Knowledge, Perception, and Preventive Practices of Livestock Workers and Household Animal Owners Regarding Anthrax in Nigeria
Bibliographic record
Abstract
Abstract Anthrax disease outbreak is a significant public health and socioeconomic problem, especially in low and middle-income countries (LMIC) like Nigeria. Inadequate knowledge and poor preventive practices against the disease among livestock workers and household animal owners remain important for disease transmission. Following the recent outbreaks in Nigeria, a cross-sectional study was carried out to assess the knowledge, perception and preventive practices of livestock workers and household animal owners regarding anthrax and the associated socioeconomic implications in Nigeria. A pretested, semi-structured, interviewer-administered questionnaire was used to elicit relevant information from the respondents (n=1025) in seven of the 36 states in Nigeria. Data were analysed using SPSS version 29. Univariate analysis was done and Chi-square test statistics was test for association between the knowledge/perception and other variables. Of the 1025 respondents, 58.6% and 79.9% demonstrated good knowledge and positive perception towards anthrax. However, there were important exposure practices, including a lack of preventive measures against anthrax infection (22.0%). Besides, only 27.7% of the respondents knew about the anthrax vaccination programme for livestock in the study area. With respect to the socioeconomic effects of the disease outbreak, 23.8% of the respondents indicated that the regulations imposed during an anthrax outbreak affect their livestock-related activities, while 40.6% were worried they might go out of business due to the anthrax outbreak. The respondents’ knowledge of anthrax was significantly associated with higher education (p=0.000), level of awareness (p=0.000) and perception of risk (p=0.000). The study reveals a relatively high level of perception but an average knowledge level regarding anthrax with associated socioeconomic impacts among livestock workers and household animal owners in Nigeria. An important knowledge gap includes the poor knowledge of the routine annual vaccination of animals. Hence, mitigation strategies should include educational programmes targeting this gap.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".