Modelling the impact of delaying vaccination against SARS-CoV-2 assuming unlimited vaccine supply.

Q1 Mathematics
Marcos Amaku, Dimas Tadeu Covas, Francisco Antonio Bezerra Coutinho, Raymundo Soares Azevedo, Eduardo Massad
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引用次数: 23

Abstract

Background: At the moment we have more than 177 million cases and 3.8 million deaths (as of June 2021) around the world and vaccination represents the only hope to control the pandemic. Imperfections in planning vaccine acquisition and difficulties in implementing distribution among the population, however, have hampered the control of the virus so far.

Methods: We propose a new mathematical model to estimate the impact of vaccination delay against the 2019 coronavirus disease (COVID-19) on the number of cases and deaths due to the disease in Brazil. We apply the model to Brazil as a whole and to the State of Sao Paulo, the most affected by COVID-19 in Brazil. We simulated the model for the populations of the State of Sao Paulo and Brazil as a whole, varying the scenarios related to vaccine efficacy and compliance from the populations.

Results: The model projects that, in the absence of vaccination, almost 170 thousand deaths and more than 350 thousand deaths will occur by the end of 2021 for Sao Paulo and Brazil, respectively. If in contrast, Sao Paulo and Brazil had enough vaccine supply and so started a vaccination campaign in January with the maximum vaccination rate, compliance and efficacy, they could have averted more than 112 thousand deaths and 127 thousand deaths, respectively. In addition, for each month of delay the number of deaths increases monotonically in a logarithmic fashion, for both the State of Sao Paulo and Brazil as a whole.

Conclusions: Our model shows that the current delay in the vaccination schedules that is observed in many countries has serious consequences in terms of mortality by the disease and should serve as an alert to health authorities to speed the process up such that the highest number of people to be immunized is reached in the shortest period of time.

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Abstract Image

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假设疫苗供应无限,对延迟接种SARS-CoV-2疫苗的影响进行建模。
背景:目前,世界各地有超过1.77亿例病例和380万例死亡(截至2021年6月),疫苗接种是控制大流行的唯一希望。然而,疫苗获取计划的不完善和在人群中实施分配的困难迄今阻碍了对该病毒的控制。方法:我们提出了一个新的数学模型来估计2019冠状病毒病(COVID-19)疫苗接种延迟对巴西病例数和死亡人数的影响。我们将该模型应用于整个巴西,以及巴西受COVID-19影响最严重的圣保罗州。我们模拟了圣保罗州和整个巴西人口的模型,改变了与人口疫苗效力和依从性相关的情景。结果:该模型预测,在没有接种疫苗的情况下,到2021年底,圣保罗和巴西将分别有近17万人和35万人死亡。相比之下,如果圣保罗和巴西有足够的疫苗供应,并因此在1月份开展疫苗接种运动,疫苗接种率、遵守情况和效力达到最高水平,它们本可以分别避免11.2万多人死亡和12.7万多人死亡。此外,对于圣保罗州和整个巴西来说,每推迟一个月,死亡人数就以对数方式单调增加。结论:我们的模型表明,目前在许多国家观察到的疫苗接种计划的延迟对疾病死亡率造成了严重后果,应向卫生当局发出警告,加快这一进程,以便在最短的时间内达到最高数量的人接种疫苗。
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
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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