Mathematical modeling and investigation on the role of demography and contact patterns in social distancing measures effectiveness in COVID-19 dissemination.

IF 0.8 4区 数学 Q4 BIOLOGY
Marco A Ridenti, Lara K Teles, Alexandre Maranhão, Vladimir K Teles
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Abstract

In this article, we investigate the importance of demography and contact patterns in determining the spread of COVID-19 and to the effectiveness of social distancing policies. We investigate these questions proposing an augmented epidemiological model with an age-structured model, with the population divided into susceptible (S), exposed (E), asymptomatic infectious (A), hospitalized (H), symptomatic infectious (I) and recovered individuals (R), to simulate COVID-19 dissemination. The simulations were carried out using six combinations of four types of isolation policies (work restrictions, isolation of the elderly, community distancing and school closures) and four representative fictitious countries generated over alternative demographic transition stage patterns (aged developed, developed, developing and least developed countries). We concluded that the basic reproduction number depends on the age profile and the contact patterns. The aged developed country had the lowest basic reproduction number ($R0=1.74$) due to the low contact rate among individuals, followed by the least developed country ($R0=2.00$), the developing country ($R0=2.43$) and the developed country ($R0=2.64$). Because of these differences in the basic reproduction numbers, the same intervention policies had higher efficiencies in the aged and least developed countries. Of all intervention policies, the reduction in work contacts and community distancing were the ones that produced the highest decrease in the $R0$ value, prevalence, maximum hospitalization demand and fatality rate. The isolation of the elderly was more effective in the developed and aged developed countries. The school closure was the less effective intervention policy, though its effects were not negligible in the least developed and developing countries.

人口和接触方式对社会距离措施在COVID-19传播中的作用的数学建模和调查。
在本文中,我们研究了人口统计学和接触模式在确定COVID-19传播和社会距离政策有效性方面的重要性。为了研究这些问题,我们提出了一个年龄结构模型的增强流行病学模型,将人群分为易感人群(S)、暴露人群(E)、无症状感染者(A)、住院患者(H)、有症状感染者(I)和康复个体(R),以模拟COVID-19的传播。模拟采用四种隔离政策(工作限制、隔离老年人、保持社区距离和关闭学校)的六种组合,以及根据不同的人口过渡阶段模式(老龄发达国家、发达国家、发展中国家和最不发达国家)产生的四个具有代表性的虚构国家。我们的结论是,基本繁殖数取决于年龄分布和接触方式。高龄发达国家由于个体间接触率低,基本繁殖数最低($R0=1.74$),其次是最不发达国家($R0=2.00$)、发展中国家($R0=2.43$)和发达国家($R0=2.64$)。由于基本再生产数字的这些差异,同样的干预政策在老龄国家和最不发达国家效率更高。在所有干预政策中,减少工作接触和社区距离是在R0$值、患病率、最大住院需求和死亡率方面产生最大降幅的政策。老年人隔离在发达国家和老龄发达国家更为有效。关闭学校是效果较差的干预政策,尽管其影响在最不发达国家和发展中国家不可忽视。
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
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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