Modeling and analysis of global epidemiology of avian influenza
The World Health Organization has activated a global preparedness plan to improve response to avian influenza outbreaks, control outbreaks, and avoid an H5N1 pandemic. The effectiveness of the plan will greatly benefit from identification of epicenters and temporal analysis of outbreaks. Accordingly, we have developed a simulation-based methodology to analyze the spread of H5N1 using stochastic interactions between waterfowl, poultry, and humans. We have incorporated our methodology into a user friendly, extensible software environment called SEARUMS. SEARUMS is an acronym for Studying the Epidemiology of Avian Influenza Rapidly Using Modeling and Simulation. It enables rapid scenario analysis to identify epicenters and timelines of H5N1 outbreaks using existing statistical data. The case studies conducted using SEARUMS have yielded results that coincide with several past outbreaks and provide non-intuitive inferences about global spread of H5N1. This article presents the methodology used for modeling the global epidemiology of avian influenza and discusses its impacts on human and poultry morbidity and mortality. The results obtained from the various case studies and scenario analyses conducted using SEARUMS along with verification experiments are also discussed. The experiments illustrate that SEARUMS has considerable potential to empower researchers, national organizations, and medical response teams with timely knowledge to combat the disease, mitigate its adverse effects, and avert a pandemic.
influenza h5n1 spatially explicit model agent-based model discrete event simulation