Long COVID brain fog and muscle pain are associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute infection.

Introduction: The incidence of long COVID is substantial, even in people with mild to moderate acute COVID-19. The role of early viral kinetics in the subsequent development of long COVID is largely unknown, especially in individuals who were not hospitalized for acute COVID-19. Methods: Seventy-three non-hospitalized adult participants were enrolled within approximately 48 hours of their first positive SARS-CoV-2 RT-PCR test, and mid-turbinate nasal and saliva samples were collected up to 9 times within the first 45 days after enrollment. Samples were assayed for SARS-CoV-2 using RT-PCR and additional SARS-CoV-2 test results were abstracted from the clinical record. Each participant indicated the presence and severity of 49 long COVID symptoms at 1-, 3-, 6-, 12-, and 18-months post-COVID-19 diagnosis. Time from acute COVID-19 illness onset to SARS-CoV-2 RNA clearance greater or less than 28 days was tested for association with the presence or absence of each of 49 long COVID symptoms at 90+ days from acute COVID-19 symptom onset. Results: Self-reported brain fog and muscle pain at 90+ days after acute COVID-19 onset were negatively associated with viral RNA clearance within 28 days of acute COVID-19 onset with adjustment for age, sex, BMI ≥ 25, and COVID vaccination status prior to COVID-19 (brain fog: aRR 0.46, 95% CI 0.22-0.95; muscle pain: aRR 0.28, 95% CI 0.08-0.94). Participants reporting higher severity brain fog or muscle pain at 90+ days after acute COVID-19 onset were less likely to have cleared SARS-CoV-2 RNA within 28 days. The acute viral RNA decay trajectories of participants who did and did not later go on to experience brain fog 90+ days after acute COVID-19 onset were distinct. Discussion: This work indicates that at least two long COVID symptoms - brain fog and muscle pain - at 90+ days from acute COVID-19 onset are specifically associated with prolonged time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute COVID-19. This finding provides evidence that delayed immune clearance of SARS-CoV-2 antigen or greater amount or duration of viral antigen burden in the upper respiratory tract during acute COVID-19 are directly linked to long COVID. This work suggests that host-pathogen interactions during the first few weeks after acute COVID-19 onset have an impact on long COVID risk months later.

Modeling in higher dimensions to improve diagnostic testing accuracy: Theory and examples for multiplex saliva-based SARS-CoV-2 antibody assays.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the importance and challenges of correctly interpreting antibody test results. Identification of positive and negative samples requires a classification strategy with low error rates, which is hard to achieve when the corresponding measurement values overlap. Additional uncertainty arises when classification schemes fail to account for complicated structure in data. We address these problems through a mathematical framework that combines high dimensional data modeling and optimal decision theory. Specifically, we show that appropriately increasing the dimension of data better separates positive and negative populations and reveals nuanced structure that can be described in terms of mathematical models. We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics. We validate the usefulness of this approach in the context of a multiplex salivary SARS-CoV-2 immunoglobulin G assay dataset. This example illustrates how our analysis: (i) improves the assay accuracy, (e.g. lowers classification errors by up to 42% compared to CI methods); (ii) reduces the number of indeterminate samples when an inconclusive class is permissible, (e.g. by 40% compared to the original analysis of the example multiplex dataset) and (iii) decreases the number of antigens needed to classify samples. Our work showcases the power of mathematical modeling in diagnostic classification and highlights a method that can be adopted broadly in public health and clinical settings.

Methodological approaches to optimize multiplex oral fluid SARS-CoV-2 IgG assay performance and correlation with serologic and neutralizing antibody responses.

BACKGROUND: Oral fluid (hereafter, saliva) is a non-invasive and attractive alternative to blood for SARS-CoV-2 IgG testing; however, the heterogeneity of saliva as a matrix poses challenges for immunoassay performance. OBJECTIVES: To optimize performance of a magnetic microparticle-based multiplex immunoassay (MIA) for SARS-CoV-2 IgG measurement in saliva, with consideration of: i) threshold setting and validation across different MIA bead batches; ii) sample qualification based on salivary total IgG concentration; iii) calibration to U.S. SARS-CoV-2 serological standard binding antibody units (BAU); and iv) correlations with blood-based SARS-CoV-2 serological and neutralizing antibody (nAb) assays. METHODS: The salivary SARS-CoV-2 IgG MIA included 2 nucleocapsid (N), 3 receptor-binding domain (RBD), and 2 spike protein (S) antigens. Gingival crevicular fluid (GCF) swab saliva samples were collected before December 2019 (n = 555) and after molecular test-confirmed SARS-CoV-2 infection from 113 individuals (providing up to 5 repeated-measures; n = 398) and used to optimize and validate MIA performance (total n = 953). Combinations of IgG responses to N, RBD and S and total salivary IgG concentration (µg/mL) as a qualifier of nonreactive samples were optimized and validated, calibrated to the U.S. SARS-CoV-2 serological standard, and correlated with blood-based SARS-CoV-2 IgG ELISA and nAb assays. RESULTS: The sum of signal to cutoff (S/Co) to all seven MIA SARS-CoV-2 antigens and disqualification of nonreactive saliva samples with ≤15 µg/mL total IgG led to correct classification of 62/62 positives (sensitivity [Se] = 100.0%; 95% confidence interval [CI] = 94.8%, 100.0%) and 108/109 negatives (specificity [Sp] = 99.1%; 95% CI = 97.3%, 100.0%) at 8-million beads coupling scale and 80/81 positives (Se = 98.8%; 95% CI = 93.3%, 100.0%] and 127/127 negatives (Sp = 100%; 95% CI = 97.1%, 100.0%) at 20-million beads coupling scale. Salivary SARS-CoV-2 IgG crossed the MIA cutoff of 0.1 BAU/mL on average 9 days post-COVID-19 symptom onset and peaked around day 30. Among n = 30 matched saliva and plasma samples, salivary SARS-CoV-2 MIA IgG levels correlated with corresponding-antigen plasma ELISA IgG (N: ρ = 0.76, RBD: ρ = 0.83, S: ρ = 0.82; all p < 0.001). Correlations of plasma SARS-CoV-2 nAb assay area under the curve (AUC) with salivary MIA IgG (N: ρ = 0.68, RBD: ρ = 0.78, S: ρ = 0.79; all p < 0.001) and with plasma ELISA IgG (N: ρ = 0.76, RBD: ρ = 0.79, S: ρ = 0.76; p < 0.001) were similar. CONCLUSIONS: A salivary SARS-CoV-2 IgG MIA produced consistently high Se (> 98.8%) and Sp (> 99.1%) across two bead coupling scales and correlations with nAb responses that were similar to blood-based SARS-CoV-2 IgG ELISA data. This non-invasive salivary SARS-CoV-2 IgG MIA could increase engagement of vulnerable populations and improve broad understanding of humoral immunity (kinetics and gaps) within the evolving context of booster vaccination, viral variants and waning immunity.

Infectious Diseases Institute at Makerere University College of Health Sciences: a case study of a sustainable capacity building model for health care, research and training.

The Infectious Diseases Institute (IDI), established in 2001, was the first autonomous institution of Makerere University set up as an example of what self-governing institutes can do in transforming the academic environment to become a rapidly progressive University addressing the needs of society This paper describes the success factors and lessons learned in development of sustainable centers of excellence to prepare academic institutions to respond appropriately to current and future challenges to global health. Key success factors included a) strong collaboration by local and international experts to combat the HIV pandemic, along with b) seed funding from Pfizer Inc., c) longstanding collaboration with Accordia Global Health Foundation to create and sustain institutional strengthening programs, d) development of a critical mass of multi-disciplinary research leaders and managers of the center, and e) a series of strong directors who built strong governance structures to execute the vision of the institute, with subsequent transition to local leadership. Conclusion: Twenty years of sustained investment in infrastructure, human capital, leadership, and collaborations present Makerere University and the sub-Saharan Africa region with an agile center of excellence with preparedness to meet the current and future challenges to global health.

Optimal decision theory for diagnostic testing: Minimizing indeterminate classes with applications to saliva-based SARS-CoV-2 antibody assays.

In diagnostic testing, establishing an indeterminate class is an effective way to identify samples that cannot be accurately classified. However, such approaches also make testing less efficient and must be balanced against overall assay performance. We address this problem by reformulating data classification in terms of a constrained optimization problem that (i) minimizes the probability of labeling samples as indeterminate while (ii) ensuring that the remaining ones are classified with an average target accuracy X. We show that the solution to this problem is expressed in terms of a bathtub-type principle that holds out those samples with the lowest local accuracy up to an X-dependent threshold. To illustrate the usefulness of this analysis, we apply it to a multiplex, saliva-based SARS-CoV-2 antibody assay and demonstrate up to a 30 % reduction in the number of indeterminate samples relative to more traditional approaches.

Post-sequelae symptoms and comorbidities after COVID-19.

The frequency, severity, and forms of symptoms months after coronavirus 2019 (COVID-19) are poorly understood, especially in community settings. To better understand and characterize symptoms months after community-based COVID-19, a retrospective cohort analysis was conducted. Three hundred and twenty-eight consecutive persons with a positive test for SARS-CoV-2 in the Johns Hopkins Health System, Maryland, March-May 2020, were selected for the study. Symptom occurrence and severity were measured through questionnaires. Of 328 persons evaluated, a median of 242 days (109-478 days) from the initial positive SARS-CoV-2 test, 33.2% reported not being fully recovered and 4.9% reported symptoms that constrained daily activities. Compared to those who reported being fully recovered, those with post-acute sequelae were more likely to report a prior history of heart attack (p < 0.01). Among those reporting long-term symptoms, men and women were equally represented (men = 34.8%, women = 34.6%), but only women reported symptoms that constrained daily activities, and 56% of them were caregivers. The types of new or persistent symptoms varied, and for many, included a deviation from prior COVID-19 health, such as being less able to exercise, walk, concentrate, or breathe. A limitation is that self-report of symptoms might be biased and/or caused by factors other than COVID-19. Overall, even in a community setting, symptoms may persist months after COVID-19 reducing daily activities including caring for dependents.

Clustering of SARS-CoV-2 Infections in Households of Patients Diagnosed in the Outpatient Setting in Baltimore, Maryland.

In an outpatient cohort in Maryland, clustering of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity within households was high, with 76% of 74 households reporting at least 1 other symptomatic person and 66% reporting another person who tested SARS-CoV-2 positive. SARS-CoV-2 positivity among household members was associated with larger household size and bedroom sharing.

Alpha-1 adrenergic receptor antagonists to prevent hyperinflammation and death from lower respiratory tract infection.

In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation, which can lead to acute respiratory distress syndrome, multi-organ failure, and death. We previously demonstrated that alpha-1 adrenergic receptor (⍺1-AR) antagonists can prevent hyperinflammation and death in mice. Here, we conducted retrospective analyses in two cohorts of patients with acute respiratory distress (ARD, n = 18,547) and three cohorts with pneumonia (n = 400,907). Federated across two ARD cohorts, we find that patients exposed to ⍺1-AR antagonists, as compared to unexposed patients, had a 34% relative risk reduction for mechanical ventilation and death (OR = 0.70, p = 0.021). We replicated these methods on three pneumonia cohorts, all with similar effects on both outcomes. All results were robust to sensitivity analyses. These results highlight the urgent need for prospective trials testing whether prophylactic use of ⍺1-AR antagonists ameliorates lower respiratory tract infection-associated hyperinflammation and death, as observed in COVID-19.

Delayed Rise of Oral Fluid Antibodies, Elevated BMI, and Absence of Early Fever Correlate With Longer Time to SARS-CoV-2 RNA Clearance in a Longitudinally Sampled Cohort of COVID-19 Outpatients.

BACKGROUND: Sustained molecular detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in the upper respiratory tract (URT) in mild to moderate coronavirus disease 2019 (COVID-19) is common. We sought to identify host and immune determinants of prolonged SARS-CoV-2 RNA detection. METHODS: Ninety-five symptomatic outpatients self-collected midturbinate nasal, oropharyngeal (OP), and gingival crevicular fluid (oral fluid) samples at home and in a research clinic a median of 6 times over 1-3 months. Samples were tested for viral RNA, virus culture, and SARS-CoV-2 and other human coronavirus antibodies, and associations were estimated using Cox proportional hazards models. RESULTS: Viral RNA clearance, as measured by SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR), in 507 URT samples occurred a median (interquartile range) 33.5 (17-63.5) days post-symptom onset. Sixteen nasal-OP samples collected 2-11 days post-symptom onset were virus culture positive out of 183 RT-PCR-positive samples tested. All participants but 1 with positive virus culture were negative for concomitant oral fluid anti-SARS-CoV-2 antibodies. The mean time to first antibody detection in oral fluid was 8-13 days post-symptom onset. A longer time to first detection of oral fluid anti-SARS-CoV-2 S antibodies (adjusted hazard ratio [aHR], 0.96; 95% CI, 0.92-0.99; P = .020) and body mass index (BMI) ≥25 kg/m2 (aHR, 0.37; 95% CI, 0.18-0.78; P = .009) were independently associated with a longer time to SARS-CoV-2 viral RNA clearance. Fever as 1 of first 3 COVID-19 symptoms correlated with shorter time to viral RNA clearance (aHR, 2.06; 95% CI, 1.02-4.18; P = .044). CONCLUSIONS: We demonstrate that delayed rise of oral fluid SARS-CoV-2-specific antibodies, elevated BMI, and absence of early fever are independently associated with delayed URT viral RNA clearance.

Self-Collected Oral Fluid Saliva Is Insensitive Compared With Nasal-Oropharyngeal Swabs in the Detection of Severe Acute Respiratory Syndrome Coronavirus 2 in Outpatients.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic control will require widespread access to accurate diagnostics. Salivary sampling circumvents swab supply chain bottlenecks, is amenable to self-collection, and is less likely to create an aerosol during collection compared with the nasopharyngeal swab. METHODS: We compared real-time reverse-transcription polymerase chain reaction Abbott m2000 results from matched salivary oral fluid (gingival crevicular fluid collected in an Oracol device) and nasal-oropharyngeal (OP) self-collected specimens in viral transport media from a nonhospitalized, ambulatory cohort of coronavirus disease 2019 (COVID-19) patients at multiple time points. These 2 sentences should be at the beginning of the results. RESULTS: There were 171 matched specimen pairs. Compared with nasal-OP swabs, 41.6% of the oral fluid samples were positive. Adding spit to the oral fluid percent collection device increased the percent positive agreement from 37.2% (16 of 43) to 44.6% (29 of 65). The positive percent agreement was highest in the first 5 days after symptoms and decreased thereafter. All of the infectious nasal-OP samples (culture positive on VeroE6 TMPRSS2 cells) had a matched SARS-CoV-2 positive oral fluid sample. CONCLUSIONS: In this study of nonhospitalized SARS-CoV-2-infected persons, we demonstrate lower diagnostic sensitivity of self-collected oral fluid compared with nasal-OP specimens, a difference that was especially prominent more than 5 days from symptom onset. These data do not justify the routine use of oral fluid collection for diagnosis of SARS-CoV-2 despite the greater ease of collection. It also underscores the importance of considering the method of saliva specimen collection and the time from symptom onset especially in outpatient populations.

The Clinical Course of COVID-19 in the Outpatient Setting: A Prospective Cohort Study.

BACKGROUND: Outpatient coronavirus disease 2019 (COVID-19) has been insufficiently characterized. To determine the progression of disease and determinants of hospitalization, we conducted a prospective cohort study. METHODS: Outpatient adults with positive reverse transcription polymerase chain reaction results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were recruited by phone between April 21 and July 23, 2020, after receiving outpatient or emergency department testing within a large health network in Maryland, United States. Symptoms were collected by participants on days 0, 3, 7, 14, 21, and 28, and portable pulse oximeter oxygen saturation (SaO2), heart rate, and temperature were collected for 15 consecutive days. Baseline demographics, comorbid conditions, and vital signs were evaluated for risk of subsequent hospitalization using negative binomial and logistic regression. RESULTS: Among 118 SARS-CoV-2-infected outpatients, the median age (interquartile range [IQR]) was 56.0 (50.0-63.0) years, and 50 (42.4%) were male. Among individuals in the first week of illness (n = 61), the most common symptoms included weakness/fatigue (65.7%), cough (58.8%), headache (45.6%), chills (38.2%), and anosmia (27.9%). Participants returned to their usual health a median (IQR) of 20 (13-38) days from symptom onset, and 66.0% of respondents were at their usual health during the fourth week of illness. Over 28 days, 10.9% presented to the emergency department and 7.6% required hospitalization. The area under the receiver operating characteristics curve for the initial home SaO2 for predicting subsequent hospitalization was 0.86 (95% CI, 0.73-0.99). CONCLUSIONS: Symptoms often persisted but uncommonly progressed to hospitalization among outpatients with COVID-19. Home SaO2 may be a helpful tool to stratify risk of hospitalization.

COVID-19 Serology at Population Scale: SARS-CoV-2-Specific Antibody Responses in Saliva.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of an ongoing pandemic that has infected over 36 million and killed over 1 million people. Informed implementation of government public health policies depends on accurate data on SARS-CoV-2 immunity at a population scale. We hypothesized that detection of SARS-CoV-2 salivary antibodies could serve as a noninvasive alternative to serological testing for monitoring of SARS-CoV-2 infection and seropositivity at a population scale. We developed a multiplex SARS-CoV-2 antibody immunoassay based on Luminex technology that comprised 12 CoV antigens, mostly derived from SARS-CoV-2 nucleocapsid (N) and spike (S). Saliva and sera collected from confirmed coronavirus disease 2019 (COVID-19) cases and from the pre-COVID-19 era were tested for IgG, IgA, and IgM to the antigen panel. Matched saliva and serum IgG responses (n = 28) were significantly correlated. The salivary anti-N IgG response resulted in the highest sensitivity (100%), exhibiting a positive response in 24/24 reverse transcription-PCR (RT-PCR)-confirmed COVID-19 cases sampled at >14 days post-symptom onset (DPSO), whereas the salivary anti-receptor binding domain (RBD) IgG response yielded 100% specificity. Temporal kinetics of IgG in saliva were consistent with those observed in blood and indicated that most individuals seroconvert at around 10 DPSO. Algorithms employing a combination of the IgG responses to N and S antigens result in high diagnostic accuracy (100%) by as early as 10 DPSO. These results support the use of saliva-based antibody testing as a noninvasive and scalable alternative to blood-based antibody testing.

Caring for patients in a new pandemic: the necessity and challenges of observational research.

Individuals with coronavirus disease 2019 (COVID-19) can develop pneumonia and a severe inflammatory response with excessive cytokine release known as the cytokine storm. The JAK inhibitor baricitinib, used to treat rheumatoid arthritis, reduces inflammation by modifying the cytokine pathway. In this issue of the JCI, Bronte, Ugel, and colleagues performed an observational longitudinal study to evaluate the use of baricitinib in 20 patients with COVID-19. The treated patients showed reduced levels of plasma IL-6, TNF, IL-1ß, and phosphorylated STAT3 as well as swift lymphocyte restoration. Notably, these patients had a dramatically favorable clinical outcome. While bias can plague uncontrolled research, this study has biological credibility and warrants randomized, controlled studies.