Scaling Up and Enhancing the Functionality of the Electronic Integrated Diseases Surveillance and Response System in Uganda, 2020-2022: Description of the Journey, Challenges, and Lessons Learned
Bibliographic record
Abstract
Unlabelled: In 2017, Uganda implemented an electronic Integrated Disease Surveillance and Response System (eIDSR) to improve data completeness and reporting timelines. However, the eIDSR system had limited functionality and was implemented on a small scale. The Ministry of Health, with support from the Infectious Disease Institute, Makerere University, and Health Information Systems Program Uganda, upgraded the system functionality and scaled up its implementation. This study describes the process and impact of upgrading eIDSR functionality and expanding its implementation across additional districts. The Ministry of Health, through its Integrated Epidemiology, Surveillance & Public Health Emergency Department, coordinated the implementation of the eIDSR. User requirements were identified through consultations with national surveillance stakeholders. The feedback informed the design and development of the upgraded eIDSR functionalities. The eIDSR rollout followed a consultative workshop to create awareness of the system among stakeholders. A curriculum was developed, and a national training of trainers was conducted. These trainers cascaded the training to the district health teams, who later cascaded the training to health workers. The training adopted an on-site training approach, where a group of national or district trainers would train new users at their desks. The eIDSR system was upgraded to the District Health Information Software 2 (DHIS2) 2.35 platform featuring faster reading and writing tracker data, handling over 100 concurrent users and enhanced case-based surveillance features on Android and web platforms. From October 2020 to September 2022, the eIDSR was rolled out in 68% (100/146) of districts. Additionally, the system permitted prompt reporting of signals of epidemic-prone diseases. Improving the functionality and the expanded geographical scope of the eIDSR system enhanced disease surveillance. Stakeholder commitment and leveraging existing structures will be needed to scale up eIDSR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".