Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise.
<p>The black solid lines represent the defined functional relationship between acute and convalescent titers after the boost and subsequent waning of titers between the samples.</p> <p>(TIF)</p>
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| _version_ | 1849927625821126656 |
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| 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 | 2025-11-25T19:00:28Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pcbi.1013708.s013 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Comparison_between_simulation_based_estimates_for_boosts_in_GM_HAI_IgG_and_IgM_that_is_experienced_after_an_infection_event_as_a_function_of_acute_GM_HAI_IgG_and_IgM_titers_individuals_under_the_varying_levels_of_observational_noise_/30715185 |
| 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 | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>The black solid lines represent the defined functional relationship between acute and convalescent titers after the boost and subsequent waning of titers between the samples.</p> <p>(TIF)</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_768ebdfce437abc37ab4562f86127f88 |
| identifier_str_mv | 10.1371/journal.pcbi.1013708.s013 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30715185 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise.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>The black solid lines represent the defined functional relationship between acute and convalescent titers after the boost and subsequent waning of titers between the samples.</p> <p>(TIF)</p>2025-11-25T19:00:28ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pcbi.1013708.s013https://figshare.com/articles/figure/Comparison_between_simulation_based_estimates_for_boosts_in_GM_HAI_IgG_and_IgM_that_is_experienced_after_an_infection_event_as_a_function_of_acute_GM_HAI_IgG_and_IgM_titers_individuals_under_the_varying_levels_of_observational_noise_/30715185CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/307151852025-11-25T19:00:28Z |
| spellingShingle | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. 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 | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| title_full | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| title_fullStr | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| title_full_unstemmed | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| title_short | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| title_sort | Comparison between simulation based estimates for boosts in GM HAI, IgG, and IgM that is experienced after an infection event as a function of acute GM HAI, IgG, and IgM titers individuals under the varying levels of observational noise. |
| 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 |