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ObjectiveTo evaluate the adoption and discontinuation of four broadly used non-pharmaceutical interventions on shifts in the covid-19 burden among US states.DesignRetrospective, observational cohort study.SettingUS state data on covid-19 between 19 January 2020 and 7 March 2021.ParticipantsUS population with a diagnosis of covid-19.Main outcome measuresEmpirically derived breakpoints in case and mortality velocities (ie, rate of change) were used to identify periods of stable, decreasing, or increasing covid-19 burden. Associations between adoption of non-pharmaceutical interventions and subsequent decreases in case or death rates were estimated by use of generalised linear models accounting for weekly variability across US states. State level case and mortality counts per day were obtained from the Covid-19 Tracking Project. State level policies on non-pharmaceutical interventions included stay-at-home orders, indoor public gathering bans (mild >10 or severe ≤10 people), indoor restaurant dining bans, and public mask mandates. National policies were not included in statistical models.Results28 602 830 cases and 511 899 deaths were recorded during the study. Odds of a reduction in covid-19 case velocity increased for stay-at-home orders (odds ratio 2.02, 95% confidence interval 1.63 to 2.52), indoor dining bans (1.62, 1.25 to 2.10), public mask mandates (2.18, 1.47 to 3.23), and severe indoor public gathering bans (1.68, 1.31 to 2.16) in univariate analysis. In mutually adjusted models, odds remained elevated for orders to stay at home (adjusted odds ratio 1.47, 95% confidence interval 1.04 to 2.07) and public mask mandates (2.27, 1.51 to 3.41). Stay-at-home orders (odds ratio 2.00, 95% confidence interval 1.53 to 2.62; adjusted odds ratio 1.89, 95% confidence interval 1.25 to 2.87) was also associated with a greater likelihood of decrease in death velocity in unadjusted and adjusted models.ConclusionsState level non-pharmaceutical interventions used in the US during the covid-19 pandemic, in particular stay-at-home orders, were associated with a decreased covid-19 burden.

BACKGROUND: Non-pharmaceutical interventions (NPIs) are mitigation strategies used to reduce the spread of transmissible diseases. The relative effectiveness of specific NPIs remains uncertain. METHODS: We used state-level Coronavirus disease 2019 (COVID-19) case and mortality data between January 19, 2020 and March 7, 2021 to model NPI policy effectiveness. Empirically derived breakpoints in case and mortality velocities were used to identify periods of stable, decreasing, or increasing COVID-19 burden. The associations between NPI adoption and subsequent decreases in case or death velocities were estimated using generalized linear models accounting for weekly variability shared across states. State-level NPI policies included: stay at home order, indoor public gathering ban (mild >10 or severe ≤10), indoor restaurant dining ban, and public mask mandate. RESULTS: 28,602,830 cases and 511,899 deaths were recorded. The odds of a decrease in COVID-19 case velocity were significantly elevated for stay at home (OR 2.02, 95% CI 1.63-2.52), indoor dining ban (OR 1.62, 95% CI 1.25-2.10), public mask mandate (OR 2.18, 95% CI 1.47-3.23), and severe gathering ban (OR 1.68, 95% CI 1.31-2.16). In mutually adjusted models, odds remained elevated for stay at home (AOR 1.47, 95% CI 1.04-2.07) and public mask mandate (AOR = 2.27, 95% CI 1.51-3.41). Stay at home (OR 2.00, 95% CI 1.53-2.62; AOR 1.89, 95% CI 1.25-2.87) was also associated with greater likelihood of decrease in death velocity in unadjusted and adjusted models. CONCLUSIONS: NPIs employed in the U.S. during the COVID-19 pandemic, most significantly stay at home orders, were associated with decreased COVID-19 burden.

BackgroundDepression causes significant morbidity, which impacts mental health, overall general health outcomes, everyday functioning and quality of life. This study aims to contribute to knowledge in the field through enhanced understanding of factors that influence depression response and remission, with consideration for design of treatment services to optimize depression outcomes within integrated care programs.MethodsUsing routine behavioral health screening and electronic health record data, we identified a retrospective cohort consisting of 615 adult patients receiving depression treatment within an integrated care program. Cohort member Patient Health Questionnaire (PHQ-9) data was analyzed for the 6 months following initiation of treatment. Multinomial regression models were estimated to identify factors associated with depression treatment response (PHQ-9

ObjectiveTo evaluate feasibility and acceptability of a health professional resilience skills training program with neurology residents.MethodsThe curriculum consists of five 1-hour-long modules that included the following skills: reflective narrative practices, emotion regulation, communication with highly distressed individuals, boundary management, and the identification of depression and trauma. Using a web-based survey tool, we administered the Brief Resilience Scale (BRS) and Abbreviated Maslach Burnout Inventory (aMBI) at baseline, in addition to a pre- and post-survey assessing change in beliefs and self-efficacy, as well as satisfaction with the intervention. Means were compared using the Wilcoxon rank-sum and signed rank tests.ResultsTwenty-two residents representing each year of training completed the pre-survey; 41% were women. Subscale scores on the aMBI revealed that 50% had moderate or high emotional exhaustion, 41% had moderate depersonalization, and 37% had moderate or low personal accomplishment, though 77.3% reported high career satisfaction. Female residents had lower scores on the BRS (mean 3.26 vs 3.88, p < 0.05), though scores on aMBI subscales did not differ by sex. Scores did not differ by year of training. Sixteen residents completed both the pre- and post-survey. Significant increases were detected in 4 of 9 self-efficacy statements. Seventy-one percent of residents were satisfied or extremely satisfied with the training.ConclusionsResidents were satisfied with the curriculum and reported improved ability to identify and cope with work-related stress. Further study is needed to evaluate the influence of skills adoption and practice on resilience and burnout.

For individuals living with human immunodeficiency virus (HIV), viral suppression positively affects quality and length of life and reduces risks for HIV transmission. Men of color who have sex with men (MoCSM) who have been diagnosed with HIV have disproportionately low rates of viral suppression, with concomitant increases in incidence. We identified specific social, structural, and psychiatric factors associated with viral suppression among a sample of 155 HIV-positive MoCSM. Cigarette smoking and biological markers of recent drug use were significantly associated with detectable viral load. In contrast, individuals reporting a history of psychiatric illness during medical examination were more likely to be virally suppressed. Further analyses demonstrated that psychiatric illness may affect virologic outcomes through increased probability of being prescribed HIV medications. Alternatively, cigarette smoking and drug use appear to negatively affect subsequent HIV Care Continuum milestones such as medication adherence. Findings provide support for comprehensive intervention programs that emphasize prevention and treatment of cigarette, methamphetamine, and other drug use, and promote improved connection to psychiatric care. Continual achievement of this goal may be a crucial step to increase rates of viral suppression and slow HIV incidence in communities of MoCSM in Los Angeles and other urban areas.

Understanding the impact of concurrency, defined as overlapping sexual partnerships, on the spread of HIV within various communities has been complicated by difficulties in measuring concurrency. Retrospective sexual history data consisting of first and last dates of sexual intercourse for each previous and ongoing partnership is often obtained through use of cross-sectional surveys. Previous attempts to empirically estimate the magnitude and extent of concurrency among these surveyed populations have inadequately accounted for the dependence between partnerships and used only a snapshot of the available data. We introduce a joint multistate and point process model in which states are defined as the number of ongoing partnerships an individual is engaged in at a given time. Sexual partnerships starting and ending on the same date are referred to as one-offs and modeled as discrete events. The proposed method treats each individual's continuation in and transition through various numbers of ongoing partnerships as a separate stochastic process and allows the occurrence of one-offs to impact subsequent rates of partnership formation and dissolution. Estimators for the concurrent partnership distribution and mean sojourn times during which a person has k ongoing partnerships are presented. We demonstrate this modeling approach using epidemiological data collected from a sample of men having sex with men and seeking HIV testing at a Los Angeles clinic. Among this sample, the estimated point prevalence of concurrency was higher among men later diagnosed HIV positive. One-offs were associated with increased rates of subsequent partnership dissolution. Copyright © 2016 John Wiley & Sons, Ltd.

BackgroundGenetic and environmental factors are believed to contribute to the development of autism, but relatively few studies have considered potential environmental risks. Here, we examine risks for autism in children related to in utero exposure to monitored ambient air toxics from urban emissions.MethodsAmong the cohort of children born in Los Angeles County, California, 1995-2006, those whose mothers resided during pregnancy in a 5-km buffer around air toxics monitoring stations were included (n = 148,722). To identify autism cases in this cohort, birth records were linked to records of children diagnosed with primary autistic disorder at the California Department of Developmental Services between 1998 and 2009 (n = 768). We calculated monthly average exposures during pregnancy for 24 air toxics selected based on suspected or known neurotoxicity or neurodevelopmental toxicity. Factor analysis helped us identify the correlational structure among air toxics, and we estimated odds ratios (ORs) for autism from logistic regression analyses.ResultsAutism risks were increased per interquartile range increase in average concentrations during pregnancy of several correlated toxics mostly loading on 1 factor, including 1,3-butadiene (OR = 1.59 [95% confidence interval = 1.18-2.15]), meta/para-xylene (1.51 [1.26-1.82]), other aromatic solvents, lead (1.49 [1.23-1.81]), perchloroethylene (1.40 [1.09-1.80]), and formaldehyde (1.34 [1.17-1.52]), adjusting for maternal age, race/ethnicity, nativity, education, insurance type, parity, child sex, and birth year.ConclusionsRisks for autism in children may increase following in utero exposure to ambient air toxics from urban traffic and industry emissions, as measured by community-based air-monitoring stations.

Although youth are at risk for exposure to adversity and trauma, many youth, especially ethnic and racial minorities, do not have access to mental health care. Resilience-building curriculums can teach important internal resilience skills and provide support to students who may not receive prevention or treatment services. We adapted a resilience curriculum initially used for military-connected youth facing adversities related to parental wartime deployments, to meet the needs of low-income, predominantly racial and ethnic minority students in a large urban school district. In this article, we describe the cultural adaptation, the implementation process, and the evaluation of the trauma-informed resilience curriculum using pre-post surveys and focus group discussions. We found significantly improved overall internal resilience scores, as well as significantly improved scores on subscales of problem-solving and empathy among students receiving the curriculum. The focus groups revealed that the curriculum enhanced connections among students, as well as students and teachers, and served as a way to destigmatize mental health issues. The acceptability of the curriculum as well as implementation successes and challenges are described. We provide suggestions for future steps for school psychologists and school social workers for implementing this curriculum.

Multistate models are useful for studying exposures that affect transitions among a set of health states. However, they can be challenging to apply when exposures are time-varying. We develop a multistate model and a method of likelihood construction that allows application of the model to data in which interventions or other exposures can be time-varying and an individual may to be exposed to multiple intervention conditions while progressing through states. The model includes cure proportions, reflecting the possibility that some individuals will never leave certain states. We apply the approach to analyze patient vaccination data from a stepped wedge design trial evaluating two interventions to increase uptake of human papillomavirus vaccination. The states are defined as the number of vaccine doses the patient has received. We model state transitions as a semi-Markov process and include cure proportions to account for individuals who will never leave a given state (e.g. never receive their next dose). Multistate models typically quantify intervention effects as hazard ratios contrasting the intensities of transitions between states in intervention versus control conditions. For multistate processes, another clinically meaningful outcome is the change in the percentage of the study population that has achieved a specific state (e.g. completion of all required doses) by a specific point in time due to an intervention. We present a method for quantifying intervention effects in this manner. We apply the model to both simulated and real-world data and also explore some conditions under which such models may give biased results. [ABSTRACT FROM AUTHOR]

There is a growing need to accurately assess exercise energy expenditure (EEE) in athletic populations that may be at risk for health disorders because of an imbalance between energy intake and energy expenditure. The Actiheart combines heart rate and uniaxial accelerometry to estimate energy expenditure above rest. The authors' purpose was to determine the utility of the Actiheart for predicting EEE in female adolescent runners (N = 39, age 15.7 ± 1.1 yr). EEE was measured by indirect calorimetry and predicted by the Actiheart during three 8-min stages of treadmill running at individualized velocities corresponding to each runner's training, including recovery, tempo, and 5-km-race pace. Repeated-measures ANOVA with Bonferroni post hoc comparisons across the 3 running stages indicated that the Actiheart was sensitive to changes in intensity (p < .01 ), but accelerometer output tended to plateau at race pace. Pairwise comparisons of the mean difference between Actiheart- and criterion-measured EEE yielded values of 0.0436, 0.0539, and 0.0753 kcal · kg-1 · min-1 during recovery, tempo, and race pace, respectively (p < .0001). Bland--Altman plots indicated that the Actiheart consistently underestimated EEE except in 1 runner's recovery bout. A linear mixed-model regression analysis with height as a covariate provided an improved EEE prediction model, with the overall standard error of the estimate for the 3 speeds reduced to 0.0101 kcal · kg-1 · min-1. Using the manufacturer's equation that combines heart rate and uniaxial motion, the Actiheart may have limited use in accurately assessing EEE, and therefore energy availability, in young, female competitive runners. [ABSTRACT FROM AUTHOR]