School of Public Health and Community Medicine

Quantitative Research

Quantitative research in public health group

We are a group of academics in the School of Public Health and Community Medicine at the University of New South Wales. We have experience in biostatistics, epidemiology, mathematical and economic modelling, with particular interest in applying these skills in the fields of infectious and chronic diseases.

Potential research (PhD or masters) students should contact the staff members listed below directly or email the group’s convenor Andrew Hayen.

Members

Associate Professor Andrew Hayen PhD
Convenor of Quantitative Research Group

Biostatistics. Statistical methods in diagnostic tests and monitoring. Statistical methods in clinical and public health research. Applications in cardiovascular diseases, osteoporosis, kidney disease and eye health. Teaching introductory and advanced biostatistics.

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Professor Raina MacIntyre (Hons 1), FRACP, FAFPHM, M App Epid, PhD

Infectious diseases epidemiology, design of clinical trials in infectious diseases, observational epidemiology in infectious diseases.

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Professor Mary-Louise McLaws DipTropPubHlth (USyd), MPHlth (USyd), PhDMed (USyd)

Patient safety and healthcare worker safety with emphasis on the epidemiology of healthcare-associated and occupational acquisition of infection. Specific interests include surveillance of infectious diseases in healthcare facility, healthcare workers' behaviour in infection control, disaster management and outbreak of infectious diseases investigation. A recent example of quantitative research using hazard analysis in my area of research in patient safety is: McLaws ML, Burrell A. Zero-risk for Central Line Associated Bloodstream Infection: Are we there yet? Crit Care Med 2012 Feb; 40(2): 388-93.

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Dr Heather Gidding PhD
Senior Research Fellow

Use of routinely collected data for epidemiological research, in particular using data linkage methods, and longitudinal data analysis techniques.

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Associate Professor Anthony Newall PhD
Associate Professor

Cost-effectiveness analysis (economic evaluation), infectious disease epidemiology, (statistical) time-series analysis, dynamic transmission models for infectious diseases.

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Dr Patrick Rawstorne BA (Hons Psych), PhD (Psych)
Senior Lecturer

Behavioural surveillance surveys; survey based research; quantitative methods; data analysis; respondent driven sampling (RDS); the use of personal digital assistants (PDAs); mental health and HIV; capacity development training in research methods.

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Dr James Wood PhD
Senior Lecturer

Modelling control strategies and particularly vaccination for infectious diseases, Parameter estimation in infectious disease models, Quantitative epidemiology and predictive models in public health. Course convenor Infectious Diseases (PHCM9782) and Mathematical Modelling of Infectious Diseases (PHCM9785).

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Dr Anita Heywood PhD
Lecturer

Categorical data analysis, analysis of routine surveillance data to evaluate vaccine programs and evidence-based vaccination policy and practice. Specific interest in vaccine-preventable diseases and knowledge, attitudes and behaviours to infectious disease risks and preventative health practices in travellers, migrant Australians and other high risk groups.

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Dr Bayzid Rahman PhD
Lecturer

Systematic review and Meta-analysis in medical and public health research. Design and analysis of data from epidemiological studies (Ecological studies, cross-sectional surveys, case-control, cohort and RCTs). Environmental exposure assessment: exposure through air and water especially to disinfection by-products in water. Spatial epidemiology: analysis of cancer rates across geographical areas, disease mapping, detection and analysis of disease clusters.

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Dr Dr Robin Turner BSc (Hons), PhD, MBiostat
Senior Lecturer

My research interests cover the areas of diagnostic tests, patient follow-up and monitoring, patient preferences for treatment, decision aids and the statistical methods underpinning these. I have expertise in the design of two stage randomised trials to understand patient preference and selection effects which can be important in decision aid trials.

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