Factors associated with never treatment and acceptability of mass drug administration for the elimination of lymphatic filariasis in Guyana, 2021
Bibliographic record
Abstract
Guyana remains one of four countries in the Americas endemic for lymphatic filariasis (LF). Elimination of LF requires repeated annual mass drug administration (MDA) with sufficient levels of coverage for success. This study assesses the acceptability and never treatment of LF MDA using data from a routine assessment survey in 2021. A subset of individuals, over 20 years of age (n = 2498), were selected to receive an expanded questionnaire to examine factors associated with acceptability and never treatment. Assessed factors include respondent demographics, knowledge, risk perceptions of LF, and opinions on the MDA programme. The majority (73%) of those with scores above the acceptability threshold (score ≥22.5) reported participating in MDA two or more times. Factors strongly and positively associated with scoring above the acceptability threshold include beliefs in importance of participation in MDA for their community (aOR = 2.8, 95%CI (1.1-7.2)), perception of importance of LF treatment (6.9 (3.2-14.7)), receiving treatment in 2021 (2.9 (1.5-5.4)), and the number of self-reported times taking treatment for LF (2.2 (1.1-4.4)). Ten percent of respondents participated in the MDA for the first time in 2021, while 15% reported never treatment during any round of LF MDA. Three factors were statistically associated with participation in MDA across the two levels of the models (level 1: took LF treatment once versus never, and level 2: took LF treatment twice versus never) included: 1) scoring above the acceptability threshold (aOR = 6.2, 95%CI(3.8-10.0)), 2) self-reported importance of participation in MDA for their community (7.1 (2.9-17.8)), and 3) personal beliefs that they should take LF treatment even if they are not sick (2.6 (1.7-3.9)). As Guyana moves closer to LF elimination, these results provide further insight and understanding into programmatic results and could inform further action following MDA activities-particularly if an approach is needed to address never treatment during MDA.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".