Developing Models to Predict the Spread of Influenza.

Since the 1918 pandemic that killed millions, influenza has continued to be an urgent public health problem worldwide. The highly contagious virus, which constantly changes through mutation and genetic reassortment into new forms, can evade a host's earlier-acquired immunity, and the illness has proven difficult to treat.

Various approaches to controlling influenza outbreaks have been tried, including vaccines and newly available drug treatments. Scientists at the Los Alamos National Laboratory are developing models designed to advance knowledge of the crucial early phases of an epidemic. These models will further understanding of the spread of influenza and other infectious diseases and help health researchers estimate the impact of control measures. Mathematical models are essential tools in understanding the potential of an epidemic. Scientists can model sets of competing forces and study their interactions to gain understanding of the essential relationships among social and biological mechanisms that influence the spread of a disease. This knowledge can help set priorities in research.

The project has two major components. The first includes key biological parameters, such as immune system response, pathogen mutations, susceptibility, and the ability of individuals to expose others to the infection. This component can be modified for other airborne organisms and will incorporate the effect of an individual's recent vaccinations, recent illness, or predisposition to a severe case.

The second component is the Los Alamos population mobility model called TRANSIMS, currently the definitive model for the transportation industry. Because advances in transportation technologies have made people--and the germs they carry--more mobile, connecting the biological and transportation components of the model will give a fine-grained look at what happens in the early phases of an epidemic, allowing scientists to predict the spread of the disease within and between urban areas. The model will be a deployable tool, providing guidance to public health agencies on allocation of personnel, vaccines, and other resources.

Two years ago, Los Alamos launched the Influenza Sequence Database. It serves as a repository for the many unpublished influenza viral sequences that reside in private databases at World Health Organization (WHO) influenza surveillance centers worldwide. Like LANL's other specialized databases, including databases covering HIV, the human papilloma virus, and bacterial genomes, the Influenza Sequence Database is an efficient way to track evolutionary patterns. Because the influenza virus is constantly mutating, predicting its evolution will be critical in vaccination efforts.

LANL's research efforts include developing statistical methods for detecting an "out-of-place" or unnatural virus. The rich collection of influenza sequences, with coordinated epidemiological information, provides a test bed for the study of emerging viral diseases, whose increasing presence is a fact of life on a planet with changing patterns of urbanization.