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新型冠状病毒(SARS-CoV-2)与喀麦隆的自我药疗:一个数学模型。

SARS-CoV-2 and self-medication in Cameroon: a mathematical model.

机构信息

Department of Mathematics and Statistics, York University, Toronto, ON Canada.

Canadian Center for Diseases Modeling (CDM), York University, Toronto, ON Canada.

出版信息

J Biol Dyn. 2021 Dec;15(1):137-150. doi: 10.1080/17513758.2021.1883130.

Abstract

Self-medication is an important initial response to illness in Africa. This mode of medication is often done with the help of African traditional medicines. Because of the misconception that African traditional medicines can cure/prevent all diseases, some Africans may opt for COVID-19 prevention and management by self-medicating. Thus to efficiently predict the dynamics of COVID-19 in Africa, the role of the self-medicated population needs to be taken into account. In this paper, we formulate and analyse a mathematical model for the dynamics of COVID-19 in Cameroon. The model is represented by a system of compartmental age-structured ODEs that takes into account the self-medicated population and subdivides the human population into two age classes relative to their current immune system strength. We use our model to propose policy measures that could be implemented in the course of an epidemic in order to better handle cases of self-medication.

摘要

自我医疗是非洲对疾病的重要初始反应。这种用药方式通常在非洲传统药物的帮助下进行。由于存在非洲传统药物可以治愈/预防所有疾病的误解,一些非洲人可能会选择自我用药来预防和管理 COVID-19。因此,为了有效地预测非洲 COVID-19 的动态,需要考虑自我用药人群的作用。在本文中,我们为喀麦隆 COVID-19 的动态制定和分析了一个数学模型。该模型由一个带有年龄结构的 ODE 系统表示,考虑了自我用药人群,并根据其当前的免疫系统强度将人口分为两个年龄组。我们使用我们的模型提出了可以在疫情期间实施的政策措施,以便更好地处理自我用药的情况。

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