Transmission of infectious diseases mostly occurs due to contacts among infected and susceptible individuals. Therefore, the characterization of the contact patterns among individu
als is a prerequisite to better understand and even predict the spread of diseases in a population. California is one of the most important states for livestock production and trade, particularly cattle and poultry. The evaluation of the livestock movements being introduced into the state, would be useful to identify highly connected areas and premises in which risk-based surveillance and outreach activities could be allocated to better prevent the risk of introduction and spread of diseases into the state. To the best of our knowledge, very few studies have been published characterizing the livestock trade network in the US and none in California, despite the potential to provide valuable insights for better prevention, tracing and control of infectious diseases.. In this project we aim to characterize the nature, extent and temporal-spatial patterns of the livestock movements (including beef, dairy, sheep, goat, swine, horses, poultry, hatching eggs and rabbits) being introduced in California as a preliminary but fundamental step to better understand livestock trade dynamics and evaluate their association with the potential risk of introduction of diseases into the State. For such purpose, we will use social network analysis (SNA) and geo-statistical analysis (scan statistics) similar to previous studies conducted by PI. The use of SNA alone or in combination with other methods in veterinary medicine is becoming highly popular due to the multiple advantages that SNA offers to handle and analyze the intrinsically complex contact information to support policies.
