针对具体国家的COVID-19模型

Q3 Mathematics Epidemiologic Methods Pub Date : 2023-01-01 DOI:10.2139/ssrn.4043977
G. Meissner, Hong Sherwin
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引用次数: 0

摘要

目的动态测量各国按人口规模统一归一化的COVID-19传播率。方法在经典SIR模型的基础上,提出了一种简化的模型来随机表示繁殖数和死亡率,直接衡量病毒进化和群体行为反应函数的综合效应。结果有证据表明,这种e(高级)-SIR模型能够拟合具体国家的经验数据,产生可解释的模型参数,用于生成适应仍在发展的大流行的概率情景。区域流行病学模型中嵌入的随机过程可为监测和规划提供可测量和可操作的信息。
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A country-specific COVID-19 model
Abstract Objectives To dynamically measure COVID-19 transmissibility consistently normalized by population size in each country. Methods A reduced-form model enhanced from the classical SIR is proposed to stochastically represent the Reproduction Number and Mortality Rate, directly measuring the combined effects of viral evolution and population behavioral response functions. Results Evidences are shown that this e(hanced)-SIR model has the power to fit country-specific empirical data, produce interpretable model parameters to be used for generating probabilistic scenarios adapted to the still unfolding pandemic. Conclusions Stochastic processes embedded within compartmental epidemiological models can produce measurables and actionable information for surveillance and planning purposes.
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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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