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      Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti

      PLoS Medicine
      Public Library of Science (PLoS)

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          Understanding individual human mobility patterns

          Despite their importance for urban planning, traffic forecasting, and the spread of biological and mobile viruses, our understanding of the basic laws governing human motion remains limited thanks to the lack of tools to monitor the time resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six month period. We find that in contrast with the random trajectories predicted by the prevailing Levy flight and random walk models, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time independent characteristic length scale and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent based modeling.
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            Social and environmental risk factors in the emergence of infectious diseases

            Fifty years ago, the age-old scourge of infectious disease was receding in the developed world in response to improved public health measures, while the advent of antibiotics, better vaccines, insecticides and improved surveillance held the promise of eradicating residual problems. By the late twentieth century, however, an increase in the emergence and re-emergence of infectious diseases was evident in many parts of the world. This upturn looms as the fourth major transition in human–microbe relationships since the advent of agriculture around 10,000 years ago. About 30 new diseases have been identified, including Legionnaires' disease, human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), hepatitis C, bovine spongiform encephalopathy (BSE)/variant Creutzfeldt-Jakob disease (vCJD), Nipah virus, several viral hemorrhagic fevers and, most recently, severe acute respiratory syndrome (SARS) and avian influenza. The emergence of these diseases, and resurgence of old ones like tuberculosis and cholera, reflects various changes in human ecology: rural-to-urban migration resulting in high-density peri-urban slums; increasing long-distance mobility and trade; the social disruption of war and conflict; changes in personal behavior; and, increasingly, human-induced global changes, including widespread forest clearance and climate change. Political ignorance, denial and obduracy (as with HIV/AIDS) further compound the risks. The use and misuse of medical technology also pose risks, such as drug-resistant microbes and contaminated equipment or biological medicines. A better understanding of the evolving social dynamics of emerging infectious diseases ought to help us to anticipate and hopefully ameliorate current and future risks.
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              Multiscale mobility networks and the large scale spreading of infectious diseases

              , , (2010)
              Among the realistic ingredients to be considered in the computational modeling of infectious diseases, human mobility represents a crucial challenge both on the theoretical side and in view of the limited availability of empirical data. In order to study the interplay between small-scale commuting flows and long-range airline traffic in shaping the spatio-temporal pattern of a global epidemic we i) analyze mobility data from 29 countries around the world and find a gravity model able to provide a global description of commuting patterns up to 300 kms; ii) integrate in a worldwide structured metapopulation epidemic model a time-scale separation technique for evaluating the force of infection due to multiscale mobility processes in the disease dynamics. Commuting flows are found, on average, to be one order of magnitude larger than airline flows. However, their introduction into the worldwide model shows that the large scale pattern of the simulated epidemic exhibits only small variations with respect to the baseline case where only airline traffic is considered. The presence of short range mobility increases however the synchronization of subpopulations in close proximity and affects the epidemic behavior at the periphery of the airline transportation infrastructure. The present approach outlines the possibility for the definition of layered computational approaches where different modeling assumptions and granularities can be used consistently in a unifying multi-scale framework.
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                Author and article information

                Journal
                10.1371/journal.pmed.1001083
                http://creativecommons.org/licenses/by/4.0/

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