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Healthcare institutions with mandatory influenza vaccination policies have over 90% vaccination rates among healthcare workers (HCWs) resulting in a population that has received the influenza vaccine in many, consecutive years. This study explored the impact of sex and other host factors in pre- and post-vaccination neutralizing antibody (nAb) titers and seroconversion against the H1N1 and H3N2 influenza A viruses (IAVs) among HCWs enrolled into a cross-sectional serosurvey during the annual Johns Hopkins Hospital employee vaccination campaign in the 2017–18 and 2018–19 seasons. The study enrolled 111 participants (male = 38, female = 73) in 2017–18 and 163 (male = 44, female = 119) in 2018–19. Serum samples were collected immediately prior to vaccination and approximately 28 days later and nAb titers to vaccine strains determined. An intersectional approach was used to disaggregate the combined effects of sex with age and body mass index (BMI) in the nAb response. Differences between the pre- or post-vaccination geometric mean nAb titers between male and female HCWs were not observed. Male HCWs were 2.86 times more likely to seroconvert compared to female HCWs in 2017–2018, but the same trend was not observed in the following year. When data were disaggregated by age and sex, older female HCWs had higher H1N1 pre- and post-vaccination nAb titers compared to male HCWs in the same age group for both vaccination campaign seasons. In both years, the decline in H3N2 pre-vaccination titers with increasing BMI was greater in female than male HCW. The sex-specific effects of age and BMI on nAb responses to seasonal influenza vaccines require greater consideration.

The burden of nosocomial respiratory infections in rural southern Africa is poorly understood. We established a surveillance program at a rural Zambian hospital to detect influenza-like illness (ILI) and respiratory infections among hospitalized patients and a cohort of healthcare workers (HCWs). Nasopharyngeal specimens from symptomatic patients and HCWs underwent broadly multiplexed molecular testing to detect viruses and atypical bacteria. During 1 year of surveillance, 15 patients (1.7% of admissions) developed ILI more than 48 hours after admission. Among 44 HCWs, 19 (43%) experienced at least one ILI episode, with a total of 31 ILI episodes detected. Respiratory viruses were detected in 45% of patient and 55% of HCW specimens. The cumulative incidence of influenza infection among HCWs over 1 year was 9%. Overall, respiratory viruses were commonly found among patients and HCWs in a rural Zambian hospital with limited infection control infrastructure.

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.

Severe respiratory infections can result in acute respiratory distress syndrome (ARDS)1. There are no effective pharmacological therapies that have been shown to improve outcomes for patients with ARDS. Although the host inflammatory response limits spread of and eventually clears the pathogen, immunopathology is a major contributor to tissue damage and ARDS1,2. Here we demonstrate that respiratory viral infection induces distinct fibroblast activation states, which we term extracellular matrix (ECM)-synthesizing, damage-responsive and interferon-responsive states. We provide evidence that excess activity of damage-responsive lung fibroblasts drives lethal immunopathology during severe influenza virus infection. By producing ECM-remodelling enzymes-in particular the ECM protease ADAMTS4-and inflammatory cytokines, damage-responsive fibroblasts modify the lung microenvironment to promote robust immune cell infiltration at the expense of lung function. In three cohorts of human participants, the levels of ADAMTS4 in the lower respiratory tract were associated with the severity of infection with seasonal or avian influenza virus. A therapeutic agent that targets the ECM protease activity of damage-responsive lung fibroblasts could provide a promising approach to preserving lung function and improving clinical outcomes following severe respiratory infections.

BackgroundSeasonal epidemics of influenza are often characterized through national or international surveillance efforts to determine vaccine efficacy and vaccine strain selection, but they do not provide detailed information about local variations in factors that can influence influenza cases and disease severity.MethodsSurveillance for influenza like illness was performed in Emergency Medicine Departments in Taipei, Taiwan and Baltimore, Maryland during the winter of 2015-16. Detailed demographic and clinical data were obtained. Nasal swabs or washes were collected for influenza virus diagnosis, sequencing and isolation. Serum was collected to determine neutralizing antibody levels.ResultsH1N1 viruses dominated both sites, but more influenza cases occurred in Taipei compared to Baltimore. H1 HA clade diversity was greater in Taipei. Vaccination rates were lower in Taipei than Baltimore, but vaccination was associated with an increase in serum neutralizing antibodies to recent H1N1 strains in Taipei, but not Baltimore. There was a higher level of preexisting immunity to circulating H1N1 strains in Baltimore.ConclusionsRegional differences in preexisting immunity and H1N1 strain circulation may have contributed to the vastly different 2015-16 influenza seasons in Taipei and Baltimore and suggest immune responses to vaccination can be affected by the degree of preexisting immunity in the population.

Background While southern Africa experiences among the highest mortality rates from respiratory infections, the burden of influenza and respiratory syncytial virus (RSV) in rural areas is poorly understood. Methods We implemented facility-based surveillance in Macha, Zambia. Outpatients and inpatients presenting with influenza-like illness (ILI) underwent testing for influenza A, influenza B, and RSV and were prospectively followed for 3 to 5 weeks to assess clinical course. Log-binomial models assessed correlates of infection and clinical severity. Results Between December 2018 and December 2019, 17% of all outpatients presented with ILI and 16% of inpatients were admitted with an acute respiratory complaint. Influenza viruses and RSV were detected in 17% and 11% of outpatient participants with ILI, and 23% and 16% of inpatient participants with ILI, respectively. Influenza (July–September) and RSV (January-April) prevalence peaks were temporally distinct. RSV (relative risk [RR]: 1.78; 95% confidence interval [CI] 1.51–2.11), but not influenza, infection was associated with severe disease among patients with ILI. Underweight patients with ILI were more likely to be infected with influenza A (prevalence ratio [PR]: 1.72; 95% CI 1.04–2.87) and to have severe influenza A infections (RR: 2.49; 95% CI 1.57–3.93). Conclusions Populations in rural Zambia bear a sizeable burden of viral respiratory infections and severe disease. The epidemiology of infections in this rural area differs from that reported from urban areas in Zambia.

BACKGROUND Influenza B accounts for approximately one fourth of the seasonal influenza burden. However, research on the importance of influenza B has received less attention compared to influenza A. We sought to describe the association of both coinfections and comorbidities with disease severity among adults presenting to emergency departments (ED) with influenza B. METHODS Nasopharyngeal samples from patients found to be influenza B positive in four US and three Taiwanese ED over four consecutive influenza seasons (2014-2018) were tested for coinfections with the ePlex RP RUO panel. Multivariable logistic regressions were fitted to model adjusted odds ratios (aOR) for two severity outcomes separately: hospitalization and pneumonia diagnosis. Adjusting for demographic factors, underlying health conditions, and the National Early Warning Score (NEWS), we estimated the association of upper respiratory coinfections and comorbidity with disease severity (including hospitalization or pneumonia). RESULTS Amongst all influenza B positive individuals (n = 446), presence of another upper respiratory pathogen was associated with an increased likelihood of hospitalization (aOR = 2.99 [95% confidence interval (95% CI): 1.14-7.85, p = 0.026]) and pneumonia (aOR = 2.27 [95% CI: 1.25-4.09, p = 0.007]). Chronic lung diseases (CLD) were the strongest predictor for hospitalization (aOR = 3.43 [95% CI: 2.98-3.95, p

During the 2014-2016 Ebola virus epidemic, more than 500 health care workers (HCWs) died in spite of the use of personal protective equipment (PPE). The Johns Hopkins University Center for Bioengineering Innovation and Design (CBID) and Jhpiego, an international nongovernmental organization affiliate of Johns Hopkins, collaborated to create new PPE to improve the ease of the doffing process.HCWs in Liberia and a US biocontainment unit compared standard Médecins Sans Frontière PPE (PPE A) with the new PPE (PPE B). Participants wore each PPE ensemble while performing simulated patient care activities. Range of motion, time to doff, comfort, and perceived risk were measured.Overall, 100% of participants preferred PPE B over PPE A (P.0001); 98.1% of respondents would recommend PPE B for their home clinical unit (P.0001). There was a trend towards greater comfort in PPE B. HCWs at both sites felt more at risk in PPE A than PPE B (71.9% vs 25% in Liberia, P.0001; 100% vs 40% in the US biocontainment unit, P.0001).HCWs preferred a new PPE ensemble to Médecins Sans Frontière PPE for high-consequence pathogens. Further studies on the safety of this new PPE need to be conducted.

BackgroundSeveral inflammatory cytokines are upregulated in severe COVID-19. We compared cytokines in COVID-19 versus influenza in order 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.MethodsThirty-seven cytokines and chemokines were measured in plasma from 145 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 utilized to determine the cytokines most important in distinguishing severe COVID-19 and influenza. Mediation analysis was utilized to identify cytokines that mediate the effect of BMI on disease severity.ResultsIL-18, IL-1β, IL-6, and TNF-α were significantly increased in COVID-19 versus influenza patients while GM-CSF, IFN-γ, IFN-λ1, IL-10, IL-15, and MCP-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 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.ConclusionsThese findings point to activation of fundamentally different innate immune pathways in SARS-CoV-2 and influenza infection, and emphasize drivers of severe COVID-19 to focus both mechanistic and therapeutic investigations.SummarySevere COVID-19 is marked by dysregulated inflammation and is associated with elevated BMI. By comparing cytokines and chemokines in patients with either COVID-19 or influenza, we identified distinct inflammatory pathways and a cytokine mediator of the effect of BMI.

Rapid point-of-care tests (POCTs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibodies vary in performance. A critical need exists to perform head-to-head comparisons of these assays. The performances of 15 different lateral flow POCTs for the detection of SARS-CoV-2-specific antibodies were compared on a well-characterized set of 100 samples. Of these, 40 samples from known SARS-CoV-2-infected, convalescent individuals (collected an average of 45 days after symptom onset) were used to assess sensitivity. Sixty samples from the prepandemic era (negative control) that were known to represent infections with other respiratory viruses (rhinoviruses A, B, and C and/or coronavirus 229E, HKU1, and NL63 OC43) were used to assess specificity. The timing of seroconversion was assessed using five lateral flow assays (LFAs) and a panel of 272 longitudinal samples from 47 patients for whom the time since symptom onset was known. Among the assays that were evaluated, the sensitivity and specificity for any reactive band ranged from 55% to 97% and from 78% to 100%, respectively. Assessing the performance of the IgM and the IgG bands alone, sensitivity and specificity ranged from 0% to 88% and 80% to 100% for IgM and from 25% to 95% and 90% to 100% for IgG, respectively. Longitudinal testing revealed that the median times after symptom onset to a positive result were 7 days (interquartile range [IQR], 5.4 to 9.8) for IgM and 8.2 days (IQR, 6.3 to 11.3) for IgG. The testing performances differed widely among LFAs, with greatest amount of variation related to the sensitivity of the assays. The IgM band was the band most likely to misclassify prepandemic samples. The appearances of IgM and IgG bands occurred almost simultaneously.

The emergence of SARS-CoV-2 and subsequent COVID-19 pandemic highlights the morbidity and potential disease severity caused by respiratory viruses. To elucidate pathogen prevalence, etiology of coinfections and URIs from symptomatic adult Emergency department patients in a pre-SARS-CoV-2 environment, we evaluated specimens from four geographically diverse Emergency departments in the United States from 2013-2014 utilizing ePlex RP RUO cartridges (Genmark Diagnostics). The overall positivity was 30.1% (241/799), with 6.6% (16/241) coinfections. Noninfluenza pathogens from most to least common were rhinovirus/enterovirus, coronavirus, human metapneumovirus and RSV, respectively. Broad differences in disease prevalence and pathogen distributions were observed across geographic regions; the site with the highest detection rate (for both mono and coinfections) demonstrated the greatest pathogen diversity. A variety of respiratory pathogens and geographic variations in disease prevalence and copathogen type were observed. Further research is required to evaluate the clinical relevance of these findings, especially considering the SARS-CoV-2 pandemic and related questions regarding SARS-CoV-2 disease severity and the presence of co-infections.

Opportunity exists to decrease healthcare-related exposure to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), preserve infection control resources, and increase care capacity by reducing the time to diagnosis of coronavirus disease 2019 (COVID-19). A retrospective cohort analysis was undertaken to measure the effect of targeted rapid molecular testing for SARS-CoV-2 on these outcomes. In comparison with standard platform testing, rapid testing was associated with a 65.6% reduction (12.6 h) in the median time to removal from the isolation cohort for patients with negative diagnostic results. This translated to an increase in COVID-19 treatment capacity of 3028 bed-hours and 7500 fewer patient interactions that required the use of personal protective equipment per week.

Rapid point-of-care tests (POCTs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibodies vary in performance. A critical need exists to perform head-to-head comparisons of these assays., Rapid point-of-care tests (POCTs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific antibodies vary in performance. A critical need exists to perform head-to-head comparisons of these assays. The performances of 15 different lateral flow POCTs for the detection of SARS-CoV-2-specific antibodies were compared on a well-characterized set of 100 samples. Of these, 40 samples from known SARS-CoV-2-infected, convalescent individuals (collected an average of 45 days after symptom onset) were used to assess sensitivity. Sixty samples from the prepandemic era (negative control) that were known to represent infections with other respiratory viruses (rhinoviruses A, B, and C and/or coronavirus 229E, HKU1, and NL63 OC43) were used to assess specificity. The timing of seroconversion was assessed using five lateral flow assays (LFAs) and a panel of 272 longitudinal samples from 47 patients for whom the time since symptom onset was known. Among the assays that were evaluated, the sensitivity and specificity for any reactive band ranged from 55% to 97% and from 78% to 100%, respectively. Assessing the performance of the IgM and the IgG bands alone, sensitivity and specificity ranged from 0% to 88% and 80% to 100% for IgM and from 25% to 95% and 90% to 100% for IgG, respectively. Longitudinal testing revealed that the median times after symptom onset to a positive result were 7 days (interquartile range [IQR], 5.4 to 9.8) for IgM and 8.2 days (IQR, 6.3 to 11.3) for IgG. The testing performances differed widely among LFAs, with greatest amount of variation related to the sensitivity of the assays. The IgM band was the band most likely to misclassify prepandemic samples. The appearances of IgM and IgG bands occurred almost simultaneously.

Objectives: The role of respiratory co-infections in modulating disease severity remains understudied in southern Africa, particularly in rural areas. This study was performed to characterize the spectrum of respiratory pathogens in rural southern Zambia and the prognostic impact of co-infections. Methods: Respiratory specimens collected from inpatient and outpatient participants in a viral surveillance program in 2018–2019 were tested for selected viruses and a typical bacteria using the Xpert Xpress Flu/RSV assay and FilmArray Respiratory Panel EZ. Participants were followed for 3–5 weeks to assess their clinical course. Multivariable regression was used to examine the role of co-infections in influencing disease severity. Results: A respiratory pathogen was detected in 63.2% of samples from 671 participants who presented with influenza-like illness. Common pathogens identified included influenza virus (18.2% of samples), respiratory syncytial virus (RSV) (11.8%), rhinovirus (26.4%), and coronavirus (6.0%). Overall, 6.4% of participants were co-infected with multiple respiratory pathogens. Compared to mono-infections, co-infections were found not to be associated with severe clinical illness either overall (relative risk (RR) 0.72, 95% confidence interval (CI) 0.39–1.32) or specifically with influenza virus (RR 0.80, 95% CI 0.14–4.46) or RSV infections (RR 0.44, 95% CI 0.17–1.11). Conclusions: Respiratory infections in rural southern Zambia were associated with a wide range of viruses. Respiratory co-infections in this population were not associated with clinical severity.

The continual emergence of novel influenza A strains from non-human hosts requires constant vigilance and the need for ongoing research to identify strains that may pose a human public health risk. Since 1999, canine H3 influenza A viruses (CIVs) have caused many thousands or millions of respiratory infections in dogs in the United States. While no human infections with CIVs have been reported to date, these viruses could pose a zoonotic risk. In these studies, the National Institutes of Allergy and Infectious Diseases (NIAID) Centers of Excellence for Influenza Research and Surveillance (CEIRS) network collaboratively demonstrated that CIVs replicated in some primary human cells and transmitted effectively in mammalian models. While people born after 1970 had little or no pre-existing humoral immunity against CIVs, the viruses were sensitive to existing antivirals and we identified a panel of H3 cross-reactive human monoclonal antibodies (hmAbs) that could have prophylactic and/or therapeutic value. Our data predict these CIVs posed a low risk to humans. Importantly, we showed that the CEIRS network could work together to provide basic research information important for characterizing emerging influenza viruses, although there were valuable lessons learned., Author summary The 2009 influenza pandemic was a stark reminder that ongoing vigilance is critical to protect the public from an influenza pandemic. The continual evolution of influenza viruses and emergence from animal reservoirs, leads to the need to quickly identify strains that pose a public health risk. In these studies, members of the National Institutes of Allergy and Infectious Diseases (NIAID) Centers for Excellence in Influenza Research and Surveillance (CEIRS) network worked together to demonstrate that the emerging canine H3 influenza viruses posed a low risk to public health and identified several therapeutic options in the event of an emergence. In addition to providing important new basic research, many lessons were learned that may be important in dealing with any emerging disease outbreak.

Biocontainment units (BCUs) are facilities used to care for patients with highly infectious diseases. However, there is limited guidance on BCU protocols and design. This study presents the first investigation of how HVAC (heating, ventilation, air‐conditioning) operating conditions influence the dissemination of fluorescent tracer particles released in a BCU. Test conditions included normal HVAC operation and exhaust failure resulting in loss of negative pressure. A suspension of optical brightener powder and water was nebulized to produce fluorescent particles simulating droplet nuclei (0.5‐5 μm). Airborne particle number concentrations were monitored by Instantaneous Biological Analyzers and Collectors (FLIR Systems). During normal HVAC operation, fluorescent tracer particles were contained in the isolation room (average concentration = 1 × 104 ± 3 × 103/Lair). Under exhaust failure, the automated HVAC system maximizes airflow into areas adjacent to isolation rooms to attempt to maintain negative pressure differential. However, 6% of the fluorescent particles were transported through cracks around doors/door handles out of the isolation room via airflow alone and not by movement of personnel or doors. Overall, this study provides a systematic method for evaluating capabilities to contain aerosolized particles during various HVAC scenarios. Recommendations are provided to improve situation‐specific BCU safety.

The Johns Hopkins Hospital created a biocontainment unit (BCU) to care for patients with highly infectious diseases while assuring healthcare worker safety. Research to date for BCU protocols and practices are based on case reports and lessons learned from patient care and exercises. This study seeks to be the first to explore the influences of healthcare worker movement and personal protective equipment (PPE) doffing on the transport of simulant pathogen particles in a BCU. A cough device released 1 μm fluorescent polystyrene beads (PSLs) in the patient room. PSL transport was then examined under 2 scenarios: (1) PSL release only, no healthcare workers; and (2) PSL release during 5-minute simulated activity by healthcare workers. Airborne PSL concentrations were quantified every second for 30 minutes per scenario by 7 optical particle sensors located throughout the BCU. PSLs were not detected in the donning room at any time nor in the doffing room during the first test scenario where no healthcare worker was present. The main difference detected between the tested scenarios was the presence of PSLs in the doffing room when healthcare workers were removing PPE, potentially due to re-aerosolization of PSLs off the exterior PPE surface or opening of the patient room door. Future work will further explore the potential for re-aerosolization of particles off of PPE during doffing. The present study provides the groundwork for a systematic method for evaluating the BCU and doffing procedures for their respective safety, and it also pilots a systematic method for evaluating potential pathogen exposure pathways for BCU healthcare workers.

Background Malaria remains an important cause of morbidity and mortality in India. Though many comprehensive studies have been carried out in Africa and Southeast Asia to characterize and examine determinants of Plasmodium falciparum and Plasmodium vivax malaria pathogenesis, fewer have been conducted in India. Methods A prospective study of malaria-positive individuals was conducted at Goa Medical College and Hospital (GMC) from 2012 to 2015 to identify demographic, diagnostic and clinical indicators associated with P. falciparum and P. vivax infection on univariate analysis. Results Between 2012 and 2015, 74,571 febrile individuals, 6287 (8.4%) of whom were malaria positive, presented to GMC. The total number of malaria cases at GMC increased more than two-fold over four years, with both P. vivax and P. falciparum cases present year-round. Some 1116 malaria-positive individuals (mean age = 27, 91% male), 88.2% of whom were born outside of Goa and 51% of whom were construction workers, were enroled in the study. Of 1088 confirmed malaria-positive patients, 77.0% had P. vivax, 21.0% had P. falciparum and 2.0% had mixed malaria. Patients over 40 years of age and with P. falciparum infection were significantly (p