Could a New COVID-19 Mutant Strain Undermine Vaccination Efforts? A Mathematical Modelling Approach for Estimating the Spread of B.1.1.7 Using Ontario, Canada, as a Case Study.
Could a New COVID-19 Mutant Strain Undermine Vaccination Efforts? A Mathematical Modelling Approach for Estimating the Spread of B.1.1.7 Using Ontario, Canada, as a Case Study.
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DOI：
10.3390/vaccines9060592
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发表时间：
2021-06-03
期刊：
影响因子：
7.8
通讯作者：
Raad A
中科院分区：
文献类型：
--
作者：
Betti M;Bragazzi N;Heffernan J;Kong J;Raad A
感染代表高度动态的过程，其特征是涉及病原体和宿主的进化变化和事件。在传染性病原体中，病毒，如严重急性呼吸综合征相关的冠状病毒2型（SARS-CoV-2），即导致目前正在进行的2019年冠状病毒病（COVID-2019）大流行的传染性病原体，具有特别高的突变率。考虑到感染因子的突变景观，重要的是要阐明其随时间的演变能力。随着新的更具传染性的COVID-19菌株在世界各地出现，必须估计这些新菌株何时可能在不同人群中超过野生型菌株。因此，我们开发了一个通用框架来估计在新出现的传染病爆发期间突变变体能够接管野生型菌株的时间。在本研究中，我们使用COVID-19作为案例研究;然而，该模型适用于任何新出现的病原体。我们设计了一个两株的数学框架来模拟野生型和突变型病毒种群，并以安大略为例，将累积病例数据拟合为模型参数。我们发现，在报告不足和当前病例水平的背景下，变异株不太可能在2021年3月/4月之前占主导地位。安大略目前的非药物干预措施需要保持更长的时间，即使有疫苗接种，以防止再次爆发。变异毒株在安大略的传播可能会通过每日报告病例的峰值扩大来观察。如果疫苗在不同毒株之间都能保持有效性，那么到2021年底，在人群中实现高水平免疫仍是可能的。我们的研究结果在公共卫生方面具有重要的实际意义，因为政策制定者和决策者配备了数学工具，可以估计新出现的传染病突变株的接管情况。
Infections represent highly dynamic processes, characterized by evolutionary changes and events that involve both the pathogen and the host. Among infectious agents, viruses, such as Severe Acute Respiratory Syndrome-related Coronavirus type 2 (SARS-CoV-2), the infectious agent responsible for the currently ongoing Coronavirus disease 2019 (COVID-2019) pandemic, have a particularly high mutation rate. Taking into account the mutational landscape of an infectious agent, it is important to shed light on its evolution capability over time. As new, more infectious strains of COVID-19 emerge around the world, it is imperative to estimate when these new strains may overtake the wild-type strain in different populations. Therefore, we developed a general-purpose framework to estimate the time at which a mutant variant is able to take over a wild-type strain during an emerging infectious disease outbreak. In this study, we used COVID-19 as a case-study; however, the model is adaptable to any emerging pathogen. We devised a two-strain mathematical framework to model a wild- and a mutant-type viral population and fit cumulative case data to parameterize the model, using Ontario as a case study. We found that, in the context of under-reporting and the current case levels, a variant strain was unlikely to dominate until March/April 2021. The current non-pharmaceutical interventions in Ontario need to be kept in place longer even with vaccination in order to prevent another outbreak. The spread of a variant strain in Ontario will likely be observed by a widened peak of the daily reported cases. If vaccine efficacy is maintained across strains, then it is still possible to achieve high levels of immunity in the population by the end of 2021. Our findings have important practical implications in terms of public health as policy- and decision-makers are equipped with a mathematical tool that can enable the estimation of the take-over of a mutant strain of an emerging infectious disease.
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DOI：
10.1126/science.aaa4339
发表时间：
2015-03-13
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Heesterbeek H;Anderson RM;Andreasen V;Bansal S;De Angelis D;Dye C;Eames KT;Edmunds WJ;Frost SD;Funk S;Hollingsworth TD;House T;Isham V;Klepac P;Lessler J;Lloyd-Smith JO;Metcalf CJ;Mollison D;Pellis L;Pulliam JR;Roberts MG;Viboud C;Isaac Newton Institute IDD Collaboration
通讯作者：
Isaac Newton Institute IDD Collaboration
影响因子：
64.8
作者：
Burch, CL;Chao, L
通讯作者：
Chao, L
影响因子：
6.7
作者：
Martins NE;Faria VG;Teixeira L;Magalhães S;Sucena É
通讯作者：
Sucena É
影响因子：
3.2
作者：
Arenas, Miguel;Araujo, Natalia M.;Perez-Losada, Marcos
通讯作者：
Perez-Losada, Marcos
影响因子：
64.5
作者：
Korber, Bette;Fischer, Will M.;Montefiori, David C.
通讯作者：
Montefiori, David C.