Associate Professors

HIV/AIDS and other infectious diseases epidemiology and control. Evaluation of interventions

The methodology of infectious disease surveillance, including the use of pre-diagnostic indicators as well as that of reportable diseases, and especially the detection of spatial and temporal clustering of events of interest. The determinants of the transmission of HIV and HCV infections. Measures of effect in epidemiology, particularly in the context of transmissible disease outbreaks.

My main research interests are in reproductive/perinatal epidemiology and women's health. My underlying focus is on addressing the impact of complex exposures on the health of women and children. When evaluating the side effects of infertility treatment, the factors that caused infertility in the first place should be taken into  account. Similarly, the higher risk of death and disease in preterm babies is most likely due both to being born too early and to the pathologies that cause preterm birth in the first place. Understanding these complex conditions better will not only lead to better clinical decisions and patient management, but also open avenues for prevention of the main factors.

Dr. Benedetti is a biostatistician with interests in  statistical challenges related to analyzing tuberculosis data; methods for analyzing individual patient data meta-analyses; and flexible regression approaches. Dr. Benedetti is an active collaborator in respiratory health (COPD, TB, asthma, sleep apnea, etc.).

I conduct research on the informatics of public health surveillance. In particular, I am interested in the development and evaluation of methods for surveillance systems that use clinical and administrative data. Previous and ongoing work includes the development of statistical methods for outbreak detection and the use of simulation modeling to evaluate surveillance systems.

Dr. Cox's public health practice and research is focused on surveillance and monitoring of sexally transmitted and bloodborne infections and related determinants among vulnerable urban populations. He also conducts epidemiological and evaluative research regarding health outcomes and care for people living with substance use disorders, HIV and hepatitis C.

Bayesian methods for biostatistical problems. In particular, methods for analysis of multiple diagnostic tests in the absence of a gold-standard and Bayesian sample size calculation in the presence of misclassification. Applications to emergency care and mental health in the elderly.

Celia Greenwood is interested in statistical methods for the analysis of genetic and genomic data.  Recently, her group has been focusing on ways of characterizing tumour abnormalities, analysis methods for rare genetic variants such as those identified by sequencing studies, and analysis of DNA methylation data.

She is an integral part of the Genetic Epidemiology group at the Lady Davis Institute and the Segal Cancer Centre where she is supported by the Weekend to End Women’s Cancers.  She is also a Director of the recently formed Ludmer Centre for Neuroinformatics and Mental Health, which is developing and implementing methods for integrating behavioural phenotypes, epigenetic, genetic and brain imaging data.

Social determinants of population health and health inequalities; measuring and monitoring health inequalities; global health and international comparisons; demography; quantitative methods.

Health effects and therapeutic applications of electro-magnetic fields. General toxicology.

Adaptive treatment strategies; doubly robust estimation; longitudinal data; causal inference

Social inequalities in health; lifecourse research; stratification and mobility; population health; quantitative methods (counterfactual account of causality); social demography (reproductive health). Current research examines the contribution of policies to the development of social inequalities in health over the life course, and particularly the impact of private health insurance on general and mental health in select OECD countries.

Dr. Caroline Quach’s research aims to prevent infections from the hospital to the community and focuses on surveillance and prevention of healthcare-associated infections as well as the epidemiology and prevention of vaccine-preventable diseases.

Evaluation of health technologies, Pharmacoepidemiology.

Bayesian inference; Disease mapping; Dynamic linear models;  Spatio-temporal processes

Health economics, health services research, and causal inference. Her research focuses on the connections between socio-economic status; health insurance and access to health care; quality and costs of health care; and health outcomes, particularly for vulnerable subgroups. Current projects examine the impacts of public and private health insurance on labor market and health outcomes and the role of racial matching between physicians and patients in racial/ethnic disparities in the quality of care.

Decision/health policy analysis and health services research. This implies the application of epidemiologic principles and explicit decision analysis to improve the quality of the information feeding into decisions. Evaluating the impact of the health services reforming the region, on the health and well-being of the population. For example, this implies surveys looking at the impact on patients and their natural care givers and analysis of administrative databases like med-Echo, vital statistics and files at the RAMQ (Regie Regionale d'assurance-maladie du Quebec).