A multimodel framework in support of malaria surveillance and control

Abstract

Mathematical models have played a significant role in understanding the complexity of malaria transmission dynamics. This paper describes the first steps in an effort to create an ensemble framework of various mathematical models, an approach that has been widely used to represent uncertainty in seasonal climate forecasting. This tool will be implemented to explore the role that both climatic and non-climatic factors play in fluctuations and trends in malaria incidence, and to offer useful information to effectively guide decision-makers in risk assessment, malaria control investments and choice of interventions. The initiative aims to contribute to a large programme, the Integrated Surveillance and Control System, an ambitious idea that has been proposed as an adaptation strategy to prevent the possible adverse effects of climate change on human health in Colombia. Currently, the ensemble framework is being used to: compare the simulation outputs of the selected models with actual malaria morbidity profiles observed in several endemic/epidemic-prone regions; assess changing climate and future scenarios; simulate the impact of indoor residual spraying campaigns; conduct stability analysis; and stimulate an interactive learning environment.