Department of Mathematics and Statistics, Washington State University, Pullman, WA, 99163, USA.
Zhengxin Yuguang Group Co. Ltd, 1 Haitang New Street, Chongqing, 400000, China.
Bull Math Biol. 2022 Aug 9;84(9):99. doi: 10.1007/s11538-022-01058-8.
COVID-19, caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a global pandemic and created unprecedented public health challenges throughout the world. Despite significant progresses in understanding the disease pathogenesis and progression, the epidemiological triad of pathogen, host, and environment remains unclear. In this paper, we develop a multiscale model to study the coupled within-host and between-host dynamics of COVID-19. The model includes multiple transmission routes (both human-to-human and environment-to-human) and connects multiple scales (both the population and individual levels). A detailed analysis on the local and global dynamics of the fast system, slow system and full system shows that rich dynamics, including both forward and backward bifurcations, emerge with the coupling of viral infection and epidemiological models. Model fitting to both virological and epidemiological data facilitates the evaluation of the influence of a few infection characteristics and antiviral treatment on the spread of the disease. Our work underlines the potential role that the environment can play in the transmission of COVID-19. Antiviral treatment of infected individuals can delay but cannot prevent the emergence of disease outbreaks. These results highlight the implementation of comprehensive intervention measures such as social distancing and wearing masks that aim to stop airborne transmission, combined with surface disinfection and hand hygiene that can prevent environmental transmission. The model also provides a multiscale modeling framework to study other infectious diseases when the environment can serve as a reservoir of pathogens.
由严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)感染引起的 COVID-19 已成为全球大流行疾病,给全世界带来了前所未有的公共卫生挑战。尽管在理解疾病发病机制和进展方面取得了重大进展,但病原体、宿主和环境的流行病学三联体仍不清楚。在本文中,我们开发了一个多尺度模型来研究 COVID-19 的宿主内和宿主间的耦合动力学。该模型包括多种传播途径(包括人与人之间和环境与人之间),并连接多个尺度(包括人口和个体水平)。对快速系统、缓慢系统和全系统的局部和全局动力学的详细分析表明,随着病毒感染和流行病学模型的耦合,丰富的动力学现象,包括前向和后向分歧,会出现。对病毒学和流行病学数据的模型拟合有助于评估少数感染特征和抗病毒治疗对疾病传播的影响。我们的工作强调了环境在 COVID-19 传播中可能发挥的作用。对感染个体进行抗病毒治疗可以延迟但不能阻止疾病爆发的出现。这些结果突出了实施全面干预措施的重要性,如社交距离和佩戴口罩,以阻止空气传播,同时结合表面消毒和手部卫生,以防止环境传播。该模型还提供了一个多尺度建模框架,可用于研究环境可以作为病原体库的其他传染病。