Identification of a Druggable Site on GRP78 at the GRP78-SARS-CoV-2 Interface and Compounds to Disrupt that Interface (preprint)

SARS-CoV-2, the virus that causes COVID-19, led to a global health emergency that claimed the lives of millions. Despite the widespread availability of vaccines, the virus continues to exist in the population in an endemic state which allows for the continued emergence of new variants. Most of the current vaccines target the spike glycoprotein interface of SARS-CoV-2, creating a selection pressure favoring viral immune evasion. Antivirals targeting other molecular interactions of SARS-CoV-2 can help slow viral evolution by providing orthogonal selection pressures on the virus. GRP78 is a host auxiliary factor that mediates binding of the SARS-CoV- 2 spike protein to human cellular ACE2, the primary pathway of cell infection. As GRP78 forms a ternary complex with SARS-CoV-2 spike protein and ACE2, disrupting the formation of this complex is expected to hinder viral entry into host cells. Here, we developed a model of the GRP78-spike protein-ACE2 complex. We then used that model together with hot spot mapping of the GRP78 structure to identify the putative binding site for spike protein on GRP78. Next, we performed structure-based virtual screening of known drug/candidate drug libraries to identify binders to GRP78 that are expected to disrupt spike protein binding to the GRP78, and thereby preventing viral entry to the host cell. A subset of these compounds have previously been shown to have some activity against SARS-CoV-2. The identified hits are starting points for the further development of novel SARS-CoV-2 therapeutics, potentially serving as proof-of-concept for GRP78 as a potential drug target for other viruses.

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic (preprint)

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests (with a high false negative rate) due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2’s propensity for asymptomatic transmission, raise the question “how reliable was contact tracing for COVID-19 in the United States”? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62%-1.68%) of transmission events with PCR testing and 0.88% (95% uncertainty interval 0.86%-0.89%) with rapid antigen testing. When considering an optimal scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6%-62.8%). These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic (preprint)

Contact tracing forms a crucial part of the public-health toolbox in mitigating and understanding emergent pathogens and nascent disease outbreaks. Contact tracing in the United States was conducted during the pre-Omicron phase of the ongoing COVID-19 pandemic. This tracing relied on voluntary reporting and responses, often using rapid antigen tests (with a high false negative rate) due to lack of accessibility to PCR tests. These limitations, combined with SARS-CoV-2s propensity for asymptomatic transmission, raise the question how reliable was contact tracing for COVID-19 in the United States? We answered this question using a Markov model to examine the efficiency with which transmission could be detected based on the design and response rates of contact tracing studies in the United States. Our results suggest that contact tracing protocols in the U.S. are unlikely to have identified more than 1.65% (95% uncertainty interval: 1.62%-1.68%) of transmission events with PCR testing and 0.88% (95% uncertainty interval 0.86%-0.89%) with rapid antigen testing. When considering an optimal scenario, based on compliance rates in East Asia with PCR testing, this increases to 62.7% (95% uncertainty interval: 62.6%-62.8%). These findings highlight the limitations in interpretability for studies of SARS-CoV-2 disease spread based on U.S. contact tracing and underscore the vulnerability of the population to future disease outbreaks, for SARS-CoV-2 and other pathogens.

The gray swan: model-based assessment of the risk of sudden failure of hybrid immunity to SARS-CoV-2 (preprint)

In the fourth year of the COVID-19 pandemic, public health authorities worldwide have adopted a strategy of learning to live with SARS-CoV-2. This has involved the removal of measures for limiting viral spread, resulting in a large burden of recurrent SARS-CoV-2 infections. Crucial for managing this burden is the concept of the so-called wall of hybrid immunity, through repeated reinfections and vaccine boosters, to reduce the risk of severe disease and death. Protection against both infection and severe disease is provided by the induction of neutralizing antibodies (nAbs) against SARS-CoV-2. However, pharmacokinetic (PK) waning and rapid viral evolution both degrade nAb binding titers. The recent emergence of variants with strongly immune evasive potential against both the vaccinal and natural immune responses raises the question of whether the wall of population-level immunity can be maintained in the face of large jumps in nAb binding potency. Here we use an agent-based simulation to address this question. Our findings suggest large jumps in viral evolution may cause failure of population immunity resulting in sudden increases in mortality. As a rise in mortality will only become apparent in the weeks following a wave of disease, reactive public health strategies will not be able to provide meaningful risk mitigation. Learning to live with the virus could thus lead to large death tolls with very little warning. Our work points to the importance of proactive management strategies for the ongoing pandemic, and to the need for multifactorial approaches to COVID-19 disease control.

The impact of vaccination frequency on COVID-19 public health outcomes: A model-based analysis (preprint)

While the rapid deployment of SARS-CoV-2 vaccines had a significant impact on the ongoing COVID-19 pandemic, rapid viral immune evasion and waning neutralizing antibody titers have degraded vaccine efficacy. Nevertheless, vaccine manufacturers and public health authorities have a number of levers at their disposal to maximize the benefits of vaccination. Here, we use an agent-based modeling framework coupled with the outputs of a population pharmacokinetic model to examine the impact of boosting frequency and durability of vaccinal response on vaccine efficacy. Our work suggests that repeated dosing at frequent intervals (multiple times a year) may offset the degradation of vaccine efficacy, preserving their utility in managing the ongoing pandemic. Our work relies on assumptions about antibody accumulation and the tolerability of repeated vaccine doses. Given the practical significance of potential improvements in vaccinal utility, clinical research to better understand the effects of repeated vaccination would be highly impactful. These findings are particularly relevant as public health authorities worldwide seek to reduce the frequency of boosters to once a year or less. Our work suggests practical recommendations for vaccine manufacturers and public health authorities and draws attention to the possibility that better outcomes for SARS-CoV-2 public health remain within reach.

Antibody escape, the risk of serotype formation, and rapid immune waning: modeling the implications of SARS-CoV-2 immune evasion (preprint)

As the COVID-19 pandemic progresses, widespread community transmission of SARS-CoV-2 has ushered in a volatile era of viral immune evasion rather than the much-heralded stability of "endemicity" or "herd immunity." At this point, an array of viral variants has rendered essentially all monoclonal antibody therapeutics obsolete and strongly undermined the impact of vaccinal immunity on SARS-CoV-2 transmission. In this work, we demonstrate that antigenic drift resulting in evasion of pre-existing immunity is highly evolutionarily favored and likely to cause waves of short-term transmission. In the long-term, invading variants that induce weak cross-immunity against pre-existing strains may co-circulate with those pre-existing strains. This would result in the formation of serotypes that increase disease burden, complicate SARS-CoV-2 control and raise the potential for increases in viral virulence. Less durable immunity does not drive positive selection as a trait, but such strains may transmit at high levels if they establish. Overall, our results draw attention to the importance of inter-strain cross-immunity as a driver of transmission trends and the importance of early immune evasion data to predict the trajectory of the pandemic.

Shielding under endemic SARS-CoV-2 conditions is easier said than done: a model-based analysis (preprint)

As the COVID-19 pandemic continues unabated, many governments and public-health bodies worldwide have ceased to implement concerted measures for limiting viral spread, placing the onus instead on the individual. In this paper, we examine the feasibility of this proposition using an agent-based model to simulate the impact of individual shielding behaviors on reinfection frequency. We derive estimates of heterogeneity in immune protection from a population pharmacokinetic (pop PK) model of antibody kinetics following infection and variation in contact rate based on published estimates. Our results suggest that individuals seeking to opt out of adverse outcomes upon SARS-CoV-2 infection will find it challenging to do so, as large reductions in contact rate are required to reduce the risk of infection. Our findings suggest the importance of a multilayered strategy for those seeking to reduce the risk of infection. This work also suggests the importance of public health interventions such as universal masking in essential venues and air quality standards to ensure individual freedom of choice regarding COVID-19.

Vaccines alone cannot slow the evolution of SARS-CoV-2 (preprint)

The rapid emergence of immune-evading viral variants of SARS-CoV-2 calls into question the practicality of a vaccine-only public health strategy for managing the ongoing COVID-19 pandemic. It has been suggested that widespread vaccination is necessary to prevent the emergence of future immune-evading mutants. Here we examine that proposition using stochastic computational models of viral transmission and mutation. Specifically, we look at the likelihood of emergence of immune escape variants requiring multiple mutations, and the impact of vaccination on this process. Our results suggest that the transmission rate of intermediate SARS-CoV-2 mutants will impact the rate at which novel immune-evading variants will appear. While vaccination can lower the rate at which new variants appear, other interventions that reduce transmission can also have the same effect. Crucially, relying solely on widespread and repeated vaccination (vaccinating the entire population multiple times a year) is not sufficient to prevent the emergence of novel immune-evading strains if transmission rates remain high within the population. Thus, vaccines alone are incapable of slowing the pace of evolution of immune evasion, and vaccinal protection against severe and fatal outcomes for COVID-19 patients is therefore not assured.

Heterogeneity in vaccinal immunity to SARS-CoV-2 can be addressed by a personalized booster strategy (preprint)

The ongoing COVID-19 pandemic has placed an unprecedented burden on global health. Crucial for managing this burden, the existing SARS-CoV-2 vaccines have substantially reduced the risk of severe disease and death up to this point. The induction of neutralizing antibodies (nAbs) by these vaccines leads to protection against both infection and severe disease. However, pharmacokinetic (PK) waning and rapid viral evolution degrade neutralizing antibody binding titers, leading to a rapid loss of vaccinal protection against infection occurring on the order of months after vaccination. Additionally, inter-individual heterogeneity in the strength and durability of the vaccine-induced neutralizing response to SARS-CoV-2 can create a further public-health risk by placing a subset of the population at risk. Here we incorporate the heterogeneity in inter-individual response into a pharmacokinetic/ pharmacodynamic (PK/PD) model to project the degree of heterogeneity in immune protection. We extend our model-based approach to examine the impact of evolutionary immune evasion on vaccinal protection. Our findings suggest that viral evolution can be expected to impact the effectiveness of vaccinal protection against severe disease, particularly for individuals with a shorter duration of immune response. One possible solution to immune heterogeneity may be more frequent boosting for individuals with a weaker immune response. We demonstrate a model-based approach to targeted boosting that involves the use of the ECLIA RBD assay to identify individuals whose immune response is insufficient for protection against severe disease. Our work suggests that vaccinal protection against severe disease is not assured and provides a path forward to reducing the risk to immunologically vulnerable individuals.

No magic bullet: limiting in-school transmission in the face of variable SARS-CoV-2 viral loads (preprint)

In the face of a long-running pandemic, understanding the drivers of ongoing SARS-CoV-2 transmission is crucial for the rational management of COVID-19 disease burden. Keeping schools open has emerged as a vital societal imperative during the pandemic, but in-school transmission of SARS-CoV-2 can contribute to further prolonging the pandemic. In this context, the role of schools in driving SARS-CoV-2 transmission acquires critical importance. Here we model in-school transmission from first principles to investigate the effectiveness of layered mitigation strategies on limiting in-school spread. We examine the effect of masks and air quality (ventilation, filtration and ionizers) on steady-state viral load in classrooms, as well as on the number of particles inhaled by an uninfected person. The effectiveness of these measures in limiting viral transmission is assessed for variants with different levels of mean viral load (Wuhan, Delta, Omicron). Our results suggest that a layered mitigation strategy can be used effectively to limit in-school transmission, with certain limitations. First, poorly designed strategies (insufficient ventilation, no masks, staying open under high levels of community transmission) will permit in-school spread even if some level of mitigation is ostensibly present. Second, for viral variants that are sufficiently contagious, it may be difficult to construct any set of interventions capable of blocking transmission once an infected individual is present, underscoring the importance of other measures. Our findings provide several practical recommendations: the use of a layered mitigation strategy that is designed to limit transmission, with other measures such as frequent surveillance testing and smaller class sizes (such as by offering remote schooling options to those who prefer it) as needed.

Endemicity is not a victory: the unmitigated downside risks of widespread SARS-CoV-2 transmission (preprint)

We have entered a new phase of the ongoing COVID-19 pandemic, as the strategy of relying solely on the current SARS-CoV-2 vaccines to bring the pandemic to an end has become infeasible. In response, public-health authorities in many countries have advocated for a strategy of using the vaccines to limit morbidity and mortality while permitting unchecked SARS-CoV-2 spread (“learning to live with the disease”). The feasibility of this strategy is critically dependent on the infection fatality rate (IFR) of COVID-19. An expectation exists, both in the lay public and in the scientific community, that future waves of the virus will exhibit decreased IFR, either due to viral attenuation or the progressive buildup of immunity. In this work, we examine the basis for that expectation, assessing the impact of virulence on transmission. Our findings suggest that large increases in virulence for SARS-CoV-2 would result in minimal loss of transmission, implying that the IFR may be free to increase or decrease under neutral evolutionary drift. We further examine the effect of changes in the IFR on the steady-state death toll under conditions of endemic COVID-19. Our modeling suggests that endemic SARS-CoV-2 implies vast transmission resulting in yearly US COVID-19 death tolls numbering in the hundreds of thousands under many plausible scenarios, with even modest increases in the IFR leading to an unsustainable mortality burden. Our findings thus highlight the critical importance of enacting a concerted strategy (involving for example global access to vaccines, therapeutics, prophylactics and nonpharmaceutical interventions) to suppress SARS-CoV-2 transmission, thereby reducing the risk of catastrophic outcomes. Our findings also highlight the importance of continued investment in novel biomedical interventions to prevent viral transmission.

A model-based approach to improve intranasal sprays for respiratory viral infections (preprint)

Drug delivery for viral respiratory infections, such as SARS-CoV-2, can be enhanced significantly by targeting the nasopharynx, which is the dominant initial infection site in the upper airway, for example by nasal sprays. However, under the standard recommended spray usage protocol (“Current Use”, or CU), the nozzle enters the nose almost vertically, resulting in sub-optimal deposition of drug droplets at the nasopharynx. Using computational fluid dynamics simulations in two anatomic nasal geometries, along with experimental validation of the generic findings in a different third subject, we have identified a new “Improved Use” (or, IU) spray protocol. It entails pointing the spray bottle at a shallower angle (almost horizontally), aiming slightly toward the cheeks. We have simulated the performance of this protocol for conically injected spray droplet sizes of 1 – 24 μ m, at two breathing rates: 15 and 30 L/min. The lower flowrate corresponds to resting breathing and follows a viscous-laminar model; the higher rate, standing in for moderate breathing conditions, is turbulent and is tracked via Large Eddy Simulation. The results show that (a) droplets sized between ∼ 6 – 14 μ m are most efficient at direct landing over the nasopharyngeal viral infection hot-spot; and (b) targeted drug delivery via IU outperforms CU by approximately 2 orders-of-magnitude, under the two tested inhalation conditions. Also quite importantly, the improved delivery strategy, facilitated by the IU protocol, is found to be robust to small perturbations in spray direction, underlining the practical utility of this simple change in nasal spray administration protocol.

The specter of Manaus: the risks of a rapid return to pre-pandemic conditions after COVID-19 vaccine rollout (preprint)

The development and deployment of several SARS-CoV-2 vaccines in a little over a year is an unprecedented achievement of modern medicine. The high levels of efficacy against transmission for some of these vaccines makes it feasible to use them to suppress SARS-CoV-2 altogether in regions with high vaccine acceptance. However, viral variants with reduced susceptibility to vaccinal and natural immunity threaten the utility of vaccines, particularly in scenarios where a return to pre-pandemic conditions occurs before the suppression of SARS- CoV-2 transmission. In this work we model the situation in the United States at present, to demonstrate how the P.1 variant of SARS-CoV-2 can cause a rebound wave of COVID-19 in a matter of months, similar to what happened in Manaus at the beginning of this year. A high burden of morbidity (and likely mortality) remains possible, even if the vaccine is partially effective against new variants and widely accepted. Our modeling suggests that variants that are already present within the population may be capable of quickly defeating the vaccines as a public health intervention, a fatal flaw in strategies that emphasize rapid reopening before achieving control of SARS-CoV-2.

Detecting in-school transmission of SARS-CoV-2 from case ratios and documented clusters (preprint)

Claims that in-person schooling has not amplified SARS-CoV-2 transmission are based on similar infection rates in schools and their surrounding communities and limited numbers of documented in-school transmission events. Simulations assuming high in-school transmission suggest that these metrics cannot exclude the possibility that transmission in schools exacerbated overall pandemic risks.

Controlling long-term SARS-CoV-2 infections is important for slowing viral evolution (preprint)

The rapid emergence and expansion of novel SARS-CoV-2 variants is an unpleasant surprise that threatens our ability to achieve herd immunity for COVID-19. These fitter SARS- CoV-2 variants often harbor multiple point mutations, conferring one or more traits that provide an evolutionary advantage, such as increased transmissibility, immune evasion and longer infection duration. In a number of cases, variant emergence has been linked to long-term infections in individuals who were either immunocompromised or treated with convalescent plasma. In this paper, we explore the mechanism by which fitter variants of SARS-CoV-2 arise during long-term infections using a mathematical model of viral evolution and identify means by which this evolution can be slowed. While viral load and infection duration play a strong role in favoring the emergence of such variants, the overall probability of emergence and subsequent transmission from any given infection is low, suggesting that viral variant emergence and establishment is a product of random chance. To the extent that luck plays a role in favoring the emergence of novel viral variants with an evolutionary advantage, targeting these low-probability random events might allow us to tip the balance of fortune away from these advantageous variants and prevent them from being established in the population.

Using translational in vitro-in vivo modeling to improve drug repurposing outcomes for inhaled COVID-19 therapeutics (preprint)

The ongoing COVID-19 pandemic has created an urgent need for antiviral treatments that can be deployed rapidly. Drug repurposing represents a promising means of achieving this objective, but repurposing efforts are often unsuccessful. A common hurdle to effective drug repurposing is a failure to achieve a sufficient therapeutic window in the new indication. A clear example is the use of ivermectin in COVID-19, where the approved dose (administered orally) fails to achieve therapeutic concentrations in the lungs. Our proposed solution to the problem of ineffective drug repurposing for COVID-19 antivirals is two-fold: to broaden the therapeutic window by reformulating therapeutics for the pulmonary route, and to select drug repurposing candidates based on their model-predicted therapeutic index for inhalation. In this article, we propose a two-stage model-driven screening and validation process for selecting inhaled antiviral drug repurposing candidates. While we have applied this approach in the specific context of COVID-19, this in vitro-in vivo translational methodology is also broadly applicable to repurposing drugs for diseases of the lower respiratory tract.

Using mixed-effects modeling to estimate decay kinetics of response to SARS-CoV-2 infection (preprint)

The duration of natural immunity in response to SARS-CoV-2 is a matter of some debate in the literature at present. For example, in a recent publication characterizing SARS-CoV-2 immunity over time, the authors fit pooled longitudinal data, using fitted slopes to infer the duration of SARS-CoV-2 immunity. In fact, such approaches can lead to misleading conclusions as a result of statistical model-fitting artifacts. To exemplify this phenomenon, we reanalyzed one of the markers (pseudovirus neutralizing titer) in the publication, using mixed-effects modeling, a methodology better suited to longitudinal datasets like these. Our findings showed that the half-life was both longer and more variable than reported by the authors. The example selected by us here illustrates the utility of mixed-effects modeling in provide more accurate estimates of the duration and heterogeneity of half-lives of molecular and cellular biomarkers of SARS-CoV-2 immunity.

Beyond the new normal: assessing the feasibility of vaccine-based elimination of SARS-CoV-2 (preprint)

As the COVID-19 pandemic drags into its second year, there is hope on the horizon, in the form of SARS-CoV-2 vaccines which promise disease elimination and a return to pre-pandemic normalcy. In this study we critically examine the basis for that hope, using an epidemiological modeling framework to establish the link between vaccine characteristics and effectiveness in bringing an end to this unprecedented public health crisis. Our findings suggest that vaccines that do not prevent infection will allow extensive endemic SARS-CoV-2 spread upon a return to pre-pandemic social and economic conditions. Vaccines that only reduce symptomatic COVID-19 or mortality will fail to mitigate serious COVID-19 mortality risks, particularly in the over-65 population, likely resulting in hundreds of thousands of US deaths on a yearly basis. Our modeling points to the possibility of complete SARS-CoV-2 elimination with high population-level compliance and a vaccine that is highly effective at reducing SARS-CoV-2 infection. Notably, vaccine-mediated reduction of transmission is critical for elimination, and in order for partially-effective vaccines to play a positive role in SARS-CoV-2 elimination, other stackable (complementary) interventions must be deployed simultaneously.

Individually Optimal Choices can be Collectively Disastrous in COVID-19 Disease Control (preprint)

Background: The word ‘pandemic’ conjures dystopian images of bodies stacked in the streets and societies on the brink of collapse. Despite this frightening picture, denialism and noncompliance with public health measures are common in the historical record, for example during the 1918 Influenza pandemic or the 2015 Ebola epidemic. The unique characteristics of SARS-CoV-2—its high basic reproduction number (R0), time-limited natural immunity and considerable potential for asymptomatic spread—exacerbate the public health repercussions of noncompliance with interventions (such as vaccines and masks) to limit disease transmission. Our work explores the rationality and impact of noncompliance with COVID-19 disease control measures. Methods: In this work, we used game theory to explore when noncompliance confers a perceived benefit to individuals. We then used epidemiological modeling to predict the impact of noncompliance on control of COVID-19, demonstrating that the presence of a noncompliant subpopulation prevents suppression of disease spread. Results: Our modeling demonstrating that noncompliance is a Nash equilibrium under a broad set of conditions, and that the existence of a noncompliant population can result in extensive endemic disease in the long-term after a return to pre-pandemic social and economic activity. Endemic disease poses a threat for both compliant and noncompliant individuals; all community members are protected if complete suppression is achieved, which is only possible with a high degree of compliance. For interventions that are highly effective at preventing disease spread, however, the consequences of noncompliance are borne disproportionately by noncompliant individuals. Conclusions: In sum, our work demonstrates the limits of free-market approaches to compliance with disease control measures during a pandemic. The act of noncompliance with disease intervention measures creates a negative externality, rendering COVID-19 disease control ineffective in the short term and making complete suppression impossible in the long term. Our work underscores the importance of developing effective strategies for prophylaxis through public health measures aimed at complete suppression and the need to focus on compliance at a population level.

From SARS-CoV-2 infection to COVID-19 disease: a proposed mechanism for viral spread to the lower airway based on in silico estimation of virion flow rates (preprint)

While the nasopharynx in the upper respiratory airway is the dominant initial infection site for SARS-CoV-2, the physiologic mechanism that launches the infection in the lower airway is still not well-understood. Based on the rapidity with which SARS-CoV-2 infection progresses to the lungs, it has been conjectured that the nasopharynx acts as the seeding zone for subsequent contamination of the lower airway via aspiration of virus-laden boluses of nasopharyngeal fluids. In this study, we examine the plausibility of this proposed mechanism. To this end, we have developed computational fluid mechanics models of the inhalation process in two medical imaging based airway reconstructions and have quantified the nasopharyngeal liquid volume ingested into the lower airspace during each aspiration. The numerical predictions are validated by comparing the number of projected aspirations (approximately 2 - 4) during an eight-hour sleep cycle with prior observational findings of 3 aspirations in human subjects. Extending the numerical trends on aspiration volume to earlier records on aspiration frequency for the entire day indicates a total aspirated nasopharyngeal liquid volume of 0.3 - 0.76 ml per day. We then used sputum assessment data from hospitalized COVID-19 patients to estimate the number of virions that are transmitted daily to the lungs via nasopharyngeal liquid boluses. For mean sputum viral load, our modeling projects that the number of virions penetrating to the lower airway per day will range over 2.1(10^6) - 5.3(10^6); for peak viral load, the corresponding number of penetrating virions hovers between 7.1(10^8) - 17.9(10^8). These findings fill in a key piece of the mechanistic puzzle of the progression from SARS-CoV-2 infection of the nasopharynx to the development of COVID-19 disease within a patient, and point to dysphagia as a potential underlying risk factor for COVID-19. The findings also have significant practical implications in the design of COVID-19 prophylactics and therapeutics that aim to constrain the pathogenic progress of the disease within the limits of the upper airway.