Trends in maternal and newborn health outcomes in Demographic Household Surveys in Papua New Guinea (2006 and 2018)

Research Opportunity
Masters by Research
Number of Honour Places Available
1
Location
Burnet Institute
Primary Supervisor Email Number Webpage
Dr Joshua Vogel joshua.vogel@burnet.edu.au
Co-supervisor Email Number Webpage
Prof Caroline Homer caroline.homer@burnet.edu.au
Dr Alyce Wilson alyce.wilson@burnet.edu.au
Dr Meghan Bohren meghan.bohren@unimelb.edu.au

Summary In this project, a student will conduct a comparative analysis of the two Demographic Health Surveys (2006 and 2018) available for Papua New Guinea, to assess trends in socio-demographic characteristics, reproductive health service utilization and maternal and newborn health outcomes.

Project Details

Demographic and Health Surveys (DHS) are large, nationally-representative household surveys that provide data for a wide range of monitoring and impact evaluation indicators across population, health, and nutrition topics. In many low- and middle-income countries (such as Papua New Guinea), the lack of national civil administrative data means that governments, international agencies and funders rely on DHS data for many reproductive health indicators.

In Papua New Guinea, a new DHS (data collected 2017-2018) will be released in late 2019, superseding the previous DHS 2006. The availability of these new data provide a unique opportunity to assess trends in key maternal and newborn health indicators in PNG over the past decade.

In this project, a student will conduct a comparative analysis of the two Demographic Health Surveys (2006 and 2018) available for Papua New Guinea, to assess trends in socio-demographic characteristics, reproductive health service utilization and maternal and newborn health outcomes. The student will work with the Global Women’s and Newborn’s Health Group at the Burnet Institute in Melbourne (primarily desk-based research). This project will allow the student to gain experience in global maternal and perinatal health epidemiology with view to a scientific publication.



Faculty Research Themes

Child Health

School Research Themes

Data science, health metrics and disease modeling



Research Opportunities

Masters by Research
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research

Graduate Research application

Honours application

Key Contact

For further information about this research, please contact a supervisor.

Research Node

Burnet Institute

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