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  1. Article: Epidemic in networked population with recurrent mobility pattern.

    Feng, Liang / Zhao, Qianchuan / Zhou, Cangqi

    Chaos, solitons, and fractals

    2020  Volume 139, Page(s) 110016

    Abstract: ... to analyse and prevent the epidemic spreading in networked population with recurrent mobility pattern. ... structure and human mobility greatly influence the dynamics of epidemic spreading. In this paper, we utilize ... relationship between mobility possibility and epidemic threshold and differences between Erdös-Rényi and power ...

    Abstract The novel Coronavirus (COVID-19) has caused a global crisis and many governments have taken social measures, such as home quarantine and maintaining social distance. Many recent studies show that network structure and human mobility greatly influence the dynamics of epidemic spreading. In this paper, we utilize a discrete-time Markov chain approach and propose an epidemic model to describe virus propagation in the heterogeneous graph, which is used to represent individuals with intra social connections and mobility between individuals and common locations. There are two types of nodes, individuals and public places, and disease can spread by social contacts among individuals and people gathering in common areas. We give theoretical results about epidemic threshold and influence of isolation factor. Several numerical simulations are performed and experimental results further demonstrate the correctness of proposed model. Non-monotonic relationship between mobility possibility and epidemic threshold and differences between Erdös-Rényi and power-law social connections are revealed. In summary, our proposed approach and findings are helpful to analyse and prevent the epidemic spreading in networked population with recurrent mobility pattern.
    Keywords covid19
    Language English
    Publishing date 2020-06-25
    Publishing country England
    Document type Journal Article
    ZDB-ID 2003919-0
    ISSN 1873-2887 ; 0960-0779
    ISSN (online) 1873-2887
    ISSN 0960-0779
    DOI 10.1016/j.chaos.2020.110016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Epidemic in networked population with recurrent mobility pattern

    Feng, Liang / Zhao, Qianchuan / Zhou, Cangqi

    Chaos, solitons, and fractals

    Abstract: ... to analyse and prevent the epidemic spreading in networked population with recurrent mobility pattern ... structure and human mobility greatly influence the dynamics of epidemic spreading In this paper, we utilize ... relationship between mobility possibility and epidemic threshold and differences between Erdös-Rényi and power ...

    Abstract The novel Coronavirus (COVID-19) has caused a global crisis and many governments have taken social measures, such as home quarantine and maintaining social distance Many recent studies show that network structure and human mobility greatly influence the dynamics of epidemic spreading In this paper, we utilize a discrete-time Markov chain approach and propose an epidemic model to describe virus propagation in the heterogeneous graph, which is used to represent individuals with intra social connections and mobility between individuals and common locations There are two types of nodes, individuals and public places, and disease can spread by social contacts among individuals and people gathering in common areas We give theoretical results about epidemic threshold and influence of isolation factor Several numerical simulations are performed and experimental results further demonstrate the correctness of proposed model Non-monotonic relationship between mobility possibility and epidemic threshold and differences between Erdös-Rényi and power-law social connections are revealed In summary, our proposed approach and findings are helpful to analyse and prevent the epidemic spreading in networked population with recurrent mobility pattern
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #728471
    Database COVID19

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  3. Article ; Online: Epidemic spreading in localized environments with recurrent mobility patterns.

    Granell, Clara / Mucha, Peter J

    Physical review. E

    2018  Volume 97, Issue 5-1, Page(s) 52302

    Abstract: ... mobility patterns-such as workplaces, university campuses, or schools-it is of critical importance ... follow clear recurrent travel patterns. This model allows analytical determination of the onset ... which may be impacted by the mobility dynamics of the individuals themselves. In confined scenarios ...

    Abstract The spreading of epidemics is very much determined by the structure of the contact network, which may be impacted by the mobility dynamics of the individuals themselves. In confined scenarios where a small, closed population spends most of its time in localized environments and has easily identifiable mobility patterns-such as workplaces, university campuses, or schools-it is of critical importance to identify the factors controlling the rate of disease spread. Here, we present a discrete-time, metapopulation-based model to describe the transmission of susceptible-infected-susceptible-like diseases that take place in confined scenarios where the mobilities of the individuals are not random but, rather, follow clear recurrent travel patterns. This model allows analytical determination of the onset of epidemics, as well as the ability to discern which contact structures are most suited to prevent the infection to spread. It thereby determines whether common prevention mechanisms, as isolation, are worth implementing in such a scenario and their expected impact.
    MeSH term(s) Communicable Diseases/transmission ; Epidemics ; Models, Theoretical ; Recurrence
    Keywords covid19
    Language English
    Publishing date 2018-06-12
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2844562-4
    ISSN 2470-0053 ; 2470-0045
    ISSN (online) 2470-0053
    ISSN 2470-0045
    DOI 10.1103/PhysRevE.97.052302
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models.

    Panigutti, Cecilia / Tizzoni, Michele / Bajardi, Paolo / Smoreda, Zbigniew / Colizza, Vittoria

    Royal Society open science

    2017  Volume 4, Issue 5, Page(s) 160950

    Abstract: ... epidemic model based on two different human mobility networks: a commuting network of France extracted ... Notwithstanding a number of successful case studies, previous works have shown that using different mobility data sources ... of simulated epidemics is significantly correlated to connectivity, traffic and population size of the seeding ...

    Abstract The recent availability of large-scale call detail record data has substantially improved our ability of quantifying human travel patterns with broad applications in epidemiology. Notwithstanding a number of successful case studies, 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. Thus, it remains unclear to what extent epidemic modelling results may vary when using different proxies for human movements. Here, we systematically compare 658 000 simulated outbreaks generated with a spatially structured epidemic model based on two different human mobility networks: a commuting network of France extracted from mobile phone data and another extracted from a census survey. We compare epidemic patterns originating from all the 329 possible outbreak seed locations and identify the structural network properties of the seeding nodes that best predict spatial and temporal epidemic patterns to be alike. We find 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.
    Keywords covid19
    Language English
    Publishing date 2017-05-17
    Publishing country England
    Document type Journal Article
    ZDB-ID 2787755-3
    ISSN 2054-5703
    ISSN 2054-5703
    DOI 10.1098/rsos.160950
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: 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, Vol 4, Iss

    2017  Volume 5

    Abstract: ... epidemic model based on two different human mobility networks: a commuting network of France extracted ... Notwithstanding a number of successful case studies, previous works have shown that using different mobility data sources ... of simulated epidemics is significantly correlated to connectivity, traffic and population size of the seeding ...

    Abstract The recent availability of large-scale call detail record data has substantially improved our ability of quantifying human travel patterns with broad applications in epidemiology. Notwithstanding a number of successful case studies, 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. Thus, it remains unclear to what extent epidemic modelling results may vary when using different proxies for human movements. Here, we systematically compare 658 000 simulated outbreaks generated with a spatially structured epidemic model based on two different human mobility networks: a commuting network of France extracted from mobile phone data and another extracted from a census survey. We compare epidemic patterns originating from all the 329 possible outbreak seed locations and identify the structural network properties of the seeding nodes that best predict spatial and temporal epidemic patterns to be alike. We find 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.
    Keywords epidemic modelling ; infectious diseases ; mobile phones ; spatial epidemiology ; Science ; Q
    Subject code 612
    Language English
    Publishing date 2017-01-01T00:00:00Z
    Publisher The Royal Society
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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