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Active RESEARCH CENTERS NIH (US)

Sustainable Cloud Operations for Research and Environmental Impact (SCORE - EI)

$809.9K USD

Funder FOGARTY INTERNATIONAL CENTER
Recipient Organization Aga Khan University (Kenya)
Country Kenya
Start Date Sep 15, 2021
End Date Jun 30, 2026
Duration 1,749 days
Number of Grantees 2
Roles Principal Investigator; Co-Investigator
Data Source NIH (US)
Grant ID 11126966
Grant Description

PROJECT SUMMARY/ABSTRACT The parent project, UZIMA-DS (UtiliZing Health Information for Meaningful Impact in East Africa through Data Science), aims to create a scalable and sustainable platform that leverages novel data assimilation approaches and advanced Artificial Intelligence (AI) and Machine Learning (ML) methods to improve health

outcomes in two key domains: maternal, newborn, and child health (MNCH), and mental health (MH). Led by the Aga Khan University in East Africa (AKU) and the University of Michigan, UZIMA-DS is a U54 Research Hub funded under the NIH Data Science for Health Discovery and Innovation in Africa Initiative.

Projects in low- and middle-income countries (LMICs) encounter significant challenges with cloud utilization, such as limited resources, tight budgets, and a lack of expertise in cloud infrastructure. These obstacles hinder the ability to scale research collaborations within the consortium and beyond. To address these issues, we

propose developing and documenting good practices for building efficient and cost-effective cloud-based data pipelines for research. We will also address scaling cloud infrastructure responsibly, ensuring that as we expand, we do so without proportionally increasing our carbon footprint. We will utilize data pipelines from the ongoing UZIMA-DS project, which processes daily Fitbit data from 500

healthcare workers on a Microsoft Azure instance. This use case will serve as a foundation for building and evaluating data pipelines using three tools and approaches within the Azure environment. Our primary goal is to develop and implement good practices for constructing efficient, cost-effective cloud-based data pipelines

that minimize environmental impact. By doing so, we aim to promote sustainable and scalable research practices in LMIC settings, captured in our motto, “Efficient Data, Sustainable Future for Research.” The impact of this work includes enhanced research efficiency, cost savings, environmental sustainability, and

empowering the DS-I Africa consortium to adopt sustainable cloud practices.

All Grantees

Aga Khan University (Kenya)

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