Based on mathematical epidemiology and evolutionary game theory, which is more effective: quarantine or isolation policy?
Based on mathematical epidemiology and evolutionary game theory, which is more effective: quarantine or isolation policy?
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DOI：
10.1088/1742-5468/ab75ea
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发表时间：
2020-03-01
影响因子：
2.4
通讯作者：
Tanimoto, Jun
中科院分区：
文献类型：
--
作者：
Alam, Muntasir;Kabir, K. M. Ariful;Tanimoto, Jun
大流行病和严重流行病的反复爆发对人的生命构成巨大威胁。本研究以疫苗接种博奕理论为基础，探讨几种强制控制策略对疾病免疫力暂时或衰退的影响。考虑到一个无限的和混合均匀的人口，我们提出的模型进一步说明了引入两个众所周知的强制控制技术，即检疫和隔离的意义，为了模拟传染病的动态，在人群中传播的先发制人的疫苗接种已部分采取流行季节开始之前。此外，我们仔细研究了这两种类型的保护措施（先发制人和强迫）使用SEIR型流行病模型的综合效果。基于进化博弈理论的深入研究，数值量化了个体接种疫苗决策的权重影响，以提高强制控制政策的有效性，从而缓解疫情传播的严重程度。一个确定性的SVEIR模型，包括接种疫苗（V）和暴露（E）的状态，提出了没有空间结构，同时实施这些干预技术。这项研究采用了一种混合控制策略，依靠检疫和隔离政策来量化疫苗的最佳需求，以彻底消除人类社会的疾病流行。此外，我们的理论研究证明了这样一个事实，即采取强制控制政策大大降低了抑制新发疾病流行所需的疫苗接种水平，并且还证实了当疫情以更高的传播率爆发时，联合政策的效果甚至更好。研究表明，隔离政策是比检疫政策更好的疾病衰减工具，特别是在疾病进展率相对较高的流行地区。然而，微小的进展率会逐渐削弱流行病爆发的速度，因此，采用适度的控制政策就足以恢复无病状态。基本上，积极措施（预防性疫苗接种）调节两个阶段之间的临界线位置，而暴露的规定（检疫或隔离）则致力于减轻疾病在流行地区的传播。因此，这两种干预技术之间的最佳相互作用在减少流行规模方面效果显著。尽管在开发新疫苗和控制战略以减轻流行病方面取得了进展，但麻疹、结核病、埃博拉和流感等许多疾病仍然持续存在。在这里，我们提出了一个动态分析的SVEIR模型，利用平均场理论开发一个简单而有效的策略，同时应用的检疫和隔离政策的基础上的流行病控制。
Outbreaks of repeated pandemics and heavy epidemics are daunting threats to human life. This study aims at investigating the dynamics of disease conferring temporary or waning immunity with several forced-control policies aided by vaccination game theory. Considering an infinite and well-mixed homogenous population, our proposed model further illustrates the significance of introducing two well-known forced control techniques, namely, quarantine and isolation, in order to model the dynamics of an infectious disease that spreads within a human population where pre-emptive vaccination has partially been taken before the epidemic season begins. Moreover, we carefully examine the combined effects of these two types (pre-emptive and forced) of protecting measures using the SEIR-type epidemic model. An in-depth investigation based on evolutionary game theory numerically quantifies the weighing impact of individuals' vaccinating decisions to improve the efficacy of forced control policies leading up to the relaxation of the epidemic spreading severity. A deterministic SVEIR model, including vaccinated (V) and exposed (E) states, is proposed having no spatial structure while implementing these intervention techniques. This study uses a mixed control strategy relying on quarantine and isolation policies to quantify the optimum requirement of vaccines for eradicating disease prevalence completely from human societies. Furthermore, our theoretical study justifies the fact that adopting forced control policies significantly reduces the required level of vaccination to suppress emerging disease prevalence, and it also confirms that the joint policy works even better when the epidemic outbreak takes place at a higher transmission rate. Research reveals that the isolation policy is a better disease attenuation tool than the quarantine policy, especially in endemic regions where the disease progression rate is relatively higher. However, a meager progression rate gradually weakens the speed of an epidemic outbreak and, therefore, applying a moderate level of control policies is sufficient to restore the disease-free state. Essentially, positive measures (pre-emptive vaccination) regulate the position of the critical line between two phases, whereas exposed provisions (quarantine or isolation) are rather dedicated to mitigating the disease spreading in endemic regions. Thus, an optimal interplay between these two types of intervention techniques works remarkably well in attenuating the epidemic size. Despite having advanced on the development of new vaccines and control strategies to mitigate epidemics, many diseases like measles, tuberculosis, Ebola, and flu are still persistent. Here, we present a dynamic analysis of the SVEIR model using mean-field theory to develop a simple but efficient strategy for epidemic control based on the simultaneous application of the quarantine and isolation policies.