Dynamical characterization of antiviral effects in COVID-19

A simple in-host model for COVID-19 with treatments: model prediction and calibration

In this paper, we provide a simple ODEs model with a generic nonlinear incidence rate function and incorporate two treatments, blocking the virus binding and inhibiting the virus replication to investigate the impact of calibration on model predictions for the SARS-CoV-2 infection dynamics. We derive conditions of the infection eradication for the long-term dynamics using the basic reproduction number, and complement the characterization of the dynamics at short-time using the resilience and reactivity of the virus-free equilibrium are considered to inform on the average time of recovery and sensitivity to perturbations in the initial virus free stage. Then, we calibrate the treatment model to clinical datasets for viral load in mild and severe cases and immune cells in severe cases. Based on the analysis, the model calibrated to these different datasets predicts distinct scenarios: eradication with a non reactive virus-free equilibrium, eradication with a reactive virus-free equilibrium, and failure of infection eradication. Moreover, severe cases generate richer dynamics and different outcomes with the same treatment. Calibration to different datasets can lead to diverse model predictions, but combining long- and short-term dynamics indicators allows the categorization of model predictions and determination of infection severity.

Response of vaccination on community transmission of COVID-19: a dynamical approach

Due to the severity of COVID-19, vaccination campaigns have been or are underway in most parts of the world. In the current circumstances, it is obligatory to examine the response of vaccination on transmission of the SARS-CoV-2 virus when there are many vaccines available. Considering the importance of vaccination, a dynamic model has been proposed to provide an insight in the same direction. A mathematical model has been developed where six population compartments viz. susceptible, infected, vaccinated, home-isolated, hospitalized and recovered population are considered. Moreover, two novel parameters are included in the model to ascertain the effectiveness and speed of the vaccination campaign. Reproduction number and local stability of both the disease-free and endemic equilibrium points are studied to examine the nature of population dynamics. Graphical results for the community stage of COVID-19 infection are simulated and compared with real data to ascertain the validity of our model. The data is then studied to understand the impact of vaccination. These numerical results evidently demonstrate that home isolation and hospitalization should continue for the infected people until the transmission of the virus from person to person reduces sufficiently after completely vaccinating every nation. This model also recommends that all type of prevention measures should still be taken to avoid any type of critical situation due to infection and also reduce the death rate.

Effectiveness of Antiviral Therapy in Highly-Transmissible Variants of SARS-CoV-2: A Modeling and Simulation Study

As of October 2021, neither established agents (e.g., hydroxychloroquine) nor experimental drugs have lived up to their initial promise as antiviral treatment against SARS-CoV-2 infection. While vaccines are being globally deployed, variants of concern (VOCs) are emerging with the potential for vaccine escape. VOCs are characterized by a higher within-host transmissibility, and this may alter their susceptibility to antiviral treatment. Here we describe a model to understand the effect of changes in within-host reproduction number R₀, as proxy for transmissibility, of VOCs on the effectiveness of antiviral therapy with molnupiravir through modeling and simulation. Molnupiravir (EIDD-2801 or MK 4482) is an orally bioavailable antiviral drug inhibiting viral replication through lethal mutagenesis, ultimately leading to viral extinction. We simulated 800 mg molnupiravir treatment every 12 h for 5 days, with treatment initiated at different time points before and after infection. Modeled viral mutations range from 1.25 to 2-fold greater transmissibility than wild type, but also include putative co-adapted variants with lower transmissibility (0.75-fold). Antiviral efficacy was correlated with R₀, making highly transmissible VOCs more sensitive to antiviral therapy. Total viral load was reduced by up to 70% in highly transmissible variants compared to 30% in wild type if treatment was started in the first 1–3 days post inoculation. Less transmissible variants appear less susceptible. Our findings suggest there may be a role for pre- or post-exposure prophylactic antiviral treatment in areas with presence of highly transmissible SARS-CoV-2 variants. Furthermore, clinical trials with borderline efficacious results should consider identifying VOCs and examine their impact in post-hoc analysis.

Effectiveness of Remdesivir, Lopinavir/Ritonavir, and Favipiravir for COVID-19 Treatment: A Systematic Review

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel strain that causes acute respiratory illnesses known as coronavirus disease 2019 (COVID-19). Currently, there is limited information regarding the therapeutic management for this disease. Several studies have stated that antivirals drugs such as remdesivir, favipiravir, and lopinavir/ritonavir may potentially inhibit the virus from spreading to the host.

OBJECTIVE

The aim of this systematic review was to summarize the clinical effectiveness and safety of remdesivir, favipiravir, and lopinavir/ritonavir on COVID-19.

METHODS

The PubMed and Cochrane Library databases were searched up to July 2021 to identify eligible experimental randomized controlled trials on remdesivir, favipiravir, and lopinavir/ritonavir for COVID-19 patients. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.

RESULTS

From 158 references, 15 studies were included in the review. The results showed that remdesivir has some potential benefits for hospitalized COVID-19 patients, as seen from clinical improvements such as faster recovery time, less duration of hospitalization, and fewer respiratory side effects among COVID-19 patients. However, the impact of remdesivir in reducing mortality remains uncertain. Treatment with favipiravir has shown promising improvement in the clinical status of COVID-19 patients, although the results suggested no significant differences in some clinical parameters such as length of hospitalizations and clinical recovery. A combination of favipiravir with other supportive therapy showed more favorable outcomes for COVID-19 patients. Furthermore, the use of lopinavir/ritonavir in COVID-19 patients reported no significant clinical improvement compared to standard care with notable adverse effect reactions.

CONCLUSION

This study provides an overview of the evidence-based role of remdesivir, favipiravir, and lopinavir/ritonavir in the management of COVID-19. A thorough assessment of the benefit-risk profile in COVID-19 patients is urgently needed. The current review was based on very limited available data; therefore, further well-designed clinical trials are required.