Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.
<p>Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.</p>...
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2025
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| _version_ | 1849927625856778240 |
|---|---|
| author | Marco Hamins-Puértolas (15238661) |
| author2 | Darunee Buddhari (625855) Henrik Salje (589157) Angkana T. Huang (12262139) Taweewun Hunsawong (798675) Derek A.T. Cummings (14971341) Stefan Fernandez (146590) Aaron Farmer (4288318) Surachai Kaewhiran (22683535) Direk Khampaen (22683538) Anon Srikiatkhachorn (110184) Sopon Iamsirithaworn (260152) Adam Waickman (118668) Stephen J. Thomas (7105673) Timothy Endy (150971) Alan L. Rothman (6835178) Kathryn B. Anderson (6835166) Isabel Rodriguez-Barraquer (233670) |
| author2_role | author author author author author author author author author author author author author author author author author |
| author_facet | Marco Hamins-Puértolas (15238661) Darunee Buddhari (625855) Henrik Salje (589157) Angkana T. Huang (12262139) Taweewun Hunsawong (798675) Derek A.T. Cummings (14971341) Stefan Fernandez (146590) Aaron Farmer (4288318) Surachai Kaewhiran (22683535) Direk Khampaen (22683538) Anon Srikiatkhachorn (110184) Sopon Iamsirithaworn (260152) Adam Waickman (118668) Stephen J. Thomas (7105673) Timothy Endy (150971) Alan L. Rothman (6835178) Kathryn B. Anderson (6835166) Isabel Rodriguez-Barraquer (233670) |
| author_role | author |
| dc.creator.none.fl_str_mv | Marco Hamins-Puértolas (15238661) Darunee Buddhari (625855) Henrik Salje (589157) Angkana T. Huang (12262139) Taweewun Hunsawong (798675) Derek A.T. Cummings (14971341) Stefan Fernandez (146590) Aaron Farmer (4288318) Surachai Kaewhiran (22683535) Direk Khampaen (22683538) Anon Srikiatkhachorn (110184) Sopon Iamsirithaworn (260152) Adam Waickman (118668) Stephen J. Thomas (7105673) Timothy Endy (150971) Alan L. Rothman (6835178) Kathryn B. Anderson (6835166) Isabel Rodriguez-Barraquer (233670) |
| dc.date.none.fl_str_mv | 2025-11-25T19:00:14Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pcbi.1013708.s007 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Distribution_of_paired_serological_data_that_fall_into_probability_buckets_when_using_Model_9_incorporating_paired_IgG_IgM_GM_HAI_and_acute_GM_HAI_serological_data_and_the_number_of_serological_assays_RT-PCR_HAI_and_EIA_that_interpret_the_i/30715155 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Medicine Biotechnology Ecology Immunology Cancer Science Policy Infectious Diseases Virology Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified since many cases linked immunosorbent assay independently utilize information hemagglutination inhibition assay globe &# 8217 currently implemented cut convalescent serum collected 87 &# 8211 82 &# 8211 real world data multiple serological assays infer infection events generate finalized interpretations bayesian mixture model prior standard interpretations pcr confirmed infections jointly model data gold standard ). f1 scores ). hai data consistently direct detection methods gold standard f1 scores infection detection eia ). including data individual assays new model igm data whether individuals transmission potential results provide recently experienced provide insight probabilistic framework population living point approaches pathogen systems kamphaeng phet interpreting results incorporating igg important role higher accuracy first test diagnostic process creating uncertainty combined metric already half 677 pairs |
| dc.title.none.fl_str_mv | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_1e5ec8dd1c3df4526794ee1d65aca24b |
| identifier_str_mv | 10.1371/journal.pcbi.1013708.s007 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30715155 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.Marco Hamins-Puértolas (15238661)Darunee Buddhari (625855)Henrik Salje (589157)Angkana T. Huang (12262139)Taweewun Hunsawong (798675)Derek A.T. Cummings (14971341)Stefan Fernandez (146590)Aaron Farmer (4288318)Surachai Kaewhiran (22683535)Direk Khampaen (22683538)Anon Srikiatkhachorn (110184)Sopon Iamsirithaworn (260152)Adam Waickman (118668)Stephen J. Thomas (7105673)Timothy Endy (150971)Alan L. Rothman (6835178)Kathryn B. Anderson (6835166)Isabel Rodriguez-Barraquer (233670)MedicineBiotechnologyEcologyImmunologyCancerScience PolicyInfectious DiseasesVirologyComputational BiologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedChemical Sciences not elsewhere classifiedsince many caseslinked immunosorbent assayindependently utilize informationhemagglutination inhibition assayglobe &# 8217currently implemented cutconvalescent serum collected87 &# 821182 &# 8211real world datamultiple serological assaysinfer infection eventsgenerate finalized interpretationsbayesian mixture modelprior standard interpretationspcr confirmed infectionsjointly model datagold standard ).f1 scores ).hai data consistentlydirect detection methodsgold standardf1 scoresinfection detectioneia ).including dataindividual assaysnew modeligm datawhether individualstransmission potentialresults providerecently experiencedprovide insightprobabilistic frameworkpopulation livingpoint approachespathogen systemskamphaeng phetinterpreting resultsincorporating iggimportant rolehigher accuracyfirst testdiagnostic processcreating uncertaintycombined metricalready half677 pairs<p>Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection.</p>2025-11-25T19:00:14ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pcbi.1013708.s007https://figshare.com/articles/dataset/Distribution_of_paired_serological_data_that_fall_into_probability_buckets_when_using_Model_9_incorporating_paired_IgG_IgM_GM_HAI_and_acute_GM_HAI_serological_data_and_the_number_of_serological_assays_RT-PCR_HAI_and_EIA_that_interpret_the_i/30715155CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307151552025-11-25T19:00:14Z |
| spellingShingle | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. Marco Hamins-Puértolas (15238661) Medicine Biotechnology Ecology Immunology Cancer Science Policy Infectious Diseases Virology Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified since many cases linked immunosorbent assay independently utilize information hemagglutination inhibition assay globe &# 8217 currently implemented cut convalescent serum collected 87 &# 8211 82 &# 8211 real world data multiple serological assays infer infection events generate finalized interpretations bayesian mixture model prior standard interpretations pcr confirmed infections jointly model data gold standard ). f1 scores ). hai data consistently direct detection methods gold standard f1 scores infection detection eia ). including data individual assays new model igm data whether individuals transmission potential results provide recently experienced provide insight probabilistic framework population living point approaches pathogen systems kamphaeng phet interpreting results incorporating igg important role higher accuracy first test diagnostic process creating uncertainty combined metric already half 677 pairs |
| status_str | publishedVersion |
| title | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| title_full | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| title_fullStr | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| title_full_unstemmed | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| title_short | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| title_sort | Distribution of paired serological data that fall into probability buckets when using Model 9 (incorporating paired IgG, IgM, GM HAI, and acute GM HAI serological data) and the number of serological assays (RT-PCR, HAI, and EIA) that interpret the individual as having an infection. |
| topic | Medicine Biotechnology Ecology Immunology Cancer Science Policy Infectious Diseases Virology Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified since many cases linked immunosorbent assay independently utilize information hemagglutination inhibition assay globe &# 8217 currently implemented cut convalescent serum collected 87 &# 8211 82 &# 8211 real world data multiple serological assays infer infection events generate finalized interpretations bayesian mixture model prior standard interpretations pcr confirmed infections jointly model data gold standard ). f1 scores ). hai data consistently direct detection methods gold standard f1 scores infection detection eia ). including data individual assays new model igm data whether individuals transmission potential results provide recently experienced provide insight probabilistic framework population living point approaches pathogen systems kamphaeng phet interpreting results incorporating igg important role higher accuracy first test diagnostic process creating uncertainty combined metric already half 677 pairs |