Transmission rates and environmental reservoirs for COVID-19 - a modeling study.

IF 1.8 4区 数学 Q3 ECOLOGY
Chayu Yang, Jin Wang
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引用次数: 0

Abstract

The coronavirus disease 2019 (COVID-19) remains a global pandemic at present. Although the human-to-human transmission route for this disease has been well established, its transmission mechanism is not fully understood. In this paper, we propose a mathematical model for COVID-19 which incorporates multiple transmission pathways and which employs time-dependent transmission rates reflecting the impact of disease prevalence and outbreak control. Applying this model to a retrospective study based on publicly reported data in China, we argue that the environmental reservoirs play an important role in the transmission and spread of the coronavirus. This argument is supported by our data fitting and numerical simulation results for the city of Wuhan, for the provinces of Hubei and Guangdong, and for the entire country of China.

Abstract Image

COVID-19 的传播率和环境库--一项模型研究。
目前,2019 年冠状病毒病(COVID-19)仍是一种全球性流行病。虽然该疾病的人际传播途径已经确定,但其传播机制尚未完全明了。本文提出了 COVID-19 的数学模型,该模型包含多种传播途径,并采用了随时间变化的传播率,反映了疾病流行和疫情控制的影响。将该模型应用于一项基于中国公开报道数据的回顾性研究,我们认为环境储库在冠状病毒的传播和扩散中发挥了重要作用。我们对武汉市、湖北省和广东省以及整个中国的数据拟合和数值模拟结果都支持这一论点。
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
Journal of Biological Dynamics ECOLOGY-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.90
自引率
3.60%
发文量
28
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.
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