Cellular-Level Characterization of Dengue and Zika Virus Infection Using Multiagent Simulation

In this paper we present a computational model aimed at characterizing the Zika viral infection at a cellular level based on measurements done on viral Dulbecco plaques over time, and describe our current state of progress in the modeling task. So far we have developed an agent-based simulation model of the dispersion of the virus on the cells conforming the viral plaque. The growth rate of the viral plaques and the number of cells counted on each plaque were used to characterize the viral infection in terms of parameters related to the fate of infected cells, such as the probability of a cell infecting its neighboring cells and the probability of an infected cell of dying at any given moment. The model can be used to predict viral plaque growth patterns similar to those observed in the laboratory. Our current efforts focus on optimizing the model parameters to fit the experimental data. Further development of the model includes the description of viral infection kinetics of specific viral strains. Our model has been developed using the agent-based modeling language Netlogo [1].