<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Domma F</submitter><funding>Gruppo Baffa</funding><pagination>109</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12846483</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>18(1)</volume><pubmed_abstract>Vaccination has been a cornerstone of the public health response to the COVID-19 pandemic, particularly in protecting older and frail populations. A detailed characterization of antibody titer dynamics and their determinants represents a crucial step toward optimizing vaccination strategies. However, antibody titers are bounded within assay-specific limited intervals and often display skewness and intra-subject correlation, which limit the suitability of conventional modeling approaches. We analyzed longitudinal antibody titer data from 608 residents and staff members of five nursing homes in Calabria (southern Italy) using beta-generalized linear mixed models (β-GLMMs). This framework enabled simultaneous modeling of the mean humoral response (μ), precision parameter (ϕ), and probability </pubmed_abstract><journal>Viruses</journal><pubmed_title>Statistical Modeling of Humoral Immune Response Dynamics to mRNA COVID-19 Vaccines in Nursing Home Residents and Healthcare Workers from Southern Italy.</pubmed_title><pmcid>PMC12846483</pmcid><funding_grant_id>The work has been made possible by the collaboration with Gruppo Baffa (Sadel Spa, Sadel San Teodoro srl, Sadel CSsrl, Casa di Cura Madonna dello Scoglio, AGI srl, Casa di Cura Villa del Rosario srl, Savelli Hospital srl,) and Casa di Cura Villa Ermelinda</funding_grant_id><pubmed_authors>Amerise I</pubmed_authors><pubmed_authors>Aceto MA</pubmed_authors><pubmed_authors>Morelli F</pubmed_authors><pubmed_authors>Domma F</pubmed_authors><pubmed_authors>Paparazzo E</pubmed_authors><pubmed_authors>Montesanto A</pubmed_authors><pubmed_authors>Cassano TS</pubmed_authors><pubmed_authors>Cosimo SC</pubmed_authors><pubmed_authors>Bellizzi D</pubmed_authors><pubmed_authors>Soraci L</pubmed_authors><pubmed_authors>Corsonello A</pubmed_authors><pubmed_authors>Passarino G</pubmed_authors></additional><is_claimable>false</is_claimable><name>Statistical Modeling of Humoral Immune Response Dynamics to mRNA COVID-19 Vaccines in Nursing Home Residents and Healthcare Workers from Southern Italy.</name><description>Vaccination has been a cornerstone of the public health response to the COVID-19 pandemic, particularly in protecting older and frail populations. A detailed characterization of antibody titer dynamics and their determinants represents a crucial step toward optimizing vaccination strategies. However, antibody titers are bounded within assay-specific limited intervals and often display skewness and intra-subject correlation, which limit the suitability of conventional modeling approaches. We analyzed longitudinal antibody titer data from 608 residents and staff members of five nursing homes in Calabria (southern Italy) using beta-generalized linear mixed models (β-GLMMs). This framework enabled simultaneous modeling of the mean humoral response (μ), precision parameter (ϕ), and probability </description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-13T03:21:54.657Z</modification><creation>2026-06-13T03:12:18.58Z</creation></dates><accession>S-EPMC12846483</accession><cross_references><pubmed>41600871</pubmed><doi>10.3390/v18010109</doi></cross_references></HashMap>