Application of loop analysis for evaluation of malaria control interventions.

BACKGROUND: Despite continuous efforts and recent rapid expansion in the financing and implementation of malaria control interventions, malaria still remains one of the most devastating global health issues. Even in countries that have been successful in reducing the incidence of malaria, malaria control is becoming more challenging because of the changing epidemiology of malaria and waning community participation in control interventions. In order to improve the effectiveness of interventions and to promote community understanding of the necessity of continued control efforts, there is an urgent need to develop new methodologies that examine the mechanisms by which community-based malaria interventions could reduce local malaria incidence.

METHODS: This study demonstrated how the impact of community-based malaria control interventions on malaria incidence can be examined in complex systems by qualitative analysis combined with an extensive review of literature. First, sign digraphs were developed through loop analysis to analyse seven interventions: source reduction, insecticide/larvicide use, biological control, treatment with anti-malarials, insecticide-treated mosquito net/long-lasting insecticidal net, non-chemical personal protection measures, and educational intervention. Then, for each intervention, the sign digraphs and literature review were combined to analyse a variety of pathways through which the intervention can influence local malaria incidence as well as interactions between variables involved in the system. Through loop analysis it is possible to see whether increases in one variable qualitatively increases or decreases other variables or leaves them unchanged and the net effect of multiple, interacting variables.

RESULTS: Qualitative analysis, specifically loop analysis, can be a useful tool to examine the impact of community-based malaria control interventions. Without relying on numerical data, the analysis was able to describe pathways through which each intervention could influence malaria incidence on the basis of the qualitative patterns of the interactions between variables in complex systems. This methodology is generalizable to various disease control interventions at different levels, and can be utilized by a variety of stakeholders such as researchers, community leaders and policy makers to better plan and evaluate their community-based disease control interventions.