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To determine the proportion of fevers caused by leptospirosis, we obtained serum specimens and epidemiologic and clinical data from patients in Galle, Sri Lanka, March-October 2007. Immunoglobulin M ELISA was performed on paired serum specimens to diagnose acute (seroconversion or 4-fold titer rise) or past (titer without rise) leptospirosis and seroprevalence (acute). We compared (individually) the diagnostic yield of acute-phase specimens and clinical impression with paired specimens for acute leptospirosis. Of 889 patients with paired specimens, 120 had acute leptosoirosis and 241 had past leptospirosis. The sensitivity and specificity of acute-phase serum specimens were 17.5% (95% confidence interval [CI] 11.2%-25.5%) and 69.2% (95% CI 65.5%-72.7%), respectively, and of clinical impression 22.9% (95% CI 15.4%-32.0%) and 91.7% (95% CI 89.2%-93.8%), respectively. For identifying acute leptospirosis, clinical impression is insensitive, and immunoglobulin M results are more insensitive and costly. Rapid, pathogen-based tests for early diagnosis are needed. [ABSTRACT FROM AUTHOR]

Hemophagocytic lymphohistiocytosis (HLH), a rare disease, results in pathological findings secondary to an abnormal proliferation of activated lymphocytes and histiocytes (tissue macrophages) and is lethal unless identified and adequately treated. Clinical features of HLH include fever, hepatosplenomegaly, cytopenias, hypertriglyceridemia, hypofibrinogenemia, elevated blood levels of ferritin, lymphadenopathy, skin rash, jaundice, and edema. Often, the symptoms of HLH are misinterpreted as infection, resulting in inadequate treatment and death. Several case studies of premature neonates with HLH have recently been published. Therapeutic guidelines for HLH exist and, when identified, HLH in the premature infant can be successfully treated resulting in resolution of symptoms. [ABSTRACT FROM AUTHOR]

Hemophagocytic lymphohistiocytosis (HLH), a rare disease, results in pathological findings secondary to an abnormal proliferation of activated lymphocytes and histiocytes (tissue macrophages) and is lethal unless identified and adequately treated. Clinical features of HLH include fever, hepatosplenomegaly, cytopenias, hypertriglyceridemia, hypofibrinogenemia, elevated blood levels of ferritin, lymphadenopathy, skin rash, jaundice, and edema. Often, the symptoms of HLH are misinterpreted as infection, resulting in inadequate treatment and death. Several case studies of premature neonates with HLH have recently been published. Therapeutic guidelines for HLH exist and, when identified, HLH in the premature infant can be successfully treated resulting in resolution of symptoms. [ABSTRACT FROM AUTHOR]

Purpose: As primary care (PC) clinics seek to integrate behavioral health (BH) services into patient care, it is crucial to understand the experiences of the clinic team and the impact on workflow and well-being. This study was designed to identify perspectives and experiences of nurse practitioner-led PC teams as they implemented a behavioral health integration (BHI) model into their Federally Qualified Health Center PC practices., Methods: We conducted in-depth qualitative interviews with staff members at three clinic sites that implemented BHI. Interviewees were asked questions about the benefits and challenges encountered in the new BHI workflow, the dynamics of the warm hand-off, the tools and resources they used and desired, and the changes they would like to see to promote efficient workflows., Results: We interviewed 21 staff members during May and June of 2020. An analysis of the qualitative data showed the most frequently reported experiences and attitudes focused on (a) the availability of behavioral health consultants (BHC); (b) procedural uses of the warm hand-off; (c) the organization's productivity goals; and (d) desired tools and resources that are generally unavailable to the clinicians but could make a difference to patient care., Conclusion: Our results can assist FQHCs and similar organizations to achieve both BHI and the Quintuple aim. Integrating BH services into PC clinics is valuable and may mitigate clinician-staff burnout. However, PC organizations desiring to integrate new sustainable care models should consider involving staff in every phase of the transitional process phase to increase staff buy-in and staff rapport.

SUMMARYDetection of the presence of infection and its etiology must be accurate and timely to facilitate appropriate antimicrobial use. Diagnostic strategies that rely solely on pathogen detection often are insufficient due to poor test characteristics, inability to differentiate colonization from infection, or protracted delay to result. Understanding the human response across different pathogens on a clinical and molecular level can provide more accurate, timely, and useful answers, especially in critical illness and diagnostic uncertainty. Improvements in understanding the human immune response including genomics, protein analysis, gene expression, and cellular morphology have led to rapid innovation of new host response-based diagnostic tests. This review describes the limitations of pathogen-focused technology and the benefits of examining the breadth of immune response to diagnose infection. It then explores biomarkers that have been studied for this purpose and scrutinizes the performance of host-based multianalyte testing. Currently cleared diagnostics and those in late-stage development are described in depth, with a focus on the purpose of testing and its utility for clinicians. Finally, it concludes by examining opportunities for further host response-derived diagnostic innovation.

Lower respiratory tract infection (LRTI) is a common reason for hospitalization and antibacterial use globally. There is considerable overlap in the clinical presentation of bacterial and viral LRTIs. Low- or middle-income countries (LMICs) face the dual challenge of appropriately targeting antibacterials for bacterial LRTI while reducing inappropriate antibacterials for viral LRTI. We propose a framework by which an electronic clinical decision support tool (eCDST) for diagnosing LRTI and reducing unnecessary antibacterial use may be developed, validated, and prospectively evaluated in an LMIC. The developed tool would be data driven, low-cost, feasible in the local setting, adaptable based on resource availability, and updated in real time, with prospective assessment to identify its clinical impact. We draw upon our team's recent experience developing an eCDST for LRTI management in Sri Lanka. Publicly sharing such processes and data is valuable, such that we can collectively improve clinical care in LMICs and other settings.

Introduction: Influenza virus infections are a major global health problem. Influenza can result in mild/moderate disease or progress to more severe disease, leading to high morbidity and mortality. Severity is thought to be primarily driven by immunopathology, but predicting which individuals are at a higher risk of being hospitalized warrants investigation into host genetics and the molecular signatures of the host response during influenza infections., Methods: Here, we performed transcriptome and genotype analysis in healthy controls and patients exhibiting mild/moderate or severe influenza (ICU patients). A unique aspect of our study was the genotyping of all participants, which allowed us to assign ethnicities based on genetic variation and assess whether the variation was correlated with expression levels., Results: We identified 169 differentially expressed genes and related molecular pathways between patients in the ICU and those who were not in the ICU. The transcriptome/genotype association analysis identified 871 genes associated to a genetic variant and 39 genes distinct between African-Americans and Caucasians. We also investigated the effects of age and sex and found only a few discernible gene effects in our cohort., Discussion: Together, our results highlight select risk factors that may contribute to an increased risk of ICU admission for influenza-infected patients. This should help to develop better diagnostic tools based on molecular signatures, in addition to a better understanding of the biological processes in the host response to influenza., Competing Interests: During the conduct of this study, ET and CW were co-founders of Predigen, Inc. and held equity in Biomeme, Inc. ET is currently employed by and holds equity in Danaher Corp. ET and CW have patents pending or granted for Methods to Diagnose and Treat Acute Respiratory Infections; Gene Expression Signatures Useful to Predict or Diagnose Sepsis and Methods of Using the Same; Methods for Characterizing Infections and Methods for Developing Tests for the Same; and Systems and methods for determining status, type, severity, and/or risk of infection. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest., (Copyright © 2024 Schughart, Smith, Tsalik, Threlkeld, Sellers, Fischer, Schreiber, Lücke, Cornberg, Debarry, Woods, McClain and Heise.)

Background: Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection., Methods: We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae , Mycoplasma pneumoniae , influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust., Results: Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96., Discussion: This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Sepsis from infection is a global health priority and clinical trials have failed to deliver effective therapeutic interventions. To address complicating heterogeneity in sepsis pathobiology, and improve outcomes, promising precision medicine approaches are helping identify disease endotypes, however, they require a more complete definition of sepsis subgroups., Methods: Here, we use RNA sequencing from peripheral blood to interrogate the host response to sepsis from participants in a global observational study carried out in West Africa, Southeast Asia, and North America (N = 494)., Results: We identify four sepsis subtypes differentiated by 28-day mortality. A low mortality immunocompetent group is specified by features that describe the adaptive immune system. In contrast, the three high mortality groups show elevated clinical severity consistent with multiple organ dysfunction. The immunosuppressed group members show signs of a dysfunctional immune response, the acute-inflammation group is set apart by molecular features of the innate immune response, while the immunometabolic group is characterized by metabolic pathways such as heme biosynthesis., Conclusions: Our analysis reveals details of molecular endotypes in sepsis that support immunotherapeutic interventions and identifies biomarkers that predict outcomes in these groups., (© 2024. The Author(s).)

Background: Antimicrobial overprescription is common for lower respiratory tract infections (LRTI), as viral and bacterial infections generally present with similar clinical features. Overprescription is associated with downstream antimicrobial resistance. This study aims to identify the prevalence and predictors of antibiotic prescription among patients hospitalized with viral LRTI., Methods: A prospective cohort study was conducted among patients aged ≥1 year hospitalized with viral LRTI in a tertiary care hospital in Southern Province, Sri Lanka from 2018-2021. Demographic, clinical, and laboratory data were recorded. Nasopharyngeal and blood samples were collected for multiplex polymerase chain reaction testing for 21 respiratory pathogens and procalcitonin (PCT) detection, respectively. Demographic and clinical features associated with antibiotic prescription were identified using Chi Square and t-tests; significant variables (p<0.05) were further included in multivariable logistic regression models. The potential impact of biomarker testing on antibiotic prescription was simulated using standard c-reactive protein (CRP) and PCT cut-offs., Results: Of 1217 patients enrolled, 438 (36.0%) had ≥1 respiratory virus detected, with 48.4% of these patients being male and 30.8% children. Influenza A (39.3%) and human rhinovirus/ enterovirus (28.3%) were most commonly detected. A total of 114 (84.4%) children and 266 (87.8%) adults with respiratory viruses were treated with antibiotics. Among children, neutrophil percentage (median 63.6% vs 47.6%, p = 0.04) was positively associated with antibiotic prescription. Among adults, headache (60.6% vs 35.1%, p = 0.003), crepitations/crackles (55.3% vs 21.6%, p<0.001), rhonchi/wheezing (42.9% vs 18.9%, p = 0.005), and chest x-ray opacities (27.4% vs 8.1%, p = 0.01) were associated with antibiotic prescription. Access to CRP and procalcitonin test results could have potentially decreased inappropriate antibiotic prescription in this study by 89.5% and 83.3%, respectively., Conclusions: High proportions of viral detection and antibiotic prescription were observed among a large inpatient cohort with LRTI. Increased access to point-of-care biomarker testing may improve antimicrobial prescription., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Medrano et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Adolescents from ethnoracially minoritized backgrounds increasingly report high rates of attempted suicide, trauma exposure, and limited access to mental healthcare services. However, less is known regarding their use of services across different youth-serving systems. This study examines the associations and interactions between self-injurious thoughts and behaviors (SITBs), race/ethnicity, and service sector utilization (mental healthcare, general healthcare, school, and social services) among a sample of trauma-exposed and treatment-seeking adolescents. Participants were treatment-seeking adolescents (N = 4406) ages 12-17 from the National Child Traumatic Stress Network Core Data Set who had available data for SITBs, race/ethnicity, services utilized, and other key variables. Mixed effects logistic regression was used to examine main and interactive effects for whether adolescents' race/ethnicity and SITBs were associated with service utilization in each of the identified service sectors. SITBs were associated with adolescents' utilization of mental healthcare (OR = 1.38 p < 0.001), general healthcare (OR = 2.30; p < 0.001), and school services (OR = 1.38 p < 0.001). NH Black adolescents reporting SITBs were less likely to use mental health services than other NH Black youths (OR = 0.53; p = 0.004). Hispanic adolescents reporting SITBs were more likely to utilize healthcare services than other Hispanic youths (OR = 1.51; p = 0.039). Trauma-exposed adolescents reporting SITBs are more likely to utilize mental healthcare, general healthcare, and school-based services than other trauma-exposed adolescents. However, NH Black adolescents experiencing SITBs may face additional barriers to utilizing mental healthcare services. Findings can be used to develop nursing practices and policies to address barriers faced by adolescents reporting SITBs., (© 2024 The Authors. Research in Nursing & Health published by Wiley Periodicals LLC.)

Lymphocyte telomere length (TL) is highly variable and shortens with age. Short telomeres may impede TL-dependent T-cell clonal expansion with viral infection. As SARS-CoV-2 infection can induce prolonged and severe T-cell lymphopenia, infected adults, and particularly older adults with short telomeres, may display severe T-cell lymphopenia. To examine the relationship between T-cell TL parameters and T-cell counts, we studied 40 patients hospitalized with severe COVID-19. T-cells were isolated from lymphocytes, counted using flow cytometry, and their TL parameters were measured using the Telomere Shortest Length Assay. The cohort (median age = 62 years, 27% female) was racially and ethnically diverse (33% White, 35% Black, and 33% Other). On intensive care unit study day 1, T-cell count (mean=1.03 x10 9 /L) was inversely related to age (p=0.007) and higher in females than males (p=0.025). Mean TL was 3.88 kilobases (kb), and 45.3% of telomeres were shorter than 3 kb. Using multiple regression analysis and adjusting for age and sex, T-cell count decreased with increased proportion of T-cell telomeres shorter than 3 kb (p=0.033) and increased with mean TL (p=0.052). Our findings suggest an association between the buildup of short telomeres within T-cells and explain in part reduced peripheral blood T-cell counts in patients with severe COVID-19. Shortened T-cell telomeres may be a risk factor for COVID-19-associated T-cell lymphopenia., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Kraft, Verhulst, Lai, Sullenger, Wang, Rountree, Chen, Woods, Denny and Aviv.)

Background: Index-cluster studies may help characterize the spread of communicable infections in the presymptomatic state. We describe a prospective index-cluster sampling strategy (ICSS) to detect presymptomatic respiratory viral illness and its implementation in a college population., Methods: We enrolled an annual cohort of first-year undergraduates who completed daily electronic symptom diaries to identify index cases (ICs) with respiratory illness. Investigators then selected 5-10 potentially exposed, asymptomatic close contacts (CCs) who were geographically co-located to follow for infections. Symptoms and nasopharyngeal samples were collected for 5 days. Logistic regression model-based predictions for proportions of self-reported illness were compared graphically for the whole cohort sampling group and the CC group., Results: We enrolled 1379 participants between 2009 and 2015, including 288 ICs and 882 CCs. The median number of CCs per IC was 6 (interquartile range, 3-8). Among the 882 CCs, 111 (13%) developed acute respiratory illnesses. Viral etiology testing in 246 ICs (85%) and 719 CCs (82%) identified a pathogen in 57% of ICs and 15% of CCs. Among those with detectable virus, rhinovirus was the most common (IC: 18%; CC: 6%) followed by coxsackievirus/echovirus (IC: 11%; CC: 4%). Among 106 CCs with a detected virus, only 18% had the same virus as their associated IC. Graphically, CCs did not have a higher frequency of self-reported illness relative to the whole cohort sampling group., Conclusions: Establishing clusters by geographic proximity did not enrich for cases of viral transmission, suggesting that ICSS may be a less effective strategy to detect spread of respiratory infection., Competing Interests: Potential conflicts of interest. M. T. M. reports grants from the Defense Advanced Research Projects Agency (DARPA) and the National Institutes of Health (NIH), and has a patent pending on “Methods to diagnose and treat acute respiratory infections.” T. W. B. reports grants from DARPA and NIH; reports owning equity in and serving as a consultant for Biomeme; and has a patent pending on Methods to diagnose and treat acute respiratory infections. E. L. T. reports consultancy fees and equity from Biomeme; has patents pending on Biomarkers for the molecular classification of bacterial infection and Methods to diagnose and treat acute respiratory infections; and is currently an employee of Danaher Diagnostics. C. W. W. and G. S. G. have patents pending on Molecular classification of bacterial infection and gene expression signatures useful to predict or diagnose sepsis and methods of using the same, and have patents issued on Methods to diagnose and treat acute respiratory disease and Methods of identifying infectious disease and assays for identifying infectious disease. C. W. W. reports owning equity in and consulting for Biomeme; reports grants from DARPA, NIH, Antibacterial Resistance Leadership Group, and Sanofi; and has received consultancy fees from bioMérieux, Roche, Biofire, Giner, and Biomeme. All other authors report no potential conflicts., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Aim: The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Materials & methods: Here we developed and implemented a machine learning algorithm, the exposure signature discovery algorithm (ESDA), to identify the most important features present in multiple epigenomic and transcriptomic datasets to produce an integrated exposure signature (ES). Results: Signatures were developed for seven exposures including Staphylococcus aureus , human immunodeficiency virus, SARS-CoV-2, influenza A (H3N2) virus and Bacillus anthracis vaccinations. ESs differed in the assays and features selected and predictive value. Conclusion: Integrated ESs can potentially be utilized for diagnosis or forensic attribution. The ESDA identifies the most distinguishing features enabling diagnostic panel development for future precision health deployment.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens., (© 2023. The Author(s).)

While the coronavirus disease 2019 (COVID-19) pandemic continues to present global challenges, sufficient time has passed to reflect on lessons learned and use those insights to inform policy and approaches to prepare for the next pandemic. In May 2022, the Duke Clinical Research Institute convened a think tank with thought leaders from academia, clinical practice, the pharmaceutical industry, patient advocacy, the National Institutes of Health, the US Food and Drug Administration, and the Centers for Disease Control and Prevention to share, firsthand, expert knowledge of the insights gained from the COVID-19 pandemic and how this acquired knowledge can help inform the next pandemic response. The think tank focused on pandemic preparedness, therapeutics, vaccines, and challenges related to clinical trial design and scale-up during the early phase of a pandemic. Based on the multi-faceted discussions, we outline 10 key steps to an improved and equitable pandemic response., Competing Interests: Potential conflicts of interest. A. F. H. reports contracts with Pfizer and Merck and consulting fees from Merck. B. L. is an employee of and owns stock in Moderna and reports support for travel to a meeting from Moderna. C. W. W. reports consulting fees from Arena Pharmaceuticals, BioFire, FHI Clinical, Giner, Karius, and SeLux Diagnostics; grants or contracts (paid to institution) from Defense Advanced Research Projects Agency, National Institutes of Health (NIH)-Antibacterial Resistance Leadership Group/National Institute of Allergy and Infectious Diseases/NIH Vaccine and Treatment Evaluation Units/National Institute of Mental Health/National Institute of General Medical Sciences, Sanofi, Najit, the Centers for Disease Control and Prevention (CDC), Patient-Centered Outcomes Research, United States Army Medical Research Acquisition Activity, Department of Defence, Abbott, and Pfizer; support for attending meetings and/or travel from the American Society for Microbiology (ASM); participation on a data and safety monitoring board (DSMB) or advisory board for IDbyDNA, Janssen, Regeneron, Roche Molecular Sciences; a leadership or fiduciary role for ASM and the American Society of Tropical Medicine and Hygiene; being employed by Duke University, Durham Veterans Affairs Hospital, Biomeme, and Equity/Founder of Predigen, Inc; and planned, issued, or pending patents for biomarkers for the molecular classification of bacterial infection, methods to diagnose and treat acute respiratory infections, gene expression signatures useful to predict or diagnose sepsis and methods of using the same, host-based molecular signatures of human infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 (coronavirus disease 2019 [COVID-19]), methods of identifying infectious disease and assays for identifying infectious disease, and nasopharyngeal protein biomarkers of acute respiratory virus infection and methods of using same. H. C. and S. C. B. are employees of and hold or may hold stock in AstraZeneca. J. W. reports being an employee of and owns stock/stock options in and received equipment, materials, drugs, medical writing, gifts, and other services from Johnson & Johnson and, as CMO, has been deposed in litigation; patents issued that do not relate to the current article (available on request); and a role on the Brooklyn College Cancer Center Advisory Board, a Brooklyn College Foundation Trustee, and on the Fellowships at Auschwitz for the Study of Professional Ethics, Academic Committee. J. R. D. is an employee and shareholder in Eli Lilly and Company. L. H. C. reports consulting fees from Regeneron for the NFL Players Association and grants or contracts from NIH for PCORI. L. S. reports stock/stock options in Novartis. L. R. is an employee of and owns stock/stock options in and received support for attending meetings and/or travel from Bayer AG. M. S. reports consulting fees from AbbVie, Assembly Bio, Antios, Arbutus, Gilead Sciences, Precision Bio, and GSK for scientific advisory boards and participation on a DSMB for Gilead Sciences and AbbVie and a role as editor of the Journal Viral Hepatitis. O. V. is an employee of Boehringer Ingelheim. P. P. has a patent pending for sotrovimab and is an employee and shareholder of Vir Biotechnology. S. N. reports consulting fees from Pardes Biosciences, Theratechnologies, and Silverback Therapeutics; stock/stock options in Vir Biotechnology; grants or contracts (paid to institution) from Gilead Sciences and AbbVie; participation on an advisory board for Vir Biotechnology, a DSMB for Personal Health Insights, Inc; and serving on an event adjudication committee for Bristol–Myers Squibb/PRA. M. A. M. reports consulting fees from Abcam; stock/stock options in Grid Therapeutics; a role as an advisory board member for GSK Belimumab Pregnancy Registry; and funding to Duke from NIAD (U01 AI151378): Centers for Research in Emerging Infectious Disease (CREID) Network Coordinating Center, HHS 75N93019C00050: Duke Collaborative Influenza Vaccine Innovation Centers (CIVICs) A: Vaccine Center, HHS 75N93019C00054: Duke CIVICs C: Clinical Core, U19 AI144177: A Global Syphilis Vaccine Targeting Outer Membrane Proteins Of Treponema pallidum, 2P01 AI089618: Structure-Function Analysis Of Infection- And Vaccine-Induced B Cell Repertoires. S. E. T. reports royalties from UptoDate; grants or contracts (paid to institution) from the CDC; payment or honoraria (to author) from the Infectious Disease Society of America (IDSA) and Emerson Hospital; support from DCRI to attend the meeting upon which this article was based. L. R. B. is involved in human immunodeficiency virus (HIV) and SARS-CoV-2 vaccine clinical trials conducted in collaboration with the NIH, HIV Vaccine Trials Network, COVID Vaccine Prevention Network, International AIDS Vaccine Initiative, Crucell/Janssen, Moderna, Military HIV Research Program, the Gates Foundation, and Harvard Medical School. reports participation on a DSMB for NIH and AMDAC Committee for the FDA (research funded by the NIH, Welcome Trust, and the Gates Foundation). R. T. G. reports a leadership or fiduciary role on the NIH COVID Treatment Guidelines Panel and IDSA COVID Treatment Guidelines Panel. R. G. reports grants (to institution) from NIH/NIAID, book chapter royalties from Elsevier, and section editor royalties from UpToDate. All remaining authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Immune responses to SARS-CoV-2 primarily target the receptor binding domain of the spike protein, which continually mutates to escape acquired immunity. Other regions in the spike S2 subunit, such as the stem helix and the segment encompassing residues 815-823 adjacent to the fusion peptide, are highly conserved across sarbecoviruses and are recognized by broadly reactive antibodies, providing hope that vaccines targeting these epitopes could offer protection against both current and emergent viruses. Here we employ computational modeling to design scaffolded immunogens that display the spike 815-823 peptide and the stem helix epitopes without the distracting and immunodominant receptor binding domain. These engineered proteins bind with high affinity and specificity to the mature and germline versions of previously identified broadly protective human antibodies. Epitope scaffolds interact with both sera and isolated monoclonal antibodies with broadly reactivity from individuals with pre-existing SARS-CoV-2 immunity. When used as immunogens, epitope scaffolds elicit sera with broad betacoronavirus reactivity and protect as "boosts" against live virus challenge in mice, illustrating their potential as components of a future pancoronavirus vaccine., (© 2023. The Author(s).)

To elucidate host response elements that define impending decompensation during SARS-CoV-2 infection, we enrolled subjects hospitalized with COVID-19 who were matched for disease severity and comorbidities at the time of admission. We performed combined single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on peripheral blood mononuclear cells (PBMCs) at admission and compared subjects who improved from their moderate disease with those who later clinically decompensated and required invasive mechanical ventilation or died. Chromatin accessibility and transcriptomic immune profiles were markedly altered between the two groups, with strong signals in CD4 + T cells, inflammatory T cells, dendritic cells, and NK cells. Multiomic signature scores at admission were tightly associated with future clinical deterioration (auROC 1.0). Epigenetic and transcriptional changes in PBMCs reveal early, broad immune dysregulation before typical clinical signs of decompensation are apparent and thus may act as biomarkers to predict future severity in COVID-19., Competing Interests: M.T.M., E.L.T., T.W.B., and C.W.W. have patents pending on Molecular Methods to Diagnose and Treat Respiratory Infections.

Background: The Panbio™ COVID-19 IgG Rapid Test Device ("Panbio™") detects IgG antibodies against the SARS-CoV-2 spike protein from viral infection or vaccination., Objectives: To determine the diagnostic sensitivity and specificity of the Panbio™ professional use test, using fingerstick whole blood and venous plasma., Study Design: Fingerstick whole blood and venous plasma from each participant were tested with Panbio™ and compared against the SARS-CoV-2 IgG II assay on the Abbott Architect™ platform (Europe) or the equivalent AdviseDx SARS-CoV-2 IgG II Abbott Alinity i™ platform (US). 447 evaluable participants were enrolled across 6 US and 9 European clinical centers., Results: For unvaccinated participants with PCR-confirmed infection ≥21 days post-symptom onset, the Panbio™ sensitivity with fingerstick whole blood was 92.6 % (95 % CI: 85.9, 96.7), and the specificity was 97.0 % (95 % CI: 93.1, 99.0). For venous plasma, the sensitivity was 90.0 % (95 % CI: 79.5, 96.2) for participants with PCR-confirmed infection and symptom onset 22-180 days ago; the specificity was 96.3 % (92.2, 98.6). For vaccinated participants, the sensitivity was 98.4 % (95 % CI: 91.2, 100.0) for fingerstick whole blood and 96.7 % (95 % CI: 88.7, 99.6) for venous plasma., Conclusion: The Panbio™ test had high sensitivity and specificity for detecting IgG against the SARS-CoV-2 spike protein., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Roy Vijesurier, Camilla Forssten, Simon Kordowich, Yin Li and Wenchi Lin report financial support was provided by 10.13039/100001316Abbott Laboratories. Pablo Ryan and Patrick T. Kennedy report financial support was provided by 10.13039/100001316Abbott Laboratories. Roy Vijesurier, Camilla Forssten, Simon Kordowich, Yin Li and Wenchi Lin report a relationship with Abbott Laboratories that includes: employment. Pablo Ryan and Patrick T. Kennedy report a relationship with Abbott Laboratories that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Background: The US Department of Veterans Affairs (VA) has dedicated significant resources toward countering the COVID-19 pandemic. Sequencing for Research Clinical and Epidemiology (SeqFORCE) and Sequencing Collaborations United for Research and Epidemiology (SeqCURE) were developed as clinical and research consortiums, respectively, focused on the genetic COVID-19 surveillance., Observations: Through genetic sequencing, VA SeqFORCE and SeqCURE collaborations contributed to the COVID-19 pandemic response and scientific understanding. Future directions for each program include the assessment of the unique impact of COVID-19 on the veteran population, as well as the adaptation of these programs to future infectious disease threats. We foresee the use of these established platforms beyond infectious diseases., Conclusions: VA SeqFORCE and SeqCURE were established as clinical and research programs dedicated to sequencing COVID-19 as part of ongoing clinical and surveillance efforts. In the future, we anticipate that having these programs embedded within the largest integrated health care system in the US will enable the study of pathogens and pandemics beyond COVID-19 and at an unprecedented scale. The investment in these programs will form an integral part of our nation's response to emerging infectious diseases, with future applications to precision medicine and beyond., Competing Interests: Author disclosures: VCM has received support from the Emory CFAR (P30 AI050409) and received investigator-initiated research grants (to the institution) and consultation fees (both unrelated to the current work) from Eli Lilly, Bayer, Gilead Sciences, and ViiV. CWW has a consulting relationship with Biomeme, Bavarian-Nordic, Pfizer, and Regeneron. CWW has also received research grants from Pfizer and Sanofi. All other authors report no actual or potential conflicts of interest or outside sources of funding with regard to this article., (Copyright © 2023 Frontline Medical Communications Inc., Parsippany, NJ, USA.)

Objective: Scalable strategies to reduce the time burden and increase contact tracing efficiency are crucial during early waves and peaks of infectious transmission., Design: We enrolled a cohort of SARS-CoV-2-positive seed cases into a peer recruitment study testing social network methodology and a novel electronic platform to increase contact tracing efficiency., Setting: Index cases were recruited from an academic medical center and requested to recruit their local social contacts for enrollment and SARS-CoV-2 testing., Participants: A total of 509 adult participants enrolled over 19 months (384 seed cases and 125 social peers)., Intervention: Participants completed a survey and were then eligible to recruit their social contacts with unique "coupons" for enrollment. Peer participants were eligible for SARS-CoV-2 and respiratory pathogen screening., Main Outcome Measures: The main outcome measures were the percentage of tests administered through the study that identified new SARS-CoV-2 cases, the feasibility of deploying the platform and the peer recruitment strategy, the perceived acceptability of the platform and the peer recruitment strategy, and the scalability of both during pandemic peaks., Results: After development and deployment, few human resources were needed to maintain the platform and enroll participants, regardless of peaks. Platform acceptability was high. Percent positivity tracked with other testing programs in the area., Conclusions: An electronic platform may be a suitable tool to augment public health contact tracing activities by allowing participants to select an online platform for contact tracing rather than sitting for an interview., Competing Interests: J.McCall is an employee of Duke University and serves as a contractor for the US Food and Drug Administration. J.P.D. is a Scientific Advisor at Veri, Inc. C.W.W. is employed by Duke University, Durham Veterans Affairs Healthcare System, and Biomeme; C.W.W. is founder and holds equity in Predigen, Inc; C.W.W. has grants from National Institutes of Health (ARLG, VTEU, NIMHO, NIGMS), DARPA, CDC, PCORI, USAMRAA, DOD, Abbott, Najit, Pfizer, and Sanofi; C.W.W. is a consultant for Arena, Biofire, FHI Clinical, and Karius; C.W.W. is on the advisory board for FHI Clinical and Regeneron, and he is a member of the Board of Directors for Global Health Innovation Alliance Accelerator; C.W.W. serves on a DSMB for Janssen. E.S.H. is an employee of and has equity in Verily Life Sciences, is founder of and has equity in KēlaHealth, and is founder of and has equity in Clinetic. For the remaining authors, no conflicts of interest were declared., (Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc.)

Many studies identified factors associated with vaccination intention and hesitancy, but factors associated with vaccination promptness and the effect of vaccination intention on vaccination promptness are unknown. This study identified factors associated with COVID-19 vaccination promptness and evaluated the role of vaccination intention on vaccination promptness in 1223 participants in a community-based longitudinal cohort study (June 2020 to December 2021). Participants answered questions regarding COVID-19 vaccination intention, vaccination status, and reasons for not receiving a vaccine. The association of baseline vaccine hesitancy with vaccination was assessed by the Kaplan-Meier survival analysis. Follow-up analyses tested the importance of other variables predicting vaccination using the Cox proportional hazards model. Older age was associated with shorter time to vaccination (HR = 1.76 [1.37-2.25] 85-year-old versus 65-year-old). Lower education levels (HR = 0.80 [0.69-0.92]), household incomes (HR = 0.84 [0.72-0.98]), and baseline vaccination intention of 'No' (HR = 0.16 [0.11-0.23]) were associated with longer times to vaccination. The most common reasons for not being vaccinated (N = 58) were vaccine safety concerns (n = 33), side effects (n = 28), and vaccine effectiveness (n = 25). Vaccination campaigns that target populations prone to hesitancy and address vaccine safety and effectiveness could be helpful in future vaccination rollouts.

We collected oral and/or rectal swabs and serum from dogs and cats living in homes with SARS-CoV-2-PCR-positive persons for SARS-CoV-2 PCR and serology testing. Pre-COVID-19 serum samples from dogs and cats were used as negative controls, and samples were tested in duplicate at different timepoints. Raw ELISA results scrutinized relative to known negative samples suggested that cut-offs for IgG seropositivity may require adjustment relative to previously proposed values, while proposed cut-offs for IgM require more extensive validation. A small number of pet dogs (2/43, 4.7%) and one cat (1/21, 4.8%) were positive for SARS-CoV-2 RNA, and 28.6 and 37.5% of cats and dogs were positive for anti-SARS-CoV-2 IgG, respectively., Competing Interests: Dorothee Bienzle is an Academic Editor for PeerJ., (©2023 Gin et al.)

Lung inflammation is a hallmark of Coronavirus disease 2019 (COVID-19) in patients who are severely ill, and the pathophysiology of disease is thought to be immune mediated. Mast cells (MCs) are polyfunctional immune cells present in the airways, where they respond to certain viruses and allergens and often promote inflammation. We observed widespread degranulation of MCs during acute and unresolved airway inflammation in SARS-CoV-2-infected mice and nonhuman primates. Using a mouse model of MC deficiency, MC-dependent interstitial pneumonitis, hemorrhaging, and edema in the lung were observed during SARS-CoV-2 infection. In humans, transcriptional changes in patients requiring oxygen supplementation also implicated cells with a MC phenotype in severe disease. MC activation in humans was confirmed through detection of MC-specific proteases, including chymase, the levels of which were significantly correlated with disease severity and with biomarkers of vascular dysregulation. These results support the involvement of MCs in lung tissue damage during SARS-CoV-2 infection in animal models and the association of MC activation with severe COVID-19 in humans, suggesting potential strategies for intervention.

Research on the COVID-19 pandemic revealed a disproportionate burden of COVID-19 infection and death among underserved populations and exposed low rates of SARS-CoV-2 testing in these communities. A landmark National Institutes of Health (NIH) funding initiative, the Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) program, was developed to address the research gap in understanding the adoption of COVID-19 testing in underserved populations. This program is the single largest investment in health disparities and community-engaged research in the history of the NIH. The RADx-UP Testing Core (TC) provides community-based investigators with essential scientific expertise and guidance on COVID-19 diagnostics. This commentary describes the first 2 years of the TC's experience, highlighting the challenges faced and insights gained to safely and effectively deploy large-scale diagnostics for community-initiated research in underserved populations during a pandemic. The success of RADx-UP shows that community-based research to increase access and uptake of testing among underserved populations can be accomplished during a pandemic with tools, resources, and multidisciplinary expertise provided by a centralized testing-specific coordinating center. We developed adaptive tools to support individual testing strategies and frameworks for these diverse studies and ensured continuous monitoring of testing strategies and use of study data. In a rapidly evolving setting of tremendous uncertainty, the TC provided essential and real-time technical expertise to support safe, effective, and adaptive testing. The lessons learned go beyond this pandemic and can serve as a framework for rapid deployment of testing in response to future crises, especially when populations are affected inequitably., Competing Interests: The authors declare a conflict of interest. Ephraim Tsalik has been a consultant for Biomeme, Inc.; has a patent pending for Methods to Diagnose and Treat Acute Respiratory Infections (US20180245154A1); and is currently employed by Danaher Corp. Michael Cohen-Wolkowiez receives support for research from the NIH [1U24-MD016258]; National Institute of Allergy and Infectious Diseases [HHSN272201500006I, 1K24-AI143971]; U.S. Food and Drug Administration [5U18-FD006298]; and industry for drug development in adults and children. Cathy A Petti receives consulting fees from Abbott Molecular and Rapid Diagnostics. Christopher Woods reports consulting fees from Arena Pharmaceuticals, BioFire, FHI Clinical, Giner, Karius, and SeLux Diagnostics. All other authors report no conflicts of interests.

Background: We evaluated the associations between baseline influenza virus-specific hemagglutination inhibition (HAI) and microneutralization (MN) titers and subsequent symptomatic influenza virus infection in a controlled human infection study., Methods: We inoculated unvaccinated healthy adults aged 18-49 years with an influenza A/California/04/2009/H1N1pdm-like virus (NCT04044352). We collected serial safety labs, serum for HAI and MN, and nasopharyngeal swabs for reverse-transcription polymerase chain reaction (RT-PCR) testing. Analyses used the putative seroprotective titer of ≥40 for HAI and MN. The primary clinical outcome was mild-to-moderate influenza disease (MMID), defined as ≥1 postchallenge positive qualitative RT-PCR test with a qualifying symptom/clinical finding., Results: Of 76 participants given influenza virus challenge, 54 (71.1%) experienced MMID. Clinical illness was generally very mild. MMID attack rates among participants with baseline titers ≥40 by HAI and MN were 64.9% and 67.9%, respectively, while MMID attack rates among participants with baseline titers <40 by HAI and MN were 76.9% and 78.3%, respectively. The estimated odds of developing MMID decreased by 19% (odds ratio, 0.81 [95% confidence interval, .62-1.06]; P = .126) for every 2-fold increase in baseline HAI. There were no significant adverse events., Conclusions: We achieved a 71.1% attack rate of MMID. High baseline HAI and MN were associated with protection from illness. Clinical Trials Registration. NCT04044352., Competing Interests: Potential conflicts of interest. J. R. O. reports grants to his institution from the National Science Foundation, Bill & Melinda Gates Foundation, Pfizer, NIH, and World Health Organization; consulting fees from Putnam; and participation on advisory boards for Pfizer, Seqirus, and Moderna, all outside the submitted work. D. I. B. reports consulting fees from Rational Vaccines and participation on an advisory board with Moderna and Dynavax, outside the submitted work. C. W. W. reports grants to his institution from Janssen and AstraZeneca, outside the submitted work. M. T. M. reports grants to his institution from NIH, outside the submitted work. R. W. F. reports grants to his institution from Pfizer, outside the submitted work, and clinical trial support from Pfizer. E. W. reports grants to his institution from Clinetic, Moderna, Pfizer, Seqirus, and Iliad Biotechnologies; consulting fees from Iliad Biotechnologies; and participation on the Vaxcyte advisory board. W. A. K. reports grants to her institution from Leidos, outside the submitted work; clinical trial support from Pfizer; subcontract from Leidos; and advisory board participation with the NIH. N. R. reports grants to her institution from Merck, Sanofi Pasteur, Quidel, Pfizer, and Lilly, outside the submitted work. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2023.)

Resolving chromatin-remodeling-linked gene expression changes at cell-type resolution is important for understanding disease states. Here we describe MAGICAL (Multiome Accessibility Gene Integration Calling and Looping), a hierarchical Bayesian approach that leverages paired single-cell RNA sequencing and single-cell transposase-accessible chromatin sequencing from different conditions to map disease-associated transcription factors, chromatin sites, and genes as regulatory circuits. By simultaneously modeling signal variation across cells and conditions in both omics data types, MAGICAL achieved high accuracy on circuit inference. We applied MAGICAL to study Staphylococcus aureus sepsis from peripheral blood mononuclear single-cell data that we generated from subjects with bloodstream infection and uninfected controls. MAGICAL identified sepsis-associated regulatory circuits predominantly in CD14 monocytes, known to be activated by bacterial sepsis. We addressed the challenging problem of distinguishing host regulatory circuit responses to methicillin-resistant and methicillin-susceptible S. aureus infections. Although differential expression analysis failed to show predictive value, MAGICAL identified epigenetic circuit biomarkers that distinguished methicillin-resistant from methicillin-susceptible S. aureus infections., Competing Interests: Competing interests A.G.L. is a military service member. This work was prepared as part of his official duties. Title 17, US Code §105 provides that copyright protection under this title is not available for any work of the US Government. Title 17, US code §101 defines a US Government work as a work prepared by a military service member or employee of the US Government as part of that person’s official duties. The views expressed in the article are those of the authors and do not necessarily express the official policy and position of the US Navy, the Department of Defense, the US Government, or the institutions affiliated with the authors. V.G.F. reports personal fees from Novartis, Debiopharm, Genentech, Achaogen, Affinium, Medicines Co., MedImmune, Bayer, Basilea, Affinergy, Janssen, Contrafect, Regeneron, Destiny, Amphliphi Biosciences, Integrated Biotherapeutics; C3J, Armata, Valanbio; Akagera, Aridis, Roche, grants from NIH, MedImmune, Allergan, Pfizer, Advanced Liquid Logics, Theravance, Novartis, Merck; Medical Biosurfaces; Locus; Affinergy; Contrafect; Karius; Genentech, Regeneron, Deep Blue, Basilea, Janssen; Royalties from UpToDate, stock options from Valanbio and ArcBio, Honoraria from Infectious Diseases of America for his service as Associate Editor of Clinical Infectious Diseases, and a patent sepsis diagnostics pending. L.C.N. has received consulting fees from work as a scientific advisor for AbbVie, ViiV Healthcare, and Cytodyn and also serves on the Board of Directors of CytoDyn and has financial interests in Ledidi AS, all for work outside of the submitted work. S.C.S. is a founder of GNOMX Corp and serves as chief scientific officer. The remaining authors declare no competing interests.

Objective: We studied the safety and efficacy of hydroxychloroquine (HCQ) as pre-exposure prophylaxis for COVID-19 in healthcare workers (HCWs), using a meta-analysis of randomised controlled trials (RCTs)., Data Sources: PubMed and EMBASE databases were searched to identify randomised trials studying HCQ., Study Selection: Ten RCTs were identified (n=5079 participants)., Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were used in this systematic review and meta-analysis between HCQ and placebo using a Bayesian random-effects model. A pre-hoc statistical analysis plan was written., Main Outcomes: The primary efficacy outcome was PCR-confirmed SARS-CoV-2 infection and the primary safety outcome was incidence of adverse events. The secondary outcome included clinically suspected SARS-CoV-2 infection., Results: Compared with placebo, HCWs randomised to HCQ had no significant difference in PCR-confirmed SARS-CoV-2 infection (OR 0.92, 95% credible interval (CI): 0.58, 1.37) or clinically suspected SARS-CoV-2 infection (OR 0.78, 95% CI: 0.57, 1.10), but significant difference in adverse events (OR 1.35, 95% CI: 1.03, 1.73)., Conclusions and Relevance: Our meta-analysis of 10 RCTs investigating the safety and efficacy of HCQ as pre-exposure prophylaxis in HCWs found that compared with placebo, HCQ does not significantly reduce the risk of confirmed or clinically suspected SARS-CoV-2 infection, while HCQ significantly increases adverse events., Prospero Registration Number: CRD42021285093., Competing Interests: Competing interests: All authors except BSA reported no financial relationship with commercial interest. BSA has received NIH funds for COVID-19-related research and holds equity in VOC Health, a start-up company that is developing novel COVID-19 testing., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Influenza causes an estimated 3 to 5 million cases of severe illness annually, along with substantial morbidity and mortality, particularly in low- and middle-income countries (LMICs). Currently, Sri Lanka has no influenza vaccination policies and does not offer vaccination within the public healthcare sector. Therefore, we performed a cost-effectiveness analysis of influenza vaccine implementation for the Sri Lankan population. We designed a static Markov model that followed a population cohort of Sri Lankans in three age groups, 0-4, 5-64, and 65+ years, through two potential scenarios: trivalent inactivated vaccination (TIV) and no TIV across twelve-monthly cycles using a governmental perspective at the national level. We also performed probabilistic and one-way sensitivity analyses to identify influential variables and account for uncertainty. The vaccination model arm reduced influenza outcomes by 20,710 cases, 438 hospitalizations, and 20 deaths compared to no vaccination in one year. Universal vaccination became cost-effective at approximately 98.01% of Sri Lanka's 2022 GDP per capita (incremental cost-effectiveness ratio = 874,890.55 Rs/DALY averted; 3624.84 USD/DALY averted). Results were most sensitive to the vaccine coverage in the 5-64-year-old age group, the cost of the influenza vaccine dose in the 5-64-years-old age group, vaccine effectiveness in the under-5-years-old age group, and the vaccine coverage in the under-5-years-old age group. No value for a variable within our estimated ranges resulted in ICERs above Rs. 1,300,000 (USD 5386.15) per DALY adverted. Providing influenza vaccines was considered highly cost-effective compared to no vaccines. However, large-scale national studies with improved data are needed to better inform estimates and determine the impact of vaccination implementation.

Background: The COVID-19 pandemic highlighted the need for early detection of viral infections in symptomatic and asymptomatic individuals to allow for timely clinical management and public health interventions., Methods: Twenty healthy adults were challenged with an influenza A (H3N2) virus and prospectively monitored from 7 days before through 10 days after inoculation, using wearable electrocardiogram and physical activity sensors. This framework allowed for responses to be accurately referenced to the infection event. For each participant, we trained a semisupervised multivariable anomaly detection model on data acquired before inoculation and used it to classify the postinoculation dataset., Results: Inoculation with this challenge virus was well-tolerated with an infection rate of 85%. With the model classification threshold set so that no alarms were recorded in the 170 healthy days recorded, the algorithm correctly identified 16 of 17 (94%) positive presymptomatic and asymptomatic individuals, on average 58 hours postinoculation and 23 hours before the symptom onset., Conclusions: The data processing and modeling methodology show promise for the early detection of respiratory illness. The detection algorithm is compatible with data collected from smartwatches using optical techniques but needs to be validated in large heterogeneous cohorts in normal living conditions. Clinical Trials Registration. NCT04204493., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Antigen tests to detect SARS-CoV-2 have emerged as a promising rapid diagnostic method for COVID-19, but they are unable to differentiate between variants of concern (VOCs). Here, we report a rapid point-of-care test (POC-T), termed CoVariant-SPOT, that uses a set of antibodies that are either tolerant or intolerant to spike protein mutations to identify the likely SARS-CoV-2 strain concurrent with COVID-19 diagnosis using antibodies targeting the nucleocapsid protein. All reagents are incorporated into a portable, multiplexed, and sensitive diagnostic platform built upon a nonfouling polymer brush. To validate CoVariant-SPOT, we tested recombinant SARS-CoV-2 proteins, inactivated viruses, and nasopharyngeal swab samples from COVID-19 positive and negative individuals and showed that CoVariant-SPOT can readily distinguish between two VOCs: Delta and Omicron. We believe that CoVariant-SPOT can serve as a valuable adjunct to next-generation sequencing to rapidly identify variants using a scalable and deployable POC-T, thereby enhancing community surveillance efforts worldwide and informing treatment selection.

Objectives: To determine whether hydroxychloroquine (HCQ) is safe and effective at preventing COVID-19 infections among health care workers (HCWs)., Methods: In a 1: 1 randomized, placebo-controlled, double-blind, parallel-group, superiority trial at 34 US clinical centers, 1360 HCWs at risk for COVID-19 infection were enrolled between April and November 2020. Participants were randomized to HCQ or matched placebo. The HCQ dosing included a loading dose of HCQ 600 mg twice on day 1, followed by 400 mg daily for 29 days. The primary outcome was a composite of confirmed or suspected COVID-19 clinical infection by day 30, defined as new-onset fever, cough, or dyspnea and either a positive SARS-CoV-2 polymerase chain reaction test (confirmed) or a lack of confirmatory testing due to local restrictions (suspected)., Results: Study enrollment closed before full accrual due to recruitment challenges. The primary end point occurred in 41 (6.0%) participants receiving HCQ and 53 (7.8%) participants receiving placebo. No difference in the proportion of participants experiencing clinical infection (estimated difference of -1.8%, 95% confidence interval -4.6-0.9%, P = 0.20) was identified nor any significant safety issues., Conclusion: Oral HCQ taken as prescribed appeared safe among HCWs. No significant clinical benefits were observed. The study was not powered to detect a small but potentially important reduction in infection., Trial Registration: NCT04334148., Competing Interests: Declaration of competing interest All authors have completed the International Committee of Medical Journal Editors uniform disclosure form and declare: support from the Patient-Centered Outcomes Research Institute (PCORI) for the reported work; Vir Biotechnology (SC); AstraZeneca, GSK, Novartis, Pulmatric, Sanofi-Aventis, Genentech, Teva (MC); Vir Biotechnology (KA); Centers for Disease Control, Infection Control Education for Major Sports, LLC, UpToDate, AHRQ, NIAID (DA); NIH (KA); Pfizer (EO); Abbott (RR)., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Lower respiratory tract infections are frequently treated with antibiotics, despite a viral cause in many cases. It remains unknown whether low procalcitonin concentrations can identify patients with lower respiratory tract infection who are unlikely to benefit from antibiotics. We aimed to compare the efficacy and safety of azithromycin versus placebo to treat lower respiratory tract infections in patients with low procalcitonin., Methods: We conducted a randomised, placebo-controlled, double-blind, non-inferiority trial at five health centres in the USA. Adults aged 18 years or older with clinically suspected non-pneumonia lower respiratory tract infection and symptom duration from 24 h to 28 days were eligible for enrolment. Participants with a procalcitonin concentration of 0·25 ng/mL or less were randomly assigned (1:1), in blocks of four with stratification by site, to receive over-encapsulated oral azithromycin 250 mg or matching placebo (two capsules on day 1 followed by one capsule daily for 4 days). Participants, non-study clinical providers, investigators, and study coordinators were masked to treatment allocation. The primary outcome was efficacy of azithromycin versus placebo in terms of clinical improvement at day 5 in the intention-to-treat population. The non-inferiority margin was -12·5%. Solicited adverse events (abdominal pain, vomiting, diarrhoea, allergic reaction, or yeast infections) were recorded as a secondary outcome. This trial is registered with ClinicalTrials.gov, NCT03341273., Findings: Between Dec 8, 2017, and March 9, 2020, 691 patients were assessed for eligibility and 499 were enrolled and randomly assigned to receive azithromycin (n=249) or placebo (n=250). Clinical improvement at day 5 was observed in 148 (63%, 95% CI 54 to 71) of 238 participants with full data in the placebo group and 155 (69%, 61 to 77) of 227 participants with full data in the azithromycin group in the intention-to-treat analysis (between-group difference -6%, 95% CI -15 to 2). The 95% CI for the difference did not meet the non-inferiority margin. Solicited adverse events and the severity of solicited adverse events were not significantly different between groups at day 5, except for increased abdominal pain associated with azithromycin (47 [23%, 95% CI 18 to 29] of 204 participants) compared with placebo (35 [16%, 12 to 21] of 221; between-group difference -7% [95% CI -15 to 0]; p=0·066)., Interpretation: Placebo was not non-inferior to azithromycin in terms of clinical improvement at day 5 in adults with lower respiratory tract infection and a low procalcitonin concentration. After accounting for both the rates of clinical improvement and solicited adverse events at day 5, it is unclear whether antibiotics are indicated for patients with lower respiratory tract infection and a low procalcitonin concentration., Funding: National Institute of Allergy and Infectious Diseases, bioMérieux., Competing Interests: Declaration of interests ELT and CWW report consulting for Biomeme. ELT, CWW, and MTM have a patent pending for Methods to Diagnose and Treat Acute Respiratory Infections (US20180245154A1). Following completion of the study, ELT became an employee of Danaher Diagnostics. EBW is a principal investigator for Pfizer-funded studies of COVID-19 vaccine, a co-investigator for a vaccine study funded by Moderna, and a member of an advisory board for Vaxcyte. NGR serves as a safety consultant for the Emmes Corporation and ICON-I, and reports research funds from Pfizer, Merck, Sanofi, Quidel, and Lilly. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Few models exist that incorporate measures from an array of individual characteristics to predict the risk of COVID-19 infection in the general population. The aim was to develop a prognostic model for COVID-19 using readily obtainable clinical variables., Methods: Over 74 weeks surveys were periodically administered to a cohort of 1381 participants previously uninfected with COVID-19 (June 2020 to December 2021). Candidate predictors of incident infection during follow-up included demographics, living situation, financial status, physical activity, health conditions, flu vaccination history, COVID-19 vaccine intention, work/employment status, and use of COVID-19 mitigation behaviors. The final logistic regression model was created using a penalized regression method known as the least absolute shrinkage and selection operator. Model performance was assessed by discrimination and calibration. Internal validation was performed via bootstrapping, and results were adjusted for overoptimism., Results: Of the 1381 participants, 154 (11.2%) had an incident COVID-19 infection during the follow-up period. The final model included six variables: health insurance, race, household size, and the frequency of practicing three mitigation behavior (working at home, avoiding high-risk situations, and using facemasks). The c-statistic of the final model was 0.631 (0.617 after bootstrapped optimism-correction). A calibration plot suggested that with this sample the model shows modest concordance with incident infection at the lowest risk., Conclusion: This prognostic model can help identify which community-dwelling older adults are at the highest risk for incident COVID-19 infection and may inform medical provider counseling of their patients about the risk of incident COVID-19 infection., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: Mitigation behaviors reduce the incidence of COVID-19 infection. Determining characteristics of groups defined by mitigation behaviors compliance may be useful to inform targeted public health policies and interventions. This study aimed to identify groups of individuals according to self-reported compliance with COVID-19 mitigation behaviors, define compliance class characteristics, and explore associations between compliance classes and important study and public health outcomes., Methods and Findings: We studied 1,410 participants in the Cabarrus County COVID-19 Prevalence and Immunity longitudinal cohort study (June 2020 to December 2021) who were asked 10 questions regarding compliance with recommended COVID-19 mitigation behaviors. By Latent Class Analysis, 1,381 participants were categorized into 3 classes (most [49.4%], moderately [45.0%], and least [5.6%] compliant). Compared with the most compliant class, the least and moderately compliant classes were younger (mean = 61.9 v. 59.0 v. 53.8 years), had fewer medical conditions per individual (1.37 v. 1.08 v. 0.77), and differed in Hispanic ethnicity (6.2% v. 2.8% v. 9.1%) and COVID-19 vaccine intention (65.8% v. 59.8% v. 35.1%). Compared to the most compliant class, the least compliant class had fewer women (54.6% v. 76.3%), fewer insured individuals (92.2% v. 97.4%), and more withdrew from study participation early (28.6% v. 16.0%). Relative to the most compliant class, the least compliant class had a higher likelihood of COVID-19 infection (OR = 2.08 [95% CI 1.13, 3.85]), lower rate of COVID-19 vaccination (72.6% v. 95.1%), and longer time to 50% COVID-19 vaccination following eligibility (8-9 vs 16 days)., Conclusions: Classes defined by mitigation behaviors compliance had distinct characteristics, including age, sex, medical history, and ethnicity, and were associated with important study and public health outcomes. Targeted public health policies and interventions according to the compliance group characteristics may be of value in current and future pandemic responses to increase compliance., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Neighbors et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Nonpharmaceutical interventions to prevent the spread of coronavirus disease 2019 also decreased the spread of respiratory syncytial virus (RSV) and influenza. Viral diagnostic testing in patients with respiratory tract infections (RTI) is a necessary tool for patient management; therefore, sensitive and specific tests are required. This scoping literature review aimed to summarize the study characteristics of commercially available sample-to-answer RSV tests., Content: PubMed and Embase were queried for studies reporting on the diagnostic performance of tests for RSV in patients with RTI (published January 2005-January 2021). Information on study design, patient and setting characteristics, and published diagnostic performance of RSV tests were extracted from 77 studies that met predefined inclusion criteria. A literature gap was identified for studies of RSV tests conducted in adult-only populations (5.3% of total subrecords) and in outpatient (7.5%) or household (0.8%) settings. Overall, RSV tests with analytical time >30 min had higher published sensitivity (62.5%-100%) vs RSV tests with analytical time ≤30 min (25.7%-100%); this sensitivity range could be partially attributed to the different modalities (antigen vs molecular) used. Molecular-based rapid RSV tests had higher published sensitivity (66.7%-100%) and specificity (94.3%-100%) than antigen-based RSV tests (sensitivity: 25.7%-100%; specificity:80.3%-100%)., Summary: This scoping review reveals a paucity of literature on studies of RSV tests in specific populations and settings, highlighting the need for further assessments. Considering the implications of these results in the current pandemic landscape, the authors preliminarily suggest adopting molecular-based RSV tests for first-line use in these settings., (© American Association for Clinical Chemistry 2022.)

Objectives: We evaluated the performance of commonly used sepsis screening tools across prospective sepsis cohorts in the USA, Cambodia and Ghana., Design: Prospective cohort studies., Setting and Participants: From 2014 to 2021, participants with two or more SIRS (Systemic Inflammatory Response Syndrome) criteria and suspected infection were enrolled in emergency departments and medical wards at hospitals in Cambodia and Ghana and hospitalised participants with suspected infection were enrolled in the USA. Cox proportional hazards regression was performed, and Harrell's C-statistic calculated to determine 28-day mortality prediction performance of the quick Sequential Organ Failure Assessment (qSOFA) score ≥2, SIRS score ≥3, National Early Warning Score (NEWS) ≥5, Modified Early Warning Score (MEWS) ≥5 or Universal Vital Assessment (UVA) score ≥2. Screening tools were compared with baseline risk (age and sex) with the Wald test., Results: The cohorts included 567 participants (42.9% women) including 187 participants from Kumasi, Ghana, 200 participants from Takeo, Cambodia and 180 participants from Durham, North Carolina in the USA. The pooled mortality was 16.4% at 28 days. The mortality prediction accuracy increased from baseline risk with the MEWS (C-statistic: 0.63, 95% CI 0.58 to 0.68; p=0.002), NEWS (C-statistic: 0.68; 95% CI 0.64 to 0.73; p<0.001), qSOFA (C-statistic: 0.70, 95% CI 0.64 to 0.75; p<0.001), UVA score (C-statistic: 0.73, 95% CI 0.69 to 0.78; p<0.001), but not with SIRS (0.60; 95% CI 0.54 to 0.65; p=0.13). Within individual cohorts, only the UVA score in Ghana performed better than baseline risk (C-statistic: 0.77; 95% CI 0.71 to 0.83; p<0.001)., Conclusions: Among the cohorts, MEWS, NEWS, qSOFA and UVA scores performed better than baseline risk, largely driven by accuracy improvements in Ghana, while SIRS scores did not improve prognostication accuracy. Prognostication scores should be validated within the target population prior to clinical use., Competing Interests: Competing interests: ET has held equity and consulted for Predigen and Biomeme, and he is an employee of Danaher Diagnostics. All other authors declared no competing interests., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework for developing AS diagnostic biomarkers. Leveraging a large prospective cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whole-blood RNA sequencing (RNA-seq) data, we identify a major functional AS program switch upon viral infection. Using an independent cohort, we demonstrate the improved accuracy of AS biomarkers for SARS-CoV-2 diagnosis compared with six reported transcriptome signatures. We then optimize a subset of AS-based biomarkers to develop microfluidic PCR diagnostic assays. This assay achieves nearly perfect test accuracy (61/62 = 98.4%) using a naive principal component classifier, significantly more accurate than a gene expression PCR assay in the same cohort. Therefore, our RNA splicing computational framework enables a promising avenue for host-response diagnosis of infection., Competing Interests: A provisional patent application on this work has been submitted, and the Icahn School of Medicine at Mount Sinai and Princeton University are in discussions about licensing the technology. Z.Z., O.G.T., and S.C.S. are co-inventors of this technology and may benefit from any licensing.

Objectives: NICU graduates require ongoing surveillance in follow-up clinics because of the risk of lower cognitive, motor, and academic performance. We hypothesized that multiple programmatic changes, including availability of telemedicine consultation before hospital discharge, would improve NICU follow-up clinic attendance rates., Methods: In this retrospective study, we included infants who survived and were premature (≤29 6/7 weeks/<1500 g) or had brain injury (grade III/IV intraventricular hemorrhage, stroke or seizure, hypoxic ischemic encephalopathy). We compared rates of follow-up for the early cohort (January 2018-June 2019; no telemedicine) with the late cohort (May 2020-May 2021; telemedicine available); and performed a mediation analysis to assess other programmatic changes for the late cohort including improved documentation to parents and primary care provider regarding NICU follow-up., Results: The rate of successful 12-month follow-up improved from 26% (early cohort) to 61% (late cohort) (P < .001). After controlling for maternal insurance, the odds of attending a 12-month follow-up visit were 3.7 times higher for infants in the late cohort, for whom telemedicine was available (confidence interval, 1.8-7.9). Approximately 37% of this effect was mediated by including information for NICU follow-up in the discharge documentation for parents (P < .001)., Conclusions: Telemedicine consultation before NICU discharge, in addition to improving communication regarding the timing and importance of NICU follow-up, was effective at improving the rate of attendance to NICU follow-up clinics., (Copyright © 2023 by the American Academy of Pediatrics.)

Using data from a longitudinal viral challenge study, we find that the post-exposure viral shedding and symptom severity are associated with a novel measure of pre-exposure cognitive performance variability (CPV), defined before viral exposure occurs. Each individual's CPV score is computed from data collected from a repeated NeuroCognitive Performance Test (NCPT) over a 3 day pre-exposure period. Of the 18 NCPT measures reported by the tests, 6 contribute materially to the CPV score, prospectively differentiating the high from the low shedders. Among these 6 are the 4 clinical measures digSym-time, digSym-correct, trail-time, and reaction-time, commonly used for assessing cognitive executive functioning. CPV is found to be correlated with stress and also with several genes previously reported to be associated with cognitive development and dysfunction. A perturbation study over the number and timing of NCPT sessions indicates that as few as 5 sessions is sufficient to maintain high association between the CPV score and viral shedding, as long as the timing of these sessions is balanced over the three pre-exposure days. Our results suggest that variations in cognitive function are closely related to immunity and susceptibility to severe infection. Further studying these relationships may help us better understand the links between neurocognitive and neuroimmune systems which is timely in this COVID-19 pandemic era., (© 2022. The Author(s).)

The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information., Competing Interests: Declaration of interests Icahn School of Medicine at Mount Sinai has submitted a provisional patent related to this work. A.C., D.G.C., S.C.S., S.H.K., and E.Z. are inventors of the technology filed through ISMMS related to this manuscript. S.H.K. receives consulting fees from Peraton. C.W.W. is a founder of Predigen, Inc, and consultant and Chief Medical Officer of Biomeme. C.W.W. also consults for Arena Pharmaceuticals, Biofire, Karius, and FHI Clinical. T.W.B. is a consultant for and equity owner in Biomeme. E.L.T. is an employee and shareholder of Danaher Corp. M.T.M., E.L.T., R.H., T.W.B., and C.W.W. are co-inventors of technology filed under patent application “Methods to Detect and Treat SARS-COV2 (COVID19) Infection.” O.G.T. is on the advisory board of Cell Systems., (Copyright © 2022 Elsevier Inc. All rights reserved.)