millions of people are affected by disasters—sudden calamitous events that disrupt communities and cause major human, material, economic, and environmental losses. Disasters can be natural (for example, earthquakes and infectious disease outbreaks) or man-made (for example, terrorist attacks and industrial accidents). Whenever a disaster strikes, governments, international bodies, and humanitarian agencies swing into action to help the affected population by providing food, water, shelter, and medical assistance. Within days of the earthquake that struck Haiti on January 12, 2010, for instance, many governments pledged large sums of money to help the Haitians, and humanitarian agencies such as Oxfam and the International Federation of Red Cross and Red Crescent Societies sent tons of food and hundreds of personnel into the country. And when a cholera outbreak began in Haiti in October 2010, the world responded by sending further assistance.
An instinctive response to any disaster is to flee the affected area, but such population movements after a disaster can increase the loss of human life by complicating the provision of relief assistance, the assessment of needs, and infectious disease surveillance. Unfortunately, there are no rapid or accurate methods available to track population movements after disasters. Relief coordinators currently rely on slow, potentially biased methods such as eye witness accounts and aerial images of shelters to track population movements. In this geospatial analysis, the researchers investigate whether position data from mobile phone SIMs (subscriber identity modules) can be used to estimate the magnitude and trends of population movements by retrospectively following the positions of SIMs in Haiti before and after the earthquake and tracking SIMs during the first few days of the cholera outbreak. Every time a SIM makes a call, the mobile phone network database records which mobile phone tower connected the call. Thus, the database can provide a geographic position for each mobile phone caller.
The researchers obtained anonymized data on the position of 1.9 million SIMs in Haiti from 42 days before the earthquake to 158 days afterwards. Nearly 200,000 SIMs that were present in Haiti's capital Port-au-Prince when the earthquake struck had left 19 days post-earthquake. Just under a third of Port-au-Prince's inhabitants were mobile phone subscribers at the time of the earthquake, so this movement of SIMs equates to the movement of about 630,000 people. Notably, although the SIM-based estimates of numbers leaving Port-au-Prince matched the estimates reported by the Haitian National Civil Protection Agency (NPCA), which were largely based on counting ship and bus movements and which were used during the relief operation, the estimated geographical distribution of displaced people reported by the NPCA was very different to that obtained by analyzing SIM movements. By contrast, the geographical distribution of the population obtained from SIM movements closely matched that reported by a retrospective United Nations Population Fund household survey. Finally, to demonstrate the feasibility of producing rapid estimates of population movements during disasters, the researchers tracked nearly 140,000 SIMs during the first 8 days of the Haitian cholera outbreak and showed that they could distribute analyses of SIM movements within 12 hours of receiving data from the mobile phone company.
These findings suggest that estimates of population movements during disasters and infectious disease outbreaks can be delivered rapidly and accurately in areas of high mobile use by analyzing mobile phone data. 86% of the world's population now has mobile phone network coverage and, in 2009, there were already 3.2 billion mobile phone subscriptions in the developing world, which has a population of 5.5 billion people. Thus, this tracking method could be useful in many parts of the world, including those particularly vulnerable to disasters. However, because mobile phone use varies between sections of society, because some areas have a low density of mobile phone towers, and because disasters can destroy these towers, this approach may not be effective in all disasters. The researchers recommend, therefore, that the use of mobile phone data for tracking population movements is evaluated further and that relationships are built up with mobile phone companies to ensure rapid implementation of the approach after future disasters.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001083.
Internal Displacement Monitoring Centre provides information on population displacement during natural disasters
The International Federation of Red Cross and Red Crescent Societies provides information in several languages about disaster management and about the 2010 earthquake in Haiti
Oxfam also has information on conflicts and natural disasters and the Haiti earthquake and cholera outbreak (in several languages)
EM-DAT, the International Disaster Database contains essential core information on 18,000 mass disasters in the world from 1990 until the present