Modelling SARS-CoV-2 Dynamics: Implications for Therapy

Abstract

medRxiv preprint Significance Statement (80/120) 47 Antiviral agents with different mechanisms of action have different curative effects 48 depending on precisely when therapy is initiated. Based on a model of viral 49 dynamics, parameterised using viral load data from SARS-CoV-2 infected patients 50 reported by Zou et al. (1), computer simulations were performed. We propose that 51 effective treatment of SARS-CoV-2 infection requires an appropriate choice of class-52 specific drugs and initiation timing as reported for treatment of other viral infections 53(2); otherwise, antivirals do not have a significant effect on the within-host viral 54 dynamics of SARS-CoV-2 and are wasted. 55

Potency and timing of antiviral therapy as determinants of duration of SARS-CoV-2 shedding and intensity of inflammatory response

“…Subtherapeutic treatments may even prolong infection by blocking adequate triggering of innate immunity and total depletion of susceptible cells, and thus, these therapies may be predisposed to drug resistance. Of note, our model’s predictions differ in this respect from those derived from other existing intra-host models of SARS-CoV-2 that do not emphasize the role of the immune response in eliminating infected cells ( 44 , 45 ). On the basis of these different projections, we suggest sampling at late time points during PEP trials.…”

“…Second, effective dosing after symptom development predicts rapid subsequent elimination of infected cells. Most current clinical trials are focused primarily on hospitalized patients, whereas our results and those from two other COVID-19 models suggest that treatment in the days immediately following symptom onset will decrease the duration of detectable viral shedding ( 44 , 45 ). Our model also predicts that early treatment (before viral peak, usually <5 days post-infection) will limit the extent of the cytolytic immune response required to clear infection.…”

Kinetics of SARS-CoV-2 infection in the human upper and lower respiratory tracts and their relationship with infectiousness

“…Dynamics of early infection. As in previous work (33,35), we first constructed a target cell limited (TCL) model (see Methods) to quantify the early dynamics of SARS-CoV-2 infection in both the URT and the LRT. We used this model to estimate key parameters, such as the time to peak viremia and the within-host basic reproductive number (R0) and their relationships with the time from infection to symptom onset, i.e.…”

“…(5). Because we used the known infection dates, we could estimate the initial dynamics more carefully than previous studies (32)(33)(34)(35)(36). In particular, we found infected individuals with a longer incubation period had lower rates of viral growth, and higher potential for presymptomatic transmission.…”

“…Mathematical modeling plays a crucial role in understanding the pathogenesis of viral diseases and in the development of effective therapeutics and treatment strategies for viruses such as HIV, hepatitis C, influenza, Zika and Ebola (26)(27)(28)(29)(30)(31). Mathematical modeling has been applied, by us and others (32)(33)(34)(35)(36), to understand SARS-CoV-2 infection in hospitalized patients and the potential impact of therapy. However, these studies modeled a single physiological compartment even though SARS-CoV-2 infects both the URT and the LRT and there were large uncertainties in the parameter estimates because the patient infection dates were unknown.…”