“Population-Based Modeling and Measurement of COVID-19”
Panelists:
Christina Ramirez, Prof. of Biostatistics UCLA
Mark Handcock, Prof. of Statistics UCLA
Patrick Heuveline, Prof. of Sociology UCLA
Hiram Beltrán-Sánchez, Prof. of Community Health Sciences
For more information on panelists’ research, see:
Patrick Heuveline. Covid-19 will reduce US life expectancy at birth by more than one year in 2020.
https://www.medrxiv.org/content/10.1101/2020.12.03.20243717v1
Mark Hancock and colleagues. Asymptomatic and Presymptomatic Transmission of 2019 Nover Coronavirus (COVID-19) Infection: An Estimation from a Cluster of Confirmed Cases in Ho Chi Minh City, Vietnam.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3630119
Watson and colleagues. Fusing a Bayesian Case Velocity Model with Random Forest for Predicting COVID-19 in the U.S.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3594606
Di Xiong and colleagues. Pseudo-likelihood based logistic regression for estimating COVID-19 infection and case fatality rates by gender, race, and age in California.
https://www.sciencedirect.com/science/article/pii/S1755436520300396?via%3Dihub
Population-Based Modeling and Measurement of COVID-19
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