Reyes-Silveyra Jorge, Mikler Armin R
Center for Computational Epidemiology and Response Analysis, University of North Texas, 1155 Union Circle 311277, Denton, 76203, TX, USA.
Department of Computer Science and Computer Engineering, Pacific Lutheran University, 1010 S 122nd St, Tacoma, 98447, WA, USA.
Theor Biol Med Model. 2016 Mar 5;13:10. doi: 10.1186/s12976-016-0033-6.
In recent epidemiological models, immunity is incorporated as a simplified value that determines the capacity of an individual to become infected or to transmit the disease. Moreover, the quality of the immune response determines the chances of infection and the length of time an individual is capable to infect others. We present a model that incorporates individuals' immune responses to, further, examine the role of the collective immune response of individuals in a population during an infectious outbreak.
We constructed a contagion model that incorporates the collective immune response of individuals represented by the superposition of individual immune responses (PIR). Multiple probability distributions are used to represent the immunocompetence of different age groups, thereby modeling the concept of Population Immune Response (PIR). Multiple experiments were conducted in which the population is divided in different age groups for which each group has a unique immune response quality and thus a different length for its immune periods. Finally, we explored the effects of implementing different vaccination strategies in the population.
The experiments displayed important variations in the outbreak dynamics as a consequence of incorporating PIR in homogeneous and mixed populations. The experiments showed that individuals with weak immune responses and those who are immune to the pathogen play a significant role in shaping the outbreak dynamics. Finally, after implementing different vaccination strategies, the results suggest that if vaccination resources are limited, the vaccination should be targeted towards individuals that spread the disease for a longer period of time.
Our results suggest that it is essential for the public health establishment to increase their understanding of the characteristics of regional demographics that could impact the quality of the immune response of the individuals. The results indicate that it is necessary to further investigate mitigation strategies to limit the capacity to transmit the disease by individuals that spread the pathogen for extended periods of time. Ultimately, this study suggests that it is crucial for public health researchers to identify appropriate targeted vaccination regimes and to explore the link between PIR and outbreak dynamics to improve the monitoring and mitigating efforts of ongoing and future epidemics.
在最近的流行病学模型中，免疫力被视为一个简化值，它决定个体被感染或传播疾病的能力。此外，免疫反应的质量决定感染几率以及个体能够感染他人的时长。我们提出一个纳入个体免疫反应的模型，以进一步研究在传染病爆发期间人群中个体集体免疫反应的作用。
我们构建了一个传染模型，该模型纳入了由个体免疫反应叠加表示的个体集体免疫反应（PIR）。使用多种概率分布来表示不同年龄组的免疫能力，从而对群体免疫反应（PIR）的概念进行建模。进行了多个实验，将人群分为不同年龄组，每个组具有独特的免疫反应质量，因此其免疫期长度也不同。最后，我们探讨了在人群中实施不同疫苗接种策略的效果。
由于在同质和混合人群中纳入了PIR，实验显示爆发动态存在重要差异。实验表明，免疫反应较弱的个体以及对病原体免疫的个体在塑造爆发动态方面发挥着重要作用。最后，在实施不同疫苗接种策略后，结果表明如果疫苗接种资源有限，疫苗接种应针对传播疾病时间较长的个体。
我们的结果表明，公共卫生机构必须加深对可能影响个体免疫反应质量的区域人口统计学特征的理解。结果表明，有必要进一步研究缓解策略，以限制长时间传播病原体的个体传播疾病的能力。最终，本研究表明，公共卫生研究人员确定合适的靶向疫苗接种方案并探索PIR与爆发动态之间的联系，对于改进当前和未来疫情的监测和缓解工作至关重要。
