Population Health Metrics During the Early Stages of the COVID-19 Pandemic: Correlative Pilot Study

Background: COVID-19 has caused nearly 1 million deaths in the United States, not to mention job losses, business and school closures, stay-at-home orders, and mask mandates. Many people have suffered increased anxiety and depression since the pandemic began. Not only have mental health symptoms become more prevalent, but alcohol consumption has also increased during this time. Helplines offer important insight into both physical and mental wellness of a population by offering immediate, anonymous, cheap, and accessible resources for health and substance use disorders (SUD) that was unobstructed by many of the mandates of the pandemic. Further, the pandemic also launched the use of wastewater surveillance, which has the potential for tracking not only population infections but also consumption of substances such as alcohol. Objective: This study assessed the feasibility of using multiple public surveillance metrics, such as helpline calls, COVID-19 cases, and alcohol metabolites in wastewater, to better understand the need for interventions or public health programs in the time of a public health emergency. Methods: Ethanol metabolites were analyzed from wastewater collected twice weekly from September 29 to December 4, 2020, in a Midwestern state. Calls made to the helpline regarding housing, health care, and mental health/SUD were correlated with ethanol metabolites analyzed from wastewater samples, as well as the number of COVID-19 cases during the sampling period. Results: Correlations were observed between COVID-19 cases and helpline calls regarding housing and health care needs. No correlation was observed between the number of COVID-19 cases and mental health/SUD calls. COVID-19 cases on Tuesdays were correlated with the alcohol metabolite ethyl glucuronide (EtG). Finally, EtG levels were negatively associated with mental health/SUD helpline calls. Conclusions: Although helpline calls provided critical services for health care and housing-related concerns early in the pandemic, evidence suggests helpline calls for mental health/SUD-related concerns were unrelated to COVID-19 metrics. Instead, COVID metrics were associated with alcohol metabolites in wastewater. Although this research was formative, with continued and expanded monitoring of population metrics, such as helpline usage, COVID-19 metrics, and wastewater, strategies can be implemented to create precision programs to address the needs of the population

Analysis of Wastewater Samples to Explore Community Substance Use in the United States: Pilot Correlative and Machine Learning Study

Background: Substance use disorder and associated deaths have increased in the United States, but methods for detecting and monitoring substance use using rapid and unbiased techniques are lacking. Wastewater-based surveillance is a cost-effective method for monitoring community drug use. However, the examination of the results often focuses on descriptive analysis. Objective: The objective of this study was to explore community substance use in the United States by analyzing wastewater samples. Geographic differences and commonalities of substance use were explored. Methods: Wastewater was sampled across the United States (n=12). Selected drugs with misuse potential, prescriptions, and over-the-counter drugs and their metabolites were tested across geographic locations for 7 days. Methods used included wastewater assessment of substances and metabolites paired with machine learning, specifically discriminant analysis and cluster analysis, to explore similarities and differences in wastewater measures. Results: Geographic variations in the wastewater drug or metabolite levels were found. Results revealed a higher use of methamphetamine (z=–2.27, P=.02) and opioids-to-methadone ratios (oxycodone-to-methadone: z=–1.95, P=.05; hydrocodone-to-methadone: z=–1.95, P=.05) in states west of the Mississippi River compared to the east. Discriminant analysis suggested temazepam and methadone were significant predictors of geographical locations. Precision, sensitivity, specificity, and F1-scores were 0.88, 1, 0.80, and 0.93, respectively. Finally, cluster analysis revealed similarities in substance use among communities. Conclusions: These findings suggest that wastewater-based surveillance has the potential to become an effective form of surveillance for substance use. Further, advanced analytical techniques may help uncover geographical patterns and detect communities with similar needs for resources to address substance use disorders. Using automated analytics, these advanced surveillance techniques may help communities develop timely, tailored treatment and prevention efforts

The Palladium-Catalyzed Aerobic Kinetic Resolution of Secondary Alcohols: Reaction Development, Scope, and Applications

The first palladium-catalyzed enantioselective oxidation of secondary alcohols has been developed, utilizing the readily available diamine (-)-sparteine as a chiral ligand and molecular oxygen as the stoichiometric oxidant. Mechanistic insights regarding the role of the base and hydrogen-bond donors have resulted in several improvements to the original system. Namely, addition of cesium carbonate and tert-butyl alcohol greatly enhances reaction rates, promoting rapid resolutions. The use of chloroform as solvent allows the use of ambient air as the terminal oxidant at 23 °C, resulting in enhanced catalyst selectivity. These improved reaction conditions have permitted the successful kinetic resolution of benzylic, allylic, and cyclopropyl secondary alcohols to high enantiomeric excess with good-to-excellent selectivity factors. This catalyst system has also been applied to the desymmetrization of meso-diols, providing high yields of enantioenriched hydroxyketones

Scale-invariance in expanding and contracting universes from two-field models

We study cosmological perturbations produced by the most general two-derivative actions involving two scalar fields, coupled to Einstein gravity, with an arbitrary field space metric, that admit scaling solutions. For contracting universes, we show that scale-invariant adiabatic perturbations can be produced continuously as modes leave the horizon for any equation of state parameter $w \ge 0$. The corresponding background solutions are unstable, which we argue is a universal feature of contracting models that yield scale-invariant spectra. For expanding universes, we find that nearly scale-invariant adiabatic perturbation spectra can only be produced for $w \approx -1$, and that the corresponding scaling solutions are attractors. The presence of a nontrivial metric on field space is a crucial ingredient in our results.Comment: 23 pages, oversight in perturbations calculation corrected, conclusions for expanding models modifie

Systematic review and metaanalysis comparing the bias and accuracy of the modification of diet in renal disease and chronic kidney disease epidemiology collaboration equations in community-based population

BACKGROUND The majority of patients with chronic kidney disease are diagnosed and monitored in primary care. Glomerular filtration rate (GFR) is a key marker of renal function, but direct measurement is invasive; in routine practice, equations are used for estimated GFR (eGFR) from serum creatinine. We systematically assessed bias and accuracy of commonly used eGFR equations in populations relevant to primary care. CONTENT MEDLINE, EMBASE, and the Cochrane Library were searched for studies comparing measured GFR (mGFR) with eGFR in adult populations comparable to primary care and reporting both the Modification of Diet in Renal Disease (MDRD) and the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations based on standardized creatinine measurements. We pooled data on mean bias (difference between eGFR and mGFR) and on mean accuracy (proportion of eGFR within 30% of mGFR) using a random-effects inverse-variance weighted metaanalysis. We included 48 studies of 26875 patients that reported data on bias and/or accuracy. Metaanalysis of within-study comparisons in which both formulae were tested on the same patient cohorts using isotope dilution-mass spectrometry-traceable creatinine showed a lower mean bias in eGFR using CKD-EPI of 2.2 mL/min/1.73 m2 (95% CI, 1.1–3.2; 30 studies; I2 = 74.4%) and a higher mean accuracy of CKD-EPI of 2.7% (1.6–3.8; 47 studies; I2 = 55.5%). Metaregression showed that in both equations bias and accuracy favored the CKD-EPI equation at higher mGFR values. SUMMARY Both equations underestimated mGFR, but CKD-EPI gave more accurate estimates of GFR