Seasonal Influenza Vaccination for Children in Thailand: A Cost-Effectiveness Analysis
Publication Date
May 26, 2015
Journal
PLOS Medicine
Authors
Aronrag Meeyai, Naiyana Praditsitthikorn, Surachai Kotirum, Wantanee Kulpeng, et al
Volume
12
Issue
5
Pages
e1001829
DOI
https://dx.plos.org/10.1371/journal.pmed.1001829
Publisher URL
http://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.1001829
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/26011712
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4444096
Europe PMC
http://europepmc.org/abstract/MED/26011712
Web of Science
000355304100007
Scopus
84930532938
Mendeley
http://www.mendeley.com/research/seasonal-influenza-vaccination-children-thailand-costeffectiveness-analysis-4
Events
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Mendeley | Further Information

{"title"=>"Seasonal Influenza Vaccination for Children in Thailand: A Cost-Effectiveness Analysis", "type"=>"journal", "authors"=>[{"first_name"=>"Aronrag", "last_name"=>"Meeyai", "scopus_author_id"=>"8558026800"}, {"first_name"=>"Naiyana", "last_name"=>"Praditsitthikorn", "scopus_author_id"=>"26325828400"}, {"first_name"=>"Surachai", "last_name"=>"Kotirum", "scopus_author_id"=>"41161492900"}, {"first_name"=>"Wantanee", "last_name"=>"Kulpeng", "scopus_author_id"=>"55566779900"}, {"first_name"=>"Weerasak", "last_name"=>"Putthasri", "scopus_author_id"=>"26429848200"}, {"first_name"=>"Ben S.", "last_name"=>"Cooper", "scopus_author_id"=>"7401623515"}, {"first_name"=>"Yot", "last_name"=>"Teerawattananon", "scopus_author_id"=>"57193358558"}], "year"=>2015, "source"=>"PLoS Medicine", "identifiers"=>{"issn"=>"15491676", "scopus"=>"2-s2.0-84930532938", "pui"=>"604771712", "doi"=>"10.1371/journal.pmed.1001829", "isbn"=>"1549-1277", "sgr"=>"84930532938", "pmid"=>"26011712"}, "id"=>"abb2cfd5-5477-3b68-a05e-c5e55cda07c1", "abstract"=>"BACKGROUND: Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly.\\n\\nMETHODS AND FINDINGS: We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups.\\n\\nCONCLUSIONS: Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries.", "link"=>"http://www.mendeley.com/research/seasonal-influenza-vaccination-children-thailand-costeffectiveness-analysis-4", "reader_count"=>29, "reader_count_by_academic_status"=>{"Librarian"=>2, "Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>3, "Other"=>4, "Student > Bachelor"=>1, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Librarian"=>2, "Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>3, "Other"=>4, "Student > Bachelor"=>1, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>2, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>12, "Agricultural and Biological Sciences"=>1, "Design"=>1, "Philosophy"=>1, "Social Sciences"=>4, "Immunology and Microbiology"=>1, "Earth and Planetary Sciences"=>1, "Economics, Econometrics and Finance"=>1, "Decision Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Design"=>{"Design"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>12}, "Social Sciences"=>{"Social Sciences"=>4}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Unspecified"=>{"Unspecified"=>3}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Switzerland"=>1}, "group_count"=>5}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2082288"], "description"=>"<p>Figure shows how the optimal policy (defined as the policy that maximizes the INB) changes with LAIV effectiveness, unit cost of LAIV, and willingness to pay (WTP) per DALY averted (cost-effectiveness threshold). (A) Base case mixing matrix. (B) Contact matrix based on physical contacts only.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426075, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.g004", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Threshold_analysis_/1426075", "title"=>"Threshold analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082304"], "description"=>"<div><p>Background</p><p>Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly.</p><p>Methods and Findings</p><p>We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups.</p><p>Conclusions</p><p>Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries.</p></div>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426088, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829", "stats"=>{"downloads"=>3, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Seasonal_Influenza_Vaccination_for_Children_in_Thailand_A_Cost_Effectiveness_Analysis_/1426088", "title"=>"Seasonal Influenza Vaccination for Children in Thailand: A Cost-Effectiveness Analysis", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082299"], "description"=>"<p>All cost parameters are given as international dollars per case.</p><p><sup>a</sup>See <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001829#pmed.1001829.s001\" target=\"_blank\">S1 Text</a>.</p><p>CrI, credible interval.</p><p>Prior distributions for health outcome and cost parameters and their sources.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426083, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.t004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prior_distributions_for_health_outcome_and_cost_parameters_and_their_sources_/1426083", "title"=>"Prior distributions for health outcome and cost parameters and their sources.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082298"], "description"=>"<p><sup>a</sup>Assigns equal probabilities to all values between 0.1 and 5, which includes the entire range of values with non-negligible probabilities from previous studies [<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001829#pmed.1001829.ref002\" target=\"_blank\">2</a>].</p><p><sup>b</sup>The serial interval is the sum of the latent period (which has an expected value of 1 d) and the infectious period (which has a gamma-distributed prior with mean 1.5 and standard deviation 0.1).</p><p>CrI, credible interval.</p><p>Prior distributions for epidemiology model used in the base case analysis.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426082, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.t003", "stats"=>{"downloads"=>2, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prior_distributions_for_epidemiology_model_used_in_the_base_case_analysis_/1426082", "title"=>"Prior distributions for epidemiology model used in the base case analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082276"], "description"=>"<p>The directed acyclic graph illustrates the dependencies between model components. Squares represent data sources, and circles represent quantities about which we are uncertain (double circles indicate quantities for which we have external information about their values, which is represented by informative prior distributions). Single and double arrows indicate stochastic and deterministic relationships, respectively, and arrows point towards the dependent variable. ILI, influenza-like illness.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426063, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.g001", "stats"=>{"downloads"=>5, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_illustration_of_analytic_framework_/1426063", "title"=>"Schematic illustration of analytic framework.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082291"], "description"=>"<p>The width of bars corresponds to the probability density, the central black line within each bar represents the interquartile range of the DALYs averted, and the white circle represents the median value. Note that all DALYs averted in those 18 y and over or under 2 y are by definition indirect in policies 1–6.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426077, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.g005", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_DALYs_averted_by_vaccination_policies_in_total_and_as_a_result_of_direct_vaccine_effects_/1426077", "title"=>"DALYs averted by vaccination policies in total and as a result of direct vaccine effects.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082285"], "description"=>"<p>(A) Cost-effectiveness plane showing samples from the posterior distributions of DALYs averted and incremental costs for the seven vaccination policies compared with no vaccination under base case assumptions. Points to the right of the solid red line (which corresponds to a threshold of I$10,000 per DALY averted) would be considered highly cost-effective compared with no vaccination in Thailand according to the WHO threshold [<a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001829#pmed.1001829.ref044\" target=\"_blank\">44</a>]. (B) CEACs under base case assumptions. (C–K) CEAFs under base case assumptions and for eight sensitivity analyses.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426072, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.g003", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cost_effectiveness_plane_cost_effectiveness_acceptability_curves_and_cost_effectiveness_acceptability_frontiers_/1426072", "title"=>"Cost-effectiveness plane, cost-effectiveness acceptability curves, and cost-effectiveness acceptability frontiers.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082283"], "description"=>"<p>Monthly numbers of laboratory-confirmed influenza cases (circles) and model predictions: median (broken line) and 95%, 90%, and 80% (gray shading) prediction intervals for the expected number of cases. Also shown is the estimated value of <i>R</i><sub>0</sub> and associated 95% CrI.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426070, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.g002", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_fits_to_laboratory_confirmed_influenza_surveillance_data_/1426070", "title"=>"Model fits to laboratory-confirmed influenza surveillance data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082297"], "description"=>"<p>Policies modeled.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426081, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.t001", "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Policies_modeled_/1426081", "title"=>"Policies modeled.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-05-26 15:23:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2082292"], "description"=>"<p>Color indicates effective reproduction number after vaccination. Columns A, B, and C use a contact matrix derived from all contacts recorded. Columns D, E, and F use a contact matrix derived from physical contacts only. In both cases, baseline immunity assumptions at the start of each influenza season are taken as the mean estimated for each of the six age groups when fitting to data under base case assumptions (21%, 25%, 33%, 33%, 38%, and 37%). <i>R</i> values in column headings indicate the assumed effective reproduction number prior to vaccination.</p>", "links"=>[], "tags"=>["sensitivity analyses", "tiv", "Seasonal Influenza Vaccination", "policy", "framework", "vaccine", "laiv", "age groups", "probability distributions", "influenza vaccination policies", "vaccination policies parameterized", "contact patterns", "data"], "article_id"=>1426079, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Aronrag Meeyai", "Naiyana Praditsitthikorn", "Surachai Kotirum", "Wantanee Kulpeng", "Weerasak Putthasri", "Ben S. Cooper", "Yot Teerawattananon"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001829.g006", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effective_reproduction_number_as_a_function_of_vaccination_policy_coverage_and_vaccine_effectiveness_/1426079", "title"=>"Effective reproduction number as a function of vaccination policy, coverage, and vaccine effectiveness.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-26 15:23:52"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"31", "full-text"=>"40", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"1", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"22", "full-text"=>"26", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"21", "full-text"=>"20", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"33", "full-text"=>"34", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"22", "full-text"=>"14", "pdf"=>"9", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"12"}
  • {"unique-ip"=>"23", "full-text"=>"22", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"25", "full-text"=>"26", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"20", "full-text"=>"19", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"25", "full-text"=>"21", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"19", "full-text"=>"17", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}
  • {"unique-ip"=>"20", "full-text"=>"16", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}
  • {"unique-ip"=>"21", "full-text"=>"19", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"10"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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