Michael Edwin, Malecela-Lazaro Mwele N, Kazura James W
Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London W2 1PG, United Kingdom.
Adv Parasitol. 2007;65:191-237. doi: 10.1016/S0065-308X(07)65003-9.
Monitoring and evaluation are critically important to the scientific management of any parasite control programme. If a management action is prescribed, monitoring plays a pivotal role in assessing the effectiveness of implemented actions, identifying necessary adaptations for management and determining when management objectives are achieved. Here, we focus on the control of the vector-borne parasitic disease, lymphatic filariasis, to show how mathematical models of parasite transmission can provide a scientific framework for supporting the optimal design of parasite control monitoring programmes by their ability to (1) enable the estimation of endpoint targets, (2) provide information on expected trends in infection due to interventions to allow rational evaluation of intervention effectiveness and calculation of the frequency of monitoring, (3) support the selection of indicators that permit reliable and statistically powerful measurement of the effects of interventions while minimizing costs and sampling intensity and (4) aid the interpretation of monitoring data for improving programme management and knowledge of the population dynamics of parasite control. The results also highlight how the use of a model-based monitoring framework will be vitally enhanced by adopting an adaptive management approach that acknowledges uncertainty and facilitates the use of monitoring data to learn about effective control, and which allows future decisions to be modified as we learn by doing. We conclude by emphasizing a pressing need to incorporate mathematical models coupled with changes to existing management systems in ongoing efforts to design and implement rational monitoring plans for evaluating filariasis and other parasitic disease control programmes.
监测和评估对于任何寄生虫控制项目的科学管理都至关重要。如果规定了管理行动，监测在评估已实施行动的有效性、确定管理所需的调整以及判定何时实现管理目标方面发挥着关键作用。在此，我们聚焦于媒介传播寄生虫病——淋巴丝虫病的控制，以展示寄生虫传播的数学模型如何能够通过以下能力为支持寄生虫控制监测项目的优化设计提供科学框架：（1）能够估计终点目标；（2）提供因干预措施导致的感染预期趋势信息，以便合理评估干预效果并计算监测频率；（3）支持选择指标，在将成本和抽样强度降至最低的同时，可靠且有统计学效力地衡量干预效果；（4）辅助解读监测数据，以改善项目管理并增进对寄生虫控制人群动态的了解。结果还凸显了通过采用适应性管理方法，基于模型的监测框架的效用将得到极大提升，这种方法承认不确定性，并便于利用监测数据了解有效控制方法，还允许在实践中学习的过程中修改未来决策。我们强调迫切需要将数学模型与现有管理系统的变革相结合，以便在设计和实施合理监测计划以评估丝虫病及其他寄生虫病控制项目的持续努力中发挥作用。
