Discussion of “Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data”

DOI10.1080/01621459.2021.1982722zbMath1506.62430OpenAlexW4200592558MaRDI QIDQ5881944

No author found.

Publication date: 14 March 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2021.1982722

zbMATH Keywords

prevalenceEM algorithmmissing dataepidemic modeleffective reproductive numberCOVID-19 transmissionserological studiesunder-ascertainment

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Uses Software

• EpiEstim

Cites Work

• A General Chain Binomial Model for Infectious Diseases
• A Hybrid EM and Monte Carlo EM Algorithm and Its Application to Analysis of Transmission of Infectious Diseases
• A Spatio-Temporal Modeling Framework for Surveillance Data of Multiple Infectious Pathogens With Small Laboratory Validation Sets
• Regression Models for Understanding COVID-19 Epidemic Dynamics With Incomplete Data

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