Approved Research This page provides a searchable list of all research protocols that have been reviewed and approved by the Uganda National Council for Science and Technology(UNCST).
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Name Title Nationality Approval Date Expiry Date Field of Science/Classification Trial Type Research Type  
Emmanuel  Luyirika BK
ID: UNCST-2025-R021521
 Destigmatizing Breast Cancer: Village Health Teams Using a Video Education Tool
REFNo: SS4394ES

1)Improve knowledge about breast cancer among VHTs 2)Evaluate if community members found this video tool to be an acceptable and helpful way to learn more about breast cancer. 3)Evaluate if VHTs found this video tool to be an acceptable and helpful way to share information about breast cancer.
Uganda 2025-12-05 18:37:27 2028-12-05 Social Science and Humanities Non-Clinical Trial Non-degree Award
Nelson Sewankambo K
ID: UNCST-2020-R014578
 Evaluation of an Information Management and Communication System for Population-wide Point-of-Care Infant Sickle Cell Disease Screening (SIMCS)- A Cluster Randomized Trial
REFNo: HS6567ES

(ii) To evaluate the impact of the SCD SIMCS on access to screening and care and outcomes of children with SCD,
 Uganda 2025-12-05 18:30:02 2028-12-05 Medical and Health Sciences Clinical Trial Non-degree Award
Julius Ssendiwala
ID:
EVALUATION OF HIV INTEGRATION INTO ROUTINE CARE AT HEALTH FACILITIES IN UGANDA: LESSONS LEARNT FROM -THE COVID-19 HIV SERVICE DELIVERY ADAPTATIONS AND THE US PRESIDENT EXECUTIVE ORDERS
REFNo: HS6720ES

1. To document the health system adaptations that occurred during the COVID-19 pandemic, and the recent US President Executive Orders and how are they are being utilized for current HIV integration efforts?
2. To document the various models of HIV integration currently being implemented, and the factors that facilitate or hinder their successful implementation
3. To assess the uptake, feasibility, and acceptability of integrating HIV services into routine healthcare services

 Uganda 2025-12-03 18:46:20 2028-12-03 Medical and Health Sciences Non-Clinical Trial Non-degree Award
Christine  Wiltshire Sekaggya
ID: UNCST-2019-R000578
 VALIDATION OF AN OFFLINE DEEP – LEARNING AI MODEL FOR ESTIMATING FVC AND FEV₁ FROM CHEST X‑RAYS IN A RESOURCE‑LIMITED UGANDAN CLINICAL SETTING.
REFNo: HS6703ES

Primary Objective
To evaluate the accuracy of an offline, deep-learning AI model in estimating forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁) by comparing AI-predicted values against spirometry-measured values.

Secondary Objective
To determine the agreement between AI-derived and spirometry-derived FEV₁/FVC ratios, and assess its utility for identifying airflow obstruction (i.e., FEV₁/FVC < 0.70).
 Uganda 2025-12-01 22:01:17 2028-12-01 Medical and Health Sciences Non-Clinical Trial Non-degree Award
Ombeva  Malande Oliver
ID: UNCST-2024-R004335
 Exploring Factors Influencing COVID-19 Vaccination Uptake: A Qualitative Study in Uganda
REFNo: SS4582ES

To explore the factors and contextual differences that influenced COVID-19 vaccination uptake in Uganda, to compare these with experiences in Burundi and Rwanda, and to identify key predictors and opportunities for regional learning
 Kenya 2025-12-01 21:44:17 2028-12-01 Social Science and Humanities Non-Clinical Trial Non-degree Award
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