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Activity Number: 35 - Epidemiological Models for Genetic Data, Biomarkers, and Rare Outcomes
Type: Contributed
Date/Time: Sunday, August 7, 2022 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #320858
Title: A Year of Work in COVID-19 Statistical Modeling
Author(s): Jorge Luis Romeu*
Companies: Syracuse University
Keywords: public health statistics; survival analysis; design of experiments; multivariate analysis; discrimination analysis; Markov chains
Abstract:

We overview a year of statistical work developing tutorials, models and analysis applications to Covid-19 issues to illustrate our methods and persuade researchers from other professions to include statistics and statisticians in their work. Section 2 describes the web page created, and its background material. Section 3 overviews Quality Control and Design of Experiments papers that, using Covid-19 data, assess whether state counties or regions should be opened or locked-down. Section 4 overviews Reliability and Logistics papers that, using patient data, help take Triage decisions. Section 5 summarizes Principal Components and Discriminant Analysis papers that, using patient data, assess the results of Covid-19 vaccine and treatment clinical trials. Section 6 overviews Stochastic Process papers that implement Markov Chain models to evaluate decisions on opening colleges and assess Covid-19 hospital and ICU needs to avoid being overwhelmed. Section 7 presents Socio-economic analyses of problems derived from the Covid-19 pandemic. Section 8 presents Quality Engineering approaches to the Design and Improvement of Covid-19 vaccine distribution systems. Section 9 summarizes our work.


Authors who are presenting talks have a * after their name.

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