Population Displacement During Disasters Predicted Using Mobile Data

Using data supplied by a mobile operator, researchers at Karolinska Institutet have shown that population movements after the 2010 Haiti earthquake followed regular patterns. This information can be used to predict beforehand the movements of people after a disaster, and thus improves chances for aid to be delivered to the right places at the right time.

Every year, tens of millions of people are displaced by natural disasters, and to date knowledge of their movement patterns has been sparse. The results of the study, now published in The Proceedings of the National Academy of Sciences (PNAS), could therefore help aid organisations to prepare and execute their relief efforts following a major disaster.

After the earthquake in Haiti, over 600,000 people left the capital Port-au-Prince, and over a million people were left homeless. With the help of mobile data provided by Digicel, the largest mobile operator in Haiti, the researchers looked for patterns in the movements of two million anonymous mobile users.

"When disaster strikes we tend to seek comfort in our nearest and dearest," says Xin Lu, who conducted the study together with colleagues Dr Linus Bengtsson and Dr Petter Holme. "We can see by the mobile data that where people were over Christmas and New Year, which was just before the earthquake, tended to be the place where they returned to afterwards."

The team also studied the everyday movements of people and found that although people moved greater distances after the earthquake compared to before, their daily movement patterns were extremely regular. Knowing a person's movements during the first three months after the earthquake, the researchers were able to show that it is possible to predict with 85 per cent probability the location of this person on a particular day in the ensuing period.

The researchers led the work on a paper last August where they, together with colleagues, showed how mobile data could be used to describe population movements after a disaster has happened. This present study takes the work a step further by showing the potential to predict population movements beforehand. Since the disaster, Linus Bengtsson and Xin Lu, both doctoral students at Karolinska Institutet's Division of Global Health, have initiated Flowminder.org, a non-profit organisation with the aim of disseminating analyses of population movements for free to relief agencies after disasters.

Xin Lu, Linus Bengtsson & Petter Holmen
Predictability of population displacement after the 2010 Haiti earthquake
PNAS, online first 18-22 June 2012

Most Popular Now

New AI Tool Predicts Protein-Protein Int…

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool...

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

New Research Shows Promise and Limitatio…

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

Hampshire Emergency Departments Digitise…

Emergency departments in three hospitals across Hampshire Hospitals NHS Foundation Trust have deployed Alcidion's Miya Emergency, digitising paper processes, saving clinical teams time, automating tasks, and providing trust-wide visibility of...

MEDICA HEALTH IT FORUM: Success in Maste…

11 - 14 November 2024, Düsseldorf, Germany. How can innovations help to master the great challenges and demands with which healthcare is confronted across international borders? This central question will be...

A "Chemical ChatGPT" for New M…

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model - a kind of...

Siemens Healthineers co-leads EU Project…

Siemens Healthineers is joining forces with more than 20 industry and public partners, including seven leading stroke hospitals, to improve stroke management for patients all over Europe. With a total...

MEDICA and COMPAMED 2024: Shining a Ligh…

11 - 14 November 2024, Düsseldorf, Germany. Christian Grosser, Director Health & Medical Technologies, is looking forward to events getting under way: "From next Monday to Thursday, we will once again...

In 10 Seconds, an AI Model Detects Cance…

Researchers have developed an AI powered model that - in 10 seconds - can determine during surgery if any part of a cancerous brain tumor that could be removed remains...

Does AI Improve Doctors' Diagnoses?

With hospitals already deploying artificial intelligence to improve patient care, a new study has found that using Chat GPT Plus does not significantly improve the accuracy of doctors' diagnoses when...