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大流行疲劳对新冠病毒传播的影响:针对意大利情况的数学建模解答

Pandemic fatigue impact on COVID-19 spread: A mathematical modelling answer to the Italian scenario.

作者信息

Meacci Luca, Primicerio Mario

机构信息

Instituto de Ciências Matemáticas e de Computação, ICMC, Universidade de São Paulo, Avenida Trabalhador Sancarlense, 400, São Carlos (SP), CEP 13566-590, Brazil.

Dipartimento di Matematica "U. Dini", Università degli Studi di Firenze, Viale Giovanni Battista Morgagni, 67/A, 50134 Firenze, Italy.

出版信息

Results Phys. 2021 Dec;31:104895. doi: 10.1016/j.rinp.2021.104895. Epub 2021 Oct 23.

DOI:10.1016/j.rinp.2021.104895
PMID:34722137
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8539631/
Abstract

The COVID-19 outbreak has generated, in addition to the dramatic sanitary consequences, severe psychological repercussions for the populations affected by the pandemic. Simultaneously, these consequences can have related effects on the spread of the virus. Pandemic fatigue occurs when stress rises beyond a threshold, leading a person to feel demotivated to follow recommended behaviours to protect themselves and others. In the present paper, we introduce a new susceptible-infected-quarantined-recovered-dead (SIQRD) model in terms of a system of ordinary differential equations (ODE). The model considers the countermeasures taken by sanitary authorities and the effect of pandemic fatigue. The latter can be mitigated by fear of the disease's consequences modelled with the death rate in mind. The mathematical well-posedness of the model is proved. We show the numerical results to be consistent with the transmission dynamics data characterising the epidemic of the COVID-19 outbreak in Italy in 2020. We provide a measure of the possible pandemic fatigue impact. The model can be used to evaluate the public health interventions and prevent with specific actions the possible damages resulting from the social phenomenon of relaxation concerning the observance of the preventive rules imposed.

摘要

新型冠状病毒肺炎(COVID-19)疫情除了造成严重的卫生后果外,还给受疫情影响的人群带来了严重的心理影响。同时,这些后果可能会对病毒传播产生相关影响。当压力超过某个阈值时,就会出现疫情疲劳,导致人们没有动力去遵循推荐的行为来保护自己和他人。在本文中,我们根据常微分方程(ODE)系统引入了一种新的易感-感染-隔离-康复-死亡(SIQRD)模型。该模型考虑了卫生当局采取的对策以及疫情疲劳的影响。后者可以通过对疾病后果的恐惧来缓解,这种恐惧是考虑到死亡率而建模的。证明了该模型的数学适定性。我们表明,数值结果与表征2020年意大利COVID-19疫情传播动态的数据一致。我们提供了一种衡量疫情疲劳可能影响的方法。该模型可用于评估公共卫生干预措施,并通过具体行动预防因放松遵守所实施预防规则的社会现象而可能造成的损害。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/551d982f115b/gr7_lrg.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/551d982f115b/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/3a1de28848f9/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/5b940b3ecbfc/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/7734d0a6486c/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/77191d265d20/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/c64316b54488/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/9d15fac7d38b/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/486f/8539631/551d982f115b/gr7_lrg.jpg

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