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A landscape epidemiology modeling framework is presented which integrates the\udsimulation outputs from an established spatial agent-based model (ABM) of malaria with a\udgeographic information system (GIS). For a study area in Kenya, five landscape scenarios\udare constructed with varying coverage levels of two mosquito-control interventions. For\udeach scenario, maps are presented to show the average distributions of three output indices\udobtained from the results of 750 simulation runs. Hot spot analysis is performed to detect\udstatistically significant hot spots and cold spots. Additional spatial analysis is conducted\udusing ordinary kriging with circular semivariograms for all scenarios. The integration of\udepidemiological simulation-based results with spatial analyses techniques within a single\udmodeling framework can be a valuable tool for conducting a variety of disease control \udactivities such as exploring new biological insights, monitoring epidemiological landscape\udchanges, and guiding resource allocation for further investigation

Landscape Epidemiology Modeling Using an Agent-Based Model and a Geographic Information System