Who We Are
About INSPIRE
INSPIRE 2.0 was launched in February 2025 as a network for sharing, harmonizing, and visualizing longitudinal population health data. Our work ensures standardized, high-quality datasets are available for research, policy development, and innovation across Africa.
Mission
To establish a sustainable infrastructure for longitudinal population health data, empowering policymakers and researchers with high-quality insights.
Vision
A future where integrated, data-driven decision-making transforms health outcomes across Africa.
About INSPIRE
INSPIRE 2.0 was launched in February 2025 as a network for sharing, harmonizing, and visualizing longitudinal population health data. Our work ensures standardized, high-quality datasets are available for research, policy development, and innovation across Africa.
Mission
To establish a sustainable infrastructure for longitudinal population health data, empowering policymakers and researchers with high-quality insights.
Vision
A future where integrated, data-driven decision-making transforms health outcomes across Africa.
Objectives
Main Objective
To demonstrate the value of a unified data system across HDSS sites in generating insights about significant global health challenges.
Sub - Objectives
- Conduct data harmonization and analysis of HDSS datasets, examine trends and relationships, and explore heterogeneity in key drivers of challenges across Africa.
- Demonstrate the value of standardization, streamlining, and linkage of internal (HDSS and nested surveys) and external datasets for studying SDoH in Africa.
- Pilot alternative cost-effective, robust, and sustainable data collection approaches or models for obtaining more robust longitudinal data from HDSS sites across Africa.
- Harness Artificial Intelligence such as Large Language Models to improve HDSS operations.
Objectives
Main Objective
To demonstrate the value of a unified data system across HDSS sites in generating insights about significant global health challenges.
Sub - Objectives
- Conduct data harmonization and analysis of HDSS datasets, examine trends and relationships, and explore heterogeneity in key drivers of challenges across Africa.
- Demonstrate the value of standardization, streamlining, and linkage of internal (HDSS and nested surveys) and external datasets for studying SDoH in Africa.
- Pilot alternative cost-effective, robust, and sustainable data collection approaches or models for obtaining more robust longitudinal data from HDSS sites across Africa.
- Harness Artificial Intelligence such as Large Language Models to improve HDSS operations.
Leadership & Team
Agnes Kiragga, PhD
Project Lead
Damazo Kadengye, PhD
Data Sytems Expert
Samuel Iddi, PhD
Research Scientist
Machine Learning Expert
Ivan Busulwa, DrPH
Program Manager
Daniel Mwanga, MSc
Data Manager
Henry Owoko, BA
M&E Research Officer
AI Researcher
Leadership & Team
Agnes Kiragga, PhD
Project Lead
Damazo Kadengye, PhD
Data Sytems Expert
Samuel Iddi, PhD
Research Scientist
Machine Learning Expert
Ivan Busulwa, DrPH
Program Manager
Daniel Mwanga, MSc
Data Manager
Henry Owoko, BA
M&E Research Officer
AI Researcher
Leadership & Team
Agnes Kiragga, PhD
Project Lead
Damazo Kadengye, PhD
Data Sytems Expert
Samuel Iddi, PhD
Research Scientist
Machine Learning Expert
Ivan Busulwa, DrPH
Program Manager
Daniel Mwanga, MSc
Data Manager
Henry Owoko, BA
M&E Research Officer
AI Researcher
Partners & Collaborators
INSPIRE collaborates with the following research and policy institutions.
Partners & Collaborators
INSPIRE collaborates with the following research and policy institutions.