Humanitarian–Development Nexus: strengthening health system preparedness, response and resilience capacities to address COVID-19 in Sudan—case study of repositioning external assistance model and focus
Bibliographic record
Abstract
The advent of the COVID-19 pandemic and the establishment of a new transitional government in Sudan with rejuvenated relations with the international community paved the way for external assistance to the EU COVID-19 response project, a project with a pioneering design within the region. The project sought to operationalize the humanitarian-development-peace nexus, perceiving the nexus as a continuum rather than sequential due to the protracted nature of emergencies in Sudan and their multiplicity and contextual complexity. It went further into enhancing peace through engaging with conflict and post-conflict-affected states and communities and empowering local actors. Learning from this experience, external assistance models to low- or middle-income countries (LMICs) should apply principles of flexibility and adaptability, while maintaining trust through transparency in exchange, to ensure sustainable and responsive action to domestic needs within changing contexts. Careful selection and diverse project team skills, early and continuous engagement with stakeholders, and robust planning, monitoring and evaluation processes were the project highlights. Yet, the challenges of political turmoil, changing Ministry of Health leadership, competing priorities and inactive coordination mechanisms had to be dealt with. While applying such an approach of a health system lens to health emergencies in LMICs is thought to be a success factor in this case, more robust technical guidance to the nexus implementation is crucial and can be best attained through encouraging further case reports analysing context-specific practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".