Skene Katherine J, Paltiel A David, Shim Eunha, Galvani Alison P
Department of Epidemiology & Public Health, Yale University School of Medicine, New Haven, CT (KJS, ADP, APG).
Department of Mathematics, College of Engineering and Natural Sciences, University of Tulsa, Tulsa, OK (ES)
Med Decis Making. 2014 May;34(4):536-49. doi: 10.1177/0272989X14523502.
There is widespread recognition that interventions targeting "superspreaders" are more effective at containing epidemics than strategies aimed at the broader
However, little attention has been devoted to determining optimal levels of coverage for targeted vaccination strategies, given the nonlinear relationship between program scale and the costs and benefits of identifying and successfully administering vaccination to potential superspreaders.
We developed a framework for such an assessment derived from a transmission model of seasonal influenza parameterized to emulate typical seasonal influenza epidemics in the US. We used this framework to estimate how the marginal benefit of expanded targeted vaccination changes with the proportion of the target population already vaccinated.
The benefit of targeting additional superspreaders varies considerably as a function of both the baseline vaccination coverage and proximity to the herd immunity threshold. The general form of the marginal benefit function starts low, particularly for severe epidemics, increases monotonically until its peak at the point of herd immunity, and then plummets rapidly. We present a simplified transmission model, primarily designed to convey qualitative insight rather than quantitative precision. With appropriate contact data, future work could address more complex population structures, such as age structure and assortative mixing patterns. Our illustrative example highlights the general economic and epidemiological findings of our method but does not address intervention design, policy, and resource allocation issues related to practical implementation of this particular scenario.
Our approach offers a means of estimating willingness to pay for search costs associated with targeted vaccination of superspreaders, which can inform policies regarding whether a targeted intervention should be implemented and, if so, up to what levels.
人们普遍认识到,针对“超级传播者”的干预措施在控制疫情方面比针对更广泛人群的策略更有效。然而,鉴于项目规模与识别并成功为潜在超级传播者接种疫苗的成本和效益之间存在非线性关系,对于确定针对性疫苗接种策略的最佳覆盖水平,关注较少。
我们开发了一个用于此类评估的框架,该框架源自季节性流感传播模型,通过参数设置来模拟美国典型的季节性流感疫情。我们使用这个框架来估计扩大针对性疫苗接种的边际效益如何随已接种目标人群的比例而变化。
针对额外超级传播者的效益会因基线疫苗接种覆盖率和与群体免疫阈值的接近程度而有很大差异。边际效益函数的一般形式起初较低,尤其是在严重疫情期间,然后单调增加,直到在群体免疫点达到峰值,随后迅速下降。我们提出了一个简化的传播模型,主要旨在传达定性见解而非定量精度。有了适当的接触数据,未来的工作可以处理更复杂的人群结构,如年龄结构和 assortative 混合模式。我们的示例突出了我们方法的一般经济和流行病学发现,但未涉及与该特定场景实际实施相关的干预设计、政策和资源分配问题。
我们的方法提供了一种估计为针对超级传播者进行针对性疫苗接种的搜索成本支付意愿的手段,这可以为有关是否应实施针对性干预以及如果实施应达到何种水平的政策提供参考。