Researcher

Dr Mark Joseph Hanly

Keywords

Biography

Mark is a lecturer and applied social statistician based at the Centre for Big Data Research in Health, UNSW Sydney. His research focuses on the analysis of large, linked administrative datasets to answer research questions related to the health and social welbeing of populations. Topics of interest include early childhood health and development, health service utilisation, Indigenous health and outcomes for vulnerable populations. As an...view more

Mark is a lecturer and applied social statistician based at the Centre for Big Data Research in Health, UNSW Sydney. His research focuses on the analysis of large, linked administrative datasets to answer research questions related to the health and social welbeing of populations. Topics of interest include early childhood health and development, health service utilisation, Indigenous health and outcomes for vulnerable populations. As an applied social statistician, he is interested in statistical methods for answering causal questions using observational data; summarising and modelling complex longitudinal data; and innovative approaches for visualising data and communicating research. Mark convenes and teaches the course HDAT9700 Statistical Modelling II as part of the MSc in Health Data Science.

Mark joined the Centre for Big Data Research in Health from the University of Bristol, where he completed his PhD in Advanced Quantitative Methods for the Health and Social Sciences. His doctoral research focused on novel approaches to correct for nonresponse bias in large household surveys. He also holds an MSc in Applied Social Research from Trinity College Dublin and a BSc (Hons) in Mathematics and Statistics from the National University of Ireland, Maynooth.  


My Grants

  • $50,000 Triple I Clinical Academic Group Seed Grant (2020) Open source modelling tools to support policy decision-making throughout the COVID-19 post-pandemic phase (CI A)
  • $1,248,388 National Health and Medical Research Council  Transforming the health system response to child maltreatment: the need for cross-jurisdictional e-cohorts (CI D)
  • $26,000 Australian Research Data Council Disseminating Research in the 21st Century (CI A)
  • $30K NSW Department of Family and Community Services (FACS) Commissioned Project Analysis report for the ‘Family is Culture’ review of Aboriginal children in Out-of-Home care in NSW. (CI B)
  • $40,000 UNSW Neuroscience, Mental Health and Addictions and SPHERE Clinical Academic Group Seed Funding Scheme Neurodevelopmental, physical and mental health consequences of early life adversity: cross-sectoral population data linkage to inform health and social policy. (AI)
  • $23,685 NSW FACS Commissioned Project Their Futures Matter – Trial Cohort (Children in residential care) (CI B)
  • $10,849 NSW FACS Commissioned Project Their Futures Matter – Early life pathways and outcomes for children in contact with child protection (CI B)

My Qualifications

  • PhD Advanced Quantitative Mehtods, University of Bristol 2015
  • MSc Applied Social Research, Trinity College Dublin 2011
  • BSc Mathematics and Statistics, National University of Ireland Maynooth 2006

My Awards

  • CovidR Contest Winner, European R-Users Meeting (2020)
  • Datathon winner, National University of Singapore - National University Health System - Massachusetts Institute of Technology (MIT) Healthcare Artificial Intelligence (AI) Datathon (2018)
  • UNSW Medicine and Teaching and Research, Excellence in the Design and Development of Programs, Courses or Other Initiatives Award (2018)
  • European Survey Research Association, Early career researcher award: runner-up (2013)
  • ESRC Advanced Quantitative Methods Studentship £16,590 PA for 3 years (+ Tuition fees) (2011)

My Research Supervision


Supervision keywords


Areas of supervision

ILP/Honours/Masters/PhD

Potential supervision areas

  • Analysis of linked data
  • Causal inference using observational data
  • Innovative data communication (interactive dashboards and apps)

My Engagement

Blog posts and articles in The Conversation

Which families delay sending their child to school and why? We crunched the numbers. (The Conversation, April 2019)

Preschool benefits Indigenous children more than other types of preschool care. (The Conversation, December 2020)

Evaluating COVID-19 exit strategies using open-source modelling tools. (The UK Public Health Rapid Support Team Blog Post, August 2020)

Australia must vaccinate 200,000 adults a day to meet October target: new modelling. (The Conversation, February 2021)

Australian vaccine rollout needs all hands on deck after laterst Astra Zeneca news, mass vaccination hubs included. (The Conversation, April 2021)


In the media

How big data can change intensive care. (UNSW Newsroom, July 2018)

'A gift of time': Children who start school later fare better, study finds. (Sydney Morning Herald, April 2019)

1 in 4 families delay thier child's school entry -- and older children are more schol-ready: big data study. (UNSW Newsroom, April 2019)

Should kids start school later? (The Educator magazine, June 2019)

UNSW wins international COVID-19 data science competition. (thesphere.com.au, June 2020)

Dr Mark Hanly talks COVOID R package (eRUM 2020). (UNSW Newsroom, June 2020)

'What's surprising is the scale of the problem': One in seven children at risk of harm by five years old. (The Sydney Morning Herald, June 2020)

Nurses accuse Commonwealth of slowing vaccine rollout and treating them as handmaidens (ABC AM, February 2021)

Emailed COVID-19 vaccine certificate part of rollout plan, as Australia gets closer to first vaccinations (ABC News, February 2021)

Is Australia's goal of vaccinating the entire adult population by October achievable? (The Guardian, February 2021)

Mass vaccination could rescue the snail-paced rollout (The Medical Republic, April 2021)


My Teaching

HDAT9700 Statistical Modelling II. Lead course developer, convenor and lecturer.

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Location

Level 2, AGSM Building (G27)

Contact

61 (2) 9385 3143

Research Activities

Funded by NHMRC Project Grant.

Promoting positive early childhood development is fundamental to improving life opportunities and outcomes for Aboriginal Australians. However, national data show that a significant proportion of Aboriginal children have markers of developmental vulnerability at school entry and this tracks through to poor literacy and numeracy outcomes across all schooling years. We currently lack information about the key drivers of positive early childhood development in Aboriginal children, and the features of local communities and early childhood service…