MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.
The purpose of this model is to better understand the dynamics of a multihost pathogen in two host system comprising of high densities of domestic hosts and sympatric wildlife hosts susceptible to the pathogen.
Leptospirosis is a neglected, bacterial zoonosis with worldwide distribution, primarily a disease of poverty. More than 200 pathogenic serovars of Leptospira bacteria exist, and a variety of species may act as reservoirs for these serovars. Human infection is the result of direct or indirect contact with Leptospira bacteria in the urine of infected animal hosts, primarily livestock, dogs, and rodents. There is increasing evidence that dogs and dog-adapted serovar Canicola play an important role in the burden of leptospirosis in humans in marginalized urban communities. What is needed is a more thorough understanding of the transmission dynamics of Leptospira in these marginalized urban communities, specifically the relative importance of dogs and rodents in the transmission of Leptospira to humans. This understanding will be vital for identifying meaningful intervention strategies.
One of the main objectives of MHMSLeptoDy is to elucidate transmission dynamics of host-adapted Leptospira strains in multi-host system. The model can also be used to evaluate alternate interventions aimed at reducing human infection risk in small-scale communities like urban slums.
MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.
An agent-based simulation of a game of basketball. The model implements most components of a standard game of basketball. Additionally, the model allows the user to test for the effect of two separate cognitive biases – the hot-hand effect and a belief in the team’s franchise player.
An artifcal stock market model that allows users to vary the number of risky assets as well as the network topology that investors forms in an attempt to understand the dynamics of the market.