Abstract

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.