Progress and experiences of implementing an integrated disease surveillance and response system in Somalia; 2016–2023
Bibliographic record
Abstract
Introduction: In 2021, a regional strategy for integrated disease surveillance was adopted by member states of the World Health Organization Eastern Mediterranean Region. But before then, member states including Somalia had made progress in integration of their disease surveillance systems. We report on the progress and experiences of implementing an integrated disease surveillance and response system in Somalia between 2016 and 2023. Methods: We reviewed 20 operational documents and identified key integrated disease surveillance and response system (IDSRS) actions/processes implemented between 2016 and 2023. We verified these through an anonymized online survey. The survey respondents also assessed Somalia's IDSRS implementation progress using a standard IDS monitoring framework Finally, we interviewed 8 key informants to explore factors to which the current IDSRS implementation progress is attributed. Results: Between 2016 and 2023, 7 key IDSRS actions/processes were implemented including: establishment of high-level commitment; development of a 3-year operational plan; development of a coordination mechanism; configuring the District Health Information Software to support implementation among others. IDSRS implementation progress ranged from 15% for financing to 78% for tools. Reasons for the progress were summarized under 6 thematic areas; understanding frustrations with the current surveillance system; the opportunity occasioned by COVID-19; mainstreaming IDSRS in strategic documents; establishment of an oversight mechanism; staggering implementation of key activities over a reasonable length of time and being flexible about pre-determined timelines. Discussion: From 2016 to 2023, Somalia registered significant progress towards implementation of IDSRS. The 15 years of EWARN implementation in Somalia (since 2008) provided a strong foundation for IDSRS implementation. If implemented comprehensively, IDSRS will accelerate country progress toward establishment of IHR core capacities. Sustainable funding is the major challenge towards IDSRS implementation in Somalia. Government and its partners need to exploit feasible options for sustainable investment in integrated disease surveillance and response.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".