Codevelopment of COVID-19 infection prevention and control guidelines in lower-middle-income countries: the ‘SPRINT’ principles
Bibliographic record
Abstract
INTRODUCTION: The COVID-19 pandemic has required the rapid development of comprehensive guidelines to direct health service organisation and delivery. However, most guidelines are based on resources found in high-income settings, with fewer examples that can be implemented in resource-constrained settings. This study describes the process of adapting and developing role-specific guidelines for comprehensive COVID-19 infection prevention and control in low-income and middle-income countries (LMICs). METHODS: We used a collaborative autoethnographic approach to explore the process of developing COVID-19 guidelines. In this approach, multiple researchers contributed their reflections, conducted joint analysis through dialogue, reflection and with consideration of experiential knowledge and multidisciplinary perspectives to identify and synthesise enablers, challenges and key lessons learnt. RESULTS: We describe the guideline development process in the Philippines and the adaptation process in Sri Lanka. We offer key enablers identified through this work, including flexible leadership that aimed to empower the team to bring their expertise to the process; shared responsibility through equitable ownership; an interdisciplinary team; and collaboration with local experts. We then elaborate on challenges including interpreting other guidelines to the country context; tensions between the ideal compared with the feasible and user-friendly; adapting and updating with evolving information; and coping with pandemic-related challenges. Based on key lessons learnt, we synthesise a novel set of principles for developing guidelines during a public health emergency. The SPRINT principles are grounded in situational awareness, prioritisation and balance, which are responsive to change, created by an interdisciplinary team navigating shared responsibility and transparency. CONCLUSIONS: Guideline development during a pandemic requires a robust and time sensitive paradigm. We summarise the learning in the 'SPRINT principles' for adapting guidelines in an epidemic context in LMICs. We emphasise that these principles must be grounded in a collaborative or codesign process and add value to existing national responses.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".