• The University of Western Australia (M431), 35 Stirling Highway,

    6009 Perth

    Australia

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Personal profile

Biography

Dawit is a Research Fellow in the Cardiovascular Research Group (CVRG) within the School of Population and Global Health (SPGH) at UWA. He is also a Fellow (GradStat) of the Royal Statistical Society, and an adjunct Research Fellow at University of Birmingham (UK) where he has worked in applied health research projects since 2019.

Dawit is a medical statistician and a health econometrician by training with a wide range of research interests that include epidemiology, econometric modelling, and health services research. He has international experience in estimating the health and economic impacts of diseases and interventions, and in conducting multimorbidity/ comorbidity studies. Dawit has particular interest in the analysis of large electronic health records (EHRs) and linked data analysis to answer epidemiological, and health-economic research questions.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Health Econometrics & Electronic Health Records (EHRs) Research, PhD, The economic burden and determinants of healthcare costs of back pain in the UK: An empirical investigation using Electronic Health Records, University of Birmingham

Sept 2016Sept 2019

Medical Statistics, MSc, Patterns of Multimorbidity in Middle-Aged and Older Adults: An Analysis of the UK Biobank Data, University of Leicester

Sept 2015Sept 2016

Statistics, Graduate Certificate, University of Sheffield

Sept 2014Jun 2015

External positions

Adjunct Research Fellow, University of Birmingham

15 Jun 2022 → …

Research expertise keywords

  • Biostatistics and epidemiology
  • Electronic health records (EHRs) research
  • Linked data analysis
  • Health econometrics
  • Chronic diseases

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