Special Interest Group - Health Equity

This SIG focuses on developing evidence to monitor, understand and reduce unfair differences in health and healthcare.

Aim To promote the use of research evidence for equity informed policy decisions


  • To share knowledge of data and methods for assessing health disparities and conducting equity informative economic evaluations
  • To connect researchers and facilitate collaboration in the economics of health equity
  • To support early career researchers with an interest in this field to develop networks
  • To share equity focused resources such as training courses, workshops and funding opportunities
  • Sharing information electronically about papers, methods workshops, conferences.
  • Hold a meeting at AHES 2022 to establish desired outcomes and activities of the group
  • Regular Zoom meet ups, frequency TBA (including, work-in-progress presentations, methods sharing and small group networking)
  • Engage with relevant health policy community consultation processes as a group (optional)
  • Establish a database of health economists in researching in this field (optional)
  • Organised session for IHEA (optional)

If you would like to join the SIG, please contact the conveners:

Anita Lal at anita.lal@deakin.edu.au

Dennis Petrie at dennis.petrie@monash.edu.au

Anagha Killedar at anagha.killedar@sydney.edu.au


Anita Lal
Anita Lal
Deakin Health Economics,

Deakin University

Dr Anita Lal is a Victorian Cancer Agency Early Career Research fellow at Deakin Health Economics, Deakin University. Her PhD, awarded in 2018, examined ways of incorporating equity into cost-effectiveness analysis for obesity prevention policies. Her current research focuses on health-related policies and programs to reduce inequities in healthcare utilisation and the distribution of cancers. Her fellowship, funded by the Victorian Government, is focused on the impacts and cost-effectiveness of targeted programs to increase bowel, breast and cervical cancer screening in under screened culturally and linguistically diverse groups in Victoria. She is a member of the Victorian Comprehensive Cancer Centre Alliance Equity Advisory Group.

Dennis Petrie
Dennis Petrie
Centre for Health Economics,

Monash University

Dennis Petrie is a Professor in the Centre for Health Economics, Monash University. He has published extensively on the economics of illicit drugs, smoking, alcohol, disability, cancer, the longitudinal measurement and evaluation of health inequalities and has led a large number of economic evaluations of healthcare interventions including alongside RCTs. He has consistently published in the leading health economics journals, with multiple papers in the Journal of Health Economics (4), Health Economics (6), Social Science & Medicine (5) and also high impact medical journals including JAMA, BMJ, PLOS Medicine, Addiction (2), Diabetologia, Diabetes Care (2), Clinical Infectious Diseases and Epidemiology (2). He specialises in analysing large and complex data sets to improve health policy decisions with a focus on reducing health inequities

Anagha Killedar
Anagha Killedar
Menzies Centre for Health Policy and Economics
University of Sydney

Dr. Anagha Killedar is a research fellow and health economist at the Menzies Centre for Health Policy and Economics, University of Sydney. She completed her PhD in 2021 with supervisors A/Prof Alison Hayes and A/Prof Thomas Lung in which she developed a model for conducting and applying equity-informative economic evaluation of childhood obesity prevention interventions. She currently works across a myriad of projects, including as chief investigator on an NHMRC-funded project to develop childhood obesity models for priority populations and as part of team commissioned by NSW Health to evaluate a progressively implemented mobile dental program for children.

Her research interests are in progressing and applying methods to incorporate equity concerns into economic evaluation in Australian health policy settings, child health and childhood obesity, and health economic modelling methods.