National Center for Biotechnology Information, NIH, Bethesda, MD, 20894, USA.
F1000Res. 2021 Apr 23;10:315. doi: 10.12688/f1000research.52341.2. eCollection 2021.
The start of 2021 was marked by the initiation of a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic. A deterministic model of epidemic evolution is analyzed, with seven compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections. When an escape variant is only modestly less infectious than the originating strain within a naïve population, the cumulative number of infections does not monotonically decrease with the rate of vaccine distribution. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host-host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20%. Mathematical modeling shows that limiting post-vaccination contacts can perceptibly affect the course of an epidemic. The consideration of limitations on post-vaccination contacts remains relevant for the entire duration of any vaccination campaign including the current status of SARS-CoV-2 vaccination.
2021 年初标志着针对新型冠状病毒 SARS-CoV-2 的全球疫苗接种运动的开始。在社会和经济限制下制定最佳分配策略具有挑战性。最佳分配还受到疫苗耐药性出现的限制。类似于慢性低剂量抗生素暴露，尚未免疫的最近接种的个体在耐药性的出现中起着不成比例的作用。经典的流行病学模型非常适合探索接种人群的行为如何影响整个流行期间感染的总人数。分析了传染病演变的确定性模型，该模型由与疫苗耐药突变体出现的关系定义的七个隔室组成，代表三个易感人群、三个感染人群和一个恢复人群。这种计算强度最小的设计能够模拟广泛参数空间中的流行病。结果用于确定使累积感染人数最小化的条件。当逃逸变异在原始种群中比原始菌株的传染性略低时，累积感染人数不会随疫苗分配率单调下降。对模型的分析还表明，接种个体在减轻或加剧疫苗耐药性爆发方面起着重要作用。接种人群中宿主-宿主接触率的调制幅度小于一个数量级，就可以改变累积感染人数 20%以上。数学模型表明，限制接种后接触可以明显影响传染病的进程。考虑到接种后的接触限制，包括当前 SARS-CoV-2 疫苗接种的现状，在任何疫苗接种运动的整个持续时间内仍然具有相关性。
