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Enregistrement W2804183057 · doi:10.5210/ojphi.v10i1.8858

Epidemiology of Suspected Pesticide Poisoning in Livestock

2018· article· en· W2804183057 sur OpenAlexaboutno aff
Judy Akkina, Leah Estberg

Notice bibliographique

RevueOnline Journal of Public Health Informatics · 2018
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueAnimal Ecology and Behavior Studies
Établissements canadiensnon disponible
Organismes subventionnairesAmerican Society for the Prevention of Cruelty to Animals
Mots-clésLivestockMedicineEnvironmental healthPesticideEpidemiologyPoison control centerAnimal welfarePoison controlInjury preventionVeterinary medicineMedical emergencyGeographyBiologyEcologyForestryPathology

Résumé

récupéré en direct d'OpenAlex

ObjectiveThis study characterizes the epidemiology of suspected pesticide poisoning in livestock in the United States (U.S.) and Canada using data from calls to the American Society for the Prevention of Cruelty to Animals (ASPCA) Animal Poison Control Center (APCC).IntroductionPesticides are used in agriculture and in the home to control pests such as insects, weeds, fungi and rodents. Pesticide poisoning in animals is usually due to misuse or accidental exposure1. Information on poisonings in livestock in North America is largely lacking2. Examples of hotlines in the U.S. for animal poisoning consultations include the APCC ($65.00 fee) and the Pet Poison Helpline (PPH) ($59.00 fee). The APCC fields calls 24 hours/day, 7 days/week about animal poisonings from the U.S., its territories and Canada. Using data from almost 4 years of APCC calls we describe the occurrence, category and class of pesticides involved, and outcomes of suspected pesticide exposures in livestock. This information is useful to raise awareness, encourage the proper use of pesticides and identify specific pesticides with negative impact on livestock health.MethodsAPHIS contracts with the APCC to receive de-identified data weekly on livestock calls for the purpose of conducting surveillance. This retrospective study used data from all calls concerning bovine, camelid, caprine, equine, ovine, porcine and poultry species from 10/1/2013 to 9/2/2017, where the caller reported suspected pesticide exposure. There were 1,025 calls regarding 3,028 animals meeting this criteria, representing 52% of all livestock calls with any type of toxic exposure. Caller type was 80% animal owners, 10% veterinarian or veterinary staff, and 10% other types. Most callers (92%) provided their zip code, with 96% of calls from the U.S. and 4% from Canada. Variables used for descriptive analysis were: species; APCC staff assessment that illness was due to pesticide exposure; severity of illness; clinical signs; first, second and third ingredients of the pesticide, and pesticide ingredient class (e.g. pyrethrin). Pesticides were grouped based on the first active ingredient into fungicide, herbicide, insecticide, and rodenticide categories.ResultsThe proportion of calls by species was equine (33%), poultry (26%), bovine (25%), caprine (8%), porcine (6%), ovine (2%), and camelid (0.5%). Some animals were exposed to >1 pesticide product and some pesticide products had >1 ingredient class. The pesticide category with the highest number of exposed animals was insecticides (2,151), followed by herbicides (839), rodenticides (765) and fungicides (286). The treemap below illustrates the number and proportions of animals exposed to the 4 pesticide categories and the top 3 pesticide classes within each category based on the first active ingredient. For all pesticide exposures in all species, no illness was reported in 68% of animals. According to assessment by APCC staff, only 35% (333) of animals showing clinical signs were considered with confidence (medium or high likelihood) to be due to pesticide exposure. For these 333 animals, severity of illness was mild for 80% (266 animals), moderate for 18% (61 animals), major for 1% (3 animals) and caused death in 1% (3 animals). Among animals with confidence that clinical signs were due to pesticide exposure the most frequent syndrome was dermatologic.ConclusionsSuspected pesticide exposure was the most frequent reason a call concerning livestock was made to the APCC. Callers reported that most animals showed no illness, and major illness or death was rare. Livestock were most frequently exposed to the insecticide category, and 46% of the animals with exposure to insecticides were exposed to the pyrethrin class. This is consistent with the phasing out of organophosphate insecticides for residential use since 2000 and the increasing use of pyrethrin insecticides3, which are considered less toxic. Limitations of this study include: 1) data from only one major animal poison control hotline was available for analysis and people may call their veterinarian directly or use the internet 2) calls regarding specific ingredients may be over represented due to corporate client relationships with the APCC 3) illness may have occurred after the call was made, therefore the proportion of animals with illness following suspected exposure may be an underestimate.References1. Wang Y, Kruzik P, Helsber A, Helsberg I, Rausch W. (2006) Pesticide poisoning in domestic animals and livestock in Austria: A 6 year retrospective study. Forensic Science International 169:157-160.2. Gwaltney-Brant SM. (2012). Epidemiology of Animal Poisonings in the United States. In: Gupta RC (Ed.), Veterinary Toxicology: Basic and Clinical Principles. Elsevier, Second ed: 80-87.3. Power LE, Sudakin DL. Pyrethrin and pyrethroid exposures in the United States: A longitudinal analysis of incidents reported to Poison Centers. (2007) J of Medical Toxicology. 3(3):94-99.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,182
Score d'incertitude au seuil0,362

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,112
Tête enseignante GPT0,385
Écart entre enseignants0,273 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2018
Routes d'admission1
Résumé présentoui

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