Monica Alexander

Assistant Professor

University of Toronto

Biography

I am an Assistant Professor in Statistical Sciences and Sociology at the University of Toronto. I received my PhD in Demography at the University of California, Berkeley. My research interests include statistical demography, mortality and health inequalities, and computational social science.

I have worked on research projects with the World Health Organization, UNICEF, the Bill and Melinda Gates Foundation, and the Human Mortality Database. I was a 2016 Fellow at Data Science for Social Good, and have worked at the ANU’s Centre for Aboriginal Economic Policy Research.

Outside of work and study I am interested in photography, cycling, and music.

A full CV can be found here.

Interests

Statistical demography
Mortality modeling
Health inequalities
Small-area population issues
Computational social science

Education

PhD (Demography), 2018

University of California, Berkeley
M.Arts (Statistics), 2015

University of California, Berkeley
M.Social Research (Demography), 2013

Australian National University
B.Science (First class honours) (Mathematics and Chemistry), 2008

University of Tasmania

Selected Publications

Trends in Black and White Opioid Mortality in the United States, 1979–2015

Recent research on the US opioid epidemic has focused on the white or total population and has largely been limited to data after 1999. However, understanding racial differences in long-term trends by opioid type may contribute to improving interventions. We analyzed age-standardized opioid mortality rates, by race and opioid type, for the US resident population from 1979 to 2015.

Monica Alexander, Mathew Kiang, Magali Barbieri

Epidemiology

Details PDF Code

Global Estimation of Neonatal Mortality using a Bayesian Hierarchical Splines Regression Model

We present a model for estimating neonatal mortality rates for all countries. Neonatal mortality is an important indicator to track progess towards the Sustainable Development Goals. The model is used by the United Nations Inter-agency Group for Child Mortality Estimation.

Monica Alexander, Leontine Alkema

Demographic Research

Details PDF

A Flexible Bayesian Model for Estimating Subnational Mortality

We present a Bayesian hierarchical model to estimate age-specific mortality at the subnational level. The model framework overcomes issues with estimating mortality in small populations, is flexible enough to be implemented in a wide variety of situations, and produces estimates of different measures of inequality across regions.

Monica Alexander, Emilio Zagheni, Magali Barbieri

Demography

Details PDF

Recent Publications

More Publications

National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis
Details PDF
Assessment of Changes in the Geographical Distribution of Opioid-Related Mortality Across the United States by Opioid Type, 1999-2016
Details PDF Code
Trends in pregnancy-associated mortality involving opioids in the United States, 2007–2016
Details PDF Code

Teaching

University of Toronto

STA4525H Demographic Methods, Winter 2019. Course materials are here: https://github.com/MJAlexander/demographic-methods

University of California, Berkeley

Instructor, Formal Demography Workshop, June 2017
Instructor, Formal Demography Workshop, August 2015
Graduate Student Instructor, Demographic Methods, Fall Semester, 2014

University of Tasmania

Tutor, Calculus and Applications I, Semester 1, 2009
Tutor, Data Handling and Statistics I, Semester 2, 2008
Demonstrator, Chemistry I, Semester 1, 2008

Other

Instructor, Introduction to Causal Inference, ITAM, March 2017
Instructor, IUSSP Workshop on Social Media Data and Demography, August 2016

Recent Posts

Analyzing name changes after marriage using a non-representative survey

07 August 2019

Introduction Recently on Twitter, sociologist Phil Cohen put out a survey asking people about their decisions to change their name (or not) after marriage. The response was impressive - there are currently over 5,000 responses. Thanks to Phil, the data from the survey are publicly available and downloadable here for anyone to do their own analysis. However, there’s an issue with using the raw data without lots of caveats: the respondents are not very representative of the broader population, and in particular tend to have a higher education level and are younger than average.

The concentration and uniqueness of baby names in Australia and the US

21 January 2019

Some great people have compiled historical data on baby names into R packages for both the US (thanks to Hadley Wickham) and Australia (thanks to the Monash group). This makes answering all manner of baby-name-related questions easy. I was interested in looking at the distribution of baby names in these populations over time — that is, how concentrated are name choices in the most popular baby names? Is there a big difference between the number of babies that are called the most popular names compared to other names, or is the distribution more evenly spread?

Professional Experience

University of Massachusetts, Amherst

Graduate Student Researcher, January 2017 – June 2018

World Health Organization

Consultant, September 2016 – June 2017

Fellow, May 2016 – September 2016

Human Mortality Database

Graduate Student Researcher, January 2015 – May 2016

UNICEF Technical Advisory Group

Consultant, March 2014 – December 2015

The Centre for Aboriginal Economic Policy Research

Research Officer, April 2012 – December 2014

Reserve Bank of Australia

Analyst/Senior Analyst, February 2010 – June 2013

Contact

monica.alexander@utoronto.ca
725 Spadina Avenue, Toronto, ON