SEROLOGICAL PREVALENCE OF OVINE AND CAPRINE BRUCELLOSIS IN BANGLADESH
Bibliographic record
Abstract
Brucellosis is considered to be the most widespread zoonosis throughout the world. It has a serious implication on human health as well as on the economic development in a developing country like Bangladesh. The objective of the present study was to determine the seroprevalence and to delineate the risk factors for Brucella seropositivity in small ruminants in Mymensingh district of Bangladesh. In the present study, serum samples were collected from a total of 2456 small ruminants (1710 goat and 746 sheep) from 13 upazilla of Mymensingh district. The data related to age, sex and location were also collected using a questionnaire. Serum samples were screened using Rose Bengal Test (RBT) and Enzyme Linked Immunosorbent Assay (ELISA). Seroprevalence of brucellosis was 9.53% in goats and 9.92% in sheep on RBT test. In goat, the highest Brucella antibody was observed in Mymensingh sadar upazilla (13%) followed by Dhobaura upazilla (12.9%). On the other hand, highest ovine Brucella antibody observed in Haluaghat upazilla (13.04%) followed by Mymensingh sadar (12.5%). The prevalence was more in adults (55.2% in goats and 57% in sheep) than young (8.6% in goat and 8.1% in sheep) and more in female goats (41.1%) and sheep (39.2%) than male goats (14.1%) and sheep (18%). ELISA test showed 33.70% (31 out of 92 RBT positive samples) positive reaction of total RBT positive reactors. The result of this study can be useful to initiate and establish a program for controlling and prevention through test and slaughter, culling of infected animal from flock and vaccination.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".