Duerr H-P, Schwehm M, Leary C C, De Vlas S J, Eichner M
Department of Medical Biometry, University of Tübingen, Germany.
Epidemiol Infect. 2007 Oct;135(7):1124-32. doi: 10.1017/S0950268807007959. Epub 2007 Feb 9.
Planning adequate public health responses against emerging infectious diseases requires predictive tools to evaluate the impact of candidate intervention strategies. With current interest in pandemic influenza very high, modelling approaches have suggested antiviral treatment combined with targeted prophylaxis as an effective first-line intervention against an emerging influenza pandemic. To investigate how the effectiveness of such interventions depends on contact structure, we simulate the effects in networks with variable degree distributions. The infection attack rate can increase if the number of contacts per person is heterogeneous, implying the existence of high-degree individuals who are potential super-spreaders. The effectiveness of a socially targeted intervention suffers from heterogeneous contact patterns and depends on whether infection is predominantly transmitted to close or casual contacts. Our findings imply that the various contact networks' degree distributions as well as the allocation of contagiousness between close and casual contacts should be examined to identify appropriate strategies of disease control measures.
规划针对新出现传染病的充分公共卫生应对措施需要预测工具来评估候选干预策略的影响。鉴于当前对大流行性流感的关注度极高，建模方法表明抗病毒治疗与有针对性的预防措施相结合是应对新出现的流感大流行的有效一线干预措施。为了研究此类干预措施的有效性如何取决于接触结构，我们在具有可变度分布的网络中模拟其效果。如果每人的接触数量存在异质性，感染攻击率可能会增加，这意味着存在可能成为超级传播者的高接触度个体。针对社会目标的干预措施的有效性会受到异质接触模式的影响，并且取决于感染主要是传播给密切接触者还是偶然接触者。我们的研究结果表明，应检查各种接触网络的度分布以及密切接触者和偶然接触者之间传染性的分配情况，以确定合适的疾病控制措施策略。
