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Background Prior observation has shown differences in COVID-19 hospitalization risk between SARS-CoV-2 variants, but limited information describes hospitalization outcomes. Methods Inpatients with COVID-19 at 5 hospitals in the eastern United States were included if they had hypoxia, tachypnea, tachycardia, or fever, and SARS-CoV-2 variant data, determined from whole-genome sequencing or local surveillance inference. Analyses were stratified by history of SARS-CoV-2 vaccination or infection. The average effect of SARS-CoV-2 variant on 28-day risk of severe disease, defined by advanced respiratory support needs, or death was evaluated using models weighted on propensity scores derived from baseline clinical features. Results Severe disease or death within 28 days occurred for 977 (29%) of 3369 unvaccinated patients and 269 (22%) of 1230 patients with history of vaccination or prior SARS-CoV-2 infection. Among unvaccinated patients, the relative risk of severe disease or death for Delta variant compared with ancestral lineages was 1.30 (95% confidence interval [CI]: 1.11–1.49). Compared with Delta, the risk for Omicron patients was .72 (95% CI: .59–.88) and compared with ancestral lineages was .94 (.78–1.1). Among Omicron and Delta infections, patients with history of vaccination or prior SARS-CoV-2 infection had half the risk of severe disease or death (adjusted hazard ratio: .40; 95% CI: .30–.54), but no significant outcome difference by variant. Conclusions Although risk of severe disease or death for unvaccinated inpatients with Omicron was lower than with Delta, it was similar to ancestral lineages. Severe outcomes were less common in vaccinated inpatients, with no difference between Delta and Omicron infections.

Background Control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission requires understanding SARS-CoV-2 replication dynamics. Methods We developed a multiplexed droplet digital polymerase chain reaction (ddPCR) assay to quantify SARS-CoV-2 subgenomic RNAs (sgRNAs), which are only produced during active viral replication, and discriminate them from genomic RNAs (gRNAs). We applied the assay to specimens from 144 people with single nasopharyngeal samples and 27 people with >1 sample. Results were compared to quantitative PCR (qPCR) and viral culture. Results sgRNAs were quantifiable across a range of qPCR cycle threshold (Ct) values and correlated with Ct values. The ratio sgRNA:gRNA was stable across a wide range of Ct values, whereas adjusted amounts of N sgRNA to a human housekeeping gene declined with higher Ct values. Adjusted sgRNA and gRNA amounts were quantifiable in culture-negative samples, although levels were significantly lower than in culture-positive samples. Daily testing of 6 persons revealed that sgRNA is concordant with culture results during the first week of infection but may be discordant with culture later in infection. sgRNA:gRNA is constant during infection despite changes in viral culture. Conclusions Ct values from qPCR correlate with active viral replication. More work is needed to understand why some cultures are negative despite presence of sgRNA.

Background There is an urgent need to understand the real-world effectiveness of remdesivir in the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods This was a retrospective comparative effectiveness study. Individuals hospitalized in a large private healthcare network in the United States from 23 February 2020 through 11 February 2021 with a positive test for SARS-CoV-2 and ICD-10 diagnosis codes consistent with symptomatic coronavirus disease 2019 (COVID-19) were included. Remdesivir recipients were matched to controls using time-dependent propensity scores. The primary outcome was time to improvement with a secondary outcome of time to death. Results Of 96 859 COVID-19 patients, 42 473 (43.9%) received at least 1 remdesivir dose. The median age of remdesivir recipients was 65 years, 23 701 (55.8%) were male, and 22 819 (53.7%) were non-White. Matches were found for 18 328 patients (43.2%). Remdesivir recipients were significantly more likely to achieve clinical improvement by 28 days (adjusted hazard ratio [aHR] 1.19, 95% confidence interval [CI], 1.16–1.22). Remdesivir patients on no oxygen (aHR 1.30, 95% CI, 1.22–1.38) or low-flow oxygen (aHR 1.23, 95% CI, 1.19–1.27) were significantly more likely to achieve clinical improvement by 28 days. There was no significant impact on the likelihood of mortality overall (aHR 1.02, 95% CI, .97–1.08). Remdesivir recipients on low-flow oxygen were significantly less likely to die than controls (aHR 0.85, 95% CI, .77–.92; 28-day mortality 8.4% [865 deaths] for remdesivir patients, 12.5% [1334 deaths] for controls). Conclusions These results support the use of remdesivir for hospitalized COVID-19 patients on no or low-flow oxygen. Routine initiation of remdesivir in more severely ill patients is unlikely to be beneficial.

BackgroundPrior observation has shown differences in COVID-19 hospitalization rates between SARS-CoV-2 variants, but limited information describes differences in hospitalization outcomes.MethodsPatients admitted to 5 hospitals with COVID-19 were included if they had hypoxia, tachypnea, tachycardia, or fever, and data to describe SARS-CoV-2 variant, either from whole genome sequencing, or inference when local surveillance showed ≥95% dominance of a single variant. The average effect of SARS-CoV-2 variant on 14-day risk of severe disease, defined by need for advanced respiratory support, or death was evaluated using models weighted on propensity scores derived from baseline clinical features.ResultsSevere disease or death within 14 days occurred for 950 of 3,365 (28%) unvaccinated patients and 178 of 808 (22%) patients with history of vaccination or prior COVID-19. Among unvaccinated patients, the relative risk of 14-day severe disease or death for Delta variant compared to ancestral lineages was 1.34 (95% confidence interval [CI] 1.13-1.55). Compared to Delta variant, this risk for Omicron patients was 0.78 (95% CI 0.62-0.97) and compared to ancestral lineages was 1.04 (95% CI 0.84-1.24). Among Omicron and Delta infections, patients with history of vaccination or prior COVID-19 had one-half the 14-day risk of severe disease or death (adjusted hazard ratio 0.46, IQR 0.34-0.62) but no significant outcome difference between Delta and Omicron infections.ConclusionsAlthough the risk of severe disease or death for unvaccinated patients with Omicron was lower than Delta, it was similar to ancestral lineages. Severe outcomes were less common in vaccinated patients, but there was no difference between Delta and Omicron infections.

Severe COVID-19 is characterized by a prothrombotic state associated with thrombocytopenia, with microvascular thrombosis being almost invariably present in the lung and other organs at postmortem examination. We evaluated the presence of antibodies to platelet factor 4 (PF4)–polyanion complexes using a clinically validated immunoassay in 100 hospitalized patients with COVID-19 with moderate or severe disease (World Health Organization score, 4 to 10), 25 patients with acute COVID-19 visiting the emergency department, and 65 convalescent individuals. Anti-PF4 antibodies were detected in 95 of 100 hospitalized patients with COVID-19 (95.0%) irrespective of prior heparin treatment, with a mean optical density value of 0.871 ± 0.405 SD (range, 0.177 to 2.706). In contrast, patients hospitalized for severe acute respiratory disease unrelated to COVID-19 had markedly lower levels of the antibodies. In a high proportion of patients with COVID-19, levels of all three immunoglobulin (Ig) isotypes tested (IgG, IgM, and IgA) were simultaneously elevated. Antibody levels were higher in male than in female patients and higher in African Americans and Hispanics than in White patients. Anti-PF4 antibody levels were correlated with the maximum disease severity score and with significant reductions in circulating platelet counts during hospitalization. In individuals convalescent from COVID-19, the antibody levels returned to near-normal values. Sera from patients with COVID-19 induced higher levels of platelet activation than did sera from healthy blood donors, but the results were not correlated with the levels of anti-PF4 antibodies. These results demonstrate that the vast majority of patients with severe COVID-19 develop anti-PF4 antibodies, which may play a role in the clinical complications of COVID-19.

Background: Epidemiology of febrile illness in Uganda is shifting due to increased HIV treatment access, emerging viruses, and increased surveillance. We investigated the aetiology and outcomes of acute febrile illness in adults presenting to hospital using a standardized testing algorithm of available assays in two tertiary care hospitals in Uganda.Methods: We recruited adults with a ≥ 38.0°C temperature or history of fever within 48 hours of presentation. Medical history, demographics, and vital signs were recorded. Testing performed included a complete blood count, renal and liver function, malaria smears, blood culture, and human immunodeficiency virus (HIV). When HIV positive; cryptococcal antigen, CD4 count, and urine lateral flow lipoarabinomannan assay for tuberculosis. Participants were followed during hospitalization and at a 1-month visit. A Cox proportional hazard regression was performed to evaluate for baseline clinical features and risk of death.Results: Of 132 participants, the median age was 33.5 years (IQR 24 to 46) and 58.3% (n=77) were female. Overall, 73 (55.3%) of 132 had a positive microbiologic result. Among those living with HIV, 31 (68.9%) of 45 had at least one positive assay; 16 (35.6%) had malaria, 14 (31.1%) tuberculosis, and 4 (8.9%) cryptococcal antigenemia. The majority (65.9%) were HIV-negative; 42 (48.3%) of 87 had at least one diagnostic assay positive; 24 (27.6%) had positive malaria smears and 1 was Xpert MTB/RIF Ultra positive. Overall, 16 (12.1%) of 132 died; 9 (56.3%) of 16 were HIV-negative, 6 died after discharge. High respiratory rate (≥22 breaths per minute) (hazard ratio [HR] 8.05; 95% CI: 1.81 to 35.69) and low (i.e., Conclusion: In those with hospitalized fever, malaria and tuberculosis were common causes of febrile illness, but most deaths were non-malarial, and most HIV-negative participants did not have a positive diagnostic result. Those with respiratory failure had a high risk of death.

Background Several inflammatory cytokines are upregulated in severe coronavirus disease 2019 (COVID-19). We compared cytokines in COVID-19 versus influenza to define differentiating features of the inflammatory response to these pathogens and their association with severe disease. Because elevated body mass index (BMI) is a known risk factor for severe COVID-19, we examined the relationship of BMI to cytokines associated with severe disease. Methods Thirty-seven cytokines and chemokines were measured in plasma from 135 patients with COVID-19, 57 patients with influenza, and 30 healthy controls. Controlling for BMI, age, and sex, differences in cytokines between groups were determined by linear regression and random forest prediction was used to determine the cytokines most important in distinguishing severe COVID-19 and influenza. Mediation analysis was used to identify cytokines that mediate the effect of BMI and age on disease severity. Results Interleukin-18 (IL-18), IL-1β, IL-6, and tumor necrosis factor-α (TNF-α) were significantly increased in COVID-19 versus influenza patients, whereas granulocyte macrophage colony-stimulating factor, interferon-γ (IFN-γ), IFN-λ1, IL-10, IL-15, and monocyte chemoattractant protein 2 were significantly elevated in the influenza group. In subgroup analysis based on disease severity, IL-18, IL-6, and TNF-α were elevated in severe COVID-19, but not in severe influenza. Random forest analysis identified high IL-6 and low IFN-λ1 levels as the most distinct between severe COVID-19 and severe influenza. Finally, IL-1RA was identified as a potential mediator of the effects of BMI on COVID-19 severity. Conclusions These findings point to activation of fundamentally different innate immune pathways in severe acute respiratory syndrome coronavirus 2 and influenza infection, and emphasize drivers of severe COVID-19 to focus both mechanistic and therapeutic investigations.

Objective:To evaluate the role of procalcitonin (PCT) results in antibiotic decisions for COVID-19 patients at hospital presentation.Design, setting, and participants:Multicenter retrospective observational study of patients ≥18 years hospitalized due to COVID-19 at the Johns Hopkins Health system. Patients who were transferred from another facility with >24 hours stay and patients who died within 48 hours of hospitalization were excluded.Methods:Elevated PCT values were determined based on each hospital’s definition. Antibiotic therapy and PCT results were evaluated for patients with no evidence of bacterial community-acquired pneumonia (bCAP) and patients with confirmed, probable, or possible bCAP. The added value of PCT testing to clinical criteria in detecting bCAP was evaluated using receiving operating curve characteristics (ROC).Results:Of 962 patients, 611 (64%) received a PCT test. ROC curves for clinical criteria and clinical criteria plus PCT test were similar (at 0.5 ng/mL and 0.25 ng/mL). By bCAP group, median initial PCT values were 0.58 ng/mL (interquartile range [IQR], 0.24–1.14), 0.23 ng/mL (IQR, 0.1–0.63), and 0.15 ng/mL (IQR, 0.09–0.35) for proven/probable, possible, and no bCAP groups, respectively. Among patients without bCAP, an elevated PCT level was associated with 1.8 additional days of CAP therapy (95% CI, 1.01–2.75; P < .01) compared to patients with a negative PCT result after adjusting for potential confounders. Duration of CAP therapy was similar between patients without a PCT test ordered and a low PCT level for no bCAP and possible bCAP groups.Conclusions:PCT results may be abnormal in COVID-19 patients without bCAP and may result in receipt of unnecessary antibiotics.

USACE’s IWR must responsibly manage its work packages through its Operations and Maintenance (O&M) annual budget. IWR has developed several models that use data to inform investment strategies for the prioritization of work packages; however, these strategies are based on old data and not predictive in nature. Because work package ranks significantly change when applying a Value Model and Monte Carlo simulation, this research focuses on the significance of a 3-year predictive budgeting model; a model which is enabled by the National Defense Authorization Act (NDAA, 2020). This research will demonstrate a forward-looking methodology using a Value to Consequence Ratio metric (VCR) for funding work packages through a decision support interface via Microsoft’s Power BI. This paper presents the framework for USACE’s Civil Works Navigation business line and creates the potential for future work to integrate other business lines utilizing System Dynamics.

Background Risk factors for progression of coronavirus 2019 (COVID-19) to severe disease or death are underexplored in U.S. cohorts. Objective To determine the factors on hospital admission that are predictive of severe disease or death from COVID-19. Design Retrospective cohort analysis. Setting Five hospitals in the Maryland and Washington, DC, area. Patients 832 consecutive COVID-19 admissions from 4 March to 24 April 2020, with follow-up through 27 June 2020. Measurements Patient trajectories and outcomes, categorized by using the World Health Organization COVID-19 disease severity scale. Primary outcomes were death and a composite of severe disease or death. Results Median patient age was 64 years (range, 1 to 108 years); 47% were women, 40% were Black, 16% were Latinx, and 21% were nursing home residents. Among all patients, 131 (16%) died and 694 (83%) were discharged (523 [63%] had mild to moderate disease and 171 [20%] had severe disease). Of deaths, 66 (50%) were nursing home residents. Of 787 patients admitted with mild to moderate disease, 302 (38%) progressed to severe disease or death: 181 (60%) by day 2 and 238 (79%) by day 4. Patients had markedly different probabilities of disease progression on the basis of age, nursing home residence, comorbid conditions, obesity, respiratory symptoms, respiratory rate, fever, absolute lymphocyte count, hypoalbuminemia, troponin level, and C-reactive protein level and the interactions among these factors. Using only factors present on admission, a model to predict in-hospital disease progression had an area under the curve of 0.85, 0.79, and 0.79, at day 2, 4, and 7, respectively. Limitation The study was done in a single health care system. Conclusion A combination of demographic and clinical variables is strongly associated with severe COVID-19 disease or death and their early onset. The COVID-19 Inpatient Risk Calculator (CIRC), using factors present on admission, can inform clinical and resource allocation decisions. Primary funding source Hopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.

Mosquitoborne diseases (e.g., malaria, dengue, and chikungunya) are endemic to India and pose diagnostic challenges during pregnancy. We evaluated an intensified short symptom screening program in India to diagnose dengue during pregnancy. During October 2017–January 2018, we screened pregnant women during antenatal surveillance for symptoms of mosquitoborne diseases (fever only, fever with conjunctivitis, fever with rash, or all 3 symptoms) within the previous 15 days. Of 5,843 pregnant women screened, 52 were enrolled and tested for dengue, chikungunya, and Zika viruses by using a Trioplex real-time reverse transcription PCR. Of 49 who had complete results, 7 (14%) were dengue positive. Of these ocular pain was seen in 4 (57%) and conjunctivitis in 7 (100%). Intensified symptom screening using conjunctivitis, in addition to rash, in pregnant women with fever might improve dengue case detection and can be included in routine symptom screening during pregnancy.

Control of SARS-CoV-2 (SCV-2) transmission is a major priority that requires understanding SCV-2 replication dynamics. We developed and validated novel droplet digital PCR (ddPCR) assays to quantify SCV-2 subgenomic RNAs (sgRNAs), which are only produced during active viral replication, and discriminate them from full-length genomic RNAs (gRNAs) in a multiplexed format. We applied this multiplex ddPCR assay to 144 cross-sectional nasopharyngeal samples. sgRNAs were quantifiable across a range of qPCR cycle threshold (Ct) values and correlated with Ct values. The ratio of sgRNA:gRNA was remarkably stable across a wide range of Ct values, whereas adjusted amounts of N sgRNA to a human housekeeping gene declined with higher Ct values. Interestingly, adjusted sgRNA and gRNA amounts were quantifiable in culture-negative samples, although levels were significantly lower than in culture-positive samples. Longitudinal daily testing of 6 persons for up to 14 days revealed that sgRNA is concordant with culture results during the first week of infection but may be discordant with culture later in infection. Further, sgRNA:gRNA is constant during infection despite changes in viral culture. These data indicate stable viral transcription during infection. More work is needed to understand why cultures are negative despite persistence of viral RNAs.

ObjectivesCOVID-19 has brought unprecedented attention to the crucial role of diagnostics in pandemic control. We compared SARS-CoV-2 test performance by sample type and modality in close contacts of SARS-CoV-2 cases.MethodsClose contacts of SARS-CoV-2 positive individuals were enrolled after informed consent. Clinician-collected nasopharyngeal (NP) swabs in viral transport media (VTM) were tested with a nucleic acid test (NAT). NP VTM and self-collected passive drool were tested using the PerkinElmer real-time reverse transcription PCR (RT-PCR) assay. For the first 4 months of study, mid-turbinate swabs were tested using the BD Veritor rapid antigen test. NAT positive NP samples were tested for infectivity using a VeroE6TMPRSS2 cell culture model.ResultsBetween November 17, 2020, and October 1, 2021, 235 close contacts of SARS-CoV-2 cases were recruited, including 95 with symptoms (82% symptomatic for <5 days) and 140 asymptomatic individuals. NP swab reference tests were positive for 53 (22.6%) participants; 24/50 (48%) were culture positive. PerkinElmer testing of NP and saliva samples identified an additional 28 (11.9%) SARS-CoV-2 cases who tested negative by clinical NAT. Antigen tests performed for 99 close contacts showed 83% positive percent agreement (PPA) with reference NAT among early symptomatic persons, but 18% PPA in others; antigen tests in 8 of 11 (72.7%) culture-positive participants were positive.ConclusionsContacts of SARS-CoV-2 cases may be falsely negative early after contact, which more sensitive platforms may identify. Repeat or serial SARS-CoV-2 testing with both antigen and molecular assays may be warranted for individuals with high pretest probability for infection.

As clinicians are faced with a deluge of new information, data science can play a key role in highlighting key features towards developing new clinical hypotheses. Indeed, insights derived from machine learning can serve as a clinical support tool by connecting care providers with results from big data analysis to identify latent patterns that may not be easily detected by even skilled human observers. In this work, we show an example of collaboration between clinicians and data scientists during the COVID-19 pandemic, identifying subgroups of COVID-19 patients with unanticipated outcomes or who are high-risk for severe disease or death. We apply a random forest classifier model to predict adverse patient outcomes early in the disease course, and we connect our classification results to unsupervised clustering of patient features that may underpin patient risk. The paradigm for using data science for hypothesis generation and clinical decision support, as well as our triage classification approach and unsupervised clustering methods to determine patient cohorts, are applicable to driving rapid hypothesis generation and iteration in a variety of clinical challenges, including future public health crises.

During the COVID-19 public health emergency, many actions have been undertaken to help ensure that patients and health care providers had timely and continued access to high-quality medical devices to respond effectively. The development and validation of new testing supplies and equipment, including collection swab, help expand the availability and capability for various diagnostic, therapeutic, and protective medical devices in high demand during the COVID-19 emergency. Here, we report the validation of a new injection-molded anterior nasal swab, ClearTip™, that was experimentally validated in a laboratory setting as well as in independent clinical studies in comparison to gold standard flocked swabs. We have also developed an in vitro anterior nasal tissue model, that offers an efficient and clinically relevant validation tool to replicate with high fidelity the clinical swabbing workflow, while being accessible, safe, reproducible, time and cost effective. ClearTip™ displayed a greater efficiency of release of inactivated virus in the benchtop model, confirmed by greater ability to report positive samples in a clinical study in comparison to flocked swabs. We also quantified in multi-center pre-clinical and clinical studies the detection of biological materials, as proxy for viral material, that showed a statistically significant difference in one study and a slight reduction in performance in comparison to flocked swabs. Taken together these results underscore the compelling benefits of non-absorbent injected molded anterior nasal swab for COVID-19 detection, comparable to standard flocked swabs. Injection-molded swabs, as ClearTip™, could have the potential to support future swab shortage, due to its manufacturing advantages, while offering benefits in comparison to highly absorbent swabs in terms comfort, limited volume collection, and potential multiple usage.

In Fall 2020, universities saw extensive transmission of SARS-CoV-2 among their populations, threatening health of the university and surrounding communities, and viability of in-person instruction. Here we report a case study at the University of Illinois at Urbana-Champaign, where a multimodal “SHIELD: Target, Test, and Tell” program, with other non-pharmaceutical interventions, was employed to keep classrooms and laboratories open. The program included epidemiological modeling and surveillance, fast/frequent testing using a novel low-cost and scalable saliva-based RT-qPCR assay for SARS-CoV-2 that bypasses RNA extraction, called covidSHIELD, and digital tools for communication and compliance. In Fall 2020, we performed >1,000,000 covidSHIELD tests, positivity rates remained low, we had zero COVID-19-related hospitalizations or deaths amongst our university community, and mortality in the surrounding Champaign County was reduced more than 4-fold relative to expected. This case study shows that fast/frequent testing and other interventions mitigated transmission of SARS-CoV-2 at a large public university.

Background The global effort to vaccinate people against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during an ongoing pandemic has raised questions about how vaccine breakthrough infections compare with infections in immunologically naive individuals and the potential for vaccinated individuals to transmit the virus. Methods We examined viral dynamics and infectious virus shedding through daily longitudinal sampling in 23 adults infected with SARS-CoV-2 at varying stages of vaccination, including 6 fully vaccinated individuals. Results The durations of both infectious virus shedding and symptoms were significantly reduced in vaccinated individuals compared with unvaccinated individuals. We also observed that breakthrough infections are associated with strong tissue compartmentalization and are only detectable in saliva in some cases. Conclusions Vaccination shortens the duration of time of high transmission potential, minimizes symptom duration, and may restrict tissue dissemination.

By incorporating platelets and PfHRP2 into standard case definitions of severe falciparum malaria, Watson et al.

In the Fall of 2020, many universities saw extensive transmission of SARS-CoV-2 among their populations, threatening the health of students, faculty and staff, the viability of in-person instruction, and the health of surrounding communities.1, 2 Here we report that a multimodal “SHIELD: Target, Test, and Tell” program mitigated the spread of SARS-CoV-2 at a large public university, prevented community transmission, and allowed continuation of in-person classes amidst the pandemic. The program combines epidemiological modelling and surveillance (Target); fast and frequent testing using a novel and FDA Emergency Use Authorized low-cost and scalable saliva-based RT-qPCR assay for SARS-CoV-2 that bypasses RNA extraction, called covidSHIELD (Test); and digital tools that communicate test results, notify of potential exposures, and promote compliance with public health mandates (Tell). These elements were combined with masks, social distancing, and robust education efforts. In Fall 2020, we performed more than 1,000,000 covidSHIELD tests while keeping classrooms, laboratories, and many other university activities open. Generally, our case positivity rates remained less than 0.5%, we prevented transmission from our students to our faculty and staff, and data indicate that we had no spread in our classrooms or research laboratories. During this fall semester, we had zero COVID-19-related hospitalizations or deaths amongst our university community. We also prevented transmission from our university community to the surrounding Champaign County community. Our experience demonstrates that multimodal transmission mitigation programs can enable university communities to achieve such outcomes until widespread vaccination against COVID-19 is achieved, and provides a roadmap for how future pandemics can be addressed.

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimated viral expansion and clearance rates and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to 'superspreading'. Viral genome loads often peaked days earlier in saliva than in nasal swabs, indicating strong tissue compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of Alpha (B.1.1.7) and previously circulating non-variant-of-concern viruses were mostly indistinguishable, indicating that the enhanced transmissibility of this variant cannot be explained simply by higher viral loads or delayed clearance. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.

Background Males experience increased severity of illness and mortality from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) compared with females, but the mechanisms of male susceptibility are unclear. Methods We performed a retrospective cohort analysis of SARS-CoV-2 testing and admission data at 5 hospitals in the Maryland/Washington DC area. Using age-stratified logistic regression models, we quantified the impact of male sex on the risk of the composite outcome of severe disease or death (World Health Organization score 5–8) and tested the impact of demographics, comorbidities, health behaviors, and laboratory inflammatory markers on the sex effect. Results Among 213 175 SARS-CoV-2 tests, despite similar positivity rates, males in age strata between 18 and 74 years were more frequently hospitalized. For the 2626 hospitalized individuals, clinical inflammatory markers (interleukin-6, C-reactive protein, ferritin, absolute lymphocyte count, and neutrophil:lymphocyte ratio) were more favorable for females than males (P < .001). Among 18–49-year-olds, male sex carried a higher risk of severe outcomes, both early (odds ratio [OR], 3.01; 95% CI, 1.75 to 5.18) and at peak illness during hospitalization (OR, 2.58; 95% CI, 1.78 to 3.74). Despite multiple differences in demographics, presentation features, comorbidities, and health behaviors, these variables did not change the association of male sex with severe disease. Only clinical inflammatory marker values modified the sex effect, reducing the OR for severe outcomes in males aged 18–49 years to 1.81 (95% CI, 1.00 to 3.26) early and 1.39 (95% CI, 0.93 to 2.08) at peak illness. Conclusions Higher inflammatory laboratory test values were associated with increased risk of severe coronavirus disease 2019 for males. A sex-specific inflammatory response to SARS-CoV-2 infection may underlie the sex differences in outcomes.

Background Serial screening is critical for restricting spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by facilitating timely identification of infected individuals to interrupt transmission. Variation in sensitivity of different diagnostic tests at different stages of infection has not been well documented. Methods In a longitudinal study of 43 adults newly infected with SARS-CoV-2, all provided daily saliva and nasal swabs for quantitative reverse transcription polymerase chain reaction (RT-qPCR), Quidel SARS Sofia antigen fluorescent immunoassay (FIA), and live virus culture. Results Both RT-qPCR and Quidel SARS Sofia antigen FIA peaked in sensitivity during the period in which live virus was detected in nasal swabs, but sensitivity of RT-qPCR tests rose more rapidly prior to this period. We also found that serial testing multiple times per week increases the sensitivity of antigen tests. Conclusions RT-qPCR tests are more effective than antigen tests at identifying infected individuals prior to or early during the infectious period and thus for minimizing forward transmission (given timely results reporting). All tests showed >98% sensitivity for identifying infected individuals if used at least every 3 days. Daily screening using antigen tests can achieve approximately 90% sensitivity for identifying infected individuals while they are viral culture positive.

Structured AbstractBackgroundRates of severe illness and mortality from SARS-CoV-2 are greater for males, but the mechanisms for this difference are unclear. Understanding the differences in outcomes between males and females across the age spectrum will guide both public health and biomedical interventions.MethodsRetrospective cohort analysis of SARS-CoV-2 testing and admission data in a health system. Patient-level data were assessed with descriptive statistics and logistic regression modeling was used to identify features associated with increased male risk of severe outcomes.ResultsIn 213,175 SARS-CoV-2 tests, despite similar positivity rates (8.2%F vs 8.9%M), males were more frequently hospitalized (28%F vs 33%M). Of 2,626 hospitalized individuals, females had less severe presenting respiratory parameters and males had more fever. Comorbidity burden was similar, but with differences in specific conditions. Medications relevant for SARS-CoV-2 were used at similar frequency except tocilizumab (M>F). Males had higher inflammatory lab values. In a logistic regression model, male sex was associated with a higher risk of severe outcomes at 24 hours (odds ratio (OR) 3.01, 95%CI 1.75, 5.18) and at peak status (OR 2.58, 95%CI 1.78,3.74) among 18-49 year-olds. Block-wise addition of potential explanatory variables demonstrated that only the inflammatory labs substantially modified the OR associated with male sex across all ages.ConclusionHigher levels of clinical inflammatory labs are the only features that are associated with the heightened risk of severe outcomes and death for males in COVID-19.Trial registrationNAFundingHopkins inHealth; COVID-19 Administrative Supplement (HHS Region 3 Treatment Center), Office of the ASPR; NIH/NCI U54CA260492 (SK), NIH/NIA U54AG062333 (SK).

The National Institutes of Health (NIH) launched the Rapid Acceleration of Diagnostics (RADxSM) Tech initiative to support the development and commercialization of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) point-of-care test devices. The primary objective of the Clinical Studies Core (CSC) was to perform SARS-CoV-2 device studies involving diverse populations and settings. Within a few months, the infrastructure for clinical studies was developed, including a master protocol, digital study platform, data management system, single IRB, and multi-site partnerships. Data from some studies are being used to support Emergency Use Authorization of novel SARS-CoV-2 test devices. The CSC reduced the typical time and cost of developing medical devices and highlighted the impactful role of academic and NIH partnership in addressing public health needs at a rapid pace during a global pandemic. The structure, deployment, and lessons learned from this experience are widely applicable to future in vitro diagnostic device clinical studies.

Predicting the clinical trajectory of individual patients hospitalized with COVID-19 is necessary to inform clinical care. This article describes the development of an online tool to predict severe illness or death in patients hospitalized with COVID-19., Visual Abstract. Development of Severe COVID-19 Adaptive Risk Predictor. Predicting the clinical trajectory of individual patients hospitalized with COVID-19 is necessary to inform clinical care. This article describes the development of an online tool to predict severe illness or death in patients hospitalized with COVID-19. Visual Abstract. Development of Severe COVID-19 Adaptive Risk Predictor. Predicting the clinical trajectory of individual patients hospitalized with COVID-19 is necessary to inform clinical care. This article describes the development of an online tool to predict severe illness or death in patients hospitalized with COVID-19., Background: Predicting the clinical trajectory of individual patients hospitalized with coronavirus disease 2019 (COVID-19) is challenging but necessary to inform clinical care. The majority of COVID-19 prognostic tools use only data present upon admission and do not incorporate changes occurring after admission. Objective: To develop the Severe COVID-19 Adaptive Risk Predictor (SCARP) (https://rsconnect.biostat.jhsph.edu/covid_trajectory/), a novel tool that can provide dynamic risk predictions for progression from moderate disease to severe illness or death in patients with COVID-19 at any time within the first 14 days of their hospitalization. Design: Retrospective observational cohort study. Setting: Five hospitals in Maryland and Washington, D.C. Patients: Patients who were hospitalized between 5 March and 4 December 2020 with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) confirmed by nucleic acid test and symptomatic disease. Measurements: A clinical registry for patients hospitalized with COVID-19 was the primary data source; data included demographic characteristics, admission source, comorbid conditions, time-varying vital signs, laboratory measurements, and clinical severity. Random forest for survival, longitudinal, and multivariate (RF-SLAM) data analysis was applied to predict the 1-day and 7-day risks for progression to severe disease or death for any given day during the first 14 days of hospitalization. Results: Among 3163 patients admitted with moderate COVID-19, 228 (7%) became severely ill or died in the next 24 hours; an additional 355 (11%) became severely ill or died in the next 7 days. The area under the receiver-operating characteristic curve (AUC) for 1-day risk predictions for progression to severe disease or death was 0.89 (95% CI, 0.88 to 0.90) and 0.89 (CI, 0.87 to 0.91) during the first and second weeks of hospitalization, respectively. The AUC for 7-day risk predictions for progression to severe disease or death was 0.83 (CI, 0.83 to 0.84) and 0.87 (CI, 0.86 to 0.89) during the first and second weeks of hospitalization, respectively. Limitation: The SCARP tool was developed by using data from a single health system. Conclusion: Using the predictive power of RF-SLAM and longitudinal data from more than 3000 patients hospitalized with COVID-19, an interactive tool was developed that rapidly and accurately provides the probability of an individual patient's progression to severe illness or death on the basis of readily available clinical information. Primary Funding Source: Hopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.

Background: Neonatal sepsis is a leading cause of childhood mortality. Antimicrobial resistance complicates management in high burden countries, such as India. We sought to determine whether early use of microbiologically active antibiotics is associated with reduced mortality of neonatal Gram-negative (GN) bloodstream infections (BSI). Methods: Between May 2017 and July 2019, we recruited neonates with GN BSI admitted to three neonatal intensive care units in India. Antibiotic use, microbial data, and clinical outcomes were prospectively collected. We assessed the association between empiric therapy including an active agent, defined by in vitro susceptibility, and 30-day all-cause mortality using Cox proportional hazard models. Findings: Of 9303 neonates admitted over a 27-month period, 3107 (33%) had at least one blood culture; 263 (3%) had a GN BSI identified at a median 6 days of life (IQR 3-11). Among isolates, 196 were Enterobacterales with 73 (37%) identified as carbapenem-resistant Enterobacterales (CRE), and 46 were Acinetobacter species with 28 (61%) being carbapenem-resistant Acinetobacter species (CRAb). Overall, 52 infants received initial empiric therapy including colistin, which was active in most (169 of 263, 64%) instances, but a minority of patients with CRE (33 of 73, 45%) and CRAb (11 of 28, 39%) received an active agent. Initial use of active antibiotics was not associated with decreased 30-day mortality for CRE or CRAb infections. Interpretation: Early initiation of currently available, active antibiotics was not associated with lower mortality among neonates with GN BSI in a setting with a high burden of carbapenem-resistant organisms. Funding: U.S. Centers for Disease Control and Prevention Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: The study was approved by the ethics committees of each participating hospital, the Johns Hopkins School of Medicine Institutional Review Board, and the Government of India Health Ministry Screening Committee.

RationaleRemdesivir and dexamethasone reduced the severity of COVID-19 in clinical trials. However, their individual or combined effectiveness in clinical practice remains unknown.ObjectivesTo examine the effectiveness of remdesivir with or without dexamethasone.MethodsWe conducted a multicenter, retrospective cohort study between March 4 and August 29, 2020. Eligible COVID cases were hospitalized patients treated with remdesivir with or without dexamethasone. We applied a Cox proportional hazards model with propensity score matching to estimate the effect of these treatments on clinical improvement by 28 days (discharge or a 2-point decrease in WHO severity score) and 28-day mortality.Measurements and Main ResultsOf 2485 COVID-19 patients admitted between March 4 and August 29, 2020, 342 received remdesivir and 157 received remdesivir plus dexamethasone. Median age was 60 years; 45% were female; 81% were non-white. Remdesivir recipients on room air or nasal cannula oxygen had a faster time to clinical improvement (median 5.0 days [IQR 4.0, 8.0], remdesivir vs. 7.0 days [IQR 5.0, 12.0], control; adjusted hazard ratio (aHR) 1.55 [1.28; 1.87]), yet those requiring higher levels of respiratory support did not benefit. Remdesivir recipients had lower, but statistically insignificant, 28-day mortality (7.6% [23 deaths], remdesivir vs. 14.9% [45 deaths], control). Adding dexamethasone trended toward lower 28-day mortality compared to remdesivir alone (5.1% [8 deaths] vs. 9.2% [17 deaths]; aHR 0.14 [0.02; 1.03]).ConclusionsRemdesivir offered a significantly faster time to clinical improvement among a cohort of predominantly non-white patients hospitalized with COVID-19, particularly with mild-moderate disease. Remdesivir plus dexamethasone may reduce mortality.

Background There is currently no single treatment that mitigates all harms caused by severe acute respiratory syndrome coronavirus 2 infection. Tocilizumab, an interleukin-6 antagonist, may have a role as an adjunctive immune-modulating therapy. Methods This was an observational retrospective study of hospitalized adult patients with confirmed coronavirus disease 2019 (COVID-19). The intervention group comprised patients who received tocilizumab; the comparator arm was drawn from patients who did not receive tocilizumab. The primary outcome was all-cause mortality censored at 28 days; secondary outcomes were all-cause mortality at discharge, time to clinical improvement, and rates of secondary infections. Marginal structural Cox models via inverse probability treatment weights were applied to estimate the effect of tocilizumab. A time-dependent propensity score–matching method was used to generate a 1:1 match for tocilizumab recipients; infectious diseases experts then manually reviewed these matched charts to identify secondary infections. Results This analysis included 90 tocilizumab recipients and 1669 controls. Under the marginal structural Cox model, tocilizumab was associated with a 62% reduced hazard of death (adjusted hazard ratio [aHR], 0.38; 95% CI, 0.21 to 0.70) and no change in time to clinical improvement (aHR, 1.13; 95% CI, 0.68 to 1.87). The 1:1 matched data set also showed a lower mortality rate (27.8% vs 34.4%) and reduced hazards of death (aHR, 0.47; 95% CI, 0.25 to 0.88). Elevated inflammatory markers were associated with reduced hazards of death among tocilizumab recipients compared with controls. Secondary infection rates were similar between the 2 groups. Conclusions Tocilizumab may provide benefit in a subgroup of patients hospitalized with COVID-19 who have elevated biomarkers of hyperinflammation, without increasing the risk of secondary infection., In this retrospective study of adult patients hospitalized with COVID-19, tocilizumab was associated with a 62% reduction in hazard of death. Tocilizumab may have a role as adjunctive therapy for COVID-19 among patients with hyperinflammation including elevated IL-6.

Profiling coronaviruses Among the coronaviruses that infect humans, four cause mild common colds, whereas three others, including the currently circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), result in severe infections. Shrock et al. used a technology known as VirScan to probe the antibody repertoires of hundreds of coronavirus disease 2019 (COVID-19) patients and pre–COVID-19 era controls. They identified hundreds of antibody targets, including several antibody epitopes shared by the mild and severe coronaviruses and many specific to SARS-CoV-2. A machine-learning model accurately classified patients infected with SARS-CoV-2 and guided the design of an assay for rapid SARS-CoV-2 antibody detection. The study also looked at how the antibody response and viral exposure history differ in patients with diverging outcomes, which could inform the production of improved vaccine and antibody therapies. Science , this issue p. eabd4250

We present here an evidence-based review of the utility, timing, and indications for laboratory test use in the domains of inflammation, cardiology, hematology, nephrology and co-infection for clinicians managing the care of hospitalized COVID-19 patients. Levels of IL-6, CRP, absolute lymphocyte count, neutrophils and neutrophil-to-lymphocyte ratio obtained upon admission may help predict the severity of COVID-19. Elevated lactate dehydrogenase, ferritin, aspartate aminotransferase, and ᴅ-dimer are associated with severe illness and mortality. Elevated cardiac troponin at hospital admission can alert clinicians to patients at risk for cardiac complications. Elevated proBNP may help distinguish a cardiac complication from noncardiac etiologies. Evaluation for co-infection is typically unnecessary in nonsevere cases but is essential in severe COVID-19, intensive care unit patients, and immunocompromised patients.

The emergence of SARS-CoV-2 has caused the current COVID-19 pandemic with catastrophic societal impact. Because many individuals shed virus for days before symptom onset, and many show mild or no symptoms, an emergent and unprecedented need exists for development and deployment of sensitive and high throughput molecular diagnostic tests. RNA-mediated oligonucleotide Annealing Selection and Ligation with next generation DNA sequencing (RASL-seq) is a highly multiplexed technology for targeted analysis of polyadenylated mRNA, which incorporates sample barcoding for massively parallel analyses. Here we present a more generalized method, capture RASL-seq (“cRASL-seq”), which enables analysis of any targeted pathogen-(and/or host-) associated RNA molecules. cRASL-seq enables highly sensitive (down to ∼1-100 pfu/ml or cfu/ml) and highly multiplexed (up to ∼10,000 target sequences) detection of pathogens. Importantly, cRASL-seq analysis of COVID-19 patient nasopharyngeal (NP) swab specimens does not involve nucleic acid extraction or reverse transcription, steps that have caused testing bottlenecks associated with other assays. Our simplified workflow additionally enables the direct and efficient genotyping of selected, informative SARS-CoV-2 polymorphisms across the entire genome, which can be used for enhanced characterization of transmission chains at population scale and detection of viral clades with higher or lower virulence. Given its extremely low per-sample cost, simple and automatable protocol and analytics, probe panel modularity, and massive scalability, we propose that cRASL-seq testing is a powerful new surveillance technology with the potential to help mitigate the current pandemic and prevent similar public health crises.

BackgroundRisk factors for poor outcomes from COVID-19 are emerging among US cohorts, but patient trajectories during hospitalization ranging from mild-moderate, severe, and death and the factors associated with these outcomes have been underexplored.MethodsWe performed a cohort analysis of consecutive COVID-19 hospital admissions at 5 Johns Hopkins hospitals in the Baltimore/DC area between March 4 and April 24, 2020. Disease severity and outcomes were classified using the WHO COVID-19 disease severity ordinal scale. Cox proportional-hazards regressions were performed to assess relationships between demographics, clinical features and progression to severe disease or death.Results832 COVID-19 patients were hospitalized; 633 (76.1%) were discharged, 113 (13.6%) died, and 85 (10.2%) remained hospitalized. Among those discharged, 518 (82%) had mild/moderate and 116 (18%) had severe illness. Mortality was statistically significantly associated with increasing age per 10 years (adjusted hazard ratio (aHR) 1.54; 95%CI 1.28-1.84), nursing home residence (aHR 2.13, 95%CI 1.41-3.23), Charlson comorbidity index (1.13; 95% CI 1.02-1.26), respiratory rate (aHR 1.13; 95%CI 1.09-1.17), D-dimer greater than 1mg/dL (aHR 2.79; 95% 1.53-5.09), and detectable troponin (aHR 2.79; 95%CI 1.53-5.09). In patients under 60, only male sex (aHR 1.7;95%CI 1.11-2.58), increasing body mass index (BMI) (aHR1.25 1.14-1.37), Charlson score (aHR 1.27; 1.1-1.46) and respiratory rate (aHR 1.16; 95%CI 1.13-1.2) were associated with severe illness or death.ConclusionsA combination of demographic and clinical features on admission is strongly associated with progression to severe disease or death in a US cohort of COVID-19 patients. Younger patients have distinct risk factors for poor outcomes.