Risk Factors for Brucella Seroprevalence in Peri-Urban Dairy Farms in Five Indian Cities
Notice bibliographique
Résumé
Brucellosis is endemic among dairy animals in India, contributing to production losses and posing a health risk to people, especially farmers and others in close contact with dairy animals or their products. Growing urban populations demand increased milk supplies, resulting in intensifying dairy production at the peri-urban fringe. Peri-urban dairying is under-studied but has implications for disease transmission, both positive and negative. In this cross-sectional study, five Indian cities were selected to represent different geographies and urbanization extent. Around each, we randomly selected 34 peri-urban villages, and in each village three smallholder dairy farms (defined as having a maximum of 10 dairy animals) were randomly selected. The farmers were interviewed, and milk samples were taken from up to three animals. These were tested using a commercial ELISA for antibodies against Brucella abortus, and factors associated with herd seroprevalence were identified. In all, 164 out of 1163 cows (14.1%, 95% CI 12.2–16.2%) were seropositive for Brucella. In total, 91 out of 510 farms (17.8%, 95% CI 14.6–21.4%) had at least one positive animal, and out of these, just seven farmers stated that they had vaccinated against brucellosis. In four cities, the farm-level seroprevalence ranged between 1.4–5.2%, while the fifth city had a seroprevalence of 72.5%. This city had larger, zero-grazing herds, used artificial insemination to a much higher degree, replaced their animals by purchasing from their neighbors, were less likely to contact a veterinarian in case of sick animals, and were also judged to be less clean. Within the high-prevalence city, farms were at higher risk of being infected if they had a young owner and if they were judged less clean. In the low-prevalence cities, no risk factors could be identified. In conclusion, this study has identified that a city can have a high burden of infected animals in the peri-urban areas, but that seroprevalence is strongly influenced by the husbandry system. Increased intensification can be associated with increased risk, and thus the practices associated with this, such as artificial insemination, are also associated with increased risk. These results may be important to identify high-risk areas for prioritizing interventions and for policy decisions influencing the structure and development of the dairy industry.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».