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  • Undergraduate Poster Abstracts
  • FRI-803 AN EPIDEMIOLOGICAL MODEL OF BOVINE RESPIRATORY SYNCYTIAL VIRUS INFECTION DYNAMICS

    • Taylor Kuramoto ;

    FRI-803

    AN EPIDEMIOLOGICAL MODEL OF BOVINE RESPIRATORY SYNCYTIAL VIRUS INFECTION DYNAMICS

    Taylor Kuramoto1, Vivian Anyaeche2, Shi Chen3, Tashika James4, Christina Lanzas2, Suzanne Lenhart4, Taylor Nelsen4.

    1Fisk University, Nashville, TN, 2University of Tennessee, Knoxville, Knoxville, TN, 3The LeMoyne Owen College, Memphis, TN, 4National Institute for Mathematical and Biological Synthesis, Knoxville, TN.

    Bovine respiratory syncytial virus (BRSV) is one etiological agent in the larger bovine respiratory disease (BRD) complex that causes damage to the respiratory tract, facilitates bacterial growth, and compromises the immune system. Negative effects of BRSV include costs stemming from death, reduced performance, poor growth, and the administration of vaccines and treatments. Understanding the effect of cattle contact networks on the transmission of the pathogens causing BRD will help reduce unnecessary treatments, costs, and public health concerns of growing drug-resistance. A stochastic agent-based epidemiological model has been developed to predict the outcome of infection under different circumstances. The model simulates the spread of BRSV using a spatially implicit contact network generated by a real time location system and visualized in NetLogo. It takes a top-down approach to understanding the complex relations between the key transmission components. The underlying theory relies on basic susceptible-infected-recovered (SIR) compartmental principles. Simulations were completed under varying initial conditions and compared susceptibility, incidence proportion, maximum prevalence, and cumulative centrality to see how disease dynamics and emergence differ under given initial conditions. Qualitative observations from the model interface and preliminary quantitative analysis indicate that cows’ social behavior and interactions affect how the virus spreads through a population. The interaction between the network structure and the disease status drives the disease dynamics. These findings indicate that decreasing the number of cows in a herd will not decrease the transmission rate but, if the network density and sociality of the cows can be controlled, so can the transmission.