2022 Health Data Analytics Graduate Fellowship for Nigerians
Deadline: January 8, 2022.
The Nigerian National Health Information System is currently weak and unable to provide the much-needed quality health data required for decision-making. Among many structural and governance barriers, this weakness is also largely due to low data analytics and coordination capacity, as well as the fragmented and disorganized manner of data systems development in the country.
Data analytics can improve health care in different ways. Some of these include; regular monitoring of health outcomes, improving decision support mechanisms, informing policy development, etc. More importantly, policymakers and stakeholders in health with the use of data and analytics will be able to make use of new tools that can provide valuable insight into the health status of the populace, quality of service delivery and financial implications.
Fellows are expected to tailor their research towards improving Nigerian health data and data systems around the following key areas:
- Health Governance
- Health outcomes
- Health financing
- Health Workforce
- Population and demographics
- Health facility service availability and readiness
- Drugs and logistics
- Service delivery
- Health Impact
- Health surveillance
The research goals can be pursued using any of the following approaches:
- Data Management
- Visual Analytics
- Data Mining
- Data Integration
- Multi-source data collation
- Advanced analytics
- Open data advocacy
- Big Data for health
- Data demand and use
- Statistical modelling of health data
- Health Information System interoperability
- Geographic Information System (GIS)
- Artificial Intelligence
- Machine learning
To be eligible for this fellowship, the individual must fulfill the following requirements;
- Must hold an acceptable form of Identification (i.e. an International passport issued by the Nigerian immigration service; Drivers’ license; Voters’ Card, National Identity Number (NIN) card)
- Must be a postgraduate student of any accredited University with a valid means of identification
- Candidates should hold a Bachelor’s degree of at least a 3.5/5.0 CGPA (Second class upper honors) for Master’s students, and at least a Merit or its equivalent in Master’s, for PhD students.
The benefits of this fellowship include:
- Up to ₦1,000,000.00 (per fellow) for postgraduate research (including research expenses e.g. equipment, data collection etc)
- Capacity building in research and health data analytics
- Possible job opportunities with eHealth4everyone on completion of the fellowship
- Access to a network of individuals with shared interests
- Mentorship and support from the administering body. This would translate into the provision of reviews and guidance during the course of their research.
- Provision of datasets on request.
Please read the eligibility section above carefully before applying
- Carefully complete each section of the HDA fellowship form(s) and attach the required documents. These include:
- Official transcripts from Academic Institution,
- Curriculum Vitae (CVs)
- Admission letters,
- Statement of purpose (maximum of 500 words),
- Research proposal/summary including timelines for execution,
- Letter of recommendation from Supervisor, Head of Department or Dean;
- A previously published paper, if available. This would be an added advantage.
- A 2-minute video of the applicant explaining their research proposal and motivation, is required.
- Applications will be reviewed on a rolling basis and awards will be given on a quarterly basis. For the next batch, Form(s) should be submitted on or before 8th January, 2022 by 11:59pm (WAT)
- The HDA fellowship committee will carefully review each proposal and make a final decision. If successful, applicants would be notified (within 8 weeks after the application deadline) that they have been selected to receive the research grant.
- Successful applicants must officially “accept” the offer via an email within a week.
- Applications will be reviewed on a rolling basis and awards will be given on a quarterly basis.