BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//California Center for Population Research - ECPv6.15.14//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://ccpr.ucla.edu
X-WR-CALDESC:Events for California Center for Population Research
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20190310T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20191103T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20200308T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20201101T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20210314T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20211107T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20201209T120000
DTEND;TZID=America/Los_Angeles:20201209T140000
DTSTAMP:20260721T142416
CREATED:20200928T212259Z
LAST-MODIFIED:20210123T024745Z
UID:10000715-1607515200-1607522400@ccpr.ucla.edu
SUMMARY:Population-Based Modeling and Measurement of COVID-19
DESCRIPTION:“Population-Based Modeling and Measurement of COVID-19”\nThe recording of the event is available here. \nPanelists: \nChristina Ramirez\, Prof. of Biostatistics UCLA\nMark Handcock\, Prof. of Statistics UCLA\nPatrick Heuveline\, Prof. of Sociology UCLA\nHiram Beltrán-Sánchez\, Prof. of Community Health Sciences \nFor more information on panelists’ research\, see: \n\nPatrick 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 \n  \nMark Handcock 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 \n  \nWatson 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 \n  \nDi 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 
URL:https://ccpr.ucla.edu/event/population-based-modeling-and-measurement-of-covid-19/
CATEGORIES:CCPR Seminar,Divisional Publish
END:VEVENT
END:VCALENDAR