Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

Abstract

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular.

Figure 1

General steps in an MCDA process adapted to risk assessment, selection of alternatives and site selection. The steps in a general MCDA and spatial MCDA are similar. First, the objective of the analysis is defined (step1). Next, the key stakeholders that should be involved in the analysis process are identified (step 2). The following steps involve defining all possible alternatives under consideration (step 3) and all of the relevant criteria for evaluating these alternatives (step 4). These steps are interchangeable and may lead to an iterative process of refining which stakeholders to involve. Next, the alternatives are assessed based on the identified criteria (step 5). Performance indicators or decision variables are created for each intersecting pair of alternative and criteria. For spatial MCDA, evaluation criterion maps are generated to evaluate the performance of alternatives. Constraint maps can also be generated to display the limitations of the values that decision variables may assume. Following this, all criteria are weighted by participating stakeholders in order to reflect the preference values of those involved (step 6). It should be noted that not all MCDA approaches make use of weighting; other ordering techniques such as pair-wise comparison can be used. Next, a mathematical combination of the criteria is performed using a decision rule and effectively combines the results of the preceding four steps (step 7). The combined criteria produce an ordering of alternatives. Finally, a sensitivity analysis is performed to examine the robustness of the ranking outcome (step 8). The end result of the MCDA process is a recommendation consisting either of the best-ranked alternative or group of alternatives.

Figure 2

Key areas for the application of spatial MCDA in managing vector-borne diseases. Three important questions that require consideration when planning prevention and control actions for the management of vector-borne diseases: what is the level of risk; how to manage disease risk; and where to target risk prevention and control? The above diagram shows how (A) risk can be assessed by mapping the intersection of all the various determinants of risk (environment, vector distribution, human population, etc). Part (B) shows how MCDA can be used to evaluate the spatial effects of different alternatives on a decision problem. Finally, part (C) shows how MCDA can be used to locate priority sites for targeting prevention and control alternatives by taking a risk map and running it through the filter of different criteria constraining the decision problem. Results from one area can be fed in as input for the other questions. However, these three questions do not necessarily need to be addressed in the above suggested order nor will a full MCDA process always be required to address such questions.