BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4//
BEGIN:VEVENT
UID:20260728T011305EDT-8208vothb4@132.216.98.100
DTSTAMP:20260728T051305Z
DESCRIPTION:SPECIAL SEMINAR\n\nW. Alton Russell\, PhD\n\nAssistant Professo
 r\n	Dept of Epidemiology\, Biostatistics & Occupational Health\n	SPGH | McGi
 ll University\n\nWHERE: In-Person | 2001 McGill College\, Rm 1203 | Zoom\n
 \nAbstract \n\nDecision-analytic models can inform measures to address imp
 ortant problems in population health and health systems. Traditionally\, d
 ecision analysts have focused on the aggregate or average impact of measur
 es on a population. Increasingly\, policy makers seek to understand the di
 stribution of impacts across diverse populations. This is for two main rea
 sons: to understand the equity implications of policies and to enable targ
 eted public health measures.\n\nI will describe how integrating data-drive
 n methods like machine learning into decision analysis can improve estimat
 ion of the impact of public health measures on diverse populations\, infor
 ming targeted interventions. I will describe two applications: dispensing 
 the overdose reversal drug naloxone to patients receiving prescription opi
 oids and tailoring the frequency of blood donations to each donors’ estima
 ted trajectory for recovering iron stores.\n\nBio\n\nW. Alton Russell\, Ph
 D\, is an Assistant Professor in the McGill School of Population and Globa
 l Health and director of the Data-Driven Decision Modeling Lab\, or D3Mod 
 lab. The D3Mod lab aims to enable the efficient\, effective\, and equitabl
 e use of finite healthcare resources by developing\, assessing\, and apply
 ing traditional decision modeling methods (mathematical modeling\, simulat
 ion\, optimization) together with data-driven methods (machine learning\, 
 Bayesian statistics). Dr. Russell received undergraduate training in Indus
 trial Engineering and Public Health at North Carolina State University\, M
 asters and Doctoral training in Management Science and Engineering at Stan
 ford University\, and postdoctoral training at the Massachusetts General H
 ospital Institute for Technology Assessment and Harvard Medical School.\n
 \nWebsite: https://mchi.mcgill.ca/decision-modeling-lab/\n
DTSTART:20230413T200000Z
DTEND:20230413T210000Z
SUMMARY:Informing targeted public health measures with data-driven decision
  modeling
URL:https://www.mcgill.ca/epi-biostat-occh/channels/event/informing-targete
 d-public-health-measures-data-driven-decision-modeling-347635
END:VEVENT
END:VCALENDAR
