Stochastic behavior of within-host progression in primary dengue infection

Abstract

Dengue is a mosquito-borne viral infection that triggers a series of intracellular events in the host immune system, which may result in an invasion of the virus into the host and cause illness with a spectrum of severity. Depending on the degree of the infection, mild to severe clinical symptoms appear when the T-cell and B-cell-initiated immune responses fail to eradicate the virus particles and subsequently become compromised. Here, we propose a mathematically tractable simple model that exhibits important biological features of dengue infection. Dynamical analysis of our model explores the factors influencing viral persistence in the body over an extended period. To investigate plausible variability in viral dynamics in different hosts, we perform stochastic simulations of our model using Gillespie’s algorithm. Our simulation results recapitulate the distribution of the intrinsic incubation period, daily viral load, and the day of peak viremia. In addition, we observe that the invasion probability of the virus into the host is correlated with the initial virus population injected by the mosquito. However, considering the biting behavior of Aedes mosquitoes, a lower initial virus injection could end up increasing the epidemic potential of the virus.