Epidemiologic analysis of Leptospira spp. infection among sheep in Pernambuco state, Brazil

Abstract

This study aimed to analyze epidemiological aspects and spatial characteristics of Lesptospira spp. infection among sheep in Pernambuco state, Brazil. A total of 426 samples were collected from unvaccinated animals aged 1 year or older, and submitted to Microscopic Agglutination Test (MAT). To study the risk factors, a standardized investigative survey of sheep farmers, with objective questions, was conducted to establish the general characteristics of the farm property production, reproductive management, and health plan. From 426 samples analyzed, 83 (19.5%; CI 15.9 - 23.6%) were positive; among them, the most prevalent serovar was Autumnalis (32.4%). Significant differences were observed between gender (OR = 0.38; CI 0.14 - 0.99), production system (OR = 2.03; CI 1.07 - 3.84), types of herd (OR = 2.28; CI 1.39 - 3.72), absence of rodents to the grain storage (OR = 0.55; CI 0.34 - 0.91), and restriction to surface waters (OR = 0.60; CI 0.37 - 0.99). Leptospira spp. infection is disseminated in sheep herds, and multiple factors can influence its occurrence. Health education programs and worker training in prevention and control of leptospirosis and other infectious diseases may be useful to reduce infection rates and economic losses caused by this disease.

Seroprevalence and predominant serogroups of Leptospira sp. in serological tests of ruminants in northeastern Brazil

“…The Autumnalis serogroup was the most frequent in goats and sheep, a result that corroborates the findings of serological surveys conducted in Paraíba, Minas Gerais and Pernambuco in previous years (HIGINO et al, 2010;ALVES et al, 2012;SALABERRY et al, 2011;COSTA et al, 2016;MACHADO et al, 2016), suggesting that this serogroup may be adapted to small ruminants. The serogroup Seramanga was the second most frequent in goats.…”

“…The frequencies for goats and sheep were 8.3% and 7.9%, respectively. Studies conducted by Tagliabue et al (2016) in Italy, and Suwancharoen et al (2013) in Thailand, reported frequencies similar to the present study (4.7% for sheep and 7.9% for goats), while other authors reported higher results in the same species, such as Aguiar et al (2010), who reported 33.3% positivity in sheep in Rondônia; Salaberry et al (2011), who reported 22.2% positivity in sheep in Minas Gerais; Martins and Lilenbaum (2013), who reported 47.4% positivity in sheep and 14.95% in goats in Rio de Janeiro; Cortizo et al (2015), who reported 50% positivity in both species in Espírito Santo; and Machado et al (2016), who reported 19.5% positivity in sheep in Pernambuco. The discrepancy among results is probably due to the characteristic environmental conditions of each region studied, and the management and control measures adopted for the herds MACHADO et al, 2016).…”

EVIDENCE OF ANTIBODIES AGAINST DIFFERENT Leptospira spp. SEROGROUPS AND FACTORS ASSOCIATED WITH ITS PRESENCE IN SHEEP FROM VERACRUZ, MEXICO

“…Serovar Hardjo had the highest prevalence with 45.9% (95%CI: 41.02-50.92), while serovar Grippotyphosa had the lowest one with 0.2% (95%CI: 0.01-1.59) (Table 2). Machado et al (2016) argued that sheep show evidence of being positive to a small number of serogroups. Twelve serogroups were used for this study but, except for serovar Pomona, seropositive animals were found to all the used serogroups.…”

Leptospira spp. in sheep of the state of Maranhao, Brazil: frequency, risk factors and foci mapping

“…Studies carried out in several Brazilian states demonstrated how prevalent this disease is in herds and animals. It was observed that in the case of Sao Paulo, 100% (FAVERO et al, 2002) and 51% (GENOVEZ et al, 2011), in Rio Grande do Sul 34% (HERRMANN et al, 2004) MACHADO et al, 2016) and in Maranhao in cattle Paixão et al (2016) found 100% of bovine reagents.…”

“…It is important to highlight the relevance of the spatial study as an alternative for the creation of control strategies and epidemiological surveillance of leptospirosis. This procedure can be performed with the use of specific software that allows the visualization, exploration, and modeling of geo-referenced data (MACHADO et al, 2016).…”