Background Aseptic meningitis represents a common diagnostic and management dilemma to clinicians. Objectives To compare the clinical epidemiology, diagnostic evaluations, management, and outcomes between adults and children with aseptic meningitis. Study Design We conducted a retrospective study from January 2005 through September 2010 at 9 Memorial Hermann Hospitals in Houston, TX. Patients age ≥ 2 months who presented with community-acquired aseptic meningitis with a CSF white blood cell count >5 cells/mm3 and a negative Gram stain and cultures were enrolled. Patients with a positive cryptococcal antigen, positive blood cultures, intracranial masses, brain abscesses, or encephalitis were excluded. Results A total of 509 patients were included; 404 were adults and 105 were children. Adults were most likely to be female, Caucasian, immunosuppressed, have meningeal symptoms (headache, nausea, stiff neck, photophobia) and have a higher CSF protein (P<0.05). In contrast, children were more likely to have respiratory symptoms, fever, and leukocytosis (P<0.05). In 410 (81%) patients, the etiologies remained unknown. Adults were more likely to be tested for and to have Herpes simplex virus and West Nile virus while children were more likely to be tested for and to have Enterovirus (P<0.001). The majority of patients were admitted (96.5%) with children receiving antibiotic therapy more frequently (P<0.001) and adults receiving more antiviral therapy (P=0.001). A total of 384 patients (75%) underwent head CT scans and 125 (25%) MRI scans; all were normal except for meningeal enhancement. All patients had a good clinical outcome at discharge. Discussion Aseptic meningitis in adults and children represent a management challenge as etiologies remained unknown for the majority of patients due to underutilization of currently available diagnostic techniques.

Daptomycin MICs of 3-4 µg/mL in the initial E. faecium blood isolate predicted microbiological failure of daptomycin therapy, suggesting that modification in the daptomycin breakpoint for enterococci should be considered.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r s = 0.69 without normalization, r s = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.

Standardized protocols for wastewater-based surveillance (WBS) for the RNA of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, are being developed and refined worldwide for early detection of disease outbreaks. We report here on lessons learned from establishing a WBS program for SARS-CoV-2 integrated with a human surveillance program for COVID-19. We have established WBS at three campuses of a university, including student residential dormitories and a hospital that treats COVID-19 patients. Lessons learned from this WBS program address the variability of water quality, new detection technologies, the range of detectable viral loads in wastewater, and the predictive value of integrating environmental and human surveillance data. Data from our WBS program indicated that water quality was statistically different between sewer sampling sites, with more variability observed in wastewater coming from individual buildings compared to clusters of buildings. A new detection technology was developed based upon the use of a novel polymerase called V2G. Detectable levels of SARS-CoV-2 in wastewater varied from 10 2 to 10 6 genomic copies (gc) per liter of raw wastewater (L). Integration of environmental and human surveillance data indicate that WBS detection of 100 gc/L of SARS-CoV-2 RNA in wastewater was associated with a positivity rate of 4% as detected by human surveillance in the wastewater catchment area, though confidence intervals were wide (β ~ 8.99 ∗ ln(100); 95% CI = 0.90–17.08; p < 0.05). Our data also suggest that early detection of COVID-19 surges based on correlations between viral load in wastewater and human disease incidence could benefit by increasing the wastewater sample collection frequency from weekly to daily. Coupling simpler and faster detection technology with more frequent sampling has the potential to improve the predictive potential of using WBS of SARS-CoV-2 for early detection of the onset of COVID-19.

Rationale: Black race and Hispanic ethnicity are associated with increased risks for coronavirus disease (COVID-19) infection and severity. It is purported that socioeconomic factors may drive this association, but data supporting this assertion are sparse. Objectives: To evaluate whether socioeconomic factors mediate the association of race/ethnicity with COVID-19 incidence and outcomes. Methods: We conducted a retrospective cohort study of adults tested for (cohort 1) or hospitalized with (cohort 2) COVID-19 between March 1, 2020, and July 23, 2020, at the University of Miami Hospital and Clinics. Our primary exposure was race/ethnicity. We considered socioeconomic factors as potential mediators of our exposure’s association with outcomes. We used standard statistics to describe our cohorts and multivariable regression modeling to identify associations of race/ethnicity with our primary outcomes, one for each cohort, of test positivity (cohort 1) and hospital mortality (cohort 2). We performed a mediation analysis to see whether household income, population density, and household size mediated the association of race/ethnicity with outcomes. Results: Our cohorts included 15,473 patients tested (29.0% non-Hispanic White, 48.1% Hispanic White, 15.0% non-Hispanic Black, 1.7% Hispanic Black, and 1.6% other) and 295 patients hospitalized (9.2% non-Hispanic White, 56.9% Hispanic White, 21.4% non-Hispanic Black, 2.4% Hispanic Black, and 10.2% other). Among those tested, 1,256 patients (8.1%) tested positive, and, of the hospitalized patients, 47 (15.9%) died. After adjustment for demographics, race/ethnicity was associated with test positivity—odds-ratio (95% confidence interval [CI]) versus non-Hispanic White for Non-Hispanic Black: 3.21 (2.60–3.96), Hispanic White: 2.72 (2.28–3.26), and Hispanic Black: 3.55 (2.33–5.28). Population density mediated this association (percentage mediated, 17%; 95% CI, 11–31%), as did median income (27%; 95% CI, 18–52%) and household size (20%; 95% CI, 12–45%). There was no association between race/ethnicity and mortality, although this analysis was underpowered. Conclusions: Black race and Hispanic ethnicity are associated with an increased odds of COVID-19 positivity. This association is substantially mediated by socioeconomic factors.