Economic and clinical impact of a novel, light-based, at-home antiviral treatment on mild-to-moderate COVID-19

Abstract

Objectives

Antiviral treatments for early intervention in patients with mild-to-moderate COVID-19 are needed as a complement to vaccination. We sought to estimate the impact on COVID-19 cases, deaths, and direct healthcare costs over 12 months following introduction of a novel, antiviral treatment, RD-X19, a light-based, at-home intervention designed for the treatment of mild-to-moderate COVID-19 infection.

Methods

A time-dependent, state transition (semi-Markov) cohort model was developed to simulate infection progression in individuals with COVID-19 in 3 US states with varying levels of vaccine uptake (Alabama, North Carolina, and Massachusetts) and at the national level between 1 June 2020 and 31 May 2021. The hypothetical cohort of patients entering the model progressed through subsequent health states after infection. Costs were assigned to each health state. Number of infections/vaccinations per day were incorporated into the model. Simulations were run to estimate outcomes (cases by severity, deaths, and direct healthcare costs) at various levels of adoption of RD-X19 (5%, 10%, 25%) in eligible infected individuals at the state and national levels and across three levels of clinical benefit based on the results from an early feasibility study of RD-X19. The clinical benefit reflects a decline in the duration of symptomatic disease by 1.2, 2.4 (base case), and 3.6 days.

Results

In the base case analysis with 10% adoption, simulated infections/deaths/direct healthcare costs were reduced by 10,059/275/$69 million in Alabama, 21,092/545/$135 million in North Carolina, and 16,670/415/$102 million in Massachusetts over 12 months. At the national level, 10% adoption reduced total infections/deaths/direct healthcare costs by 686,722/17,748/$4.41 billion.

Conclusion

At-home, antiviral treatment with RD-X19 or other interventions with similar efficacy that decrease both symptomatic days and transmission probabilities can be used in concert with vaccines to reduce COVID-19 cases, deaths, and direct healthcare costs.

Keywords:

• COVID-19
• economic model
• antiviral treatment
• health care costs
• hospitalization

JEL Classification Codes:

• I18
• I
• E17
• E1
• E
• I1

Introduction

The effect of the coronavirus disease 2019 (COVID-19) pandemic on daily life is unprecedented. In the United States (US), more than 77 million confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and over 900,000 COVID-19 deaths have been recorded through February 2022¹. As the world vaccinates against SARS-CoV-2, the transformation from pandemic phase to endemic phase has begun; however, that transformation will not end the threat or need for complementary treatments. The Institute for Health Metrics and Evaluation projected that the 2021–2022 winter surge in the Northern hemisphere would be similar to that of 2019–2020, with transmission continuing throughout 2022². This surge was observed with the rapid spread of the omicron variant, and future variants could result in similar case escalation³. In the absence of broadly available therapeutic interventions, even with widespread vaccination and without new virulent strains, vaccine hesitancy, waning vaccine efficacy, immunosuppression from other diseases and their treatment, and clinical risk factors (e.g. obesity and older age) pose a risk for serious COVID-19 illness in as much as 40% of the adult population^4–6.

Beyond the human toll, the economic impact of COVID-19 is similarly staggering. Globally, the pandemic has caused supply chain disruptions, labor shortages, and the deepest worldwide recession since World War II⁷. In the second quarter of 2020, the US experienced its largest decline in gross domestic product (GDP) in 70 years as a result of the pandemic⁸. Economic losses directly attributable to the COVID-19 pandemic include lost jobs, reduced industrial output, increased health care costs, and massive economic stimulus distributions. Although a definitive cost has not been calculated, the COVID-19 economic toll in the US is estimated to be in the tens of trillions of United States dollars (USD)⁹.

COVID-19 vaccines are cost-effective, but not uniformly: the cost per quality-adjusted life year (QALY) gained is estimated at $8,200 for individuals over 65 years of age but $94,000 for those with low risk of hospitalization and death¹⁰. The first approved pharmacologic treatment, remdesivir, is now available in both the outpatient and inpatient settings, and though clinically proven to reduce time to discharge/recovery and to reduce hospitalizations in high risk patients, this drug requires multiple days of intravenous infusion and the price of remdesivir is at least several thousand dollars for a typical six vial treatment course for those with private insurance¹¹. Monoclonal antibody (mAb) therapies were also only authorized for patients at high risk for developing severe disease, leaving a gap in treatment options for the broader population of patients with mild-to-moderate disease. Further, the uptake of mAbs (e.g. casirivimab/imdevimab and bamlanivimab/etesevimab) has been challenged by difficulty in getting both patients and mAbs to suitable outpatient treatment facilities and by the decreased efficacy against omicron and other variants leading to the selective withdrawal of certain emergency use authorizations¹². Therapies that can be used at-home for mild-to-moderate COVID-19 and made readily available through large scale, equitable deployment are also needed¹³. Recently, two orally administered antivirals (nirmatrelvir/ritonavir tablets and molnupiravir capsules) have been authorized for the treatment of individuals with mild-to-moderate COVID-19 who are at high risk for progressing to severe disease^14,15. A course of treatment for both of these therapies, each comprising a 5-day course of pills taken at home, resulted in reductions in viral load, hospitalizations, and deaths.

Empirical evidence supports the use of limited wavelength light to both prevent and treat a number of diseases including psoriasis¹⁶, Barrett’s esophagus¹⁷, microbial infections such as tuberculosis^18,19, and Propionibacterium acne²⁰. Similarly, blue light treatment represents a novel approach to mitigate the threat of SARS-CoV-2, and light delivery devices for use at-home may serve as a new treatment option for COVID-19²¹. Accessing supply chains orthogonal to those used by pharmacological interventions, these devices could be manufactured in high volume, made available through standard distribution channels, and be rapidly deployed and readily stockpiled for future need. One such light-based treatment, the EmitBio RD-X19, is an investigational device designed to enable patients with mild-to-moderate COVID-19 to self-administer precisely engineered doses of blue light through the mouth to the oropharynx and surrounding tissues²².

In a randomized, double-blind, sham-controlled early feasibility study of RD-X19, subjects were enrolled based on a positive SARS-CoV-2 rapid antigen test within 3 days of symptom onset and having at least 2 moderate COVID-19 symptoms at baseline (NCT04662671). Subjects self-administered 5-minute, twice-daily treatments with RD-X19 for 4 days and were medically monitored for the duration of the study (8 days). For safety and tolerability, assessments included local site reactions (pain, induration, erythema) and the presence, type, severity, and attribution of any device-related treatment-emergent adverse events. Efficacy outcome measures included assessments of SARS-CoV-2 saliva viral load and clinical assessments of COVID-19.

At the end of study (Day 8), the mean change in log10 saliva viral load was −3.29 for RD-X19 and −1.81 for sham, demonstrating a treatment benefit of −1.48 logs or approximately a 95% reduction compared to placebo. Among the clinical outcome measures, differences between RD-X19 and sham were also observed, with a shortened duration of symptomatic disease of 2.4 days in RD-X19 treated subjects compared to sham treated subjects²³. There were no local application site reactions and no device-related adverse events.

In this manuscript, we present a simulation model to estimate the population-level benefits resulting from the introduction of the RD-X19 treatment based on the results of the RD-X19 early feasibility study. More broadly, this simulation also is useful to assess how any intervention used as a complement to vaccines that reduces the duration of COVID-19 symptomatic disease and transmission probabilities impacts healthcare costs, incidence, and mortality due to COVID-19. Simulation models provide an approach to estimate the clinical and economic benefits from the introduction of interventions like RD-X19 to mitigate infectious disease outbreak. As such we simulated estimates of the reductions in COVID-19 disease (mild, moderate, and severe), mortality, and direct health care costs for introduction of the treatment prior to the 2020 winter surge in 3 US states with varying degrees of COVID-19 vaccinations and at the US national level.

Methods

Cost-consequence analysis

A cost-consequence analysis was performed using a time-dependent, state transition (semi-Markov) cohort model to retrospectively estimate benefits (compared with standard practice) associated with the use of RD-X19 for the treatment of mild-to-moderate COVID-19 in each state and nationally (US) in accordance with best practice standards for economic evaluations²⁴. The impact of the device was modeled over 12 months of the pandemic from 1 June 2020 to 31 May 2021. A US healthcare payer perspective was adopted. Three states were selected to represent variability in infection, control and vaccination rates (as of 30 May 2021): Alabama (29.2% fully-vaccinated), North Carolina (36.1% fully-vaccinated), and Massachusetts (53.4% fully-vaccinated)²⁵. Similarly, 3 levels of reduced symptomatic days relative to the standard were evaluated (1.2, 2.4, and 3.6 fewer symptomatic days); the base case of 2.4 days reflected the time to symptom resolution in the RD-X19 early feasibility study²³. The lower boundary of clinical benefit represented a 50% reduction in efficacy from the results (50% of 2.4 days = 1.2 days) of the study and is found to be similar to that of the approved influenza antiviral baloxavir marboxil²⁶. The upper boundary of 3.6 days represents a benefit 150% greater than expected (150% of 2.4 days = 3.6 days) from the device efficacy results from the early feasibility study.

Model structure

The patients in the hypothetical cohort entering the model progressed through a series of 15 health states after SARS-CoV-2 infection based on calculated transition probabilities (Figure 1). The proportion of the model cohort that became infected with SARS-CoV-2 in each cycle was based on the number of newly reported COVID-19 cases, the number of individuals fully-vaccinated in each cycle, and the current number of infected individuals. The length of time that an individual remains contagious impacts the number of new cases observed each model cycle. A detailed description of the model is provided in the Online Supplement. When reporting results, the model ran from the first timepoint (March 2020), but no results were recorded before 1 June 2020. The reason for running the model from the first timepoint was to populate all model 15 health states with realistic values before beginning collection of results and to verify that the model accurately represented disease progression. A summary of the calculated transition probabilities for standard practice and RD-X19 arms (which are the same for all modelled US states) of the model are provided in Supplemental Figures S1 and S2.

Figure 1. Cost-consequence model schematic. Abbreviations. COVID-19: coronavirus disease 2019; MV, mechanical ventilation.

Infectious health states covered mild, moderate, and severe COVID-19 infections, are aligned to definitions outlined by the National Institutes of Health (NIH), and incorporate guidance provided by the Center for Drug Evaluation and Research at the U.S. Food and Drug Administration (FDA) (Table 1)²⁷. Within moderate infection, the model further differentiates between management at home or in the inpatient setting, whereas severe infection was split between those requiring mechanical ventilation (MV) or not. Following recovery from acute infection, any infection severity could potentially lead to long COVID-19. Mortality from any model health state is possible. Further details of the model structure and modeling assumptions can be found in the Online Supplement. All model inputs were identified through targeted searches of either peer-reviewed published literature or publicly available data provided by state and federal government. Model inputs and selected references are provided in Table 2.

Table 1. COVID-19 testing, disease severity, and symptoms²⁷.

	FDA authorized SARS-CoV-2 diagnostic test	Clinical signs and symptoms
Mild COVID-19	(+)	Symptoms of mild illness with COVID-19 that could include fever, cough, sore throat, headache, muscle or joint pain, unexplained chills or sweats, nausea (with or without vomiting) or other non-respiratory symptoms that may alter daily living (e.g. loss of taste or smell), and Do not have shortness of breath, dyspnea, abnormal chest imaging, or any other clinical signs indicative of moderate or severe COVID-19.
Moderate COVID-19	(+)	Symptoms of moderate illness with COVID-19, which could include any symptom of mild illness or dyspnea (shortness of breath) with exertion, and Clinical signs suggestive of lower airway involvement, such as resting respiratory rate ≥20 breaths per minute or imaging indicating lower airway disease with an oxygen saturation (SpO2) ≥94% on room air at sea level.
Severe COVID-19	(+)	Symptoms suggestive of severe systemic illness with COVID-19, which could include any symptom of moderate illness or shortness of breath at rest, and Clinical signs indicative of severe systemic illness, such as resting respiratory rate ≥30 per minute, heart rate ≥125 per minute, lung infiltrates >50%, or SpO2 < 94% on room air at sea level or PaO2/FiO2 < 300 mm Hg.

Adapted from National Institutes of Health Center for Drug Evaluation Research (NIH CDER)²⁸.

Abbreviations. +, SARS-CoV-2-positive; COVID-19, coronavirus disease 2019; FDA, Food and Drug Administration; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Table 2. Model inputs.

Parameter		Base case value	Range in deterministic sensitivity analyses		Distribution for probabilistic analyses	Source
			Lower	Upper
Population characteristics
US National	Total population, n	329,301,587	–	–	None	^29
	Population ≥18 years, %	77.90%	70.11%	85.69%	Beta
	Gender (female), %	50.80%	45.72%	55.88%	Beta
	Average age of adult population, years	38.5	34.7	42.4	Normal
	Adults initially infected with COVID-19 (March 2020), %	0.000161%	0.00014%	0.00018%	Beta	^30
Alabama	Total population, n	4,903,185	–	–	None	^29
	Population ≥18 years, %	77.80%	70.02%	85.58%	Beta
	Gender (female), %	51.70%	46.53%	56.87%	Beta
	Average age of adult population, years	39.4	35.5	43.3	Normal
	Adults initially infected with COVID-19 (March 2020), %	0.01081%	0.00973%	0.01189%	Beta	^30
North Carolina	Total population, n	10,488,084	–	–	None	^29
	Population ≥18 years, %	78.10%	70.29%	85.91%	Beta
	Gender (female), %	51.40%	46.26%	56.54%	Beta
	Average age of adult population, years	39.1	35.2	43.0	Normal
	Adults initially infected with COVID-19, %	0.000639%	0.000575%	0.000703%	Beta	^29
Massachusetts	Total population, n	6,892,503	–	–	None	^29
	Population ≥18 years, %	80.40%	72.36%	88.44%	Beta
	Gender (female), %	51.50%	46.35%	56.65%	Beta
	Average age of adult population, n	39.7	35.7	43.7	Normal
	Adults initially infected with COVID-19, %	0.00001%	0.00001%	0.00002%	Beta	^30
COVID-19 infections
COVID-19 infections positively diagnosed, %		23.81%	20.41%	27.78%	Beta	^30
Baseline distribution, %	Mild COVID-19	74.24%	–	–	Dirichlet	^31
	Moderate COVID-19	14.19%	–	–	Dirichlet
	Severe COVID-19	11.57%	–	–	Dirichlet
COVID-19 incubation period, days		5.20	4.68	5.72	Normal	^32
Moderate COVID-19 cases resolved at home, %		75.67%	68.10%	83.23%	Beta	^27
Severe COVID-19 cases requiring MV, %		30.50%	27.45%	33.55%	Beta	^33
COVID-19 symptomatic days, days	Mild	6.71	6.04	7.38	Normal	^23
	Moderate (Home)	6.71	6.04	7.38	Normal
	Moderate (Hospital)	17.00	15.30	18.70	Normal	^34
	Severe (without MV)	21.00	18.90	23.10	Normal
	Severe (with MV)	23.00	20.70	25.30	Normal
COVID-19 recovery days, days	Mild	12.00	10.80	13.20	Normal	^35
	Moderate (Home)	12.00	10.80	13.20	Normal
	Moderate (Hospital)	12.00	10.80	13.20	Normal
	Severe (without MV)	12.58	11.32	13.84	Normal	^34
	Severe (with MV)	28.00	25.20	30.80	Normal
COVID-19 cases progressing, %	Mild COVID-19 to Moderate COVID-19	5.77%	5.19%	6.35%	Beta	^36
	Moderate COVID-19 to Severe COVID-19	20.20%	18.18%	22.22%	Beta	^37
COVID-19 progression, time to progress, days	Mild COVID-19 to Moderate COVID-19	29.00	26.10	31.90	Normal	^36
	Moderate COVID-19 to Severe COVID-19	14.00	12.60	15.40	Normal	^37
Long COVID-19	After mild infection, %	32.67%	29.40%	35.93%	Beta	^38
	After mild infection, %	31.25%	28.13%	34.38%	Beta
	After mild infection, %	31.25%	28.13%	34.38%	Beta
	Duration, days	180.00	162.00	198.00	Normal	^39
Vaccination inputs
Vaccine efficacy, %	Reduction in infections	95.00%	85.50%	100.00%	Beta	^40
	Reduction in hospitalizations	86.00%	77.40%	94.60%	Beta	^41
Intervention efficacy
Reduction in infectious days, days	Mild COVID-19	2.38	2.14	2.61	Normal	^23
	Moderate (Home) COVID-19	2.38	2.14	2.61	Normal
Costs
RD-X19 device cost, $		$0	–	–	None
Health-state costs, $	Mild COVID-19	$57	$51	$63	Gamma	^9
	Moderate (Home) COVID-19	$3,045	$2,741	$3,350	Gamma
	Moderate (Hospital) COVID-19	$9,763	$8,787	$10,739	Gamma	^42
	Severe COVID-19 (without MV)	$14,366	$12,929	$15,803	Gamma	^9
	Severe COVID-19 (with MV)	$33,247	$29,922	$36,572	Gamma	^43
	Post-mild COVID-19	$0	$0	$0	Gamma	^Assumption
	Post-moderate COVID-19	$1,743	$1,569	$1,918	Gamma	^9
	Post-severe COVID-19	$4,213	$3,792	$4,634	Gamma
	Long COVID-19	$0	$0	$0	Gamma	^Assumption
	Recovered	$0	$0	$0	Gamma	^9

The primary cost outcomes were simulated estimates of the total direct incremental cost (total cost when the intervention was adopted minus total standard practice cost) and total direct incremental cost per individual that received the intervention. Clinical outcomes included number of COVID-19 infections and deaths, both in total and stratified by infection severity. Deterministic sensitivity analysis (DSA), probabilistic sensitivity analysis (PSA) randomly sampling model inputs over 1,000 iterations, and scenario analyses (varying uptake, efficacy, and date of introduction of intervention) were performed. No formal statistical testing was conducted.

COVID-19 characteristics

The proportions of diagnosed COVID-19 infections that were mild (74.2%), moderate (14.19%), and severe (11.57%) were fixed across the model time horizon³¹, as were the proportions of moderate cases managed at home, severe cases requiring MV, and the probabilities of experiencing infection progression and long COVID-19^31,33,36,37. Mean duration of infectious and recovery days and time to infection progression differ by infection severity. The time course of long COVID-19 is fixed. Vaccine efficacy was assumed to be 95% for the prevention of laboratory confirmed infection and 86% for vaccine efficacy against COVID-19-related hospitalization (partially vaccinated individuals were not considered to be vaccinated within the context of the model, nor was any drop in efficacy modeled with reduced protections against disease caused by emerging variants of concern, making estimates more conservative)^40,41.

RD-X19 treatment (anti-viral intervention)

The base case was modeled on results from an early feasibility trial of the RD-X19 device, designed as an anti-viral treatment to be used as a complement to vaccines to reduce COVID-19 symptomatic days of disease and duration of SARS-CoV-2 infectivity. RD-X19 was made available to patients with mild-to-moderate COVID-19, ages 18 years and up, who were also eligible for at-home disease management as identified via model assumptions. The course of treatment was twice-daily dosing for 4 days. The model base case assumed that the intervention was available to 10% of all eligible infected individuals starting in the fourth month (1 June 2020 after 3 months model run without intervention) of the model time horizon and that the intervention reduced symptomatic days by 2.4 relative to the standard.

Healthcare costs

A cost was assigned to each infected health state (excluding long COVID-19) and post-COVID-19 health states (excluding post-mild COVID-19). Each health state cost was assumed to account for all aspects of care. In order to identify the costs impacted by the intervention over the cost of the intervention itself, intervention cost was assumed to be $0. All costs, reported in 2020 USD ($), are shown in Table 2.

Results

Cost analysis

In the base case analysis, use of the intervention led to simulated estimates of total direct health care cost savings ranging from $68,788,691 to $135,299,936 across the 3 US states modeled and $4,408,120,862 at the national level (Table 3). The cost saving per person receiving intervention ranged from $2,015 to $2,515 (Table 3). Table 3 presents results of scenario analyses that varied the proportion of eligible infected individuals receiving intervention (5%, 10% [base case], and 25%) alongside alternative intervention clinical benefit scenarios where the time to no or mild symptoms was assumed to be 50% above ([3.6 days [150%]) and 50% below (1.2 days, [50%]) the base case of 2.4 days (100%). Adoption of the intervention results in cost savings per person treated for all combinations with results ranging from a low of $997 (5%, 1.2 days, Alabama) to a high of $3,969 (25%, 3.6 days, Massachusetts). Maximum cost savings per state evaluated with 25% uptake and 150% efficacy (3.6-day reduction) were $250,164,905 in Alabama, $490,498,555 in North Carolina, and $365,729,833 in Massachusetts.

Table 3. Total cost saving and cost saving per person receiving RD-X19.

Costs saving per person per state receiving RD-X19		RD-X19 uptake: Proportion of individuals diagnosed with Mild COVID-19 or Moderate (Home) COVID-19 and receiving RD-X19 (%)
		5%	10%	25%
Efficacy of RD-X19 for Mild COVID-19 or Moderate (Home) COVID-19 individuals	Alabama
	150% (3.6 days)	−$3,011	−$3,043	−$3,140
	100% (2.4 days)	−$2,001	−$2,015	−$2,057
	50% (1.2 days)	−$997	−$1,000	−$1,011
	North Carolina
	150% (3.6 days)	−$3,229	−$3,269	−$3,392
	100% (2.4 days)	−$2,144	−$2,161	−$2,215
	50% (1.2 days)	−$1,068	−$1,072	−$1,085
	Massachusetts
	150% (3.6 days)	−$3,756	−$3,808	−$3,969
	100% (2.4 days)	−$2,492	−$2,515	−$2,586
	50% (1.2 days)	−$1,241	−$1,246	−$1,263
	US National
	150% (3.6 days)	−$3,262	−$3,303	−$3,429
	100% (2.4 days)	−$2,166	−$2,184	−$2,239
	50% (1.2 days)	−$1,078	−$1,083	−$1,096
Total costs per state		RD-X19 uptake: Proportion of individuals diagnosed with Mild COVID-19 or Moderate (Home) COVID-19 and receiving RD-X19 (%)
		5%	10%	25%
Efficacy of RD-X19 for Mild COVID-19 or Moderate (Home) COVID-19 individuals	Alabama
	150% (3.6 days)	−$51,734,270	−$102,613,045	−$250,164,905
	100% (2.4 days)	−$34,584,791	−$68,788,691	−$169,128,810
	50% (1.2 days)	−$17,340,089	−$34,584,791	−$85,748,225
	North Carolina
	150% (3.6 days)	−$101,783,931	−$201,715,989	−$490,498,555
	100% (2.4 days)	−$68,062,155	−$135,299,936	−$332,094,333
	50% (1.2 days)	−$34,134,283	−$68,062,155	−$168,610,507
	Massachusetts
	150% (3.6 days)	−$76,821,422	−$151,785,366	−$365,729,833
	100% (2.4 days)	−$51,421,489	−$102,014,940	−$248,880,202
	50% (1.2 days)	−$25,814,535	−$51,421,489	−$127,002,692
	US National
	150% (3.6 days)	−$3,316,141,651	−$6,572,031,814	−$15,980,911,318
	100% (2.4 days)	−$2,217,467,578	−$4,408,120,862	−$10,819,943,826
	50% (1.2 days)	−$1,112,089,834	−$2,217,467,578	−$5,493,414,397

Base case results are indicated by a blue fill. The incremental cost represents the total cost difference between the RD-X19 and standard practice arms of the model split across all individuals eligible to receive RD-X19. A negative result indicates that switching to RD-X19 leads to a cost reduction.

Abbreviation. COVID-19, coronavirus disease 2019.

Results of deterministic and probabilistic sensitivity analyses are shown in Figure 2. In a deterministic sensitivity analysis, model inputs were varied to identify those with the greatest changes in cost savings per person receiving the intervention. The interventional efficacy (reduction in symptomatic days) and the proportions of the total population over the age of 18 years and of confirmed COVID-19 infections were shown to drive the greatest changes in the cost savings per person receiving the intervention. For Alabama, North Carolina, and Massachusetts, the average probabilistic savings per person receiving intervention (tornado plots) were $2,028 (interquartile range [IQR]: $1,772–$2,242), $2,207 (IQR: $1,909–$2,458), and $2,521 (IQR: $2,204–$2,788), respectively.

Figure 2. Deterministic and probabilistic sensitivity analyses by state. Abbreviation. MV, mechanical ventilation.

COVID-19 incidence and mortality

The base case simulation analysis revealed that intervention with RD-X19 led to an estimated reduction in the cumulative number of mild, moderate, and severe COVID-19 infections across all states as well as a reduction in mortality; the reduction in COVID-19 infections ranged from 10,060 to 21,092 (Figure 3), whereas between 275 and 545 deaths were prevented across all modeled US states (Table 4). At the national level, introduction of the device reduced cases by 686,722 and deaths by 17,748 (Table 4).

Figure 3. Number of cases by severity prevented by state as a function of RD-X19 clinical benefit.

Table 4. Lives saved and cases reduced as a function of efficacy and date of introduction of RD-X19 (base case with 10% penetration).

			RD-X19 introduction: Month where RD-X19 becomes available
			Total incremental infections			Total incremental deaths
			12 months (From June 2020)	8 months (From October 2020)	4 months (From February 2020)	12 months (From June 2020)	8 months (From October 2020)	4 months (From February 2020)
RD-X19 efficacy: effectiveness of RD-X19 for Mild COVID-19 or Moderate (Home) COVID-19 individuals	Alabama
	150% 3.6 days	Mild	−11,164	−4,246	−394	−1	−1	0
		Moderate	−2,130	−809	−74	−19	−8	−1
		Severe	−1,729	−656	−60	−389	−164	−19
		Total	−15,023	−5,712	−527	−410	−172	−20
	100% (Nominal) 2.4 days	Mild	−7,476	−2,830	−263	−1	−1	0
		Moderate	−1,426	−539	−50	−13	−5	−1
		Severe	−1,158	−437	−40	−261	−109	−13
		Total	−10,059	−3,807	−352	−275	−115	−13
	50% 1.2 days	Mild	−3,754	−1,415	−132	0	0	0
		Moderate	−716	−270	−25	−7	−3	0
		Severe	−581	−219	−20	−131	−55	−6
		Total	−5,052	−1,903	−176	−138	−58	−7
	North Carolina
	150% 3.6 days	Mild	−23,422	−9,988	−1,472	−2	−2	−1
		Moderate	−4,455	−1,897	−277	−39	−18	−3
		Severe	−3,600	−1,528	−220	−771	−353	−58
		Total	−31,476	−13,413	−1,969	−812	−373	−62
	100% (Nominal) 2.4 days	Mild	−15,695	−6,663	−982	−2	−1	0
		Moderate	−2,985	−1,265	−185	−26	−12	−2
		Severe	−2,412	−1,019	−147	−517	−236	−39
		Total	−21,092	−8,948	−1,314	−545	−249	−41
	50% 1.2 days	Mild	−7,888	−3,334	−491	−1	−1	0
		Moderate	−1,500	−633	−92	−13	−6	−1
		Severe	−1,212	−510	−73	−260	−118	−19
		Total	−10,600	−4,477	−657	−274	−125	−21
	Massachusetts
	150% 3.6 days	Mild	−18,523	−7,939	−1,385	−2	−1	0
		Moderate	−3,501	−1,496	−258	−30	−14	−3
		Severe	−2,798	−1,190	−200	−586	−272	−52
		Total	−24,821	−10,625	−1,843	−618	−287	−56
	100% (Nominal) 2.4 days	Mild	−12,442	−5,295	−924	−1	−1	0
		Moderate	−2,351	−998	−172	−20	−9	−2
		Severe	−1,877	−793	−134	−394	−181	−35
		Total	−16,670	−7,085	−1,229	−415	−192	−37
	50% 1.2 days	Mild	−6,268	−2,649	−462	−1	0	0
		Moderate	−1,184	−499	−86	−10	−5	−1
		Severe	−945	−396	−67	−198	−91	−17
		Total	−8,397	−3,544	−615	−209	−96	−19
	US National
	150% 3.6 days	Mild	−762,815	−316,004	−47,135	−81	−52	−16
		Moderate	−144,990	−59,952	−8,858	−1,268	−567	−96
		Severe	−117,022	−48,232	−7,008	−25,126	−11,272	−1,822
		Total	−1,024,827	−424,187	−63,001	−26,475	−11,891	−1,933
	100% (Nominal) 2.4 days	Mild	−511,178	−210,771	−31,440	−54	−35	−11
		Moderate	−97,149	−39,984	−5,908	−850	−379	−64
		Severe	−78,394	−32,163	−4,674	−16,844	−7,522	−1,214
		Total	−686,722	−282,918	−42,022	−17,748	−7,935	−1,289
	50% 1.2 days	Mild	−256,908	−105,435	−15,728	−27	−17	−5
		Moderate	−48,820	−20,000	−2,955	−427	−189	−32
		Severe	−39,387	−16,086	−2,338	−8,468	−3,764	−607
		Total	−345,114	−141,521	−21,021	−8,923	−3,971	−644

Base case results are indicated by a blue fill. A negative result indicates that switching to RD-X19 results in a reduction in the total number of individuals infected and diagnosed with COVID-19 individuals in the model as well as a reduction in the total number of COVID-19-related deaths across the model time horizon (1 June 2020 to 31 May 2021).

Abbreviation.COVID-19, coronavirus disease 2019.

Additionally, the same alternative RD-X19 clinical benefit levels (1.2 days, 2.4 days, and 3.6 days) are presented alongside scenarios for intervention availability in Table 4 (June 2020 before the second wave [base case], October 2020 before the third wave, and February 2021 at the tail end of the third wave once vaccines had become available). For each scenario, including the shortest intervention availability time combined with the lowest level of clinical benefit, 10% adoption of RD-X19 reduced both confirmed COVID-19 infections and deaths at each of the individual state and national levels.

Discussion

The COVID-19 pandemic has catalyzed scientific innovation to prevent infection as well as reduce disease burden and transmission in those who develop COVID-19. Although no formal global estimates have been published, the effort has likely prevented millions of symptomatic cases and hundreds of thousands of deaths worldwide. In the US alone, it is estimated that vaccines prevented approximately 139,000 deaths in the first 5 months they were available⁴⁴. However successful, the approved prevention and control strategies continue to leave many individuals at risk of serious illness and death^45,46. Given the distrust of traditional medicine that has emerged in some populations^47,48 during the pandemic, novel antiviral innovations such as RD-X19 are needed in addition to conventional antiviral therapies (e.g. nirmatrelvir/ritonavir tablets and molnupiravir capsules) that may abrogate social, political, operational, and economic constraints of embracing early treatment interventions.

Our model describes how any antiviral treatment with efficacy similar (+/‒ 50%) to RD-X19, as demonstrated in an early feasibility study, can prevent infections, deaths, and associated direct health care costs in outpatients with mild-to-moderate COVID-19 by reducing viral load, symptomatic days, and secondary transmission.

We recreated the course of the pandemic in 3 states representing those with lower, middle, and high vaccine uptake and at the US national level through a mathematical model using data from the CDC. Our results showed that the introduction of RD-X19 to only 10% of eligible patients (base case) with a diagnosis of mild or moderate (outpatient) in North Carolina, a state near the midpoint of vaccine adoption during the modeled period, could have resulted in between 10,600 and 31,476 fewer COVID-19 cases and between 274 and 812 fewer deaths, depending upon real-world effectiveness. The model shows similar cases averted and deaths prevented for the low- and high- vaccine status states of Alabama (cases reduced: 5,051–15,023; deaths averted: 138–410) and Massachusetts (cases reduced: 8,937–24,822; deaths averted: 209–615). In addition, our model describes how early intervention can meaningfully reduce direct health care expenditures. With 25% of the mild-to-moderate (outpatient) infected population using RD-X19 as a complement to vaccines, direct health care expenditures were reduced by approximately $332 million in North Carolina over 12 months. Even at an uptake as low as 5%, direct health care costs were reduced by approximately $68 million in the state. For the other states considered, reductions ranged from a low of approximately $35 million (5%, Alabama) to a high of approximately $249 million (25%, Massachusetts). Using the model to estimate the impact at the national level, subject to the limitations of extrapolation, revealed that at 10% utilization (2.1 million RD-X19 treatments deployed over 12 months), not only were the aggregate number of symptomatic days of illness reduced by 5.04 million but health care expenditures were reduced by approximately $4.4 billion, total infections by 686,722, and total deaths by 17,748.

Finally, our model also shows that antiviral therapeutics like RD-X19, which target delivery to infected individuals early in the disease process (within 3 days of symptom onset and following a positive COVID test), are a necessary and important complement to vaccines broadly delivered to healthy individuals. For example, over the first 5 months that they were available, 124 million full vaccine courses were delivered, preventing an estimated 139,000 deaths (1 life saved for every 892 full courses)⁴⁴. In our model, over the same period and in the base case of 10% uptake, 2.1 million antiviral RD-X19 interventions were self-administered to sick individuals, preventing an additional 17,748 deaths (1 life saved for every 118 interventions, 0.85%). We acknowledge that beyond the model time horizon (May 2021), vaccination rates have increased across the US and globally. However, the emergence of the omicron variant and the likelihood that other variants will emerge, the lack of a robust booster program, booster hesitancy, and breakthrough infections in the US highlight the continued need for new treatment options.

Further, the lifesaving benefits of antiviral therapeutics have now been demonstrated in large, international randomized controlled trials and validate the disease progression model reported in the current work. For example, Merck reported a treatment benefit over placebo of 1 life saved for every 83 courses (1.2%) of molnupiravir administered in their Phase 3 trial¹⁵. Similarly, Pfizer reported a treatment benefit over placebo of 1 life saved for every 90 courses (1.1%) of nirmatrelvir/ritonavir administered¹⁴.

Early interventions such as RD-X19 that not only reduce days of symptomatic disease but also interrupt infection transmission could have a profound impact on the course of the pandemic. Over the past 2 years, we have experienced how the introduction of control measures resulted in significant benefits but also had unintended consequences. While we cannot model or predict the effects on human behavior with the introduction of this type of strategy, we believe that deployed as a complement to vaccines, interventions be they a device like RD-X19 or other antiviral therapies, can accelerate the transition from pandemic to endemic, helping the world return to pre-pandemic conditions. Further, they can maintain utility during the endemic stage by continuing to reduce morbidity, mortality, and direct health care costs, thereby providing relief for infected individuals and their families and reducing societal burdens.

Limitations

This simulation of the impact of a novel, light-based, antiviral intervention administered at home for COVID-19 has several limitations inherent to any modeling exercise. Where possible in our model, we have accounted for these limitations with a combination of conservative assumptions and sensitivity analyses. First, we assumed that treatment benefit was uniform across all adult populations in the modeled cohort. Although this is an exemplary target, it may not be the case in practice for all interventions, especially during the early stages of implementation (e.g. RD-X19 has to-date been evaluated only in the population aged 18–65 years). Second, risk of reinfection is not considered in the model, although evidence suggests up to a 7% risk of symptomatic reinfection⁴⁹. Third, though infectiousness varies over the COVID-19 disease trajectory, we assumed it was constant. We verified that this did not change the findings by providing sensitivity analyses showing that even with intervention efficacy reduced to 50% of the base case, a decline in the incidence of overall infections and deaths was still observed. Fourth, we assumed that uptake of the treatment was instantaneous to modeled levels (5%, 10% and 25%) early in the modeled period. Even with a conservative estimate of 5% uptake, the effects of the device on the trajectory of the pandemic and resultant outcomes were meaningful. Fifth, we assumed that all vaccines, regardless of manufacturer, were equally efficacious (95%), with efficacy instantaneous upon completion of the course of the vaccine (2 doses of the mRNA vaccines and 1 dose of the Johnson & Johnson), that efficacy was constant for the complete duration of the 12-month model period, and that all recipients were protected from infection, not just symptomatic disease. These assumptions estimate that a higher proportion of the population is protected at a higher level than in practice, and therefore drive fewer individuals available for infection in both arms of the model. Additionally, this simulation was based on the observed COVID-19 incidence and vaccination data available at the conclusion of the modeled period. As such, we were not able to project into the future and can only hypothesize the potential impact of introducing RD-X19 or comparable antiviral treatments on potential future waves of COVID-19. Finally, the early feasibility study providing the reference for the base case of shortened duration of symptomatic disease by 2.4 days compared with sham-treated subjects is small (NCT04662671). Although larger studies are needed to confirm the results, and one such study is on-going (NCT04966013), this limitation is considered in the current work through the inclusion of a lower boundary condition of 1.2 days. Further, beyond RD-X19, the model can be used to evaluate the impact of other antiviral therapies on the course of the current pandemic and following endemic, regardless of the method of administration.

Conclusions

Although COVID-19 is likely to evolve into an endemic disease requiring periodic vaccination, many will remain at risk of illness and death due to the emergence of SARS-CoV-2 variants as well as existing and evolving social, political, and economic constraints. Interventions capable of reducing the duration of symptomatic disease and decreasing secondary transmission are needed as a complement to vaccines. Using the novel light-based, antiviral treatment RD-X19 as an example, our simulations show that even with modest efficacy and uptake, the morbidity, mortality, and health care costs can be reduced via deployment of an at-home treatment for mild-to-moderate COVID-19.

Transparency

Declaration of funding

This study was funded by EmitBio, Inc.

Declaration of financial/other relationships

RS, RTT are employees of Coreva Scientific; SG was an employee of Coreva Scientific during model design, interpretation, and initial manuscript development. DE, NS and JO are employees of EmitBio, Inc. MO was an employee of EmitBio, Inc. during model design. CB, JKK, and BF are employees of Cardinal Health.

DE reports personal fees from EmitBio, Inc., its parent, KnowBio LLC, and its Affiliates, outside the submitted work. In addition, Dr. Emerson has a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 17/410,154 issued, a patent ORAL ILLUMINATION DEVICE, 29/757,911 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128935 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210138259 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128936 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128937 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128938 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 11,147,984 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 2021-518715 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, PCT/US21/19785 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210379400 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 2021239894 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210290970 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210290975 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210290971 pending, and a patent ORAL ILLUMINATION DEVICE, 29/780,830 pending.

JO reports personal fees from EmitBio, Inc. its parent, KnowBio LLC, and its Affiliates, outside the submitted work.

NS reports personal fees from EmitBio, Inc., its parent, KnowBio LLC, and its Affiliates, outside the submitted work; In addition, NS has a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 17/410,154 issued, a patent ORAL ILLUMINATION DEVICE, 29/757,911 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128935 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210138259 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128936 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128937 pending, a patent PHOTOTHERAPEUTIC LIGHT FOR TREATMENT OF PATHOGENS, US20210128938 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 11,147,984 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 2021-518715 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, PCT/US21/19785 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210379400 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, 2021239894 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210290970 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210290975 pending, a patent ILLUMINATION DEVICES FOR INDUCING BIOLOGICAL EFFECTS, US20210290971 pending, a patent ORAL ILLUMINATION DEVICE, 29/780,830 pending, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, 15/222,199 issued, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, 15/222,243 issued, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, ZL 2016 8 00559361 issued, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, BR 11 2018 001874 0 pending, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, BR 12 2020 024964 1 pending, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, 202010561507.X pending, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, 16831333.6 pending, a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, 16/709,550 pending, and a patent SYSTEMS AND METHODS FOR PHOTOTHERAPEUTIC MODULATION OF NITRIC OXIDE, 16/898,385 pending.

MO reports personal fees from EmitBio, Inc., its parent, KnowBio LLC, and its Affiliates, outside the submitted work

Peer reviewers on this manuscript have received an honorarium from JME for their review work but have no other relevant financial relationships to disclose.

Author contributions

SG [study concept and design, interpretation of data, drafting manuscript, approval of final manuscript]; RS [study concept and design, interpretation of data, drafting manuscript, approval of final manuscript], DE [interpretation of data, translation of model results to real-world implementation, drafting manuscript, approval of final manuscript], NS [study concept and design, interpretation of data, approval of final manuscript], CS [study concept and design, interpretation of data, drafting manuscript, approval of final manuscript], JO [interpretation of data, approval of final manuscript], MO [study concept and design], RTT [study concept and design, interpretation of data, drafting manuscript, approval of final manuscript], JKK [study concept and design, interpretation of data, drafting manuscript, approval of final manuscript], BF [study concept and design, interpretation of data, drafting manuscript, approval of final manuscript].

Acknowledgements

No assistance in the preparation of this article is to be declared.