模拟世界不同地区COVID-19大流行的发病率和死亡率

Q3 Mathematics
R. P. de Oliveira, J. Achcar, A. Nunes
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引用次数: 9

摘要

本文报道了一项利用新型冠状病毒(SARS-CoV-2)引起的COVID-19疾病流行病学相关计数数据的广泛研究。所考虑的数据集是指119个国家在固定时期内每天报告的病例数和死亡人数。在数据分析方面,采用了贝塔回归模型,假设世界不同区域有可能发现影响不同国家流行病行为的重要经济、卫生和社会因素。采用贝叶斯方法对模型进行拟合。这项研究得出了一些有趣的结论,面对即将到来的全球大流行的艰难时期,流行病学家、卫生当局和公众可能会对此非常感兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling the incidence and death rates of COVID-19 pandemic in different regions of the world
Abstract This paper reports a broad study using epidemic-related counting data of COVID-19 disease caused by the novel coronavirus (SARS-CoV-2). The considered dataset refers to 119 countries’ daily counts of reported cases and deaths in a fixed period. For the data analysis, it has been adopted a beta regression model assuming different regions of the world where it was possible to discover important economic, health and social factors affecting the behavior of the pandemic in different countries. The Bayesian method was applied to fit the proposed model. Some interesting conclusions were obtained in this study, which could be of great interest to epidemiologists, health authorities, and the general public in the face of the forthcoming hard times of the global pandemic.
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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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