Abstract

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