Depression and Anxiety on Twitter During the COVID-19 Stay-At-Home Period in 7 Major U.S. Cities.

Introduction: Although surveys are a well-established instrument to capture the population prevalence of mental health at a moment in time, public Twitter is a continuously available data source that can provide a broader window into population mental health. We characterized the relationship between COVID-19 case counts, stay-at-home orders because of COVID-19, and anxiety and depression in 7 major U.S. cities utilizing Twitter data. Methods: We collected 18 million Tweets from January to September 2019 (baseline) and 2020 from 7 U.S. cities with large populations and varied COVID-19 response protocols: Atlanta, Chicago, Houston, Los Angeles, Miami, New York, and Phoenix. We applied machine learning‒based language prediction models for depression and anxiety validated in previous work with Twitter data. As an alternative public big data source, we explored Google Trends data using search query frequencies. A qualitative evaluation of trends is presented. Results: Twitter depression and anxiety scores were consistently elevated above their 2019 baselines across all the 7 locations. Twitter depression scores increased during the early phase of the pandemic, with a peak in early summer and a subsequent decline in late summer. The pattern of depression trends was aligned with national COVID-19 case trends rather than with trends in individual states. Anxiety was consistently and steadily elevated throughout the pandemic. Google search trends data showed noisy and inconsistent results. Conclusions: Our study shows the feasibility of using Twitter to capture trends of depression and anxiety during the COVID-19 public health crisis and suggests that social media data can supplement survey data to monitor long-term mental health trends.

Domestic violence calls for police service in five US cities during the COVID-19 pandemic of 2020.

BACKGROUND: When COVID-19 stay-at-home orders were instituted, there were concerns that isolation may lead to increases in domestic violence (DV). Reports of increased rates of DV during the stay-at-home period have been suggestive of this but inconsistent across different locations. We sought to complement the existing studies by characterizing changes in DV trends in US cities of Chicago, Los Angeles (LA), New York City (NYC), Philadelphia, and Phoenix using police call volume data from January 1st, 2018, through Dec 31st, 2020. METHODS: The stay-at-home orders were generally instituted for most US states in the second half of March 2020. We used the call volume for the pre-COVID-19 period (Jan. 2018 to Feb. 2020) to model a forecast against the stay-at-home order period (Mar. - May 2020) and the period after lifting the order (June - Dec. 2020) using the interrupted autoregressive integrated moving average (ARIMA) time series model. RESULTS: During the stay-at-home order, increases in mean DV calls relative to pre-COVID-19 were observed in Chicago (47.8%), Phoenix (18.4%), NYC (3.5%), and LA (3.4%), but a decrease in Philadelphia (-4.9%). After lifting the stay-at-home order, changes in mean calls relative to pre-COVID-19 remained elevated in Chicago, slightly elevated in Phoenix, and returned to baseline in NYC and LA. CONCLUSION: Results suggest that the stay-at-home orders may have contributed to an increase in DV calls in some cities (Phoenix, and to a smaller extent LA, NYC), but the increase seen in Chicago (and to some extent Phoenix) persisted beyond the stay-at-home order and therefore may not be attributable to the stay-at-home orders. Additional studies are needed to help explain why the association between stay-at-home orders and DV police call volume seems to only appear in some locations.

Clinical Validation of Rapid Gout Detection Method and Kit.

Gout is an inflammatory arthritis, which causes intense, acute pain due to the buildup of uric acid crystals in synovial fluid. The gold standard for gout diagnosis consists of synovial fluid analysis by polarized light microscopy, which is costly, time-intensive, and technique-dependent, therefore meriting a more efficient, inexpensive, and accessible method for diagnosis. We previously developed and validated a novel colorimetric gout detection method and device based on the reduction of silver nitrate by uric acid; here, we clinically validated our method and device using arthroscopically obtained synovial fluid samples from gout patients. We successfully identified uric acid crystals in clinical samples via our colorimetric method, visualized uric acid crystals in synovial fluid via handheld microscopy, and determined that silver nitrate stain did not interfere with the microscopic visualization of uric acid crystals necessary for diagnosis. We also developed and validated a method of processing turbid clinical samples for use in our device to prevent the obscuration of uric acid crystals by suspended material. Our method and device will clinically facilitate the immediate colorimetric diagnosis of gout and the subsequent bedside visualization of uric acid crystals in both ideal and turbid synovial fluid samples, allowing for a point-of-care diagnosis of gout.

Incidence of brain and spinal cord cancer and county-level radon levels in New Jersey, Wisconsin, Minnesota, Pennsylvania, and Iowa, USA.

Ionizing radiation at diagnostic and therapeutic doses is a known contributor to the development of brain and spinal cord (CNS) cancer. However, little is known about risk from exposure to radon, a natural radiation source which the general population is exposed to residentially and environmentally. This study investigated correlations between mean county radon levels and CNS cancer incidence in five highly populated and radon-enriched US states (Minnesota, mean radon level 4.6 pCi/L; Wisconsin, 5.7 pCi/L; Pennsylvania, 8.6 pCi/L; Iowa, 6.1 pCi/L; and New Jersey, 4.4 pCi/L). Mean radon levels per county were accessed through AirChek, which provides publicly available radon data measured in residences and workplaces. CNS cancer incidence data were accessed through the states' health department websites and span differing amounts of time due to the publicly accessible nature of the data, though all time spans were over 10 years. Negative binomial regressions were run to assess correlations between mean radon and CNS cancer incidence per county. Quantile maps were constructed and Moran's I was calculated to assess spatial autocorrelation in residuals; no spatial autocorrelation was evident. Iowa was the only state with a significant positive association between radon and CNS incidence; no associations were detected in other states, and a negative association was observed in the 5 states combined. This study does not provide evidence that radon is a risk factor for CNS cancer; however, the possibility of an association cannot be ruled out due to limitations of the study, principally its ecologic nature and lack of individual-level exposure data.

Rapid Gout Detection Method and Kit.

Gout is a form of arthritis characterized by buildup of uric acid in synovial fluid, which causes severe swelling and can harm joints, tendons, and other tissues. It affects approximately 4% of the United States population, or approximately 8.3 million people nationwide and is therefore a topic of epidemiologic consideration due to its prevalence. Gout is typically diagnosed via polarized microscopy of arthroscopically-aspirated synovial fluid, which is a costly, time-consuming, labor-intensive, and technically complex procedure, warranting a simpler and less complex method for diagnosis. Here, we propose and validate a colorimetric method which is based on the ability of uric acid to reduce silver nitrate. We also assessed how the colorimetric change can be accelerated by changing the concentration of silver nitrate or adding different silver catalysts, as well as develop a matrix bed for improved handling and ease of use. When translated to the clinic, this diagnostic method for gout will have the potential to increase diagnostic efficiency and accelerate patient care at the bedside.

Expression of Genes Involved in Stress, Toxicity, Inflammation, and Autoimmunity in Relation to Cadmium, Mercury, and Lead in Human Blood: A Pilot Study.

There is growing evidence of immunotoxicity related to exposure to toxic trace metals, and an examination of gene expression patterns in peripheral blood samples may provide insights into the potential development of these outcomes. This pilot study aimed to correlate the blood levels of three heavy metals (mercury, cadmium, and lead) with differences in gene expression in 24 participants from the Long Island Study of Seafood Consumption. We measured the peripheral blood mRNA expression of 98 genes that are implicated in stress, toxicity, inflammation, and autoimmunity. We fit multiple linear regression models with multiple testing correction to correlate exposure biomarkers with mRNA abundance. The mean blood Hg in this cohort was 16.1 µg/L, which was nearly three times the Environmental Protection Agency (EPA) reference dose (5.8 µg/L). The levels of the other metals were consistent with those in the general population: the mean Pb was 26.8 µg/L, and the mean Cd was 0.43 µg/L. The expression of three genes was associated with mercury, four were associated with cadmium, and five were associated with lead, although none were significant after multiple testing correction. Little evidence was found to associate metal exposure with mRNA abundance for the tested genes that were associated with stress, toxicity, inflammation, or autoimmunity. Future work should provide a more complete picture of physiological reactions to heavy metal exposure.

Cytokines as Biomarkers and Their Respective Clinical Cutoff Levels.

Cytokines, including interleukins, interferons, tumor necrosis factors, and chemokines, have a variety of pro- and anti-inflammatory effects in the body through a number of biochemical pathways and interactions. Stimuli, actions, interactions, and downstream effects of cytokines have been investigated in more depth in recent years, and clinical research has also been conducted to implicate cytokines in causal patterns in certain diseases. However, particular cutoffs of cytokines as biomarkers for disease processes have not been well studied, and this warrants future work to potentially improve diagnoses for diseases with inflammatory markers. A limited number of studies in this area are reviewed, considering diseases correlated with abnormal cytokine profiles, as well as specific cutoffs at which cytokines have been deemed clinically useful for diagnosing those diseases through Receiver Operator Characteristics modeling. In light of studies such as those discussed in this review, cytokine testing has the potential to support diagnosis due to its lack of invasiveness and low cost, compared to other common types of testing for infections and inflammatory diseases.

Mercury exposure, serum antinuclear antibodies, and serum cytokine levels in the Long Island Study of Seafood Consumption: A cross-sectional study in NY, USA.

Mercury (Hg) is a well-known neurotoxin, and has been more recently studied specifically as an immunotoxin. In experimental and a few epidemiologic studies, Hg has been associated with distinct cytokine profiles and antinuclear antibody (ANA) positivity, though patterns at lower levels of exposure, typical of seafood consumers with a western diet, are not well characterized. Seafood consumers (n=287) recruited on Long Island, NY completed food frequency and health questionnaires and provided blood for analysis of Hg, poly-unsaturated fatty acids (omega-3 and omega-6 fatty acids), selenium (Se), ANA, and several cytokines (IL-1ß, IL-4, IL-10, TNF-α, IL-17, IFN-γ, and IL-1ra). Logistic and linear regression analyses were conducted to evaluate associations between serum Hg and cytokines and ANA. Adjusted models accounted for gender, age, ethnicity, income, education, smoking, BMI, selenium, omega-3 fatty acids, omega-6 fatty acids, omega-6/omega-3 ratio, and fish intake. Sex-stratified models were also generated with the expectation that immune profiles would differ between women and men. Median blood Hg was 4.58µg/L with 90th %ile =19.8µg/L. Nine individuals displayed ANA positivity at serum titers above 1:80; many of the cytokines were below detection limits, and the ability to detect was used in the logistic regression analyses. In linear and logistic regression analyses, Hg was not significantly associated with any of the seven investigated cytokines or with ANA-positivity. Therefore, Hg was not associated with altered immune profiles in this population of seafood consumers.

Demographic Profiles, Mercury, Selenium, and Omega-3 Fatty Acids in Avid Seafood Consumers on Long Island, NY.

Seafood consumption is known to confer nutritional benefits and risks from contaminant exposure. Avid seafood consumers are neither well-characterized with regard to their demographic profile nor their underlying risk-benefit profile. Contaminants [e.g., mercury (Hg)] and nutrients [e.g., selenium (Se), omega-3 fatty acids] are prevalent in some seafood. Participants (N = 285) recruited on Long Island, NY, completed food frequency and health questionnaires and received blood draws analyzed for Hg, omega-3s, and Se. Participants were categorized based on frequency and type of seafood consumption. Logistic regression analyses evaluated relationships between seafood consumption and demographics, and were age- and sex-adjusted. t tests assessed relationships between seafood consumption patterns and biomarkers Hg, omega-3s, and Se. Consumption of both tuna and salmon was associated with older age: those aged 55-75 and over 75 years old were more likely than participants aged 18-34 to eat tuna and salmon (OR 2.27; 95% CI 1.05, 4.89 and OR 3.67; 95% CI 1.20, 11.20, respectively). Males were less likely than females to eat fish other than tuna or salmon (OR 0.58; 95% CI 0.34, 0.97). Caucasians were more likely to consume tuna (OR 0.31; 95% CI 0.10, 0.96) or salmon and tuna (OR 0.34; 95% CI 0.12, 0.91), while non-Caucasians were more likely to consume other fish types (OR 2.73; 95% CI 1.45, 5.12). Total blood Hg was associated with weekly consumption of any type of fish (p = 0.01) and with salmon and tuna consumption (p = 0.01). Salmon was associated with plasma omega-3s (p = 0.01). Se was not associated with fish intake categories. Risk communicators can use these findings to influence seafood preferences of different demographic groups.