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<p>Lassa fever is an acute viral hemorrhagic disease endemic to West Africa and remains a significant threat to both public health and economic stability in the region, particularly in Nigeria. Its complex transmission dynamics, compounded by delayed behavioral responses in affected populations, have made the disease difficult to control. This study presents a novel mathematical modeling framework that integrates non-pharmaceutical interventions—specifically, quarantine measures and public enlightenment campaigns—within a fractional-order epidemic model. The model employs the Atangana–Baleanu fractional derivative in the Caputo sense and utilizes the Laplace Adomian Decomposition Method to incorporate memory and hereditary effects observed in real-world disease transmission. The analysis explores the impact of fractional-order parameters and conducts sensitivity analysis, with the basic reproduction number (<InlineEquation ID="IEq1"> <EquationSource Format="MATHML"><math> <msub> <mi>R</mi> <mn>0</mn> </msub> </math></EquationSource> <EquationSource Format="TEX">$R_{0}$</EquationSource> </InlineEquation>) derived using the next-generation matrix method. Stability analyses are also performed to evaluate the model’s robustness. By incorporating vital dynamics and behavioral feedback mechanisms, the framework provides a more realistic approach to assessing the time-dependent effects of public health strategies and population responses. Simulation results reveal that while quarantine and awareness interventions individually reduce transmission rates, their combined implementation offers the most effective strategy—significantly lowering both the basic reproduction number and peak infection levels. This study contributes to the growing field of fractional epidemic modeling by offering evidence-based insights for designing cost-effective, resource-conscious intervention strategies. The findings offer practical guidance for public health authorities, policymakers, and epidemic response teams in controlling future outbreaks of Lassa fever and similar diseases.</p>

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Modelling the impact of quarantine and public enlightenment on the dynamics of Lassa fever using numerical analysis

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  • 出版模式：

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  • 发表日期：

    2026年1月19日

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  • Adewole Mukaila Ajileye,
  • Akeem Olarewaju Yunus

摘要

Lassa fever is an acute viral hemorrhagic disease endemic to West Africa and remains a significant threat to both public health and economic stability in the region, particularly in Nigeria. Its complex transmission dynamics, compounded by delayed behavioral responses in affected populations, have made the disease difficult to control. This study presents a novel mathematical modeling framework that integrates non-pharmaceutical interventions—specifically, quarantine measures and public enlightenment campaigns—within a fractional-order epidemic model. The model employs the Atangana–Baleanu fractional derivative in the Caputo sense and utilizes the Laplace Adomian Decomposition Method to incorporate memory and hereditary effects observed in real-world disease transmission. The analysis explores the impact of fractional-order parameters and conducts sensitivity analysis, with the basic reproduction number ( R 0 $R_{0}$ ) derived using the next-generation matrix method. Stability analyses are also performed to evaluate the model’s robustness. By incorporating vital dynamics and behavioral feedback mechanisms, the framework provides a more realistic approach to assessing the time-dependent effects of public health strategies and population responses. Simulation results reveal that while quarantine and awareness interventions individually reduce transmission rates, their combined implementation offers the most effective strategy—significantly lowering both the basic reproduction number and peak infection levels. This study contributes to the growing field of fractional epidemic modeling by offering evidence-based insights for designing cost-effective, resource-conscious intervention strategies. The findings offer practical guidance for public health authorities, policymakers, and epidemic response teams in controlling future outbreaks of Lassa fever and similar diseases.