Can mobile phone data replace census surveys in spatial epidemiology of infectious diseases? A new scientific paper weighs in

The recent availability of human mobility data has impacted several research fields, ranging from urban planning to social sciences. One of its most successful applications has undoubtedly been the spatial epidemiology of infectious diseases, though previous works have shown that using different mobility data sources – such as mobile phone data or census surveys – to parametrize infectious disease models can generate divergent outcomes.

In a new paper, out in Royal Society Open Science, a team of researchers including ISI Foundation Research Leader Vittoria Colizza, ISI Principal Researcher Michele Tizzoni and ISI Applied Data Science Manager Paolo Bajardi compares over 650k outbreaks generated with a spatially structured epidemic model based on two different human mobility networks in France (a commuting network extracted from mobile phone data and another extracted from a census survey), with the goal of testing the goodness of the mobile phone mobility network to replace the census survey mobility network.

Results show that similarity of simulated epidemics is significantly correlated to connectivity, traffic and population size of the seeding nodes, suggesting that the adequacy of mobile phone data for infectious disease models becomes higher when epidemics spread between highly connected and heavily populated locations, such as large urban areas: mobile phones are more reliable in central regions than peripheral ones. Scientists suggest that continued work along these directions is important to understand how to measure epidemiologically relevant patterns of movement to be further integrated into computational models which can ultimately help in forecasting and controlling disease spread.

Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models , Cecilia Panigutti, Michele Tizzoni, Paolo Bajardi, Zbigniew Smoreda, Vittoria Colizza. Royal Society Open Science, 17 May 2017.