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Social Models and Algorithms for Optimization of Contact Immunity of Oral Polio Vaccine

机译:口服脊髓灰质炎疫苗接触免疫性优化的社会模型和算法

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Oral polio vaccine (OPV) can produce contact immunity and help protect more individuals than the vaccinated from polio. To better capture the utilization of OPV's contact immunity, we model the community as a social network, and formulate the task of maximizing the contact immunity effect as an optimization problem on graphs, which is to find a sequence of vertices to be "vaccinated" to maximize the total number of "infected" vertices. Furthermore, we consider the restriction imported by immune deficient individuals, and study related problems. We present polynomial-time algorithms for these problems on trees, and show the intractability of problems on general graphs.
机译:口服脊髓灰质炎疫苗(OPV)可以产生接触性免疫力,并有助于保护比接种脊髓灰质炎疫苗的人更多的人。为了更好地利用OPV的接触免疫功能,我们将社区建模为一个社交网络,并制定了最大化接触免疫效果的任务,作为图上的优化问题,即找到要“接种”的顶点序列。最大化“感染”顶点的总数。此外,我们考虑了免疫缺陷个体引入的限制,并研究了相关问题。我们提出了针对树上这些问题的多项式时间算法,并在一般图形上显示了问题的难处理性。

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