Investigating the impact of vaccine hesitancy on an emerging infectious disease: a mathematical and numerical analysis.

IF 1.8 4区数学 Q3 ECOLOGY Journal of Biological Dynamics Pub Date : 2024-12-01 Epub Date: 2024-01-04 DOI:10.1080/17513758.2023.2298988

Indunil M Hewage, Kevin E M Church, Elissa J Schwartz

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Abstract

Throughout the last two centuries, vaccines have been helpful in mitigating numerous epidemic diseases. However, vaccine hesitancy has been identified as a substantial obstacle in healthcare management. We examined the epidemiological dynamics of an emerging infection under vaccination using an SVEIR model with differential morbidity. We mathematically analyzed the model, derived $R_{0}$ , and provided a complete analysis of the bifurcation at $R_{0} = 1$ . Sensitivity analysis and numerical simulations were used to quantify the tradeoffs between vaccine efficacy and vaccine hesitancy on reducing the disease burden. Our results indicated that if the percentage of the population hesitant about taking the vaccine is 10%, then a vaccine with 94% efficacy is required to reduce the peak of infections by 40%. If 60% of the population is reluctant about being vaccinated, then even a perfect vaccine will not be able to reduce the peak of infections by 40%.

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调查疫苗犹豫不决对新发传染病的影响：数学和数值分析。

在过去的两个世纪中，疫苗在缓解众多流行病方面发挥了重要作用。然而，疫苗犹豫不决已被认为是医疗保健管理中的一大障碍。我们使用具有不同发病率的 SVEIR 模型研究了疫苗接种下新发传染病的流行动态。我们对模型进行了数学分析，得出了 R0，并对 R0=1 时的分岔进行了完整分析。我们利用敏感性分析和数值模拟来量化疫苗效力和疫苗犹豫不决对减少疾病负担的权衡。我们的结果表明，如果对接种疫苗犹豫不决的人口比例为 10%，那么需要 94% 效力的疫苗才能将感染峰值降低 40%。如果 60% 的人口不愿意接种疫苗，那么即使是完美的疫苗也无法将感染高峰降低 40%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY

CiteScore

4.90

自引率

3.60%

发文量

审稿时长

33 weeks

期刊介绍： Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.