Rectal artesunate for severe malaria, implementation research, Zambia
Bibliographic record
Abstract
Objective: To determine whether the positive results of a single-district pilot project focused on rectal artesunate administration at the community level in Zambia could be replicated on a larger scale. Methods: In partnership with government, in 10 rural districts during 2018-2021 we: (i) trained community health volunteers to administer rectal artesunate to children with suspected severe malaria and refer them to a health facility; (ii) supported communities to establish emergency transport, food banks and emergency savings to reduce referral delays; (iii) ensured adequate drug supplies; (iv) trained health workers to treat severe malaria with injectable artesunate; and (v) monitored severe malaria cases and associated deaths via surveys, health facility data and a community monitoring system. Results: Intervention communities accessed quality-assured rectal artesunate from trained community health volunteers, and follow-on treatment for severe malaria from health workers. Based on formal data from the health management information system, reported deaths from severe malaria reduced significantly from 3.1% (22/699; 95% confidence interval, CI: 2.0-4.2) to 0.5% (2/365; 95% CI: 0.0-1.1) in two demonstration districts, and from 6.2% (14/225; 95% CI: 3.6-8.8) to 0.6% (2/321; 95% CI: 0.0-1.3) in eight scale-up districts. Conclusion: Despite the effects of the coronavirus disease, our results confirmed that pre-referral rectal artesunate administered by community health volunteers can be an effective intervention for severe malaria among young children. Our results strengthen the case for wider expansion of the pre-referral treatment in Zambia and elsewhere when combined with supporting interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".