The Spread of African Swine Fever (ASF) in East Nusa Tenggara, Indonesia, Analyzed Using a Mathematical Modeling Approach
Bibliographic record
Abstract
African swine fever (ASF) is a highly contagious viral disease that results in very high mortality rates among pigs and causes significant economic losses worldwide.In Indonesia, ASF has spread to 32 provinces since the first outbreak in 2019, with East Nusa Tenggara being one of the most severely affected areas.This study developed a nonlinear differential equation model to analyze the dynamics of ASF transmission and evaluate the combined effectiveness of biosecurity measures and vector control strategies in controlling the disease's spread.The model calculates the basic reproductive number both without and with vectors.An integrated approach that combines biosecurity measures and optimal vector control can significantly reduce the risk of infection, depending on the effectiveness of biosecurity (p) and the effectiveness of tick vector control (q).These findings suggest that the synergistic approach of combining biosecurity and optimal vector control is highly effective in reducing the spread of ASF in East Nusa Tenggara.This provides a scientific foundation for developing adaptive disease control policies in Indonesia.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".