Management Of Chronic Noncommunicable Diseases After Natural Disasters In The Caribbean: A Scoping Review
Bibliographic record
Abstract
Extreme weather events in the Caribbean region are becoming increasingly severe because of climate change. The region also has high rates of poorly controlled chronic noncommunicable diseases (NCDs), which were responsible for at least 30 percent of deaths after two recent hurricanes. We conducted a scoping review of literature published between 1974 and 2020 to understand the burden and management of chronic NCDs in the Caribbean after natural disasters. Of the twenty-nine articles included in this review, most described experiences related to Hurricanes Dorian (2019) and Irma and Maria (2017) and the Haiti earthquake (2010). Challenges included access to medication, acute care services, and appropriate food, as well as communication difficulties and reliance on ad hoc volunteers and outside aid. Mitigating these challenges requires different approaches, including makeshift points of medication dispensing, disease surveillance systems, and chronic disease self-management education programs. Evidence is needed to inform policies to build resilient health systems and integrate NCD management into regional and national disaster preparedness and response plans.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".