Epidemiologically Optimal Static Networks from Temporal Network Data
Events
Loading … Spinner

Mendeley | Further Information

{"title"=>"Epidemiologically Optimal Static Networks from Temporal Network Data", "type"=>"journal", "authors"=>[{"first_name"=>"Petter", "last_name"=>"Holme", "scopus_author_id"=>"7003326827"}], "year"=>2013, "source"=>"PLoS Computational Biology", "identifiers"=>{"sgr"=>"84880787397", "doi"=>"10.1371/journal.pcbi.1003142", "pui"=>"369438562", "pmid"=>"23874184", "scopus"=>"2-s2.0-84880787397", "issn"=>"1553734X"}, "id"=>"712da213-12e8-31a7-879e-dfc787322910", "abstract"=>"One of network epidemiology's central assumptions is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We discuss these observations in the context of the temporal and topological structure of the data sets.", "link"=>"http://www.mendeley.com/research/epidemiologically-optimal-static-networks-temporal-network-data", "reader_count"=>81, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>9, "Researcher"=>26, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>21, "Student > Postgraduate"=>1, "Student > Master"=>9, "Student > Bachelor"=>5, "Lecturer > Senior Lecturer"=>2, "Professor"=>5, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>9, "Researcher"=>26, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>21, "Student > Postgraduate"=>1, "Student > Master"=>9, "Student > Bachelor"=>5, "Lecturer > Senior Lecturer"=>2, "Professor"=>5, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>11, "Engineering"=>4, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>9, "Agricultural and Biological Sciences"=>11, "Medicine and Dentistry"=>5, "Veterinary Science and Veterinary Medicine"=>3, "Business, Management and Accounting"=>1, "Physics and Astronomy"=>19, "Social Sciences"=>2, "Computer Science"=>14}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>19}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>11}, "Computer Science"=>{"Computer Science"=>14}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>9}, "Unspecified"=>{"Unspecified"=>11}, "Environmental Science"=>{"Environmental Science"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>3}}, "reader_count_by_country"=>{"United States"=>4, "China"=>2, "Japan"=>2, "Denmark"=>1, "Italy"=>2, "United Kingdom"=>1, "Australia"=>1, "Switzerland"=>1, "Spain"=>1}, "group_count"=>2}

Scopus | Further Information

{"@_fa"=>"true", "link"=>[{"@_fa"=>"true", "@ref"=>"self", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84880787397"}, {"@_fa"=>"true", "@ref"=>"author-affiliation", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84880787397?field=author,affiliation"}, {"@_fa"=>"true", "@ref"=>"scopus", "@href"=>"https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84880787397&origin=inward"}, {"@_fa"=>"true", "@ref"=>"scopus-citedby", "@href"=>"https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84880787397&origin=inward"}], "prism:url"=>"https://api.elsevier.com/content/abstract/scopus_id/84880787397", "dc:identifier"=>"SCOPUS_ID:84880787397", "eid"=>"2-s2.0-84880787397", "dc:title"=>"Epidemiologically Optimal Static Networks from Temporal Network Data", "dc:creator"=>"Holme P.", "prism:publicationName"=>"PLoS Computational Biology", "prism:issn"=>"1553734X", "prism:eIssn"=>"15537358", "prism:volume"=>"9", "prism:issueIdentifier"=>"7", "prism:pageRange"=>nil, "prism:coverDate"=>"2013-07-01", "prism:coverDisplayDate"=>"July 2013", "prism:doi"=>"10.1371/journal.pcbi.1003142", "citedby-count"=>"33", "prism:aggregationType"=>"Journal", "subtype"=>"ar", "subtypeDescription"=>"Article", "article-number"=>"e1003142", "source-id"=>"4000151810", "openaccess"=>"1", "openaccessFlag"=>true}

Facebook

  • {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fploscompbiol%2Farticle%3Fid%3D10.1371%252Fjournal.pcbi.1003142", "share_count"=>0, "like_count"=>0, "comment_count"=>0, "click_count"=>0, "total_count"=>0}

Twitter

Counter

  • {"month"=>"7", "year"=>"2013", "pdf_views"=>"114", "xml_views"=>"24", "html_views"=>"1261"}
  • {"month"=>"8", "year"=>"2013", "pdf_views"=>"102", "xml_views"=>"41", "html_views"=>"1944"}
  • {"month"=>"9", "year"=>"2013", "pdf_views"=>"24", "xml_views"=>"0", "html_views"=>"132"}
  • {"month"=>"10", "year"=>"2013", "pdf_views"=>"18", "xml_views"=>"2", "html_views"=>"160"}
  • {"month"=>"11", "year"=>"2013", "pdf_views"=>"8", "xml_views"=>"1", "html_views"=>"113"}
  • {"month"=>"12", "year"=>"2013", "pdf_views"=>"8", "xml_views"=>"1", "html_views"=>"70"}
  • {"month"=>"1", "year"=>"2014", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"59"}
  • {"month"=>"2", "year"=>"2014", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"51"}
  • {"month"=>"3", "year"=>"2014", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"44"}
  • {"month"=>"4", "year"=>"2014", "pdf_views"=>"7", "xml_views"=>"2", "html_views"=>"59"}
  • {"month"=>"5", "year"=>"2014", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"56"}
  • {"month"=>"6", "year"=>"2014", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"7", "year"=>"2014", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"31"}
  • {"month"=>"8", "year"=>"2014", "pdf_views"=>"3", "xml_views"=>"3", "html_views"=>"18"}
  • {"month"=>"9", "year"=>"2014", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"31"}
  • {"month"=>"10", "year"=>"2014", "pdf_views"=>"4", "xml_views"=>"1", "html_views"=>"25"}
  • {"month"=>"11", "year"=>"2014", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"25"}
  • {"month"=>"12", "year"=>"2014", "pdf_views"=>"6", "xml_views"=>"1", "html_views"=>"20"}
  • {"month"=>"1", "year"=>"2015", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"32"}
  • {"month"=>"2", "year"=>"2015", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"23"}
  • {"month"=>"3", "year"=>"2015", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"27"}
  • {"month"=>"4", "year"=>"2015", "pdf_views"=>"4", "xml_views"=>"1", "html_views"=>"24"}
  • {"month"=>"5", "year"=>"2015", "pdf_views"=>"15", "xml_views"=>"0", "html_views"=>"22"}
  • {"month"=>"6", "year"=>"2015", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"62"}
  • {"month"=>"7", "year"=>"2015", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"66"}
  • {"month"=>"8", "year"=>"2015", "pdf_views"=>"8", "xml_views"=>"1", "html_views"=>"29"}
  • {"month"=>"9", "year"=>"2015", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"18"}
  • {"month"=>"10", "year"=>"2015", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"50"}
  • {"month"=>"11", "year"=>"2015", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"31"}
  • {"month"=>"12", "year"=>"2015", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"65"}
  • {"month"=>"1", "year"=>"2016", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"20"}
  • {"month"=>"2", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"27"}
  • {"month"=>"3", "year"=>"2016", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"31"}
  • {"month"=>"4", "year"=>"2016", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"24"}
  • {"month"=>"5", "year"=>"2016", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"15"}
  • {"month"=>"6", "year"=>"2016", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"32"}
  • {"month"=>"7", "year"=>"2016", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"29"}
  • {"month"=>"8", "year"=>"2016", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"32"}
  • {"month"=>"9", "year"=>"2016", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"26"}
  • {"month"=>"10", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"31"}
  • {"month"=>"11", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"28"}
  • {"month"=>"12", "year"=>"2016", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"24"}
  • {"month"=>"1", "year"=>"2017", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"30"}
  • {"month"=>"2", "year"=>"2017", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"3", "year"=>"2017", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"33"}
  • {"month"=>"4", "year"=>"2017", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"40"}
  • {"month"=>"5", "year"=>"2017", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"49"}
  • {"month"=>"6", "year"=>"2017", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"16"}
  • {"month"=>"7", "year"=>"2017", "pdf_views"=>"14", "xml_views"=>"0", "html_views"=>"22"}
  • {"month"=>"8", "year"=>"2017", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"18"}
  • {"month"=>"9", "year"=>"2017", "pdf_views"=>"11", "xml_views"=>"1", "html_views"=>"26"}
  • {"month"=>"10", "year"=>"2017", "pdf_views"=>"8", "xml_views"=>"2", "html_views"=>"20"}
  • {"month"=>"11", "year"=>"2017", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"22"}
  • {"month"=>"12", "year"=>"2017", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"17"}
  • {"month"=>"1", "year"=>"2018", "pdf_views"=>"17", "xml_views"=>"0", "html_views"=>"16"}
  • {"month"=>"2", "year"=>"2018", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"3", "year"=>"2018", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"11"}
  • {"month"=>"4", "year"=>"2018", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"6"}
  • {"month"=>"5", "year"=>"2018", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"6", "year"=>"2018", "pdf_views"=>"8", "xml_views"=>"1", "html_views"=>"18"}
  • {"month"=>"7", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"5", "html_views"=>"10"}
  • {"month"=>"8", "year"=>"2018", "pdf_views"=>"11", "xml_views"=>"1", "html_views"=>"5"}
  • {"month"=>"9", "year"=>"2018", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"10", "year"=>"2018", "pdf_views"=>"12", "xml_views"=>"2", "html_views"=>"11"}
  • {"month"=>"11", "year"=>"2018", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"12"}
  • {"month"=>"12", "year"=>"2018", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"4"}
  • {"month"=>"1", "year"=>"2019", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"18"}
  • {"month"=>"2", "year"=>"2019", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"19"}
  • {"month"=>"3", "year"=>"2019", "pdf_views"=>"12", "xml_views"=>"3", "html_views"=>"7"}
  • {"month"=>"4", "year"=>"2019", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"4"}
  • {"month"=>"5", "year"=>"2019", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"6", "year"=>"2019", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"4"}
  • {"month"=>"7", "year"=>"2019", "pdf_views"=>"9", "xml_views"=>"0", "html_views"=>"6"}
  • {"month"=>"8", "year"=>"2019", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"1"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1122718"], "description"=>"<p>Panel A shows the number of (non-zero degree) vertices in the network; B displays the average degree; C gives the relative size of the largest connected component; while D shows the corresponding figure to C for null models of the same degree sequences as in C, but otherwise random. The error bars are displayed if they are about the same size as the symbols and show the standard error.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "optimized", "representations", "synthetic"], "article_id"=>748429, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Topology_of_the_optimized_network_representations_for_synthetic_data_/748429", "title"=>"Topology of the optimized network representations for synthetic data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122715"], "description"=>"<p>Steps 1–2 represent the configuration model used to create a static network. Then, in Step 3, we assign active intervals (time periods where contacts are allowed). In Step 4–6, we assign contact times within the intervals from the same interevent time distribution.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "schematic", "synthetic", "temporal"], "article_id"=>748425, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.g003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_schematic_illustration_of_how_we_generate_synthetic_temporal_networks_/748425", "title"=>"A schematic illustration of how we generate synthetic temporal networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122713"], "description"=>"<p>Panel A shows data for the time-slice networks; B displays results for the ongoing networks and C gives the picture for the exponential-threshold representation. The dotted line illustrates the exponential form of the region of optimality (the equation being τ/<i>T</i> = 2<i>e</i><sup>Ω/0.32</sup>). The quantities of dimension time are, as indicated, rescaled by the total sampling time <i>T</i> (2,232 days in this case).</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "parameter"], "article_id"=>748424, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.g002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_performance_of_the_network_representation_as_a_function_of_parameter_values_for_the_Prostitution_data_/748424", "title"=>"The performance of the network representation ρ as a function of parameter values for the <i>Prostitution</i> data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122726"], "description"=>"<p>The last column shows values for the network of accumulated contacts. For the <i>Gallery</i> data, the values are averaged over the 69 days. The values in parentheses represent the standard error in the order of the last digit. The largest values for each data set are highlighted with boldface. The parameters of temporal dimensions—<i>t</i><sub>start</sub>, <i>t</i><sub>stop</sub> and τ—are measured in units of the total sampling time <i>T</i> of the respective data set (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#pcbi-1003142-t001\" target=\"_blank\">Table 1</a>).</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "empirical"], "article_id"=>748437, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.t002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maximal_performance_values_for_the_empirical_data_sets_/748437", "title"=>"Maximal performance values for the empirical data sets.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122711"], "description"=>"<p>To the left in all panels is a temporal network where each horizontal line is the timeline of a vertex. The vertical curves symbolize the contact between two vertices as one timestep. Panel A shows the construction of the time-slice network. Two vertices are connected if they have at least one contact in the time interval [<i>t</i><sub>start</sub>,<i>t</i><sub>stop</sub>]. In panel B, a vertex pair is connected if they have contacts before <i>t</i><sub>start</sub> and after <i>t</i><sub>stop</sub>. Finally, panel C illustrates how the contact sequence is reduced to a weighted graph that is converted to an unweighted graph by requiring an edge to have a weight over a certain threshold Ω. The thickness of the lines in panel C is proportional to the weight between the pair.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks"], "article_id"=>748422, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.g001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_the_network_representations_/748422", "title"=>"Illustration of the network representations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122725"], "description"=>"<p><i>S</i> is the fraction of vertices in the largest connected component. <i>d</i> is the average pathlength in the largest connected component. The quantities with subscript 0 are values from a reference model with the same degree sequence as the original network, but otherwise being random. These are averages over 10<sup>4</sup> randomizations and all the digits are significant to one standard deviation. The values for the <i>Gallery</i> data are averaged over the 69 days of sampling. The standard deviations of these mean values are indicated in the parentheses in the same way as in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#pcbi-1003142-t001\" target=\"_blank\">Tables 1</a> and <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#pcbi-1003142-t002\" target=\"_blank\">2</a>.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "optimized", "time-slice", "networks", "empirical"], "article_id"=>748436, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.t003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_properties_of_the_optimized_time_slice_networks_of_the_empirical_contact_sequences_/748436", "title"=>"Network properties of the optimized time-slice networks of the empirical contact sequences.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122722"], "description"=>"<p>Notations correspond to those of <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#pcbi-1003142-t003\" target=\"_blank\">Table 3</a>.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "accumulated"], "article_id"=>748433, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.t006", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_properties_of_the_network_of_accumulated_contacts_/748433", "title"=>"Network properties of the network of accumulated contacts.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122720"], "description"=>"<p>Notations correspond to those of <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#pcbi-1003142-t003\" target=\"_blank\">Table 3</a>.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "optimized", "exponential-threshold"], "article_id"=>748431, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.t005", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_properties_of_the_optimized_exponential_threshold_networks_/748431", "title"=>"Network properties of the optimized exponential-threshold networks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122721"], "description"=>"<p>Notations correspond to those of <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#pcbi-1003142-t003\" target=\"_blank\">Table 3</a>.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "optimized"], "article_id"=>748432, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.t004", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_properties_of_the_optimized_ongoing_networks_/748432", "title"=>"Network properties of the optimized ongoing networks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122716"], "description"=>"<p>We display the maximum value of the Spearman rank correlation as a function of the overlap parameter μ (a model-parameter controlling the fraction of concurrent relationships). Error bars showing the standard error would be smaller than the symbol size and are not plotted.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "representations", "synthetic"], "article_id"=>748427, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.g004", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Performance_of_the_network_representations_on_the_synthetic_data_sets_/748427", "title"=>"Performance of the network representations on the synthetic data sets.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122733", "https://ndownloader.figshare.com/files/1122735", "https://ndownloader.figshare.com/files/1122736", "https://ndownloader.figshare.com/files/1122737", "https://ndownloader.figshare.com/files/1122739"], "description"=>"<div><p>One of network epidemiology's central assumptions is that the contact structure over which infectious diseases propagate can be represented as a static network. However, contacts are highly dynamic, changing at many time scales. In this paper, we investigate conceptually simple methods to construct static graphs for network epidemiology from temporal contact data. We evaluate these methods on empirical and synthetic model data. For almost all our cases, the network representation that captures most relevant information is a so-called exponential-threshold network. In these, each contact contributes with a weight decreasing exponentially with time, and there is an edge between a pair of vertices if the weight between them exceeds a threshold. Networks of aggregated contacts over an optimally chosen time window perform almost as good as the exponential-threshold networks. On the other hand, networks of accumulated contacts over the entire sampling time, and networks of concurrent partnerships, perform worse. We discuss these observations in the context of the temporal and topological structure of the data sets.</p></div>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "optimal", "static", "networks", "temporal"], "article_id"=>748444, "categories"=>["Sociology", "Biological Sciences", "Medicine"], "users"=>["Petter Holme"], "doi"=>[nil, nil, nil, nil, nil], "stats"=>{"downloads"=>23, "page_views"=>44, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Epidemiologically_Optimal_Static_Networks_from_Temporal_Network_Data/748444", "title"=>"Epidemiologically Optimal Static Networks from Temporal Network Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-07-18 04:25:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/1122723"], "description"=>"<p><i>N</i>, <i>M</i> and <i>L</i> are the number of individuals, edges in the accumulated network (pairs with at least one contact) and contacts, respectively. λ is the per-contact transmission probability used in the disease-spreading simulations. <i>T</i> is the total sampling time. <i>B</i> is the burstiness index of the entire set of interevent times between pairs of at least two contacts. The values for the <i>Gallery</i> data are averaged over all 69 days. The values in parentheses show the standard errors of the number in the order of its last decimal. For details of the definitions of parameters, see the <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003142#s4\" target=\"_blank\">Methods</a> section.</p>", "links"=>[], "tags"=>["Population biology", "epidemiology", "Infectious disease epidemiology", "Infectious diseases", "Infectious disease modeling", "Sociology", "social networks", "temporal"], "article_id"=>748434, "categories"=>["Medicine", "Biological Sciences", "Sociology"], "users"=>["Petter Holme"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003142.t001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Empirical_data_sets_8212_Sizes_and_basic_temporal_statistics_/748434", "title"=>"Empirical data sets—Sizes and basic temporal statistics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-07-18 04:25:18"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"7"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"7", "cited-by"=>"0", "year"=>"2013", "month"=>"8"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"13", "cited-by"=>"0", "year"=>"2013", "month"=>"9"}
  • {"unique-ip"=>"8", "full-text"=>"12", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"10"}
  • {"unique-ip"=>"13", "full-text"=>"14", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"11"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"2", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2013", "month"=>"12"}
  • {"unique-ip"=>"15", "full-text"=>"19", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"1"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2014", "month"=>"2"}
  • {"unique-ip"=>"11", "full-text"=>"19", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"3"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"4"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"5", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"12", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"14", "full-text"=>"12", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"8", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"7", "full-text"=>"4", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"3"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
  • {"unique-ip"=>"15", "full-text"=>"15", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"7"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"5", "full-text"=>"7", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"1", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"3", "full-text"=>"1", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"2", "full-text"=>"4", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"9", "full-text"=>"3", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"4", "full-text"=>"6", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"5", "full-text"=>"0", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"3", "full-text"=>"1", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"9", "full-text"=>"3", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"7", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"10", "full-text"=>"6", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"2", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Computer and information sciences", "average_usage"=>[297, 488, 616, 724, 828, 939, 1038, 1127, 1223, 1311, 1393, 1479, 1556]}, {"subject_area"=>"/Computer and information sciences/Data visualization", "average_usage"=>[293, 478, 588, 673, 782, 884, 973, 1055, 1126, 1239, 1329, 1404, 1497]}, {"subject_area"=>"/Computer and information sciences/Network analysis", "average_usage"=>[340, 548, 701, 844, 945, 1073, 1189, 1282, 1391, 1488, 1562, 1660, 1731]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[264, 460, 584, 692, 794, 887, 978, 1067, 1154, 1241, 1328, 1408, 1474]}, {"subject_area"=>"/Medicine and health sciences/Infectious diseases", "average_usage"=>[297, 523, 655, 765, 866, 971, 1070, 1159, 1256, 1337, 1424, 1496, 1568]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[259, 431, 541, 639, 727, 816, 898, 980, 1061, 1136, 1214, 1294, 1356]}, {"subject_area"=>"/Social sciences", "average_usage"=>[289, 475, 593, 703, 805, 902, 990, 1078, 1158, 1250, 1336, 1417, 1482]}, {"subject_area"=>"/Social sciences/Sociology", "average_usage"=>[310, 523, 656, 780, 900, 1024, 1120, 1219, 1308, 1395, 1468, 1570, 1642]}]}

F1000Prime | Further Information

Loading … Spinner
There are currently no alerts