Center for Global Health, Health Sciences Center, University of New Mexico, Albuquerque, NM 87131, USA.
Transbound Emerg Dis. 2012 Oct;59(5):464-9. doi: 10.1111/j.1865-1682.2011.01301.x. Epub 2012 Feb 24.
When an exotic infectious disease invades a susceptible environment, protection zones are enforced. Historically, such zones have been shaped as circles of equal radius (ER), centred on the location of infected premises. Because the ER policy seems to assume that epidemic dissemination is driven by a similar number of secondary cases generated per primary case, it does not consider whether local features, such as connectivity, influence epidemic dispersal. Here we explored the efficacy of ER protection zones. By generating a geographically explicit scenario that mimicked an actual epidemic, we created protection zones of different geometry, comparing the cost-benefit estimates of ER protection zones to a set of alternatives, which considered a pre-existing connecting network (CN) - the road network. The hypothesis of similar number of cases per ER circle was not substantiated: the number of units at risk per circle differed up to four times among ER circles. Findings also showed that even a small area (of <115 km(2) ) revealed network properties. Because the CN policy required 20% less area to be protected than the ER policy, and the CN-based protection zone included a 23.8% greater density of units at risk/km(2) than the ER-based alternative, findings supported the view that protection zones are likely to be less costly and more effective if they consider connecting structures, such as road, railroad and/or river networks. The analysis of local geographical factors (contacts, vectors and connectivity) may optimize the efficacy of control measures against epidemics.
当一种外来传染病侵入易感环境时，就会实施保护区。从历史上看，这些区域的形状是半径相等（ER）的圆，以感染场所的位置为中心。由于 ER 政策似乎假设传染病传播是由每个原发病例产生的相同数量的继发病例驱动的，因此它没有考虑到本地特征（如连通性）是否会影响传染病的传播。在这里，我们探讨了 ER 保护区的效果。通过生成一个模仿实际疫情的地理明确情景，我们创建了不同几何形状的保护区，将 ER 保护区的成本效益估计与一组替代方案进行了比较，这些替代方案考虑了一个预先存在的连接网络（CN）-道路网络。每个 ER 圆的病例数相似的假设并没有得到证实：每个 ER 圆的风险单位数量差异高达 4 倍。研究结果还表明，即使是一个小区域（<115km2）也显示出了网络特性。由于 CN 政策需要保护的面积比 ER 政策少 20%，并且基于 CN 的保护区每公里风险单位密度比基于 ER 的替代方案高 23.8%，因此研究结果支持了这样一种观点，即如果保护区考虑到连接结构（如道路、铁路和/或河流网络），则可能成本更低，效果更好。分析本地地理因素（接触、媒介和连通性）可以优化针对传染病的控制措施的效果。
