A Spatial Agent-Based Model and a Multi-Dimensional Data Warehouse for Malaria Research

Human malaria is transmitted only by female Anopheles mosquitoes, which are regarded as the primary vector for transmission. Agent-Based Modeling (ABM) is a powerful tool for representing complex biological systems. Following a biological core model of An. gambiae for malaria entomology, we develop agent-based simulation models (ABMs). For the ABMs, we describe the verification & validation (V&V) processes, a spatial extension, and a landscape generator tool. Using the spatial ABM, we demonstrate the effects of spatial heterogeneity, investigate the impact of vector control interventions, and describe an example application by integrating the ABM with a geographic information system (GIS).

For malaria, there is a growing need to integrate the existing heterogeneous data sources. Data warehouses (DWs) and dimensional modeling (DM) can be viable alternatives to meet this challenge. We describe the design and implementation of a multi-dimensional DW, to be integrated into the Vector Ecology and Control Network (VECNet) Cyberinfrastructure (CI) analytical framework, which provides a robust way to store, access, and analyze malaria-related data.