Risk factors for Cryptosporidium infection in small ruminants in northern Greece

Copyright © 2022 Elsevier B.V. All rights reserved..

The knowledge of risk factors for Cryptosporidium spp. infection in small ruminants is based on limited data. Therefore, the current research aimed to describe the prevalence and risk factors associated with the occurrence of Cryptosporidium infection in sheep and goat herds in northern Greece. Hence, 530 fresh fecal samples from 59 sheep and goat farms were collected and examined for Cryptosporidium oocysts using microscopy of fecal smears stained by the modified Ziehl-Neelsen technique. The overall prevalence of Cryptosporidium infection for both host species was 34% (180/530; 95% confidence interval (CI): 29.9-38). Specifically, the prevalence for sheep and goats was 33.5% (112/334; 95% CI: 28.4-35.6) and 34.7% (68/196; 95% CI: 28-41.4), respectively. Additionally, standardized questionnaires were filled-in to collect data regarding animals' health status, feeding, and other management practices in each farm. In total 22 risk factors hypothesized to be associated with Cryptosporidium infection were investigated. Multiple logistic regression analysis showed that farms with stagnant water were 11.78 (95% CI: 66-61.5) times more likely to be infected with Cryptosporidium than farms without stagnant water (p < 0.05). Furthermore, farms with more than 25% of their animals suffering from diarrhea were 17.39 (95% CI: 3.43-88.3) times more likely to be infected with Cryptosporidium than farms with ≤ 25% of the animals having diarrhea (p < 0.05). These results suggest that the animal health status and the prevailing environmental conditions play an important role in transmitting Cryptosporidium spp. infection.

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:309

Enthalten in:

Veterinary parasitology - 309(2022) vom: 16. Sept., Seite 109769

Sprache:

Englisch

Beteiligte Personen:

Papanikolopoulou, Vasiliki [VerfasserIn]
Lafi, Shwakat Q [VerfasserIn]
Papadopoulos, Elias [VerfasserIn]
Diakou, Anastasia [VerfasserIn]
Xiao, Lihua [VerfasserIn]
Giadinis, Nektarios D [VerfasserIn]

Links:

Volltext

Themen:

059QF0KO0R
Cryptosporidium
Journal Article
Livestock
Logistic regression
Prevalence
Water

Anmerkungen:

Date Completed 23.08.2022

Date Revised 23.08.2022

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.vetpar.2022.109769

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM344270742