Viral Load Kinetics of Severe Acute Respiratory Syndrome Coronavirus 2 in Hospitalized Individuals With Coronavirus Disease 2019

In silico identification of viral loads in cough-generated droplets - Seamless integrated analysis of CFPD-HCD-EWF

BACKGROUND AND OBJECTIVE

Respiratory diseases caused by respiratory viruses have significantly threatened public health worldwide. This study presents a comprehensive approach to predict viral dynamics and the generation of stripped droplets within the mucus layer of the respiratory tract during coughing using a larynx-trachea-bifurcation (LTB) model.

METHODS

This study integrates computational fluid-particle dynamics (CFPD), host-cell dynamics (HCD), and the Eulerian wall film (EWF) model to propose a potential means for seamless integrated analysis. The verified CFPD-HCD coupling model based on a 3D-shell model was used to characterize the severe acute respiratory syndrome, coronavirus 2 (SARS-CoV-2) dynamics in the LTB mucus layer, whereas the EWF model was employed to account for the interfacial fluid to explore the generation mechanism and trace the origin site of droplets exhaled during a coughing event of an infected host.

RESULTS

The results obtained using CFPD delineated the preferential deposition sites for droplets in the laryngeal and tracheal regions. Thus, the analysis of the HCD model showed that the viral load increased rapidly in the laryngeal region during the peak of infection, whereas there was a growth delay in the tracheal region (up to day 8 after infection). After two weeks of infection, the high viral load gradually migrated towards the glottic region. Interestingly, the EWF model demonstrated a high concentration of exhaled droplets originating from the larynx. The coupling technique indicated a concurrent high viral load in the mucus layer and site of origin of the exhaled droplets.

CONCLUSIONS

This interdisciplinary research underscores the seamless analysis from initial exposure to virus-laden droplets, the dynamics of viral infection in the LTB mucus layer, and the re-emission from the coughing activities of an infected host. Our efforts aimed to address the complex challenges at the intersection of viral dynamics and respiratory health, which can contribute to a more detailed understanding and targeted prevention of respiratory diseases.

Changes in Lymphocyte Subpopulations after Remdesivir Therapy for COVID-19: A Brief Report

Remdesivir (RDV) has demonstrated clinical benefit in hospitalized COronaVIrus Disease (COVID)-19 patients. The objective of this brief report was to assess a possible correlation between RDV therapy and the variation in lymphocyte subpopulations. We retrospectively studied 43 hospitalized COVID-19 patients: 30 men and 13 women (mean age 69.3 ± 15 years); 9/43 had received RDV therapy. Six patients had no need for oxygen (severity group 0); 22 were on oxygen treatment with a fraction of inspired oxygen (FiO2) ≤ 50% (group 1); 7 on not-invasive ventilation (group 2); 3 on invasive mechanical ventilation (group 3); and 5 had died (group 4). Cytofluorimetric assessment of lymphocyte subpopulations showed substantial changes after RDV therapy: B lymphocytes and plasmablasts were significantly increased (p = 0.002 and p = 0.08, respectively). Cytotoxic T lymphocytes showed a robust reduction (p = 0.008). No changes were observed in CD4+-T cells and natural killers (NKs). There was a significant reduction in regulatory T cells (Tregs) (p = 0.02) and a significant increase in circulating monocytes (p = 0.03). Stratifying by disease severity, after RDV therapy, patients with severity 0-2 had significantly higher B lymphocyte and monocyte counts and lower memory and effector cytotoxic T cell counts. Instead, patients with severity 3-4 had significantly higher plasmablast and lower memory T cell counts. No significant differences for CD4+-T cells, Tregs, and NKs were observed. Our brief report showed substantial changes in the lymphocyte subpopulations analyzed between patients who did not receive RDV therapy and those after RDV treatment. Despite the small sample size, due to the retrospective nature of this brief report, the substantial changes in lymphocyte subpopulations reported could lead to speculation on the role of RDV treatment both on immune responses against the virus and on the possible downregulation of the cytokine storm observed in patients with more severe disease.

Symptom and Viral Rebound in Untreated SARS-CoV-2 Infection

BACKGROUND

Although symptom and viral rebound have been reported after nirmatrelvir-ritonavir treatment, the trajectories of symptoms and viral load during the natural course of COVID-19 have not been well described.

OBJECTIVE

To characterize symptom and viral rebound in untreated outpatients with mild to moderate COVID-19.

DESIGN

Retrospective analysis of participants in a randomized, placebo-controlled trial. (ClinicalTrials.gov: NCT04518410).

SETTING

Multicenter trial.

PATIENTS

563 participants receiving placebo in the ACTIV-2/A5401 (Adaptive Platform Treatment Trial for Outpatients With COVID-19) platform trial.

MEASUREMENTS

Participants recorded the severity of 13 symptoms daily between days 0 and 28. Nasal swabs were collected for SARS-CoV-2 RNA testing on days 0 to 14, 21, and 28. Symptom rebound was defined as a 4-point increase in total symptom score after improvement any time after study entry. Viral rebound was defined as an increase of at least 0.5 log10 RNA copies/mL from the immediately preceding time point to a viral load of 3.0 log10 copies/mL or higher. High-level viral rebound was defined as an increase of at least 0.5 log10 RNA copies/mL to a viral load of 5.0 log10 copies/mL or higher.

RESULTS

Symptom rebound was identified in 26% of participants at a median of 11 days after initial symptom onset. Viral rebound was detected in 31% and high-level viral rebound in 13% of participants. Most symptom and viral rebound events were transient, because 89% of symptom rebound and 95% of viral rebound events occurred at only a single time point before improving. The combination of symptom and high-level viral rebound was observed in 3% of participants.

LIMITATION

A largely unvaccinated population infected with pre-Omicron variants was evaluated.

CONCLUSION

Symptom or viral relapse in the absence of antiviral treatment is common, but the combination of symptom and viral rebound is rare.

PRIMARY FUNDING SOURCE

National Institute of Allergy and Infectious Diseases.

Remdesivir Influence on SARS-CoV-2 RNA Viral Load Kinetics in Nasopharyngeal Swab Specimens of COVID-19 Hospitalized Patients: A Real-Life Experience

There are still conflicting data on the virological effects of the SARS-CoV-2 direct antivirals used in clinical practice, in spite of the documented clinical efficacy. The aim of this monocentric retrospective study was to compare virologic and laboratory data of patients admitted due to SARS-CoV-2 infection from March to December 2020 treated with either remdesivir (R), a protease inhibitor (lopinavir or darunavir/ritonavir (PI)) or no direct antiviral drugs (NT). Viral load variation was indirectly assessed through PCR cycle threshold (Ct) values on the nasopharyngeal swab, analyzing the results from swabs obtained at ward admission and 7 (±2) days later. Overall, 253 patients were included: patients in the R group were significantly older, more frequently males with a significantly higher percentage of severe COVID-19, requiring more often intensive care admission, compared to the other groups. Ct variation over time did not differ amongst the three treatment groups and did not seem to be influenced by corticosteroid use, even after normalization of the treatment groups for disease severity. Non-survivors had lower Ct on admission and showed a significantly slower viral clearance compared to survivors. CD4 T-lymphocytes absolute count assessed at ward admission correlated with a reduced Ct variation over time. In conclusion, viral clearance appears to be slower in COVID-19 non-survivors, while it seems not to be influenced by the antiviral treatment received.

SARS-CoV-2 viremia and COVID-19 mortality: A prospective observational study

BACKGROUND

SARS-CoV-2 viremia has been found to be a potential prognostic factor in patients hospitalized for COVID-19.

OBJECTIVE

We aimed to assess the association between SARS-CoV-2 viremia and mortality in COVID-19 hospitalized patients during different epidemic periods.

METHODS

A prospective COVID-19 registry was queried to extract all COVID-19 patients with an available SARS-CoV-2 viremia performed at hospital admission between March 2020 and January 2022. SARS-CoV-2 viremia was assessed by means of GeneFinderTM COVID-19 Plus RealAmp Kit assay and SARS-CoV-2 ELITe MGB® Kit using <45 cycle threshold to define positivity. Uni and multivariable logistic regression model were built to assess the association between SARS-CoV-2 positive viremia and death.

RESULTS

Four hundred and forty-five out of 2,822 COVID-19 patients had an available SARS-CoV-2 viremia, prevalently males (64.9%) with a median age of 65 years (IQR 55-75). Patients with a positive SARS-CoV-2 viremia (86/445; 19.3%) more frequently presented with a severe or critical disease (67.4% vs 57.1%) when compared to those with a negative SARS-CoV-2 viremia. Deceased subjects (88/445; 19.8%) were older [75 (IQR 68-82) vs 63 (IQR 54-72)] and showed more frequently a detectable SARS-CoV-2 viremia at admission (60.2% vs 22.7%) when compared to survivors. In univariable analysis a positive SARS-CoV-2 viremia was associated with a higher odd of death [OR 5.16 (95% CI 3.15-8.45)] which was confirmed in the multivariable analysis adjusted for age, biological sex and, disease severity [AOR 6.48 (95% CI 4.05-10.45)]. The association between positive SARS-CoV-2 viremia and death was consistent in the period 1 February 2021-31 January 2022 [AOR 5.86 (95% CI 3.43-10.16)] and in subgroup analysis according to disease severity: mild/moderate [AOR 6.45 (95% CI 2.84-15.17)] and severe/critical COVID-19 patients [AOR 6.98 (95% CI 3.68-13.66)].

CONCLUSIONS

SARS-CoV-2 viremia resulted associated to COVID-19 mortality and should be considered in the initial assessment of COVID-19 hospitalized patients.

Plasma SARS-CoV-2 RNA Levels as a Biomarker of Lower Respiratory Tract SARS-CoV-2 Infection in Critically Ill Patients With COVID-19

Plasma SARS-CoV-2 viral RNA (vRNA) levels are predictive of COVID-19 outcomes in hospitalized patients, but whether plasma vRNA reflects lower respiratory tract (LRT) vRNA levels is unclear. We compared plasma and LRT vRNA levels in serially collected samples from mechanically ventilated patients with COVID-19. LRT and plasma vRNA levels were strongly correlated at first sampling (n = 33, r = 0.83, P < 10-9) and then declined in parallel in available serial samples except in nonsurvivors who exhibited delayed vRNA clearance in LRT samples. Plasma vRNA measurement may offer a practical surrogate of LRT vRNA burden in critically ill patients, especially early after ICU admission.

Impact of Remdesivir on SARS-CoV-2 Clearance in a Real-Life Setting: A Matched-Cohort Study

Background

Evidence regarding the impact of remdesivir (RDV) on SARS-CoV-2 viral clearance (VC) is scarce. The aim of this study was to compare VC timing in hospitalized COVID-19 patients who did or did not receive RDV.

Methods

This was a matched-cohort study of patients hospitalized with pneumonia, a SARS-CoV-2-positive nasopharyngeal swab (NPS) at admission, and at least one NPS during follow-up. Patients who received RDV (cases) and those who did not (controls) were matched in a 1:2 ratio by age, sex, and PaO₂/FiO₂ (P/F) values at admission. NPSs were analyzed using real-time polymerase chain reaction. Time to VC (within 30 days after hospital discharge) was estimated using the Kaplan-Meier curve. A multivariable Cox proportional hazard model was fitted to determine factors associated with VC.

Results

There were 648 patients enrolled in the study (216 cases and 432 controls). VC was observed in 490 patients (75.6%), with a median time of 25 (IQR 16-34) days. Overall, time to VC was similar between cases and controls (p = 0.519). However, time to VC was different when considering both RDV treatment status and age (p = 0.007). A significant finding was also observed when considering both RDV treatment status and P/F values at admission (p = 0.007). A multivariate analysis showed that VC was associated with a younger age (aHR = 0.990, 95% CI 0.983-0.998 per every 10-year increase in age; p = 0.009) and a higher baseline P/F ratio (aHR=1.275, 95% CI 1.029-1.579; p=0.026), but not with RDV treatment status.

Conclusion

Time to VC was similar in cases and controls. However, there was a benefit associated with using RDV in regard to time to VC in younger patients and in those with a P/F ratio ≤200 mmHg at hospital admission.

Viral and Symptom Rebound in Untreated COVID-19 Infection

Background

There are reports of viral RNA and symptom rebound in people with COVID-19 treated with nirmatrelvir/ritonavir. Since the natural course of viral and symptom trajectories of COVID-19 has not been well described, we evaluated the incidence of viral and symptom rebound in untreated outpatients with mild-moderate COVID-19.

Methods

The study population included 568 participants enrolled in the ACTIV-2/A5401 platform trial who received placebo. Anterior nasal swabs were collected for SARS-CoV-2 RNA testing on days 0-14, 21 and 28. Participants recorded the severity of 13 targeted symptoms daily from day 0 to 28. Viral rebound was defined as ≥0.5 log10 viral RNA copies/mL increase and symptom rebound was defined as a 4-point total symptom score increase from baseline. Baseline was defined as study day 4 (primary analysis) or 8 days from symptom onset (secondary analysis).

Findings

In both the primary and secondary analyses, 12% of participants had viral rebound. Viral rebounders were older than non-rebounders (median 54 vs 47 years, P=0.04). Symptom rebound occurred in 27% of participants after initial symptom improvement and in 10% of participants after initial symptom resolution. The combination of high-level viral rebound to ≥5.0 log10 RNA copies/mL and symptom rebound after initial improvement was observed in 1-2% of participants.

Interpretation

Viral RNA rebound or symptom relapse in the absence of antiviral treatment is common, but the combination of high-level viral and symptom rebound is rare.

SARS-CoV-2 Virology

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in 2020 and has led to an unprecedented global pandemic. Understanding the virology behind SARS-CoV-2 infection has provided key insights into our efforts to develop antiviral agents and control the COVID-19 pandemic. In this review, the authors focus on the genomic features of SARS-CoV-2, its intrahost and interhost evolution, viral dynamics in respiratory tract, and systemic dissemination.

Human-Immune-System (HIS) humanized mouse model (DRAGA: HLA-A2.HLA-DR4.Rag1KO.IL-2RγcKO.NOD) for COVID-19

We report a Human Immune System (HIS)-humanized mouse model ("DRAGA": HLA-A2.HLA-DR4.Rag1KO.IL-2 RγcKO.NOD) for COVID-19 research. DRAGA mice express transgenically HLA-class I and class-II molecules in the mouse thymus to promote human T cell development and human B cell Ig-class switching. When infused with human hematopoietic stem cells from cord blood reconstitute a functional human immune system, as well as human epi/endothelial cells in lung and upper respiratory airways expressing the human ACE2 receptor for SARS-CoV-2. The DRAGA mice were able to sustain SARS-CoV-2 infection for at least 25 days. Infected mice showed replicating virus in the lungs, deteriorating clinical condition, and human-like lung immunopathology including human lymphocyte infiltrates, microthrombi and pulmonary sequelae. Among the intra-alveolar and peri-bronchiolar lymphocyte infiltrates, human lung-resident (CD103⁺) CD8⁺ and CD4⁺ T cells were sequestered in epithelial (CD326⁺) lung niches and secreted granzyme B and perforin, suggesting anti-viral cytotoxic activity. Infected mice also mounted human IgG antibody responses to SARS-CoV-2 viral proteins. Hence, HIS-DRAGA mice showed unique advantages as a surrogate in vivo human model for studying SARS-CoV-2 immunopathological mechanisms and testing the safety and efficacy of candidate vaccines and therapeutics.

SARS-CoV-2 nucleocapsid urine antigen in hospitalized patients with Covid-19

Background

SARS-CoV-2 nucleocapsid antigen (N-Ag) can be detected in the blood of patients with Covid-19. We used a highly sensitive and specific assay to explore the presence of N-Ag in urine during the course of Covid-19, and explore its relationship with the severity of the disease.

Methods

We studied urine and blood N-Ag using highly sensitive immunoassay in 82 patients with a SARS-CoV-2 infection proven by PCR.

Results

In the first and second weeks of Covid-19, hospitalized patients tested positive for urinary N-Ag (81.25% and 71.79%, respectively), and blood N-Ag (93.75% and 94.87%, respectively). High urinary N-Ag levels were associated with the absence of SARS-CoV-2 nucleocapsid antibodies, admission in intensive care units, high C-reactive protein levels, lymphopenia, eosinopenia, and high lactate dehydrogenase. A higher accuracy was observed for urine N-Ag as a predictor of severe Covid-19 compared to blood N-Ag.

Conclusions

Our study demonstrate that N-Ag is present in the urine of patients hospitalized in the early phase of Covid-19. As a direct marker of SARS-CoV-2, urinary N-Ag reflects the dissemination of viral compounds in the body. Urine N-Ag may be a useful marker for disease severity of SARS-CoV-2 infections.

Remdesivir significantly reduces SARS-CoV-2 viral load on nasopharyngeal swabs in hospitalized patients with COVID-19: a retrospective case-control study

Remdesivir is a broad‐spectrum antiviral agent able to inhibit the RNA polymerase of SARS‐CoV‐2. At present, studies focusing on the effect of remdesivir on viral load (VL) are few and with contrasting results. Aim of the present study was to evaluate the effect of remdesivir on SARS‐CoV‐2 VL from nasopharyngeal swabs (cycle threshold criterion) in a sample of patients treated with the drug, compared with patients who did not receive the antiviral treatment. This retrospective analysis evaluated patients with (1) real‐time polymerase chain reaction (RT‐PCR) confirmed COVID‐19 diagnosis and (2) availability of at least two positive nasopharyngeal swabs analysed with the same analytic platform (ORF target gene, Ingenius ELITe, ELITechGroup, Puteaux, France). Upper respiratory specimens from nasopharyngeal swabs were collected at admission (T0) and 7–14 days after treatment, upon clinical decision. A total of 27 patients treated with remdesivir (Group A) met the inclusion criteria and were compared with 18 patients (Group B) treated with standard care, matched for baseline clinical characteristics. At baseline, both remdesivir‐treated and nontreated patients showed comparable VLs (21.73 ± 6.81 vs. 19.27 ± 5.24, p = 0.348). At the second swab, remdesivir‐treated patients showed a steeper VL reduction with respect to controls (34.28 ± 7.73 vs. 27.22 ± 3.92; p < 0.001). Longitudinal linear model estimated a mean decrease in cycle threshold equal to 0.61 (SE: 0.09) per day in remdesivir‐treated versus 0.33 (SE: 0.10) per day in remdesivir nontreated patients (p for heterogeneity = 0.045). The present study shows that the administration of remdesivir in hospitalized COVID‐19 patients significantly reduces the VL on nasopharyngeal swabs.

Remdesivir's effect on viral load has not been extensively studied

Remdesivir‐treated patients showed a steeper viral load reduction compared to controls

This could impact on the optimal timing of administration to prevent disease progression

Plasma SARS-CoV-2 RNA levels as a biomarker of lower respiratory tract SARS-CoV-2 infection in critically ill patients with COVID-19

Plasma SARS-CoV-2 viral RNA (vRNA) levels are predictive of COVID-19 outcomes in hospitalized patients, but whether plasma vRNA reflects lower respiratory tract (LRT) vRNA levels is unclear. We compared plasma and LRT vRNA levels in simultaneously collected longitudinal samples from mechanically-ventilated patients with COVID-19. LRT and plasma vRNA levels were strongly correlated at first sampling (r=0.83, p<10 -8 ) and then declined in parallel except in non-survivors who exhibited delayed vRNA clearance in LRT samples. Plasma vRNA measurement may offer a practical surrogate of LRT vRNA burden in critically ill patients, especially early in severe disease.

Recommendations for the management of COVID-19 in patients with haematological malignancies or haematopoietic cell transplantation, from the 2021 European Conference on Infections in Leukaemia (ECIL 9)

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel virus that spread worldwide from 2019 causing the Coronavirus disease 19 (COVID-19) pandemic. SARS-CoV-2 infection is characterised by an initial viral phase followed in some patients by a severe inflammatory phase. Importantly, immunocompromised patients may have a prolonged viral phase, shedding infectious viral particles for months, and absent or dysfunctional inflammatory phase. Among haematological patients, COVID-19 has been associated with high mortality rate in acute leukaemia, high risk-myelodysplastic syndromes, and after haematopoietic cell transplant and chimeric-antigen-receptor-T therapies. The clinical symptoms and signs were similar to that reported for the overall population, but the severity and outcome were worse. The deferral of immunodepleting cellular therapy treatments is recommended for SARS-CoV-2 positive patient, while in the other at-risk cases, the haematological treatment decisions must be weighed between individual risks and benefits. The gold standard for the diagnosis is the detection of viral RNA by nucleic acid testing on nasopharyngeal-swabbed sample, which provides high sensitivity and specificity; while rapid antigen tests have a lower sensitivity, especially in asymptomatic patients. The prevention of SARS-CoV-2 infection is based on strict infection control measures recommended for aerosol-droplet-and-contact transmission. Vaccinations against SARS-CoV-2 has shown high efficacy in reducing community transmission, hospitalisation and deaths due to severe COVID-19 disease in the general population, but immunosuppressed/haematology patients may have lower sero-responsiveness to vaccinations. Moreover, the recent emergence of new variants may require vaccine modifications and strategies to improve efficacy in these vulnerable patients. Beyond supportive care, the specific treatment is directed at viral replication control (antivirals, anti-spike monoclonal antibodies) and, in patients who need it, to the control of inflammation (dexamethasone, anti-Il-6 agents, and others). However, the benefit of all these various prophylactic and therapeutic treatments in haematology patients deserves further studies.

A proposed fractional dynamic system and Monte Carlo-based back analysis for simulating the spreading profile of COVID-19

This paper presents a dynamic system for estimating the spreading profile of COVID-19 in Thailand, taking into account the effects of vaccination and social distancing. For this purpose, a compartmental network is built in which the population is divided into nine mutually exclusive nodes, including susceptible, insusceptible, exposed, infected, vaccinated, recovered, quarantined, hospitalized, and dead. The weight of edges denotes the interaction between the nodes, modeled by a series of conversion rates. Next, the compartmental network and corresponding rates are incorporated into a system of fractional partial differential equations to define the model governing the problem concerned. The fractional degree corresponding to each compartment is considered the node weight in the proposed network. Next, a Monte Carlo-based optimization method is proposed to fit the fractional compartmental network to the actual COVID-19 data of Thailand collected from the World Health Organization. Further, a sensitivity analysis is conducted on the node weights, i.e., fractional orders, to reveal their effect on the accuracy of the fit and model predictions. The results show that the flexibility of the model to adapt to the observed data is markedly improved by lowering the order of the differential equations from unity to a fractional order. The final results show that, assuming the current pandemic situation, the number of infected, recovered, and dead cases in Thailand will, respectively, reach 4300, 4.5 × 10 6 , and 36,000 by the end of 2021.

Mathematical Modeling of Remdesivir to Treat COVID-19: Can Dosing Be Optimized?

The antiviral remdesivir has been approved by regulatory bodies such as the European Medicines Agency (EMA) and the US Food and Drug administration (FDA) for the treatment of COVID-19. However, its efficacy is debated and toxicity concerns might limit the therapeutic range of this drug. Computational models that aid in balancing efficacy and toxicity would be of great help. Parametrizing models is difficult because the prodrug remdesivir is metabolized to its active form (RDV-TP) upon cell entry, which complicates dose-activity relationships. Here, we employ a computational model that allows drug efficacy predictions based on the binding affinity of RDV-TP for its target polymerase in SARS-CoV-2. We identify an optimal infusion rate to maximize remdesivir efficacy. We also assess drug efficacy in suppressing both wild-type and resistant strains, and thereby describe a drug regimen that may select for resistance. Our results differ from predictions using prodrug dose-response curves (pseudo-EC50s). We expect that reaching 90% inhibition (EC90) is insufficient to suppress SARS-CoV-2 in the lungs. While standard dosing mildly inhibits viral polymerase and therefore likely reduces morbidity, we also expect selection for resistant mutants for most realistic parameter ranges. To increase efficacy and safeguard against resistance, we recommend more clinical trials with dosing regimens that substantially increase the levels of RDV-TP and/or pair remdesivir with companion antivirals.