The impact of prophylactic and antiviral treatments for COVID-19: a modelling study

Abstract

Layman's Summary Since early 2020, a pandemic is occurring due to Coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 can range from an asymptomatic disease to mild, severe or critical respiratory disease, that can lead to death. Certain groups of people in the general population are more at risk of severe disease and death, such as the elderly (60 years and older), people with chronic diseases, and/or obesity, among others. Additionally, SARS-CoV-2 has the capacity of mutating, that is, the ability of altering its characteristics, which can increase its capability to infect people, the severity of the disease, and/or decrease the immune response. All these characteristics point to the importance of implementing transmission control measures, such as social distancing, face-masks, quarantine and isolation, and others. As some of the measures implemented are not sustainable in the long term, parallel to their implementation, vaccinations were also being developed, as well as, prophylactic (i.e., preventive) and antiviral treatments. These measures have the capacity of preventing severe disease, therefore hospitalisation and death, which is very important from a public health perspective. By preventing the need of hospital care, COVID-19 hospitalisation health care related costs could be averted, and the burden on hospital capacity is reduced as a consequence, as well. Thus, it is important to understand what impact prophylactic and antiviral treatments could have for settings with varying levels of vaccination coverage. This project aims to identify through mathematical modelling, how pre-exposure prophylaxis (PrEP) and antiviral treatments can prevent COVID-19 hospitalisations, in settings with different vaccination and booster coverages. For this purpose, a mathematical model of SARS-CoV-2 transmission was used. Simulations in three main different vaccination coverage settings (high, moderate, and low) were conducted over a one-year period, and two different efficacies of oral antivirals, 30% and 89%, were modelled based on clinical trial results. For an antiviral with 89% efficacy given only to the high-risk group, results show that there were 29%, 32% and 36% less hospitalisations in high, moderate, and low vaccination settings, respectively, when compared to no treatment. If coverage is increased to the total population, there are less 56%, 60%, and 63% hospitalisations for each respective vaccination setting. Averted hospitalisations increase between 1 to 5% if PrEP is also implemented, across all vaccination settings. Costs of vaccination decrease, and costs of hospitalisation increase with decreased vaccination coverage. Across all three vaccination settings, increasing spending on antivirals with higher efficacy (89%) by around 80% to increase antiviral coverage from high-risk group to total population could avert an additional 40% of hospitalisations. Overall, the projections of the model suggest that both prophylactic and antiviral treatments can be a useful additional public health measures to decrease hospitalisations, and consequently ICU cases and deaths. The preliminary economic analysis conducted, even with some limitations, highlighted the benefit of these treatments to reduce total costs. Additional modelling will be useful to further analyse the benefits and drawbacks of antiviral treatment. Therefore, informing policy makers on the most optimal public health and cost-effective outcome.