Proactive home-based malaria management in rural communities of Bassar Health District in northern Togo from 2014 to 2017: PECADOM + , a pilot experiment
Bibliographic record
Abstract
BACKGROUND: Togo's National Malaria Control Programme has initiated an active home-based malaria management model for all age groups in rural areas of Bassar Health District. This report describes the model, reports its main results, and determines the factors associated with positive rapid diagnostic test results. METHODS: From 2014 to 2017, in three peripheral care units of Bassar Health District (Binaparba, Nangbani, and Baghan), community health workers visited residents' homes weekly to identify patients with malaria symptoms, perform rapid diagnostic tests in symptomatic patients, and give medication to positive cases. Univariate and multivariate logistic regression models were used to determine the factors associated with positive tests. RESULTS: The study covered 11,337 people (817 in 2014, 1804 in 2015, 2638 in 2016, and 6078 in 2017). The overall mean age was 18 years (95% CI 5-29; min-max: 0-112 years). The median age was 10 years (SD: 16.9). The proportions of people tested positive were 75.3% in Binaparba, 77.4% in Nangbani, and 56.6% in Baghan. The 5-10 age group was the most affected category (24.2% positive tests). Positive tests were more frequent during the rainy than during the dry season (62 vs. 38%) and the probability of positive test was 1.76 times higher during the rainy than during the dry season (adjusted OR = 1.74; 95% CI 1.60-1.90). A fever (37.5 °C or higher) increased significantly the probability of positive test (adjusted OR = 2.19; 95% CI 1.89-2.54). The risk of positive test was 1.89 times higher in passive than in active malaria detection (adjusted OR = 1.89; 95% CI 1.73-2.0). CONCLUSIONS: This novel experimental community and home-based malaria management in Togo suggested that active detection of malaria cases is feasible within 24 h, which allows rapid treatments before progression to often-fatal complications. This PECADOM + program will help Togo's National Malaria Control Programme reduce malaria morbidity and mortality in remote and hard-to-reach communities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".