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University of Texas Rio Grande Valley
School of Mathematical and Statistical Sciences Faculty Publications and Presentations
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Full-Text Articles in Medicine and Health Sciences
An Independent Analysis Of A Retrospective Cohort Of 30,423 Covid-19 Patients Treated At Ihu-Mediterranean In Marseille, France: Part 2, A Real-Life Assessment Of Covid-19 Vaccination Efficacy, Valere Lounnas, Eleftherios Gkioulekas, Marc Rendell, Alexis Lacout, Xavier Azalbert, Christian Perronne
An Independent Analysis Of A Retrospective Cohort Of 30,423 Covid-19 Patients Treated At Ihu-Mediterranean In Marseille, France: Part 2, A Real-Life Assessment Of Covid-19 Vaccination Efficacy, Valere Lounnas, Eleftherios Gkioulekas, Marc Rendell, Alexis Lacout, Xavier Azalbert, Christian Perronne
School of Mathematical and Statistical Sciences Faculty Publications and Presentations
A cohort of 30,423 Covid-19 patients treated between March 2020 and December 2021 at the IHU-Méditerranée Infection in Marseille (France) was retrospectively analyzed in terms of treatment attempted and disease worsening factors to quantify vaccination efficacy with respect to the composite endpoint of transfer to intensive care unit or death, within a couple of months (56 days) from admission. Within limitations of the data and of the models, after adequate adjustment for sampling biases, multivariate logistic regression analyses were performed to determine unadjusted and adjusted odds ratios (ORs) for the subset of patients admitted after the Covid-19 vaccination program was …
Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh
Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh
School of Mathematical and Statistical Sciences Faculty Publications and Presentations
In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …