Department of Mathematics and Statistics, University of Guelph, Canada.
BMC Public Health. 2011 Sep 28;11:739. doi: 10.1186/1471-2458-11-739.
The potential benefits of coordinating infectious disease eradication programs that use campaigns such as supplementary immunization activities (SIAs) should not be over-looked. One example of a coordinated approach is an adaptive "sequential strategy": first, all annual SIA budget is dedicated to the eradication of a single infectious disease; once that disease is eradicated, the annual SIA budget is re-focussed on eradicating a second disease, etc. Herd immunity suggests that a sequential strategy may eradicate several infectious diseases faster than a non-adaptive "simultaneous strategy" of dividing annual budget equally among eradication programs for those diseases. However, mathematical modeling is required to understand the potential extent of this effect.
Our objective was to illustrate how budget allocation strategies can interact with the nonlinear nature of disease transmission to determine time to eradication of several infectious diseases under different budget allocation strategies. Using a mathematical transmission model, we analyzed three hypothetical vaccine-preventable infectious diseases in three different countries. A central decision-maker can distribute funding among SIA programs for these three diseases according to either a sequential strategy or a simultaneous strategy. We explored the time to eradication under these two strategies under a range of scenarios.
For a certain range of annual budgets, all three diseases can be eradicated relatively quickly under the sequential strategy, whereas eradication never occurs under the simultaneous strategy. However, moderate changes to total SIA budget, SIA frequency, order of eradication, or funding disruptions can create disproportionately large differences in the time and budget required for eradication under the sequential strategy. We find that the predicted time to eradication can be very sensitive to small differences in the rate of case importation between the countries. We also find that the time to eradication of all three diseases is not necessarily lowest when the least transmissible disease is targeted first.
Relatively modest differences in budget allocation strategies in the near-term can result in surprisingly large long-term differences in time required to eradicate, as a result of the amplifying effects of herd immunity and the nonlinearities of disease transmission. More sophisticated versions of such models may be useful to large international donors or other organizations as a planning or portfolio optimization tool, where choices must be made regarding how much funding to dedicate to different infectious disease eradication efforts.
协调使用诸如补充免疫活动（SIAs）等运动的传染病根除计划的潜在好处不应被忽视。一种协调方法的例子是适应性的“序贯策略”：首先，所有年度 SIA 预算都专门用于根除一种传染病；一旦该疾病被根除，年度 SIA 预算就重新集中用于根除第二种疾病，依此类推。群体免疫表明，序贯策略可能比将年度预算平均分配给这些疾病的根除计划的非适应性“同时策略”更快地根除几种传染病。然而，需要数学建模来理解这种效果的潜在程度。
我们的目标是说明预算分配策略如何与疾病传播的非线性性质相互作用，以确定在不同预算分配策略下几种传染病根除的时间。我们使用数学传播模型分析了三个不同国家的三种假设的疫苗可预防传染病。中央决策者可以根据序贯策略或同时策略在这三个 SIA 计划之间分配资金。我们在一系列方案下探讨了这两种策略下的根除时间。
在一定的年度预算范围内，所有三种疾病都可以在序贯策略下相对较快地根除，而在同时策略下则从未发生过根除。然而，总 SIA 预算、SIA 频率、根除顺序或资金中断的适度变化会导致序贯策略下根除所需的时间和预算产生不成比例的巨大差异。我们发现，预测的根除时间对各国之间病例输入率的微小差异非常敏感。我们还发现，当目标是最具传染性的疾病时，并非所有三种疾病的根除时间都一定最短。
在短期内，预算分配策略的相对较小差异可能会导致根除所需时间的长期差异非常大，这是由于群体免疫的放大效应和疾病传播的非线性。此类模型的更复杂版本可能对大型国际捐助者或其他组织有用，作为规划或投资组合优化工具，其中必须针对将多少资金用于不同的传染病根除工作做出选择。
