![]() ![]() Inevitably there will be questions about privacy and commercial interests when dealing with mobile phone records. At little cost, this can help answer the type of questions that have previously been logistically challenging: how many people were likely to have been affected when a tsunami hit at 2.07pm? How have people reacted in the days following a devastating earthquake? How have mobility patterns changed in light of movement restrictions implemented for an Ebola outbreak? Distribution maps can be easily drawn up for any period required – for example day vs night, weekday vs weekend, workday vs holiday differences. By using just this small segment of anonymised data that is already stored by mobile network operators, it is possible to rapidly produce detailed and up-to-date population distribution maps, sidestepping the need for the cumbersome once-a-decade census in providing such population count data.Īs these phone call records are continually collected, this also provides unprecedented insight into the nature of human population dynamics. This opens up some interesting possibilities. The team measured the density of phone calls per cell tower and, adjusting for biases in phone usage, have been able to produce population density maps of equivalent accuracy to those produced from a census. The recent study by Flowminder director Andy Tatem, Pierre Deville and colleagues, published in the Proceedings of the US National Academy of Sciences draws upon just a few months of this type of anonymised data from France and Portugal. ![]() So with millions of phone users per nation, this provides a surprisingly accurate picture of human activity. This information – the anonymous ID of the user, the time and the location of the tower the call was routed through – is recorded for billing purposes by phone network operators. Every time an individual makes or receives a call or text, it is routed through the nearest receiving cell network tower. Phone subscriptions have rocketed in the last few years, with the highest rates of adoption in the world’s lowest-income nations. This is where mobile phones can provide invaluable data, using the call connection records that are updated by the second. But currently these population distribution details are largely drawn from a census – typically undertaken only every ten years (the most recent in the UK was in 2011, and in the US in 2010), which means that without other sources of information the details quickly become inaccurate or incomplete. ![]() This makes them an excellent potential source of information about population distributions and movements.įor example, in the event of a natural disaster, disease outbreak, terrorist attack or conflict, knowing where people are and how many may be affected is vital for planning a response. Mobile phones are becoming integral parts of our lives, penetrating into areas of the developing world that lack much of the fixed infrastructure taken for granted elsewhere. There are now more mobile phones in use than there are people in the world to use them – some 7.2 billion phones. To measure the impact of this population growth there is a need for accurate, spatially-explicit, high resolution maps that correctly identify population distributions through time. ![]() The effects of such rapid demographic growth are well documented, influencing the economies, environment and health of these nations. The global human population is projected to increase from 7 billion to over 9 billion between 20, with much of this growth concentrated in low-income countries. ![]()
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