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  
Adalbert Aineomucunguzi
ID:
Conservation Research to monitor Grey Crowned Cranes in Uganda
REFNo: NS518ES

1. Understand movement, long-term survival and landscape use of the Grey Crowned Cranes.
2. Provide data on Grey Crowned Crane populations and their distribution in Uganda
3. Advance our understanding of landscape use (particularly agriculture) and its influence on size and distribution of crane populations
4. Identify areas where the potential exists for crane conservation interventions

Uganda 2023-05-11 14:53:15 2026-05-11 Natural Sciences Non-Clinical Trial Non-degree Award
Ali Ssetaala
ID: UNCST-2021-R011817
CHILI- Adaptation
REFNo: HS2758ES

To support development of a new screening test for Cervical Cancer detecting high risk HPV DNA phenotypes and cancer proteins biomarkers in low-income countries.

Specific Objectives
1. To collect and analyze self-samples
2. To identify high risk HPV DNA in the self-samples
3. To link the levels of proteins measured in the self-samples with the cervical cancer lessions detected by papsmear and VIA.
4. To evaluate the effect of confounding factors on the cervical cancer protein levels in the self-samples

2.To understand user’s perspectives regarding (self-) sampling

Uganda 2023-05-11 14:52:00 2026-05-11 Medical and Health Sciences Non-Clinical Trial Non-degree Award
Simon Kigozi Peter
ID: UNCST-2022-R009813
Studying Incidence of Malaria from Routine Health Facility Reporting to Assess Impact of Targeted Control Interventions: Transforming Surveillance for Malaria Control
REFNo: HS2783ES

4. Investigate the level of residual burden of malaria missed by routine surveillance using randomised surveys.,3. Estimate the impact of targeted control intervention on incidence of malaria within health-facility-catchments.,2. Describe population spatial access to routinely reporting health facilities and estimate health facility catchments.,1. Evaluate the quality of routine HMIS data generated through the national surveillance system (DHIS-2) against facility register records.,To investigate the effectiveness of HMIS-based incidence in assessing the impact of targeted control interventions on malaria burden, through the following objectives.,
Uganda 2023-05-11 14:50:40 2026-05-11 Medical and Health Sciences Non-Clinical Trial Non-degree Award
Arthur  Mpimbaza
ID: UNCST-2022-R008866
Malaria rapid diagnostic test (RDT) capture and reporting assessment (MaCRA): Uganda protocol
REFNo: HS2747ES

Primary
1. Measure agreement between HCW and panel RDT results in Uganda.
Secondary
2. Measure the association between key characteristics of HCWs, RDT guidelines, health systems, malaria epidemiology and patient demographics and type of agreement/disagreement between the HCW and panel RDT results.
3. Understand how characteristics of HCWs, RDT guidelines, health systems, malaria epidemiology, and patient demographics affect the ability of HCWs to accurately implement, interpret, use, record and report RDT results.
4. Assess the fidelity of data entry from health facility registers to the health management information system (HMIS).
5. Determine the degree of over- and under- treatment for malaria and associations with characteristics of HCWs, RDT guidelines, health systems, malaria epidemiology and patient demographics.
6. Determine whether there is an observer impact of the study on monthly test positivity rates (TPRs).
7. Develop a database of photos of results from various RDT brands that can be used to train an artificial intelligence application to automate the interpretation and reporting of RDTs.
8. Classify common unusual RDT results that appear in RDT photos and assess patterns of errors to guide NMP and PMI on issues related to RDT administration and case management practices.
9. Calculate the accuracy of HealthPulse (Audere, Seattle, WA), a smartphone-based application that uses artificial intelligence to interpret RDT results, compared to the panel RDT results after training on a random selection of RDT photographs.
10. Compare agreement of RDT results read at one week and one month after administration with the initial read to determine the durability of RDT results over time.

Uganda 2023-05-11 14:45:16 2026-05-11 Medical and Health Sciences Non-Clinical Trial Non-degree Award
Dominik Biesalski
ID:
The Drivers, Effects and Measurement of Time Use Among the Urban Poor: Evidence from Uganda
REFNo: SS1674ES

Get insights into the time use patterns of urban workers and understand their effects on productivity and well-being.
Germany 2023-05-11 14:41:00 2026-05-11 Social Science and Humanities Clinical Trial Degree Award
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