Epidemiological Insights into Maedi-Visna Virus in Algeria: First National Seroprevalence Survey and Risk Factor Profiling in Sheep Herds - Takfarinas Idres; Nasir Adam Ibrahim; Ali Lamara; Sofiane Boudjellaba; Assia Derguini; Nosiba Sulaiman Basher; Soraya Temim; Mohammed Saad Aleissa; Yahia Chebloune (Animals)
Maedi-visna virus (MVV), a small ruminant lentivirus causing chronic multisystemic disease in sheep, poses significant economic burdens due to reduced productivity and a lack of effective treatments. Despite its worldwide prevalence, epidemiological data from Algeria remain absent. This first national seroprevalence study aimed to elucidate MVV distribution, risk factors, and transmission dynamics in Algerian sheep herds. A cross-sectional survey of 1400 sheep across four regions (East, Center, West, South) was conducted, with sera analyzed via indirect ELISA (IDvet). Risk factors (geography, age, sex, breed, farming system) were evaluated using chi-square tests and Cramer’s V. Overall seroprevalence was 9.07% (95% CI: 7.57–10.57), with significant variation by sex (females: 20.44% vs. males: 3.68%; p < 0.05), age (1–5 years: 6.86% vs. <1 year: 0.29%; p = 0.01), and region (Central: 3.36% vs. Eastern: 0.86%; p < 0.05). Notably, no association was found with breed or farming system (p ≥ 0.08), contrasting prior studies and suggesting region-specific transmission dynamics. Females exhibited heightened seropositivity, implicating prolonged herd retention and vertical transmission risks. Geographic disparities highlighted industrialized farming in central Algeria as a potential transmission amplifier. Strikingly, seronegative animals in high-prevalence herds hinted at genetic resistance, warranting further investigation. This study provides foundational insights into MVV epidemiology in North Africa, underscoring the need for targeted surveillance, ewe-focused control measures, and genetic research to mitigate transmission. The absence of prior national data elevates its significance, offering actionable frameworks for resource-limited settings and enriching the global understanding of SRLV heterogeneity.