EDAM: Ethiopian Data Analytics and Modelling Consortium

Background

• Ethiopia faces a triple burden of infectious diseases (HIV, malaria and TB), noncommunicable diseases, and nutritional deficiencies.
• The country has made strong progress in health data collection, alongside growing national capacity in data analytics and modelling.
• Key gaps remain in using routine health system data to guide timely evidence informed policy decisions, including limited real-time analysis of sex and gender differences across diseases and services.
• Better surveillance and modelling of health threats could improve the responsiveness of the health system and save lives.

Aim

• To build a sustainable, locally owned and locally led national consortium that links real-time health data, modelling and policy decision-making across Ethiopia.
• To strengthen the health evidence pipeline by reducing data fragmentation, improving data quality and enabling faster translation of findings into evidence-based policy.
• To advance data equity by improving sex-disaggregation of data during data collection, analysis reporting and use.
• Enhance gender equity in the Ethiopian data science workforce.

Methodology

• Establish the governance and operating structures of the EDAM consortium, a partnership between Ethiopian data science institutions including the Ministry of Health.
• Conduct a detailed analysis of the health data ecosystem to identify and understand barriers/enablers to equitable inclusion of sex and gender considerations in data modelling.
• Build the capacity of researchers and research institutions in Ethiopia in advanced data modelling, AI and sex-disaggregated data analysis methods.
• Co-develop a national policy for sex-disaggregation of health data.
• Collaborate with an Ethiopian gender advisory committee to implement strategies to improve gender equity in the data science workforce.

EDAM is a collaboration between the Women's Health Programme at The George Institute for Global Health and the Department for Infectious Disease Epidemiology in Imperial College London's School of Public Health.