HEALTHCARE DURING TRAVEL: A GEOSENTINEL DESCRIPTIVE ANALYSIS, 2017-2020
Bibliographic record
Abstract
surveillance but its performance is not yet assed.The purpose is to describe the CBS's usefulness, acceptability, representativeness and reactivity in Tillaberi region.Methods: This is a cross sectional study that included all AFP cases notified by surveillance system from January 2014 to July 2022."CDC-Atlanta Guidelines 2003" were used to assess the studied attributes.We performed descriptive analysis using defined variables presented in proportions, median, interquartile range (IQR) and sex ratio.Usefulness: Non Polio AFP Rate (NPAFP-R) before CBS (2014) and during CBS (2022).Acceptability: percentage of stool samples collected within 14 days after paralysis onset and received to the laboratory in good condition.Representativeness: true AFP cases, AFP cases age group and their distribution in place and time.Reactivity: timeline between paralysis onset and the stool samples reception at the national laboratory.Findings: The NPAFP-R per 10 0,0 0 0 under 15 children ranged from 1.9 in 2014 to 26.1 in 2022.The percentage of AFP cases with two stool samples collected within 14 days after paralysis onset and received at the laboratory in good condition was 73.4%(122/166).True AFP cases represented 97.6%(166/170), belonged to under 15 age group, were from all CBS implementing districts and were notified every year of CBS implementation.Male to female sex ratio was 1.27(93/73).The median timeline between the paralysis onset and stool samples reception at the laboratory was 21 days, IQR (16-31).Conclusion: CBS was useful, representative, less acceptable and not reactive.Stakeholders capacity building, monitoring and appropriate means for samples transportation from the collection site to the national laboratory could improve its acceptability and reactivity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".