Predicting state level suicide fatalities in the united states with realtime data and machine learning.

Digital trace data and machine learning techniques are increasingly being adopted to predict suicide-related outcomes at the individual level; however, there is also considerable public health need for timely data about suicide trends at the population level. Although significant geographic variation in suicide rates exist by state within the United States, national systems for reporting state suicide trends typically lag by one or more years. We developed and validated a deep learning based approach to utilize real-time, state-level online (Mental Health America web-based depression screenings; Google and YouTube Search Trends), social media (Twitter), and health administrative data (National Syndromic Surveillance Program emergency department visits) to estimate weekly suicide counts in four participating states. Specifically, per state, we built a long short-term memory (LSTM) neural network model to combine signals from the real-time data sources and compared predicted values of suicide deaths from our model to observed values in the same state. Our LSTM model produced accurate estimates of state-specific suicide rates in all four states (percentage error in suicide rate of -2.768% for Utah, -2.823% for Louisiana, -3.449% for New York, and -5.323% for Colorado). Furthermore, our deep learning based approach outperformed current gold-standard baseline autoregressive models that use historical death data alone. We demonstrate an approach to incorporate signals from multiple proxy real-time data sources that can potentially provide more timely estimates of suicide trends at the state level. Timely suicide data at the state level has the potential to improve suicide prevention planning and response tailored to the needs of specific geographic communities.

Seasonal Trends in Emergency Department Visits for Mental and Behavioral Health Conditions Among Children and Adolescents Aged 5-17 Years - United States, January 2018-June 2023.

Mental and behavioral health conditions among school-aged children, including substance use disorders and overall emotional well-being, are a public health concern in the United States. Timely data on seasonal patterns in child and adolescent conditions can guide optimal timing of prevention and intervention strategies. CDC examined emergency department (ED) visit data from the National Syndromic Surveillance Program for 25 distinct conditions during January 2018-June 2023 among U.S. children and adolescents aged 5-17 years, stratified by age group. Each year, during 2018-2023, among persons aged 10-14 and 15-17 years, the number and proportion of weekly ED visits for eight conditions increased in the fall school semester and remained elevated throughout the spring semester; ED visits were up to twice as high during school semesters compared with the summer period. Among children aged 5-9 years, the number and proportion of visits increased for five mental and behavioral health conditions. Seasonal increases in ED visits for some conditions among school-aged children warrant enhanced awareness about mental distress symptoms and the challenges and stressors in the school environment. Systemic changes that prioritize protective factors (e.g., physical activity; nutrition; sleep; social, community, or faith-based support; and inclusive school and community environments) and incorporate preparedness for increases in conditions during back-to-school planning might improve child and adolescent mental health.

Emergency Department Visits Involving Mental Health Conditions, Suicide-Related Behaviors, and Drug Overdoses Among Adolescents - United States, January 2019-February 2023.

The U.S. adolescent mental and behavioral health crisis is ongoing,* with high pre-COVID-19 pandemic baseline rates† (1) and further increases in poor mental health (2), suicide-related behaviors (3), and drug overdose deaths (4) reported during 2020-2021. CDC examined changes in U.S. emergency department (ED) visits for mental health conditions (MHCs) overall and for nine specific MHCs,§ suicide-related behaviors (including suspected suicide attempts), and drug-involved overdoses (including opioids) among children and adolescents aged 12-17 years (adolescents) during January 2019-February 2023, overall and by sex. Compared with fall 2021, by fall 2022, decreases in weekly ED visits were reported among all adolescents, and females specifically, for MHCs overall, suicide-related behaviors, and drug overdoses; weekly ED visits among males were stable. During this same period, increases in weekly ED visits for opioid-involved overdoses were detected. Mean weekly ED visits in fall 2022 for suicide-related behaviors and MHCs overall were at or lower than the 2019 prepandemic baseline, respectively, and drug overdose visits were higher. Differences by sex were observed; levels among females were at or higher than prepandemic baselines for these conditions. These findings suggest some improvements as of fall 2022 in the trajectory of adolescent mental and behavioral health, as measured by ED visits; however, poor mental and behavioral health remains a substantial public health problem, particularly among adolescent females. Early identification and trauma-informed interventions, coupled with expanded evidence-based, comprehensive prevention efforts, are needed to support adolescents' mental and behavioral health.

Eat Better to Look Better: The Relationship between Food Availability, UV Brightness of the Major Claw, and Mating Success of the Fiddler Crab Austruca lactea.

Many factors affect male fiddler crab courting and female choice during underground mating, including claw-waving patterns, claw-waving frequency, hood structures, burrow quality, and visible and ultraviolet signals of the major claw. Under food-limited conditions, fiddler crabs decrease their investments in reproduction-e.g., lower their claw-waving frequency. However, the effect of food availability on the visible or ultraviolet signals important for courtship success is unknown, not only for fiddler crabs, but for crustaceans in general. This is the first study to explore the influence of food availability on the early stages of female choice in Austruca lactea. In the present study, we tested (1) the effect of food availability on the UV brightness of A. lactea's major claw and burrow quality and (2) the correlation between A. lactea courtship success and the UV brightness of its major claw. Our results showed that higher food availability increased the UV brightness of the major claw and enhanced the male's burrow quality. The UV component to the signal is important for courtship success. The males with a UV component of signal on their major claw had a higher courtship success. This is an indication that food availability may affect the attractiveness of male fiddler crabs.

Directing Group-Promoted Inert C-O Bond Activation Using Versatile Boronic Acid as a Coupling Agent.

A simple Ni(cod)2 and carbene mediated strategy facilitates the efficient catalytic cross-coupling of methoxyarenes with a variety of organoboron reagents. Directing groups facilitate the activation of inert C-O bonds in under-utilized aryl methyl ethers enabling their adaptation for C-C cross-coupling reactions as less toxic surrogates to the ubiquitous haloarenes. The method reported enables C-C cross-coupling with readily available and economical arylboronic acid reagents, which is unprecedented, and compares well with other organoboron reagents with similarly high reactivity. Extension to directing group assisted chemo-selective C-O bond cleavage, and further application towards the synthesis of novel bifunctionalized biaryls is reported. Key to the success of this protocol is the use of directing groups proximal to the reaction center to facilitate the activation of the inert C-OMe bond.

Syndromic Surveillance of Emergency Department Visits for Acute Adverse Effects of Marijuana, Tri-County Health Department, Colorado, 2016-2017.

OBJECTIVES: In Colorado, legalization of recreational marijuana in 2014 increased public access to marijuana and might also have led to an increase in emergency department (ED) visits. We examined the validity of using syndromic surveillance data to detect marijuana-associated ED visits by comparing the performance of surveillance queries with physician-reviewed medical records. METHODS: We developed queries of combinations of marijuana-specific International Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes or keywords. We applied these queries to ED visit data submitted through the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) syndromic surveillance system at 3 hospitals during 2016-2017. One physician reviewed the medical records of ED visits identified by ≥1 query and calculated the positive predictive value (PPV) of each query. We defined cases of acute adverse effects of marijuana (AAEM) as determined by the ED provider's clinical impression during the visit. RESULTS: Of 44 942 total ED visits, ESSENCE queries detected 453 (1%) as potential AAEM cases; a review of 422 (93%) medical records identified 188 (45%) true AAEM cases. Queries using ICD-10 diagnostic codes or keywords in the triage note identified all true AAEM cases; PPV varied by hospital from 36% to 64%. Of the 188 true AAEM cases, 109 (58%) were among men and 178 (95%) reported intentional use of marijuana. Compared with noncases of AAEM, cases were significantly more likely to be among non-Colorado residents than among Colorado residents and were significantly more likely to report edible marijuana use rather than smoked marijuana use ( P < .001). CONCLUSIONS: ICD-10 diagnostic codes and triage note keyword queries in ESSENCE, validated by medical record review, can be used to track ED visits for AAEM.

Validation of a Syndromic Case Definition for Detecting Emergency Department Visits Potentially Related to Marijuana.

OBJECTIVES: Reliable methods are needed to monitor the public health impact of changing laws and perceptions about marijuana. Structured and free-text emergency department (ED) visit data offer an opportunity to monitor the impact of these changes in near-real time. Our objectives were to (1) generate and validate a syndromic case definition for ED visits potentially related to marijuana and (2) describe a method for doing so that was less resource intensive than traditional methods. METHODS: We developed a syndromic case definition for ED visits potentially related to marijuana, applied it to BioSense 2.0 data from 15 hospitals in the Denver, Colorado, metropolitan area for the period September through October 2015, and manually reviewed each case to determine true positives and false positives. We used the number of visits identified by and the positive predictive value (PPV) for each search term and field to refine the definition for the second round of validation on data from February through March 2016. RESULTS: Of 126 646 ED visits during the first period, terms in 524 ED visit records matched ≥1 search term in the initial case definition (PPV, 92.7%). Of 140 932 ED visits during the second period, terms in 698 ED visit records matched ≥1 search term in the revised case definition (PPV, 95.7%). After another revision, the final case definition contained 6 keywords for marijuana or derivatives and 5 diagnosis codes for cannabis use, abuse, dependence, poisoning, and lung disease. CONCLUSIONS: Our syndromic case definition and validation method for ED visits potentially related to marijuana could be used by other public health jurisdictions to monitor local trends and for other emerging concerns.