登革热在不同人群中的传播分析

Q3 Mathematics Epidemiologic Methods Pub Date : 2021-01-01 DOI:10.1515/em-2020-0046
A. Dwivedi, Ram Keval
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引用次数: 5

摘要

摘要目的:媒介传播疾病在人群中传播迅速。控制技术必须应用于这种疾病,并迅速发挥作用。我们通过纳入易感媒介和受感染人之间的标准发病率关系,提出了登革热的区室模型,以观察模型的可管理参数对基本繁殖数的影响。方法:采用下一代矩阵法计算基本繁殖数,研究无病平衡点和地方病平衡点的局部稳定性和全局稳定性,并对模型进行敏感性分析。结果:研究了任意初始条件下无病/地方病状态的全局行为主义。与其他参数相比,媒介生物种群的叮咬率对基本繁殖数的影响更大。结论:控制该病的传播途径是控制该病传播潜力的重要途径。
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Analysis for transmission of dengue disease with different class of human population
Abstract Objectives: Vector-borne diseases speedily infest the human population. The control techniques must be applied to such ailment and work swiftly. We proposed a compartmental model of dengue disease by incorporating the standard incidence relation between susceptible vectors and infected humans to see the effect of manageable parameters of the model on the basic reproduction number. Methods: We compute the basic reproduction number by using the next -generation matrix method to study the local and global stability of disease free and endemic equilibrium points along with sensitivity analysis of the model. Results: Numerical results are explored the global behaviourism of disease-free/endemic state for a choice of arbitrary initial conditions. Also, the biting rate of vector population has more influence on the basic reproduction number as compared the other parameters. Conclusion: In this paper, shows that controlling the route of transmission of this disease is very important if we plan to restrict the transmission potential.
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来源期刊
Epidemiologic Methods
Epidemiologic Methods Mathematics-Applied Mathematics
CiteScore
2.10
自引率
0.00%
发文量
7
期刊介绍: Epidemiologic Methods (EM) seeks contributions comparable to those of the leading epidemiologic journals, but also invites papers that may be more technical or of greater length than what has traditionally been allowed by journals in epidemiology. Applications and examples with real data to illustrate methodology are strongly encouraged but not required. Topics. genetic epidemiology, infectious disease, pharmaco-epidemiology, ecologic studies, environmental exposures, screening, surveillance, social networks, comparative effectiveness, statistical modeling, causal inference, measurement error, study design, meta-analysis
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