Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of...Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of nodes(individuals)connected bylinks(sometimes as a temporal network where the links are not continuously active)and the disease as a compartmental model(whereindividuals are assigned states with respect to the disease and follow certain transition rules between the states).In this paper,we discussfast algorithms for such simulations and also compare two commonly used versions,one where there is a constant recovery rate(the numberof individuals that stop being infectious per time is proportional to the number of such people);the other where the duration of the diseaseis constant.The results show that,for most practical purposes,these versions are qualitatively the same.展开更多
Our daily life leaves an increasing amount of digital traces,footprints that are improving our lives.Data-mining tools,like recommender systems,convert these traces to information for aiding decisions in an ever-incre...Our daily life leaves an increasing amount of digital traces,footprints that are improving our lives.Data-mining tools,like recommender systems,convert these traces to information for aiding decisions in an ever-increasing number of areas in our lives.The feedback loop from what we do,to the information this produces,to decisions what to do next,will likely be an increasingly important factor in human behavior on all levels from individuals to societies.In this essay,we review some effects of this feedback and discuss how to understand and exploit them beyond mapping them on more well-understood phenomena.We take examples from models of spreading phenomena in social media to argue that analogies can be deceptive,instead we need to fresh approaches to the new types of data,something we exemplify with promising applications in medicine.展开更多
基金Basic science research program through the national research foundation of Korea(NRF)funded by the ministry of education(2013R1A1A2011947)
文摘Network epidemiology has become a core framework for investigating the role of human contact patterns in the spreadingof infectious diseases.In network epidemiology,one represents the contact structure as a network of nodes(individuals)connected bylinks(sometimes as a temporal network where the links are not continuously active)and the disease as a compartmental model(whereindividuals are assigned states with respect to the disease and follow certain transition rules between the states).In this paper,we discussfast algorithms for such simulations and also compare two commonly used versions,one where there is a constant recovery rate(the numberof individuals that stop being infectious per time is proportional to the number of such people);the other where the duration of the diseaseis constant.The results show that,for most practical purposes,these versions are qualitatively the same.
基金supported by the Swedish Research Foundation and the WCU Program through NRF Korea funded by MEST under Grant No.R31-2008-10029
文摘Our daily life leaves an increasing amount of digital traces,footprints that are improving our lives.Data-mining tools,like recommender systems,convert these traces to information for aiding decisions in an ever-increasing number of areas in our lives.The feedback loop from what we do,to the information this produces,to decisions what to do next,will likely be an increasingly important factor in human behavior on all levels from individuals to societies.In this essay,we review some effects of this feedback and discuss how to understand and exploit them beyond mapping them on more well-understood phenomena.We take examples from models of spreading phenomena in social media to argue that analogies can be deceptive,instead we need to fresh approaches to the new types of data,something we exemplify with promising applications in medicine.
