Extinction Times of Epidemic Outbreaks in Networks
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{"title"=>"Extinction times of epidemic outbreaks in networks", "type"=>"journal", "authors"=>[{"first_name"=>"Petter", "last_name"=>"Holme", "scopus_author_id"=>"7003326827"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84891297012", "sgr"=>"84891297012", "issn"=>"19326203", "arxiv"=>"1310.3932", "doi"=>"10.1371/journal.pone.0084429", "pmid"=>"24386377", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pui"=>"372005886"}, "id"=>"cc77c614-6427-3cb5-b124-274d88300daa", "abstract"=>"In the Susceptible-Infectious-Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold.", "link"=>"http://www.mendeley.com/research/extinction-times-epidemic-outbreaks-networks", "reader_count"=>29, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>6, "Researcher"=>9, "Student > Ph. D. Student"=>7, "Student > Master"=>5, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>6, "Researcher"=>9, "Student > Ph. D. Student"=>7, "Student > Master"=>5, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Nursing and Health Professions"=>1, "Mathematics"=>5, "Agricultural and Biological Sciences"=>4, "Medicine and Dentistry"=>2, "Physics and Astronomy"=>9, "Social Sciences"=>1, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>9}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>5}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"United States"=>2, "United Kingdom"=>1, "France"=>1, "Germany"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1328998"], "description"=>"<p>Panels A and B show curves based on the configuration model with exponent –2; C and D show similar plots for exponent –2.5; E and F are corresponding plots for exponent –3; G shows the coefficients of determination for the Erdős-Rényi model. The abbreviations are explained in the Methods section. All data points are averaged over 1000 networks. Error bars would have been smaller than the symbol size.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "Population biology", "epidemiology", "Infectious disease epidemiology", "Theoretical biology", "Applied mathematics", "Complex systems", "Infectious diseases", "Sociology", "Computational sociology", "metrics", "maximal", "extinction", "functions"], "article_id"=>886928, "categories"=>["Biological Sciences", "Mathematics", "Medicine", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0084429.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_R_2_values_for_the_correlation_between_various_distance_metrics_and_maximal_time_to_extinction_as_functions_of_number_of_vertices_/886928", "title"=>"<i>R</i><sup>2</sup> values for the correlation between various distance metrics and maximal time to extinction as functions of number of vertices.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-26 04:13:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1328995"], "description"=>"<p>Panel A shows the average time to extinction as a function of the per-contact transmission probability. Panel B shows the average fraction of vertices at some point affected by the outbreak. For an intermediate value the outbreak lives longer than for other λ (A). These figures are made for one realization of the configuration model with power-law degree distribution with parameter values <i>N</i> = 200 and γ = 2.5. We sampled 501 equidistant values of λ, averaged over 10<sup>6</sup> runs of the disease simulation. The curves were smoothed to remove small fluctuations (the general curvature on a scale larger than λ≈0.001 is unaltered).</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "Population biology", "epidemiology", "Infectious disease epidemiology", "Theoretical biology", "Applied mathematics", "Complex systems", "Infectious diseases", "Sociology", "Computational sociology"], "article_id"=>886925, "categories"=>["Biological Sciences", "Mathematics", "Medicine", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0084429.g001", "stats"=>{"downloads"=>2, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_maximum_of_the_time_to_extinction_/886925", "title"=>"The maximum of the time to extinction.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-26 04:13:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1328996"], "description"=>"<p>A shows the results for the configuration model; B displays the result for the configuration model with added clustering; C shows the outcome for the Erdős-Rényi model. One dot gives the value for one realization of the network models (they have transparency to visualize the overlap of points). There are 1000 points per size. Error bars in would have been smaller than the symbol size.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "Population biology", "epidemiology", "Infectious disease epidemiology", "Theoretical biology", "Applied mathematics", "Complex systems", "Infectious diseases", "Sociology", "Computational sociology", "maximal", "extinction"], "article_id"=>886926, "categories"=>["Biological Sciences", "Mathematics", "Medicine", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0084429.g002", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatter_plots_of_the_maximal_time_to_extinction_as_function_of_SWAE_/886926", "title"=>"Scatter plots of the maximal time to extinction as function of SWAE.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-26 04:13:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1329000"], "description"=>"<p>Panel A shows data for the configuration model; B is for the configuration model with added triangles; C is for the Erdős-Rényi model. All points are averaged over 1000 network realizations.</p>", "links"=>[], "tags"=>["Computational biology", "Population modeling", "Infectious disease modeling", "Population biology", "epidemiology", "Infectious disease epidemiology", "Theoretical biology", "Applied mathematics", "Complex systems", "Infectious diseases", "Sociology", "Computational sociology", "averages", "maximizing", "functions"], "article_id"=>886930, "categories"=>["Biological Sciences", "Mathematics", "Medicine", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0084429.g004", "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_averages_of_955_values_maximizing_the_time_to_extinction_as_functions_of_the_system_size_/886930", "title"=>"The averages of λ-values maximizing the time to extinction, as functions of the system size.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-12-26 04:13:19"}

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Relative Metric

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