没有保证免疫力的流行病动态。

IF 1.2 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Journal of Mathematics in Industry Pub Date : 2021-01-01 Epub Date: 2021-02-22 DOI:10.1186/s13362-021-00101-y
Kurt Langfeld
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引用次数: 0

摘要

严重急性呼吸系统综合症冠状病毒 2(SARS-CoV-2)的大流行提出了一种新型疾病传播动力学。我们在此研究的是受感染的病原体只有在持续感染一段时间 τ 后才能恢复并产生免疫力的情况。因此,基本场论的阶段描述了疾病的动态特征:(i) 大流行阶段和 (ii) 反应机制。统计场理论提供了受感染病原体峰值率的上限。有效的控制策略需要将疾病控制在反应机制中(没有 "第二波")。我们利用一个理想化的疾病网络对该模型进行了定量测试。该模型出色地描述了 SARS-CoV-2 在中国武汉市的流行传播情况。我们发现,只有 30% 的康复者产生了免疫力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Dynamics of epidemic diseases without guaranteed immunity.

Dynamics of epidemic diseases without guaranteed immunity.

Dynamics of epidemic diseases without guaranteed immunity.

Dynamics of epidemic diseases without guaranteed immunity.

The pandemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) suggests a novel type of disease spread dynamics. We here study the case where infected agents recover and only develop immunity if they are continuously infected for some time τ. For large τ, the disease model is described by a statistical field theory. Hence, the phases of the underlying field theory characterise the disease dynamics: (i) a pandemic phase and (ii) a response regime. The statistical field theory provides an upper bound of the peak rate of infected agents. An effective control strategy needs to aim to keep the disease in the response regime (no 'second' wave). The model is tested at the quantitative level using an idealised disease network. The model excellently describes the epidemic spread of the SARS-CoV-2 outbreak in the city of Wuhan, China. We find that only 30% of the recovered agents have developed immunity.

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来源期刊
Journal of Mathematics in Industry
Journal of Mathematics in Industry MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
5.00
自引率
0.00%
发文量
12
审稿时长
13 weeks
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