Knowledge, Attitude, and Practices of Swine Farmers related to Livestock Biosecurity: A Case Study of African Swine Fever in Vietnam
Bibliographic record
Abstract
Purpose: African Swine Fever (ASF), one of the world’s most contagious and deadly livestock infectious diseases, was introduced to Vietnam in 2019 and has since become one of the biggest threats to the country’s porcine industry. To this day, very little is known about the major drivers of ASF outbreaks – in particular, the generally low levels of biosecurity found on smallholder farms in Vietnam. The main objective of this paper is to assess the knowledge disparities, diverging attitudes, and different practices among smallholder pig farming households that influence the adoption, implementation, and continuation of ASF biosecurity measures in Vietnam. Research Method: Structured questionnaire surveys were conducted to 183 smallholder pig farming households in December 2020 in four districts of Dong Nai, the largest pig production province in Vietnam. The determinants of farmers’ knowledge and attitude toward ASF were estimated using an ordinal probit regression; a panel-data probit regression approximated the probability of farmers adopting biosecurity measures. Findings: It was found that, prior to the first outbreaks of ASF in Vietnam in 2019, surveyed pig farmers generally had an inadequate level of knowledge about ASF to be able to successfully prevent and control the disease’s spread. Rather, farmers only managed to significantly improve their understanding of ASF after outbreaks had begun. Model estimates indicate that a better understanding of ASF ultimately helped improve farmers’ attitudes toward ASF biosecurity measures. Additionally, farmers with previous experience in dealing with other livestock infectious disease outbreaks were, in most cases, found to be more willing to implement ASF biosecurity measures. Together, deeper understanding of ASF and more positive attitudes towards ASF prevention and control measures contributed to an overall increase in the likelihood of farmers adopting and implementing appropriate ASF biosecurity practices. Originality/ Value: This paper highlights the need for improved community education campaigns in efforts to prevent and contain ASF outbreaks, as well as the need for increased financial assistance and support for swine farmers to enable them to adopt effective biosecurity practices.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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".