Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia, United States of America.
PLoS One. 2012;7(6):e36573. doi: 10.1371/journal.pone.0036573. Epub 2012 Jun 11.
If repeated interventions against multiple outbreaks are not feasible, there is an optimal level of control during the first outbreak. Any control measures above that optimal level will lead to an outcome that may be as sub-optimal as that achieved by an intervention that is too weak. We studied this scenario in more detail.
An age-stratified ordinary-differential-equation model was constructed to study infectious disease outbreaks and control in a population made up of two groups, adults and children. The model was parameterized using influenza as an example. This model was used to simulate two consecutive outbreaks of the same infectious disease, with an intervention applied only during the first outbreak, and to study how cumulative attack rates were influenced by population composition, strength of inter-group transmission, and different ways of triggering and implementing the interventions. We assumed that recovered individuals are fully immune and the intervention does not confer immunity.
RESULTS/CONCLUSION: The optimal intervention depended on coupling between the two population sub-groups, the length, strength and timing of the intervention, and the population composition. Population heterogeneity affected intervention strategies only for very low cross-transmission between groups. At more realistic values, coupling between the groups led to synchronization of outbreaks and therefore intervention strategies that were optimal in reducing the attack rates for each subgroup and the population overall coincided. For a sustained intervention of low efficacy, early intervention was found to be best, while at high efficacies, a delayed start was better. For short interventions, a delayed start was always advantageous, independent of the intervention efficacy. For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak's beginning as the trigger.
如果针对多次暴发的重复干预不可行,那么在首次暴发期间存在一个最佳控制水平。任何高于该最佳水平的控制措施都会导致结果不如干预力度太弱的情况理想。我们更详细地研究了这种情况。
使用年龄分层的常微分方程模型来研究由两个群体(成人和儿童)组成的人群中的传染病暴发和控制。使用流感作为示例对模型进行参数化。该模型用于模拟两次相同传染病的连续暴发,仅在首次暴发期间实施干预,并研究人群构成、组间传播强度以及干预触发和实施方式的不同如何影响累积发病率。我们假设康复个体具有完全免疫力,且干预不会提供免疫力。
结果/结论:最佳干预取决于两个人群亚群之间的耦合、干预的持续时间、强度和时机以及人口构成。人口异质性仅对组间的低交叉传播有影响。在更现实的情况下,群体之间的耦合导致暴发同步,因此在降低每个亚组和总体人群的发病率方面最佳的干预策略是一致的。对于持续低效的干预,我们发现早期干预效果最好,而对于高效干预,延迟开始效果更好。对于短期干预,延迟开始始终是有利的,而与干预效果无关。对于大多数情况,与使用暴发开始后的指定持续时间作为触发因素的策略相比,在一定比例的儿童感染后开始干预似乎更能实现接近最佳的结果,从而更稳健。