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Impact of heterogeneous distribution of immunization probability on recurrent epidemic outbreaks

机译:免疫概率异质分布对复发性流行病爆发的影响

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The heterogeneous distribution of immunization probability has been proven to suppress the recurrent epidemic outbreaks effectively, but the reason for this interesting phenomenon is still unclear. To solve this problem, the effects of immunization probability on the maximal infected density and the average infected density are investigated, and it's found that large immunization probability will depress the maximal infected density sharply. Moreover, it's proved that small immunization probability is of great importance, which could not only reduce the cost of immunization at low risk but also decrease the outbreak risk of the next year by making the average infected density larger in the current year. Besides, a generalized immunization strategy is presented, which makes the immunization strategy easy to carry out and meanwhile keeps the maximal and the average infected density almost as good as those in the original dynamic immunization strategy. Moreover, the control effects in eight real networks are also investigated, which proves the usefulness of the modified dynamic immunization strategy. Our work proves the usefulness of the heterogeneous distribution of immunization probability and may present theoretical guidance for the government and the public to control the recurrent epidemic outbreaks.
机译:已证明免疫概率的异质分布是有效地抑制复发流行病爆发,但这种有趣现象的原因尚不清楚。为了解决这个问题,研究了免疫概率对最大感染密度和平均感染密度的影响,发现大的免疫概率将急剧下降最大的感染密度。此外,证明了小的免疫概率具有重要意义,这不仅可以降低风险低的免疫成本,而且通过使本年度的平均感染密度更大,降低了明年的爆发风险。此外,提出了广义免疫策略,这使得免疫策略易于进行,同时保持最大化和平均感染的密度几乎与原始动态免疫策略中那些一样好。此外,还研究了八个真实网络中的控制效应,这证明了改性动态免疫策略的有用性。我们的工作证明了免疫概率异质分布的有用性,并可能为政府和公众提供理论指导,以控制复发流行病爆发。

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