Zika virus dynamics: Effects of inoculum dose, the innate immune response and viral interference

Abstract

Experimental Zika virus infection in non-human primates results in acute viral load dynamics that can be well-described by mathematical models. The inoculum dose that would be received in a natural infection setting is likely lower than the experimental infections and how this difference affects the viral dynamics and immune response is unclear. Here we study a dataset of experimental infection of non-human primates with a range of doses of Zika virus. We develop new models of infection incorporating both an innate immune response and viral interference with that response. We find that such a model explains the data better than models with no interaction between virus and the immune response. We also find that larger inoculum doses lead to faster dynamics of infection, but approximately the same total amount of viral production.

Experimental infections with Zika virus strains reveal high vector competence of Aedes albopictus and Aedes aegypti populations from Gabon (Central Africa) for the African virus lineage

“…aegypti (“Aaa” form from Mexico) infected with ZIKV [ 54 ]. How these differences in the quantity of viral particles delivered in saliva can be interpreted in terms of TE is not clear, but it was recently proposed the inoculum dose could influence ZIKV dynamics in non-human primates [ 55 ].…”

Kinetics of Asian and African Zika virus lineages over single‐cycle and multi‐cycle growth in culture: Gene expression, cell killing, virus production, and mathematical modeling

“…Bernhauerová et al (2020) used a different strain and estimated a higher infection rate, longer eclipse phase (delay), faster cell death, and higher virus production rate. The study in nonhuman primates that Best et al (2021) modeled used two ZIKV strains including our Asian strain, and estimated the same population average parameters for both strains. In their work, they fixed the duration of the eclipse phase (delay) at a value that was shorter than our estimate, and the viral clearance rate they used was much higher than ours, which is reasonable because the virus is more prone to be cleared in vivo than in vitro due to the presence of the immune system.…”

“…We have addressed the context and limitations of our models (Rules 1 and 4). While previous works combined quantitative measures and computational models to analyze the ZIKV infection in vitro or in vivo (Bernhauerová et al, 2020;Best et al, 2017Best et al, , 2021de Mello, Tao, Kim, Vicchiarelli, et al, 2018)…”

“…Recently, Bernhauerová et al (2020) applied this modeling approach to multi-step infection of ZIKV, but only of one strain of the African lineage (MR766); their characterization of virus decay was more consistent with a gammadistributed delay model, where particles appear initially stable, than the more commonly observed exponential decay. Other examples to quantitatively understand ZIKV infection include the immune response to explain in vivo data from human patients and nonhuman primates, providing insight into the interaction between ZIKV and the immune response (Best & Perelson, 2018;Best et al, 2017Best et al, , 2021. Moreover, the antiviral activity of Favipiravir (FAV) of ZIKV cultured in plates and a dynamic hollow-fiber system was elucidated using a mechanism-based model that successfully predicted the viral burden profiles under dynamic FAV concentrations mimicking clinical regimens de Mello, Tao, Kim, Vicchiarelli, et al, 2018).…”

Timing HIV infection with a simple and accurate population viral dynamics model

“…Population nonlinear mixed-effects ( pNLME) modelling is a powerful tool to estimate mechanistic model parameters from longitudinal data across individuals [10,11]. It has been used extensively in pharmacokinetic modelling [12,13] and, in recent years, increasingly applied to viral dynamics [14][15][16][17][18][19].…”