Emergency Medical Services Encounters for Firearm Injuries - 858 Counties, United States, January 2019-September 2023.

Firearm-related deaths and injuries have increased in recent years. Comprehensive and timely information on firearm injuries and the communities and geographic locations most affected by firearm violence is crucial for guiding prevention activities. However, traditional surveillance systems for firearm injury, which are mostly based on hospital encounters and mortality-related data, often lack information on the location where the shooting occurred. This study examined annual and monthly rates of emergency medical services (EMS) encounters for firearm injury per 100,000 total EMS encounters during January 2019-September 2023 in 858 counties in 27 states, by patient characteristics and characteristics of the counties where the injuries occurred. Overall, annual rates of firearm injury EMS encounters per 100,000 total EMS encounters ranged from 222.7 in 2019 to 294.9 in 2020; rates remained above prepandemic levels through 2023. Rates were consistently higher among males than females. Rates stratified by race and ethnicity were highest among non-Hispanic Black or African American persons; rates stratified by age group were highest among persons aged 15-24 years. The greatest percentage increases in annual rates occurred in urban counties and in counties with higher prevalence of severe housing problems, higher income inequality ratios, and higher rates of unemployment. States and communities can use the timely and location-specific data in EMS records to develop and implement comprehensive firearm injury prevention strategies to address the economic, social, and physical conditions that contribute to the risk for violence, including improvements to physical environments, secure firearm storage, and strengthened social and economic supports.

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.

Association of Recent Violence Encounters With Suicidal Ideation Among Adolescents With Depression.

Importance: Suicide prevention is an important component of depression management. Knowledge about depressed adolescents with increased risk for suicide can inform suicide prevention efforts. Objective: To describe the risk of documented suicidal ideation within a year following a diagnosis of depression and to examine how the risk of documented suicidal ideation differed by recent violence encounter status among adolescents with new depression diagnoses. Design, Setting, and Participants: Retrospective cohort study in clinical settings including outpatient facilities, emergency departments, and hospitals. Using IBM's Explorys database containing electronic health records from 26 US health care networks, this study observed a cohort of adolescents with new depression diagnoses from 2017 to 2018 for up to 1 year. Data were analyzed from July 2020 to July 2021. Exposures: Recent violence encounter was defined by a diagnosis of child maltreatment (physical, sexual, or psychological abuse or neglect) or physical assault within 1 year before depression diagnosis. Main Outcomes and Measures: The main outcome was diagnosis of suicidal ideation within 1 year following depression diagnosis. Multivariable adjusted risk ratios of suicidal ideation were calculated for overall recent violence encounters and for individual forms of violence. Results: Among a total of 24 047 adolescents with depression, 16 106 (67.0%) were female and 13 437 (55.9%) were White. A total of 378 had experienceda violence (hereafter, encounter group) and 23 669 had not (hereafter, nonencounter group). Following the diagnosis of depression, 104 adolescents with any past-year violence encounter (27.5%) documented suicidal ideation within 1 year. In contrast, 3185 adolescents in the nonencounter group (13.5%) experienced thoughts of suicide following the diagnosis of depression. In multivariable analyses, those with any violence encounter had 1.7 times (95% CI 1.4-2.0) higher risk of documented suicidal ideation compared with those in the nonencounter group (P < .001). Among different forms of violence, sexual abuse (risk ratio, 2.1; 95% CI, 1.6-2.8) and physical assault (risk ratio, 1.7; 95% CI, 1.3-2.2) were associated with significantly increased risk of suicidal ideation. Conclusions and Relevance: Among adolescents with depression, persons who experienced past-year violence encounters showed a higher rate of suicidal ideation than those who had not. These findings highlight the importance of identifying and accounting for past violence encounters when treating adolescents with depression to reduce risk of suicide. Public health approaches to prevent violence may help to avert morbidity associated with depression and suicidal ideation.

Development of a Machine Learning Model to Estimate US Firearm Homicides in Near Real Time.

Importance: Firearm homicides are a major public health concern; lack of timely mortality data presents considerable challenges to effective response. Near real-time data sources offer potential for more timely estimation of firearm homicides. Objective: To estimate near real-time burden of weekly and annual firearm homicides in the US. Design, Setting, and Participants: In this prognostic study, anonymous, longitudinal time series data were obtained from multiple data sources, including Google and YouTube search trends related to firearms (2014-2019), emergency department visits for firearm injuries (National Syndromic Surveillance Program, 2014-2019), emergency medical service activations for firearm-related injuries (biospatial, 2014-2019), and National Domestic Violence Hotline contacts flagged with the keyword firearm (2016-2019). Data analysis was performed from September 2021 to September 2022. Main Outcomes and Measures: Weekly estimates of US firearm homicides were calculated using a 2-phase pipeline, first fitting optimal machine learning models for each data stream and then combining the best individual models into a stacked ensemble model. Model accuracy was assessed by comparing predictions of firearm homicides in 2019 to actual firearm homicides identified by National Vital Statistics System death certificates. Results were also compared with a SARIMA (seasonal autoregressive integrated moving average) model, a common method to forecast injury mortality. Results: Both individual and ensemble models yielded highly accurate estimates of firearm homicides. Individual models' mean error for weekly estimates of firearm homicides (root mean square error) varied from 24.95 for emergency department visits to 31.29 for SARIMA forecasting. Ensemble models combining data sources had lower weekly mean error and higher annual accuracy than individual data sources: the all-source ensemble model had a weekly root mean square error of 24.46 deaths and full-year accuracy of 99.74%, predicting the total number of firearm homicides in 2019 within 38 deaths for the entire year (compared with 95.48% accuracy and 652 deaths for the SARIMA model). The model decreased the time lag of reporting weekly firearm homicides from 7 to 8 months to approximately 6 weeks. Conclusions and Relevance: In this prognostic study of diverse secondary data on machine learning, ensemble modeling produced accurate near real-time estimates of weekly and annual firearm homicides and substantially decreased data source time lags. Ensemble model forecasts can accelerate public health practitioners' and policy makers' ability to respond to unanticipated shifts in firearm homicides.

Emergency Department Visits for Firearm Injuries Before and During the COVID-19 Pandemic - United States, January 2019-December 2022.

During the COVID-19 pandemic, the U.S. firearm homicide rate increased by nearly 35%, and the firearm suicide rate remained high during 2019-2020 (1). Provisional mortality data from the National Vital Statistics System indicate that rates continued to increase in 2021: the rates of firearm homicide and firearm suicide in 2021 were the highest recorded since 1993 and 1990, respectively (2). Firearm injuries treated in emergency departments (EDs), the primary setting for the immediate medical treatment of such injuries, gradually increased during 2018-2019 (3); however, more recent patterns of ED visits for firearm injuries, particularly during the COVID-19 pandemic, are unknown. Using data from the National Syndromic Surveillance Program (NSSP),* CDC examined changes in ED visits for initial firearm injury encounters during January 2019-December 2022, by year, patient sex, and age group. Increases in the overall weekly number of firearm injury ED visits were detected at certain periods during the COVID-19 pandemic. One such period during which there was a gradual increase was March 2020, which coincided with both the declaration of COVID-19 as a national emergency† and a pronounced decrease in the total number of ED visits. Another increase in firearm injury ED visits occurred in late May 2020, concurrent with a period marked by public outcry related to social injustice and structural racism (4), changes in state-level COVID-19-specific prevention strategies,§ decreased engagement in COVID-19 mitigation behaviors (5), and reported increases in some types of crime (4). Compared with 2019, the average number of weekly ED visits for firearm injury was 37% higher in 2020, 36% higher in 2021, and 20% higher in 2022. A comprehensive approach is needed to prevent and respond to firearm injuries in communities, including strategies that engage community and street outreach programs, implement hospital-based violence prevention programs, improve community physical environments, enhance secure storage of firearms, and strengthen social and economic supports.

County-Level Social Vulnerability and Emergency Department Visits for Firearm Injuries - 10 U.S. Jurisdictions, January 1, 2018-December 31, 2021.

At least 100,000 persons in the United States experience a fatal or nonfatal firearm injury each year.* CDC examined rates of firearm injury emergency department (ED) visits by community social vulnerability using data from CDC's Firearm Injury Surveillance Through Emergency Rooms (FASTER) program.† ED visit data, shared with CDC's National Syndromic Surveillance Program (NSSP)§ during 2018-2021, were analyzed for 647 counties in 10 FASTER-funded jurisdictions.¶ County-level social vulnerability data were obtained from the 2018 Social Vulnerability Index (SVI).** Rates of ED visits for firearm injuries (number of firearm injury ED visits per 100,000 ED visits) were calculated across tertile levels of social vulnerability. Negative binomial regression models were used to estimate rate ratios (RRs) and associated 95% CIs comparing rates of ED visits across social vulnerability levels. During 2018-2021, compared with rates in counties with low overall social vulnerability, the firearm injury ED visit rate was 1.34 times as high in counties with medium social vulnerability and 1.80 times as high in counties with high social vulnerability. Similar patterns were observed for the SVI themes of socioeconomic status and housing type and transportation, but not for the themes of household composition and disability status or racial and ethnic minority status and language proficiency. More timely data†† on firearm injury ED visits by social vulnerability can help identify communities disproportionately experiencing elevated firearm injury rates. States and communities can use the best available evidence to implement comprehensive prevention strategies that address inequities in the social and structural conditions that contribute to risk for violence, including creating protective community environments, strengthening economic supports, and intervening to reduce harms and prevent future risk (e.g., with hospital-based violence intervention programs) (1,2).

Estimating Weekly National Opioid Overdose Deaths in Near Real Time Using Multiple Proxy Data Sources.

Importance: Opioid overdose is a leading public health problem in the United States; however, national data on overdose deaths are delayed by several months or more. Objectives: To build and validate a statistical model for estimating national opioid overdose deaths in near real time. Design, Setting, and Participants: In this cross-sectional study, signals from 5 overdose-related, proxy data sources encompassing health, law enforcement, and online data from 2014 to 2019 in the US were combined using a LASSO (least absolute shrinkage and selection operator) regression model, and weekly predictions of opioid overdose deaths were made for 2018 and 2019 to validate model performance. Results were also compared with those from a baseline SARIMA (seasonal autoregressive integrated moving average) model, one of the most used approaches to forecasting injury mortality. Exposures: Time series data from 2014 to 2019 on emergency department visits for opioid overdose from the National Syndromic Surveillance Program, data on the volume of heroin and synthetic opioids circulating in illicit markets via the National Forensic Laboratory Information System, data on the search volume for heroin and synthetic opioids on Google, and data on post volume on heroin and synthetic opioids on Twitter and Reddit were used to train and validate prediction models of opioid overdose deaths. Main Outcomes and Measures: Model-based predictions of weekly opioid overdose deaths in the United States were made for 2018 and 2019 and compared with actual observed opioid overdose deaths from the National Vital Statistics System. Results: Statistical models using the 5 real-time proxy data sources estimated the national opioid overdose death rate for 2018 and 2019 with an error of 1.01% and -1.05%, respectively. When considering the accuracy of weekly predictions, the machine learning-based approach possessed a mean error in its weekly estimates (root mean squared error) of 60.3 overdose deaths for 2018 (compared with 310.2 overdose deaths for the SARIMA model) and 67.2 overdose deaths for 2019 (compared with 83.3 overdose deaths for the SARIMA model). Conclusions and Relevance: Results of this serial cross-sectional study suggest that proxy administrative data sources can be used to estimate national opioid overdose mortality trends to provide a more timely understanding of this public health problem.

Vital Signs: Changes in Firearm Homicide and Suicide Rates - United States, 2019-2020.

INTRODUCTION: The majority of homicides (79%) and suicides (53%) in the United States involved a firearm in 2020. High firearm homicide and suicide rates and corresponding inequities by race and ethnicity and poverty level represent important public health concerns. This study examined changes in firearm homicide and firearm suicide rates coinciding with the emergence of the COVID-19 pandemic in 2020. METHODS: National vital statistics and population data were integrated with urbanization and poverty measures at the county level. Population-based firearm homicide and suicide rates were examined by age, sex, race and ethnicity, geographic area, level of urbanization, and level of poverty. RESULTS: From 2019 to 2020, the overall firearm homicide rate increased 34.6%, from 4.6 to 6.1 per 100,000 persons. The largest increases occurred among non-Hispanic Black or African American males aged 10-44 years and non-Hispanic American Indian or Alaska Native (AI/AN) males aged 25-44 years. Rates of firearm homicide were lowest and increased least at the lowest poverty level and were higher and showed larger increases at higher poverty levels. The overall firearm suicide rate remained relatively unchanged from 2019 to 2020 (7.9 to 8.1); however, in some populations, including AI/AN males aged 10-44 years, rates did increase. CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: During the COVID-19 pandemic, the firearm homicide rate in the United States reached its highest level since 1994, with substantial increases among several population subgroups. These increases have widened disparities in rates by race and ethnicity and poverty level. Several increases in firearm suicide rates were also observed. Implementation of comprehensive strategies employing proven approaches that address underlying economic, physical, and social conditions contributing to the risks for violence and suicide is urgently needed to reduce these rates and disparities.

Using the Centers for Disease Control and Prevention's National Syndromic Surveillance Program Data to Monitor Trends in US Emergency Department Visits for Firearm Injuries, 2018 to 2019.

STUDY OBJECTIVE: We describe trends in emergency department (ED) visits for initial firearm injury encounters in the United States. METHODS: Using data from the Centers for Disease Control and Prevention's National Syndromic Surveillance Program, we analyzed monthly and yearly trends in ED visit rates involving a firearm injury (calculated as the number of firearm injury-related ED visits divided by the total number of ED visits for each month and multiplied by 100,000) by sex-specific age group and US region from 2018 to 2019 and conducted Joinpoint regression to detect trend significance. RESULTS: Among approximately 215 million ED visits captured in the National Syndromic Surveillance Program from January 2018 to December 2019, 132,767 involved a firearm injury (61.6 per 100,000 ED visits). Among males, rates of firearm injury-related ED visits significantly increased for all age groups between 15 and 64 years during the study period. Among females, rates of firearm injury-related ED visits significantly increased for all age groups between 15 and 54 years during the study period. By region, rates significantly changed in the northeast, southeast, and southwest for males and females during the study period. CONCLUSION: These analyses highlight a novel data source for monitoring trends in ED visits for firearm injuries. With increased and effective use of state and local syndromic surveillance data, in addition to improvements to firearm injury syndrome definitions by intent, public health professionals could better detect unusual patterns of firearm injuries across the United States for improved prevention and tailored response efforts.

Pediatric Emergency Department Visits Before and During the COVID-19 Pandemic - United States, January 2019-January 2022.

Emergency departments (EDs) in the United States remain a frontline resource for pediatric health care emergencies during the COVID-19 pandemic; however, patterns of health-seeking behavior have changed during the pandemic (1,2). CDC examined changes in U.S. ED visit trends to assess the continued impact of the pandemic on visits among children and adolescents aged 0-17 years (pediatric ED visits). Compared with 2019, pediatric ED visits declined by 51% during 2020, 22% during 2021, and 23% during January 2022. Although visits for non-COVID-19 respiratory illnesses mostly declined, the proportion of visits for some respiratory conditions increased during January 2022 compared with 2019. Weekly number and proportion of ED visits increased for certain types of injuries (e.g., drug poisonings, self-harm, and firearm injuries) and some chronic diseases, with variation by pandemic year and age group. Visits related to behavioral concerns increased across pandemic years, particularly among older children and adolescents. Health care providers and families should remain vigilant for potential indirect impacts of the COVID-19 pandemic, including health conditions resulting from delayed care, and increasing emotional distress and behavioral health concerns among children and adolescents.

Trends in US Emergency Department Visits for Mental Health, Overdose, and Violence Outcomes Before and During the COVID-19 Pandemic.

Importance: The coronavirus disease 2019 (COVID-19) pandemic, associated mitigation measures, and social and economic impacts may affect mental health, suicidal behavior, substance use, and violence. Objective: To examine changes in US emergency department (ED) visits for mental health conditions (MHCs), suicide attempts (SAs), overdose (OD), and violence outcomes during the COVID-19 pandemic. Design, Setting, and Participants: This cross-sectional study used data from the Centers for Disease Control and Prevention's National Syndromic Surveillance Program to examine national changes in ED visits for MHCs, SAs, ODs, and violence from December 30, 2018, to October 10, 2020 (before and during the COVID-19 pandemic). The National Syndromic Surveillance Program captures approximately 70% of US ED visits from more than 3500 EDs that cover 48 states and Washington, DC. Main Outcomes and Measures: Outcome measures were MHCs, SAs, all drug ODs, opioid ODs, intimate partner violence (IPV), and suspected child abuse and neglect (SCAN) ED visit counts and rates. Weekly ED visit counts and rates were computed overall and stratified by sex. Results: From December 30, 2018, to October 10, 2020, a total of 187 508 065 total ED visits (53.6% female and 46.1% male) were captured; 6 018 318 included at least 1 study outcome (visits not mutually exclusive). Total ED visit volume decreased after COVID-19 mitigation measures were implemented in the US beginning on March 16, 2020. Weekly ED visit counts for all 6 outcomes decreased between March 8 and 28, 2020 (March 8: MHCs = 42 903, SAs = 5212, all ODs = 14 543, opioid ODs = 4752, IPV = 444, and SCAN = 1090; March 28: MHCs = 17 574, SAs = 4241, all ODs = 12 399, opioid ODs = 4306, IPV = 347, and SCAN = 487). Conversely, ED visit rates increased beginning the week of March 22 to 28, 2020. When the median ED visit counts between March 15 and October 10, 2020, were compared with the same period in 2019, the 2020 counts were significantly higher for SAs (n = 4940 vs 4656, P = .02), all ODs (n = 15 604 vs 13 371, P < .001), and opioid ODs (n = 5502 vs 4168, P < .001); counts were significantly lower for IPV ED visits (n = 442 vs 484, P < .001) and SCAN ED visits (n = 884 vs 1038, P < .001). Median rates during the same period were significantly higher in 2020 compared with 2019 for all outcomes except IPV. Conclusions and Relevance: These findings suggest that ED care seeking shifts during a pandemic, underscoring the need to integrate mental health, substance use, and violence screening and prevention services into response activities during public health crises.

Chronic Diseases, Health Conditions, and Other Impacts Associated With Rape Victimization of U.S. Women.

Sexual violence (SV) is an urgent public health issue that is common and has lifelong effects on health. Previous scholarship has documented the association of SV victimization with numerous health conditions and impacts, but much of this past work has focused on negative health outcomes associated with child sexual abuse using non-nationally representative samples. This article used a nationally representative female sample to examine health conditions associated with any lifetime experience of rape. We also examined injury and health outcomes (e.g., fear, injury) resulting from any violence by a perpetrator of rape. About two in five rape victims (39.1%) reported injury (e.g., bruises, vaginal tears), and 12.3% reported a sexually transmitted disease as a result of the rape victimization. Approximately 71.3% of rape victims (an estimated 16.4 million women) experienced some form of impact as a result of violence by a rape perpetrator. Among U.S. women, the adjusted odds of experiencing asthma, irritable bowel syndrome, frequent headaches, chronic pain, difficulty sleeping, activity limitations, poor physical or mental health, and use of special equipment (e.g., wheelchair) were significantly higher for lifetime rape victims compared with non-victims. This article fills gaps in our understanding of health impacts associated with rape of women and is the only nationally representative source of this information to our knowledge. Primary prevention efforts in youth that seek to prevent the first occurrence of rape and other forms of SV may be most effective for reducing the long-term health effects of this violence.

Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.

Importance: Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making. Objective: To estimate weekly suicide fatalities in the US in near real time. Design, Setting, and Participants: This cross-sectional national study used a machine learning pipeline to combine signals from several streams of real-time information to estimate weekly suicide fatalities in the US in near real time. This 2-phase approach first fits optimal machine learning models to each individual data stream and subsequently combines predictions made from each data stream via an artificial neural network. National-level US administrative data on suicide deaths, health services, and economic, meteorological, and online data were variously obtained from 2014 to 2017. Data were analyzed from January 1, 2014, to December 31, 2017. Exposures: Longitudinal data on suicide-related exposures were obtained from multiple, heterogeneous streams: emergency department visits for suicide ideation and attempts collected via the National Syndromic Surveillance Program (2015-2017); calls to the National Suicide Prevention Lifeline (2014-2017); calls to US poison control centers for intentional self-harm (2014-2017); consumer price index and seasonality-adjusted unemployment rate, hourly earnings, home price index, and 3-month and 10-year yield curves from the Federal Reserve Economic Data (2014-2017); weekly daylight hours (2014-2017); Google and YouTube search trends related to suicide (2014-2017); and public posts on suicide on Reddit (2 314 533 posts), Twitter (9 327 472 tweets; 2015-2017), and Tumblr (1 670 378 posts; 2014-2017). Main Outcomes and Measures: Weekly estimates of suicide fatalities in the US were obtained through a machine learning pipeline that integrated the above data sources. Estimates were compared statistically with actual fatalities recorded by the National Vital Statistics System. Results: Combining information from multiple data streams, the machine learning method yielded estimates of weekly suicide deaths with high correlation to actual counts and trends (Pearson correlation, 0.811; P < .001), while estimating annual suicide rates with low error (0.55%). Conclusions and Relevance: The proposed ensemble machine learning framework reduces the error for annual suicide rate estimation to less than one-tenth of that of current forecasting approaches that use only historical information on suicide deaths. These findings establish a novel approach for tracking suicide fatalities in near real time and provide the potential for an effective public health response such as supporting budgetary decisions or deploying interventions.

Interpersonal Violence Victimization Among High School Students - Youth Risk Behavior Survey, United States, 2019.

Adolescent interpersonal violence victimization is an adverse childhood experience and a serious public health problem for youths, their families, and communities. Violence victimization includes dating violence, sexual violence, and bullying. Youth Risk Behavior Survey data for 2019 were used to examine physical and sexual dating violence; sexual violence by anyone; and bullying victimization, whether on school property or electronic, of U.S. high school students by sex, race/ethnicity, and sexual identity. In addition, this report explores frequency of dating violence and frequency of sexual violence among students who reported these forms of victimization and presents composites of dating violence and bullying. Findings reveal that 8.2% of students reported physical dating violence; 8.2% reported sexual dating violence; 10.8% reported sexual violence by anyone, of which 50% of cases were by a perpetrator other than a dating partner; 19.5% reported bullying on school property; and 15.7% reported electronic bullying victimization during the previous 12 months. Approximately one in eight students reported any dating violence, and one in four reported any bullying victimization. Female students; lesbian, gay, and bisexual students; and students not sure of their sexual identity reported the highest prevalence estimates across all five violence victimization types, any and both forms of dating violence, and any bullying victimization. Non-Hispanic white students reported the highest prevalence of bullying victimization. Among students experiencing physical or sexual dating violence or sexual violence by anyone, the most common frequency reported was one time during the previous year; higher frequency was more prevalent among male students compared with female students. These findings provide a contextual understanding of the prevalence of interpersonal violence of U.S. high school students, highlighting those with highest prevalence. Findings can be used by public health professionals to guide prevention efforts with youths in schools and communities.

Rapid Sentinel Surveillance for COVID-19 - Santa Clara County, California, March 2020.

On February 27, 2020, the Santa Clara County Public Health Department (SCCPHD) identified its first case of coronavirus disease 2019 (COVID-19) associated with probable community transmission (i.e., infection among persons without a known exposure by travel or close contact with a patient with confirmed COVID-19). At the time the investigation began, testing guidance recommended focusing on persons with clinical findings of lower respiratory illness and travel to an affected area or an epidemiologic link to a laboratory-confirmed COVID-19 case, or on persons hospitalized for severe respiratory disease and no alternative diagnosis (1). To rapidly understand the extent of COVID-19 in the community, SCCPHD, the California Department of Public Health (CDPH), and CDC began sentinel surveillance in Santa Clara County. During March 5-14, 2020, four urgent care centers in Santa Clara County participated as sentinel sites. For this investigation, county residents evaluated for respiratory symptoms (e.g., fever, cough, or shortness of breath) who had no known risk for COVID-19 were identified at participating urgent care centers. A convenience sample of specimens that tested negative for influenza virus was tested for SARS-CoV-2 RNA. Among 226 patients who met the inclusion criteria, 23% had positive test results for influenza. Among patients who had negative test results for influenza, 79 specimens were tested for SARS-CoV-2, and 11% had evidence of infection. This sentinel surveillance system helped confirm community transmission of SARS-CoV-2 in Santa Clara County. As a result of these data and an increasing number of cases with no known source of transmission, the county initiated a series of community mitigation strategies. Detection of community transmission is critical for informing response activities, including testing criteria, quarantine guidance, investigation protocols, and community mitigation measures (2). Sentinel surveillance in outpatient settings and emergency departments, implemented together with hospital-based surveillance, mortality surveillance, and serologic surveys, can provide a robust approach to monitor the epidemiology of COVID-19.

Syndromic Surveillance of Suicidal Ideation and Self-Directed Violence - United States, January 2017-December 2018.

Suicide is a growing public health problem in the United States, claiming approximately 47,000 lives in 2017 (1). However, deaths from suicide represent only a small part of a larger problem because each year millions of persons experience suicidal ideation and engage in suicidal and nonsuicidal self-directed violence, both risk factors for suicide (2). Emergency departments (EDs) are an important setting for monitoring these events in near real time (3-5). From 2001 to 2016, ED visit rates for nonfatal self-harm increased 42% among persons aged ≥10 years (1). Using data from CDC's National Syndromic Surveillance Program (NSSP), ED visits for suicidal ideation, self-directed violence, or both among persons aged ≥10 years during January 2017-December 2018 were examined by sex, age group, and U.S. region. During the 24-month period, the rate of ED visits for suicidal ideation, self-directed violence, or both increased 25.5% overall, with an average increase of 1.2% per month. Suicide prevention requires comprehensive and multisectoral approaches to addressing risk at personal, relationship, community, and societal levels. ED syndromic surveillance data can provide timely trend information and can support more targeted and prompt public health investigation and response. CDC's Preventing Suicide: A Technical Package of Policy, Programs, and Practices includes tailored suicide prevention strategies for health care settings (6).

Prevalence and Correlates of Receiving Medical Advice to Increase Physical Activity in U.S. Adults: National Health and Nutrition Examination Survey 2013-2016.

INTRODUCTION: National objectives recommend healthcare professionals provide physical activity advice. This study examined health and demographic characteristics associated with receipt of medical advice to increase physical activity among U.S. health care-utilizing adults and differences in associations by age group. METHODS: Analyses included 8,410 health care-utilizing adults aged ≥20 years from the 2013-2016 National Health and Nutrition Examination Surveys (analyzed in 2018). Logistic regression was used to examine associations between receipt of medical advice to increase physical activity in the past year and measured health conditions, reported health behaviors, and demographic characteristics. Models were stratified by age group (20-39, 40-59, and ≥60 years). RESULTS: Physical activity medical advice was received by 42.9% (95% CI=40.8, 44.9) of adults overall. By age group, 32.7% of younger adults, 46.7% of middle-aged adults, and 48.9% of older adults received advice. Among all adults and across all age groups, receipt of advice was higher among adults with chronic health conditions: obesity (63.0%, 95% CI=60.3, 65.7), hypertension (56.5%, 95%=CI 53.8, 59.2), diabetes (69.8%, 95% CI=66.5, 72.8), hypercholesterolemia (55.6%, 95% CI=52.3, 59.0), and low high-density lipoprotein cholesterol (53.8%, 95% CI=50.1, 57.4). Among all adults, those with obesity, hypertension, and diabetes had significantly greater odds of receipt of advice after adjustment. Stronger associations between diabetes and hypercholesterolemia and receiving physical activity advice were observed among younger adults. CONCLUSIONS: Receipt of physical activity medical advice was highest among adults with specific chronic health conditions, and this pattern was stronger among younger adults with diabetes and hypercholesterolemia. However, most health care-utilizing adults did not receive physical activity medical advice.

Network influences on the development and implementation of active transportation policies in six U.S. cities.

Many communities have prioritized policy and built environment changes to promote active transportation (AT). However, limited information exists on the partnerships and processes necessary to develop and implement such policy and environmental changes, particularly among organizations in non-health sectors. Within the transportation sector, metropolitan planning organizations (MPOs) are increasingly recognized as organizations that can support AT policies. This study examined inter-organizational relationships among MPOs and their partners working to advance AT policies in six U.S. cities. In fall 2015, an average of 22 organizations in each city participated in an online survey about partnerships with MPOs and other organizations developing and implementing AT policies. Measures included organizational characteristics and relational attributes including: level of AT policy collaboration, information transmission, resource sharing, and perceived decisional power. Descriptive network analysis and exponential random graph modeling were used to examine organizational attributes and relational predictors associated with inter-organizational collaboration in each network. MPOs served as collaborative intermediaries, connecting other organizations around AT policies, in half of the cities examined. Organizations in each city were more likely to collaborate around AT policies when partners communicated at least quarterly. In half of the cities, the probability of AT policy collaboration was higher when two agencies exchanged resources and when organizations had perceived decisional authority. Network analysis helped identify factors likely to improve partnerships around AT policies. Results may contribute to best practices for collaboration among researchers, practitioners, policymakers, and advocates across diverse sectors seeking to promote population-level physical activity.