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Introduction <p>Biosecurity measures are crucial for controlling infectious diseases in poultry farms. It involves all measures aiming at preventing disease-causing agents from entering the farm (external biosecurity) and those measures practiced with the aim of preventing the spread of disease-causing organisms within the farm (internal biosecurity). However, their implementation is often limited in low-income countries due to various factors such as socioeconomic challenges, farming practices and limited resources. The aim of this study was to explore the current biosecurity levels and their related factors in commercial layer chicken farms.</p> Methods <p>We conducted a cross-sectional survey of 203 randomly selected commercial layer farms with ≥ 200 birds across Dar es Salaam (<i>n</i> = 154), Morogoro (<i>n</i> = 28), and Unguja (<i>n</i> = 21) regions from March-June 2023. Biosecurity practices were scored using an adapted Biocheck.UGent™ tool (0-100 scale). One-way Analysis of Variance (ANOVA) and t-tests were used for comparing biosecurity scores across groups when data met normality assumptions, while the non-parametric Kruskal-Wallis (K-W) H test and Mann-Whitney (M-W) test served as alternatives when the normality assumption was not met. Further, we used multiple linear regression to identify factors associated with biosecurity implementation; with results reported as standardized beta coefficients (β) and 95% confidence intervals.</p> Results <p>Mean biosecurity scores were significantly (<i>p</i> &lt; .001) below global benchmarks with overall biosecurity 58.2 ± 8.6, external biosecurity (preventing disease entry) at 60.5 ± 8.7 and internal biosecurity (preventing disease spread within the farm) at 52.9 ± 14.5 compared to global averages of 72%, 67% and 77% respectively. The average external biosecurity scores was significantly lower in farms supervised by farmers with primary education (57.8 ± 7.9) than both those under farmers with secondary education (61.3 ± 9.3, <i>p</i> = .042) and tertiary education (62.1 ± 8.2, <i>p</i> = .019). Farm experience of &gt; 2 years significantly improved internal biosecurity practices (55.0 ± 14.6 vs. 47.0 ± 12.9, <i>p</i> = .002). Further, large-scale operations demonstrated superior internal biosecurity compared to small-scale farms (63.1 ± 16.4 vs. 51.5 ± 12.8, <i>p</i> = .002). Multiple regression analysis (F₇,₁₉₅=2.279, <i>p</i> = .030, R²=0.076) revealed that secondary education (β = 0.224, 95% CI: 1.03–6.73, <i>p</i> = .007) and tertiary education (β = 0.209, 95% CI: 0.82–7.20, <i>p</i> = .014) were independently associated with higher biosecurity scores compared to primary education.</p> Conclusion <p>This paper provides the first assessment of biosecurity implementation in commercial layer farms in Tanzania comparing it with global benchmarks. Biosecurity implementations were largely influenced by three key factors; education level, scale of production, and farming experience. These findings indicate that tailored interventions and evidenced-based policies are essential for strengthening biosecurity practices, and potentially enhancing poultry health and productivity in layer farms.</p>

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Biosecurity practices and their determining factors in commercial layer chickens in selected regions of Tanzania

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月6日

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  • Siha Mdemu,
  • Augustine B. Matondo,
  • Jens Peter Christensen,
  • Ahmed E. Amasha,
  • Helena A. Ngowi,
  • Erica Westwood,
  • Sunday O. Ochai,
  • Hezron E. Nonga,
  • Kristina Osbjer,
  • Robinson H. Mdegela

摘要

Introduction

Biosecurity measures are crucial for controlling infectious diseases in poultry farms. It involves all measures aiming at preventing disease-causing agents from entering the farm (external biosecurity) and those measures practiced with the aim of preventing the spread of disease-causing organisms within the farm (internal biosecurity). However, their implementation is often limited in low-income countries due to various factors such as socioeconomic challenges, farming practices and limited resources. The aim of this study was to explore the current biosecurity levels and their related factors in commercial layer chicken farms.

Methods

We conducted a cross-sectional survey of 203 randomly selected commercial layer farms with ≥ 200 birds across Dar es Salaam (n = 154), Morogoro (n = 28), and Unguja (n = 21) regions from March-June 2023. Biosecurity practices were scored using an adapted Biocheck.UGent™ tool (0-100 scale). One-way Analysis of Variance (ANOVA) and t-tests were used for comparing biosecurity scores across groups when data met normality assumptions, while the non-parametric Kruskal-Wallis (K-W) H test and Mann-Whitney (M-W) test served as alternatives when the normality assumption was not met. Further, we used multiple linear regression to identify factors associated with biosecurity implementation; with results reported as standardized beta coefficients (β) and 95% confidence intervals.

Results

Mean biosecurity scores were significantly (p < .001) below global benchmarks with overall biosecurity 58.2 ± 8.6, external biosecurity (preventing disease entry) at 60.5 ± 8.7 and internal biosecurity (preventing disease spread within the farm) at 52.9 ± 14.5 compared to global averages of 72%, 67% and 77% respectively. The average external biosecurity scores was significantly lower in farms supervised by farmers with primary education (57.8 ± 7.9) than both those under farmers with secondary education (61.3 ± 9.3, p = .042) and tertiary education (62.1 ± 8.2, p = .019). Farm experience of > 2 years significantly improved internal biosecurity practices (55.0 ± 14.6 vs. 47.0 ± 12.9, p = .002). Further, large-scale operations demonstrated superior internal biosecurity compared to small-scale farms (63.1 ± 16.4 vs. 51.5 ± 12.8, p = .002). Multiple regression analysis (F₇,₁₉₅=2.279, p = .030, R²=0.076) revealed that secondary education (β = 0.224, 95% CI: 1.03–6.73, p = .007) and tertiary education (β = 0.209, 95% CI: 0.82–7.20, p = .014) were independently associated with higher biosecurity scores compared to primary education.

Conclusion

This paper provides the first assessment of biosecurity implementation in commercial layer farms in Tanzania comparing it with global benchmarks. Biosecurity implementations were largely influenced by three key factors; education level, scale of production, and farming experience. These findings indicate that tailored interventions and evidenced-based policies are essential for strengthening biosecurity practices, and potentially enhancing poultry health and productivity in layer farms.