Sero-Epidemiology of Lumpy Skin Disease Virus, Swat Valley Switzerland, Pakistan
Bibliographic record
Abstract
Lumpy Skin Disease (LSD) is a viral illness caused by the LSD virus. It ranks among the most economically impactful transboundary and emerging diseases affecting cattle. In Swat district, Khyber Pakhtunkhwa (KPK), an outbreak investigation was conducted from January 2023 to July 2023. In the latter part of 2022, an outbreak of Lumpy Skin Disease (LSD) affected all seven tehsils of Swat district, prompting a comprehensive investigation. Numerous animals underwent examination, and blood samples were collected from those actively infected. The Veterinary Research and Disease Investigation Center Balogram (VRDIC Balogram) played a central role in characterizing the virus using various molecular techniques and conventional PCR. Clinical examinations were conducted on both infected and in-contact animals, accompanied by a questionnaire survey designed to pinpoint potential risk factors associated with the disease. The findings indicated that LSD was present in 27.94% (443/1585) of the examined animals, with blood samples collected from 443 clinically positive cases for further laboratory analysis. Among different age groups, morbidity rates were notably higher in mixed breeds compared to indigenous breeds, detailed as 30% (52/170), 24% (38/160), 28% (34/120), 33% (20/60), and 53% (29/55). Mortality rates and case fatality were significantly elevated in young animals compared to other age groups. Conventional PCR confirmed that DNA extracts from blood samples collected from higher number of animals virus isolates were positive for LSDV The questionnaire survey highlighted communal points, such as markets, watering, and grazing areas, as common sources of infection, along with the introduction of sick animals to the herd. These findings provide valuable insights into the dynamics and risk factors associated with the LSD outbreak in the Swat district. In conclusion, the economic losses resulting from the LSD outbreak were substantial. Recommendations include enhancing diagnostic facilities, implementing strategic control measures, and raising awareness within communities for early detection and reporting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".