This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Many existing and emerging pathogens are multi-host pathogens that cross into human populations. It is difficult to predict how those pathogens will spread, because each species can have very different infectivity, immune response and ecological characteristics. The proposed research uses an innovative and powerful modeling approach that combines biological theory, published data and computer simulations to predict immune response, viral dynamics and epidemic spread from host mass. The research focuses on West Nile Virus (WNV), a pathogen that has spread rapidly across the US with severe consequences to human health. Because WNV is well-studied in the laboratory and in ecological field studies, there is sufficient information to build accurate computer models and to test their predictions. The models predict how WNV spreads within and between bird host species using Metabolic Scaling Theory (MST). MST identifies profound and predictable differences in the physiology, life history and ecology of different species based on their mass.
The aims of this project are to predict 1) the time course of viremia in each infective bird species 2) characteristics of bird species that harbor sufficient WNV to infect mosquito vectors, 3) how long those bird species are infective, and 4) which bird communities have a combination of species that enable WNV to persist. MST guides these predictions by relating rates of viral replication, immune response and ecological interaction to mass.
Aim 1 predicts the time course of viremia, including the concentration of virus in blood each day post infection and the duration of viremia that is sufficient to infect mosquito vectors. The duration of infective viremia is an important determinant of epidemic spread which is modeled in Aim 2.
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