The Advisory Committee on Immunization Practices (ACIP) recommends annual influenza and COVID-19 vaccination for all persons aged ≥6 months, including adults aged ≥18 years. ACIP also recommends a single lifetime dose of respiratory syncytial virus (RSV) vaccine for adults aged ≥75 years and for those aged 60-74 years who are at increased risk for severe RSV disease. Data from the National Immunization Survey-Adult COVID Module, a random-digit-dialed cellular telephone survey of U.S. adults aged ≥18 years, are used to monitor influenza, COVID-19, and RSV vaccination coverage. By the week ending November 9, 2024, an estimated 34.7% of adults aged ≥18 years reported having received an influenza vaccine, and 17.9% reported having received a COVID-19 vaccine for the 2024-25 respiratory virus season; 39.7% of adults aged ≥75 years, and 31.6% of adults aged 60-74 years at increased risk for severe RSV, had ever received an RSV vaccine. Coverage varied by jurisdiction and demographic characteristics and was lowest among younger adults and those without health insurance. Although early season estimates indicate that many adults are unprotected from respiratory virus infections, many appeared open to vaccination: overall, approximately 35% and 41% of adults aged ≥18 years reported that they definitely or probably will receive or were unsure about receiving influenza and COVID-19 vaccines, respectively, and 40% of adults aged ≥75 years reported that they definitely or probably will receive or were unsure about receiving RSV vaccine. Health care providers and immunization programs still have time to expand outreach activities and promote vaccination to increase coverage in preparation for the height of the respiratory virus season. Using these data can help health care providers and immunization programs identify undervaccinated populations and understand vaccination patterns to guide planning, implementation, and evaluation of vaccination activities.

INTRODUCTION: The Vaccines for Children (VFC) program was established in 1994 to provide recommended vaccines at no cost to eligible children and help ensure that all U.S. children are protected from life-threatening vaccine-preventable diseases. METHODS: CDC analyzed data from the 2012-2022 National Immunization Survey-Child (NIS-Child) to assess trends in vaccination coverage with ≥1 dose of measles, mumps, and rubella vaccine (MMR), 2-3 doses of rotavirus vaccine, and a combined 7-vaccine series, by VFC program eligibility status, and to examine differences in coverage among VFC-eligible children by sociodemographic characteristics. VFC eligibility was defined as meeting at least one of the following criteria: 1) American Indian or Alaska Native; 2) insured by Medicaid, Indian Health Service (IHS), or uninsured; or 3) ever received at least one vaccination at an IHS-operated center, Tribal health center, or urban Indian health care facility. RESULTS: Overall, approximately 52.2% of U.S. children were VFC eligible. Among VFC-eligible children born during 2011-2020, coverage by age 24 months was stable for ≥1 MMR dose (88.0%-89.9%) and the combined 7-vaccine series (61.4%-65.3%). Rotavirus vaccination coverage by age 8 months was 64.8%-71.1%, increasing by an average of 0.7 percentage points annually. Among all children born in 2020, coverage was 3.8 (≥1 MMR dose), 11.5 (2-3 doses of rotavirus vaccine), and 13.8 (combined 7-vaccine series) percentage points lower among VFC-eligible than among non-VFC-eligible children. CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE: Although the VFC program has played a vital role in increasing and maintaining high levels of childhood vaccination coverage for 30 years, gaps remain. Enhanced efforts must ensure that parents and guardians of VFC-eligible children are aware of, have confidence in, and are able to obtain all recommended vaccines for their children.

During the 2023-24 respiratory virus season, the Advisory Committee on Immunization Practices recommends influenza and COVID-19 vaccines for all persons aged ≥6 months, and respiratory syncytial virus (RSV) vaccine is recommended for persons aged ≥60 years (using shared clinical decision-making), and for pregnant persons. Data from the National Immunization Survey-Adult COVID Module, a random-digit-dialed cellular telephone survey of U.S. adults aged ≥18 years, are used to monitor influenza, COVID-19, and RSV vaccination coverage. By December 9, 2023, an estimated 42.2% and 18.3% of adults aged ≥18 years reported receiving an influenza and updated 2023-2024 COVID-19 vaccine, respectively; 17.0% of adults aged ≥60 years had received RSV vaccine. Coverage varied by demographic characteristics. Overall, approximately 27% and 41% of adults aged ≥18 years and 53% of adults aged ≥60 years reported that they definitely or probably will be vaccinated or were unsure whether they would be vaccinated against influenza, COVID-19, and RSV, respectively. Strong provider recommendations for and offers of vaccination could increase influenza, COVID-19, and RSV vaccination coverage. Immunization programs and vaccination partners are encouraged to use these data to understand vaccination patterns and attitudes toward vaccination in their jurisdictions to guide planning, implementation, strengthening, and evaluation of vaccination activities.

BACKGROUND: Studies evaluating the association between prenatal ultrasounds and autism spectrum disorder (ASD) have largely produced negative results. Concern remains due to the rising identification of children with ASD and ultrasound use. OBJECTIVE: To evaluate the association between prenatal ultrasound use and ASD. METHODS: We used data from the Study to Explore Early Development, a multisite case-control study of preschool-aged children with ASD implemented during 2007-2012. We recruited cases from children receiving developmental disability services and randomly selected population controls from birth records. ASD case status was based on in-person standardised assessments. We stratified analyses by pre-existing maternal medical conditions and pregnancy complications associated with increased ultrasound use (ultrasound indications) and used logistic regression to model case status by increasing ultrasound counts. For pregnancies with medical record data on ultrasound timing, we conducted supplementary tests to model associations by trimester of exposure. RESULTS: Among 1524 singleton pregnancies, ultrasound indications were more common for ASD cases than controls; respectively, for each group, no indications were reported for 45.1% and 54.2% of pregnancies, while ≥2 indications were reported for 26.1% and 18.4% of pregnancies. The percentage of pregnancies with multiple ultrasounds varied by case status and the presence of ultrasound indications. However, stratified regression models showed no association between increasing ultrasound counts and case status, either for pregnancies without (aOR 1.01, 95% CI 0.92, 1.11) or with ultrasound indications (aOR 1.01, 95% CI 0.95, 1.08). Trimester-specific analyses using medical record data showed no association in any individual trimester. CONCLUSIONS: We found no evidence that prenatal ultrasound use increases ASD risk. Study strengths included gold-standard assessments for ASD case classification, comparison of cases with controls, and a stratified sample to account for conditions associated both with increased prenatal ultrasound use and ASD.

This article describes a significant decline in emergency department visits for acute life-threatening conditions during the COVID-19 pandemic, suggesting that patients may be delaying or avoiding care or unable to access care during the pandemic.

PROBLEM ADDRESSED: To better understand the factors associated with family cancer history (FCH) information and cancer information seeking, we model the process an individual undergoes when assessing whether to gather FCH and seek cancer information and compare models by sociodemographics and family history of cancer. We used cross-sectional data from the Health Information National Trends Survey (HINTS 5, Cycle 2) and variables (e.g., emotion and self-efficacy) associated with the Theory of Motivated Information Management to assess the process of FCH gathering and information seeking. We completed path analysis to assess the process of FCH gathering and stratified path models. RESULTS: Those who felt they could lower their chances of getting cancer (emotion) were more confident in their ability to complete FCH on a medical form (self-efficacy; B = 0.11, p < .0001) and more likely to have discussed FCH with family members (B = 0.07, p < .0001). Those who were more confident in their ability to complete a summary of their family history on a medical form were more likely to have discussed FCH with family members (B = 0.34, p < .0001) and seek other health information (B = 0.24, p < .0001). Stratified models showed differences in this process by age, race/ethnicity, and family history of cancer. IMPLICATIONS FOR PUBLIC HEALTH RESEARCH AND PRACTICE: Tailoring outreach and education strategies to address differences in perceived ability to lower chances of getting cancer (emotion) and confidence in the ability to complete FCH (self-efficacy) could help encourage less engaged individuals to learn about their FCH and gather cancer information.

Cancer survivors (persons who have received a diagnosis of cancer, from the time of diagnosis throughout their lifespan)* have increased risk for severe COVID-19 illness and mortality (1). This report describes characteristics of deaths reported to CDC's National Vital Statistics System (NVSS), for which cancer was listed as the underlying or a contributing cause (cancer deaths) during January 1, 2018-July 2, 2022. The underlying causes of death, including cancer and COVID-19, were examined by week, age, sex, race and ethnicity, and cancer type. Among an average of approximately 13,000 weekly cancer deaths, the percentage with cancer as the underlying cause was 90% in 2018 and 2019, 88% in 2020, and 87% in 2021. The percentage of cancer deaths with COVID-19 as the underlying cause differed by time (2.0% overall in 2020 and 2.4% in 2021, ranging from 0.2% to 7.2% by week), with higher percentages during peaks in the COVID-19 pandemic. The percentage of cancer deaths with COVID-19 as the underlying cause also differed by the characteristics examined, with higher percentages observed in 2021 among persons aged 65 years (2.4% among persons aged 65-74 years, 2.6% among persons aged 75-84 years, and 2.4% among persons aged 85 years); males (2.6%); persons categorized as non-Hispanic American Indian or Alaska Native (AI/AN) (3.4%), Hispanic or Latino (Hispanic) (3.2%), or non-Hispanic Black or African American (Black) (2.5%); and persons with hematologic cancers, including leukemia (7.4%), lymphoma (7.3%), and myeloma (5.8%). This report found differences by age, sex, race and ethnicity, and cancer type in the percentage of cancer deaths with COVID-19 as the underlying cause. These results might guide multicomponent COVID-19 prevention interventions and ongoing, cross-cutting efforts to reduce health disparities and address structural and social determinants of health among cancer survivors, which might help protect those at disproportionate and increased risk for death from COVID-19.

In 2018, colorectal cancer (CRC) was the second most diagnosed cancer and the second leading cause of cancer death among cancers that affect both men and women (3). Screening for CRC can lead to fewer cases of cancer through the removal of polyps before they become cancer, the detection of cancers at their earliest stages, and the prevention of cancer deaths (4). | | Studies from the UK of screening by sigmoidoscopy and from the US of screening by colonoscopy showed that even 1-time or infrequent screening has long-term benefits (5,6). Another study showed that 83% of people who were not up to date with CRC screening had never been screened and outlined multiple barriers to getting tested (7). | | We measured the change in prevalence of adults who reported no CRC screening from 2012 to 2020. We also used data on the use of CRC screening tests in 2020 to update a previous report on up-to-date screening (8).

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.

Approximately 15.5 million cancer survivors were alive in the United States in 2016 with expected growth to 26.1 million by 2040 (1). Cancer survivors are living longer because of advances in early detection and treatment, but face psychosocial, cognitive, financial, and physical challenges (1,2). Physical challenges include cardiovascular complications, partly because cancer and cardiovascular disease (CVD) share some cumulative risk factors including tobacco use, physical inactivity, obesity, poor diet, hypertension, diabetes, and dyslipidemia (3). In addition, many cancer treatments damage the heart, and some cancer types increase risk for developing CVD (4). The recognition and management of heart disease in cancer survivors has given rise to the discipline of cardio-oncology, which focuses on the cardiovascular health of this population (5). CVD risk has been previously estimated using prediction models, and studies suggest that physician-patient communication using predicted heart age rather than predicted 10-year risk has led to a more accurate perception of excess heart age, encouraged actions to adopt a healthy lifestyle, and improved modifiable CVD risk factors (6,7). Using the nonlaboratory-based Framingham Risk Score (FRS) to estimate 10-year risk for developing CVD, predicted heart age is estimated from the 10-year risk of CVD (predicted by age, sex, diabetes status, smoking status, systolic blood pressure, hypertension treatment status, and body mass index); it is the age of an otherwise healthy person with the same predicted risk, with all other risk factors included in the prediction model at the normal level (systolic blood pressure of 125 mmHg, no hypertension treatment, body mass index of 22.5, nonsmoker, and nondiabetic) (6). Using data from the Behavioral Risk Factor Surveillance System (BRFSS), this study estimates predicted heart age, excess heart age (difference between predicted heart age and actual age), and racial/ethnic and sociodemographic disparities in predicted heart age among U.S. adult cancer survivors and noncancer participants aged 30-74 years using previously published methods (7). A total of 22,759 men and 46,294 women were cancer survivors with a mean age of 48.7 and 48.3 years, respectively. The predicted heart age and excess heart age among cancer survivors were 57.2 and 8.5 years, respectively, for men and 54.8 and 6.5 years, respectively, for women, and varied by age, race/ethnicity, education and income. The use of predicted heart age by physicians to encourage cancer survivors to improve modifiable risk factors and make heart healthy choices, such as tobacco cessation, regular physical activity, and a healthy diet to maintain a healthy weight, can engage survivors in informed cancer care planning after diagnosis.

The purpose of this study is to present a variety of measures that quantify equity in cancer outcomes, demonstrate how the measures perform in various cancer types, and identify counties, or Bright Spots, that meet the criteria of those measures. Using county-level age adjusted death rates for 2007-2016 from the National Center for Health Statistics, we determined counties that had both equitable and optimal outcomes for the black and white death rates across five cancer types, lung/bronchus, prostate, breast, colorectal, and liver cancers. The number of counties that met the criteria ranged from 0 to 442 depending on cancer type and measure used, and prostate and male liver cancer consistently had the lowest number of Bright Spots with a maximum of 3 counties meeting the most lenient criteria. This study presents several ways to examine equity, using rate ratios and standard error measures, in cancer mortality outcomes. It highlights areas with positive progress towards equity and areas potential need for equity-focused cancer control planning. Examining local areas of positive deviance can inform cancer control programming and planning around health equity.

Among U.S. men, prostate cancer is the second leading cause of cancer-related death (1). Past studies documented decreasing incidence of prostate cancer overall since 2000 but increasing incidence of distant stage prostate cancer (i.e., signifying spread to parts of the body remote from the primary tumor) starting in 2010 (2,3). Past studies described disparities in prostate cancer survival by stage, age, and race/ethnicity using data covering ≤80% of the U.S. population (4,5). To provide recent data on incidence and survival of prostate cancer in the United States, CDC analyzed data from population-based cancer registries that contribute to U.S. Cancer Statistics (USCS).* Among 3.1 million new cases of prostate cancer recorded during 2003-2017, localized, regional, distant, and unknown stage prostate cancer accounted for 77%, 11%, 5%, and 7% of cases, respectively, but the incidence of distant stage prostate cancer significantly increased during 2010-2017. During 2001-2016, 10-year relative survival for localized stage prostate cancer was 100%. Overall, 5-year survival for distant stage prostate cancer improved from 28.7% during 2001-2005 to 32.3% during 2011-2016; for the period 2001-2016, 5-year survival was highest among Asian/Pacific Islanders (API) (42.0%), followed by Hispanics (37.2%), American Indian/Alaska Natives (AI/AN) (32.2%), Black men (31.6%), and White men (29.1%). Understanding incidence and survival differences by stage, race/ethnicity, and age can guide public health planning related to screening, treatment, and survivor care. Future research into differences by stage, race/ethnicity, and age could inform interventions aimed at improving disparities in outcomes.

BACKGROUND: Although pediatric cancer mortality and survival have improved in the United States over the past 40 years, differences exist by age, race/ethnicity, cancer site, and economic status. To assess progress, this study examined recent mortality and survival data for individuals younger than 20 years. METHODS: Age-adjusted death rates were calculated with the National Vital Statistics System for 2002-2016. Annual percent changes (APCs) and average annual percent changes (AAPCs) were calculated with joinpoint regression. Five-year relative survival was calculated on the basis of National Program of Cancer Registries data for 2001-2015. Death rates and survival were estimated overall and by sex, 5-year age group, race/ethnicity, cancer type, and county-based economic markers. RESULTS: Death rates decreased during 2002-2016 (AAPC, -1.5), with steeper declines during 2002-2009 (APC, -2.6), and then plateaued (APC, -0.4). Leukemia and brain cancer were the most common causes of death from pediatric cancer, and brain cancer surpassed leukemia in 2011. Death rates decreased for leukemia and lymphoma but were unchanged for brain, bone, and soft-tissue cancers. From 2001-2007 to 2008-2015, survival improved from 82.0% to 85.1%. Survival was highest in both periods among females, those aged 15 to 19 years, non-Hispanic Whites, and those in counties in the top 25% by economic status. Survival improved for leukemias, lymphomas, and brain cancers but plateaued for bone and soft-tissue cancers. CONCLUSIONS: Although overall death rates have decreased and survival has increased, differences persist by sex, age, race/ethnicity, cancer type, and economic status. Improvements in pediatric cancer outcomes may depend on improving therapies, access to care, and supportive and long-term care.

Risk for severe coronavirus disease 2019 (COVID-19)-associated illness (illness requiring hospitalization, intensive care unit [ICU] admission, mechanical ventilation, or resulting in death) increases with increasing age as well as presence of underlying medical conditions that have shown strong and consistent evidence, including chronic obstructive pulmonary disease, cardiovascular disease, diabetes, chronic kidney disease, and obesity (1-4). Identifying and describing the prevalence of these conditions at the local level can help guide decision-making and efforts to prevent or control severe COVID-19-associated illness. Below state-level estimates, there is a lack of standardized publicly available data on underlying medical conditions that increase the risk for severe COVID-19-associated illness. A small area estimation approach was used to estimate county-level prevalence of selected conditions associated with severe COVID-19 disease among U.S. adults aged ≥18 years (5,6) using self-reported data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS) and U.S. Census population data. The median prevalence of any underlying medical condition in residents among 3,142 counties in all 50 states and the District of Columbia (DC) was 47.2% (range = 22.0%-66.2%); counties with the highest prevalence were concentrated in the Southeast and Appalachian region. Whereas the estimated number of persons with any underlying medical condition was higher in population-dense metropolitan areas, overall prevalence was higher in rural nonmetropolitan areas. These data can provide important local-level information about the estimated number and proportion of persons with certain underlying medical conditions to help guide decisions regarding additional resource investment, and mitigation and prevention measures to slow the spread of COVID-19.

As of July 5, 2020, approximately 2.8 million coronavirus disease 2019 (COVID-19) cases and 130,000 COVID-19-associated deaths had been reported in the United States (1). Populations historically affected by health disparities, including certain racial and ethnic minority populations, have been disproportionally affected by and hospitalized with COVID-19 (2-4). Data also suggest a higher prevalence of infection with SARS-CoV-2, the virus that causes COVID-19, among persons experiencing homelessness (5). Safety-net hospitals,(dagger) such as Boston Medical Center (BMC), which provide health care to persons regardless of their insurance status or ability to pay, treat higher proportions of these populations and might experience challenges during the COVID-19 pandemic. This report describes the characteristics and clinical outcomes of adult patients with laboratory-confirmed COVID-19 treated at BMC during March 1-May 18, 2020. During this time, 2,729 patients with SARS-CoV-2 infection were treated at BMC and categorized into one of the following mutually exclusive clinical severity designations: exclusive outpatient management (1,543; 56.5%), non-intensive care unit (ICU) hospitalization (900; 33.0%), ICU hospitalization without invasive mechanical ventilation (69; 2.5%), ICU hospitalization with mechanical ventilation (119; 4.4%), and death (98; 3.6%). The cohort comprised 44.6% non-Hispanic black (black) patients and 30.1% Hispanic or Latino (Hispanic) patients. Persons experiencing homelessness accounted for 16.4% of patients. Most patients who died were aged >/=60 years (81.6%). Clinical severity differed by age, race/ethnicity, underlying medical conditions, and homelessness. A higher proportion of Hispanic patients were hospitalized (46.5%) than were black (39.5%) or non-Hispanic white (white) (34.4%) patients, a finding most pronounced among those aged <60 years. A higher proportion of non-ICU inpatients were experiencing homelessness (24.3%), compared with homeless patients who were admitted to the ICU without mechanical ventilation (15.9%), with mechanical ventilation (15.1%), or who died (15.3%). Patient characteristics associated with illness and clinical severity, such as age, race/ethnicity, homelessness, and underlying medical conditions can inform tailored strategies that might improve outcomes and mitigate strain on the health care system from COVID-19.

Previous studies investigating the association between dysmorphology and cognitive, behavioral, and developmental outcomes among individuals with autism spectrum disorder (ASD) have been limited by the binary classification of dysmorphology and lack of comparison groups. We assessed the association using a continuous measure of dysmorphology severity (DS) in preschool children aged 2-5 years (322 with ASD and intellectual disability [ID], 188 with ASD without ID, and 371 without ASD from the general population [POP]). In bivariate analyses, an inverse association between DS and expressive language, receptive language, fine motor, and visual reception skills was observed in children with ASD and ID. An inverse association of DS with fine motor and visual reception skills, but not expressive language and receptive language, was found in children with ASD without ID. No associations were observed in POP children. These results persisted after exclusion of children with known genetic syndromes or major morphologic anomalies. Quantile regression models showed that the inverse relationships remained significant after adjustment for sex, race/ethnicity, maternal education, family income, study site, and preterm birth. DS was not associated with autistic traits or autism symptom severity, behaviors, or regression among children with ASD with or without ID. Thus, DS was associated with a global impairment of cognitive functioning in children with ASD and ID, but only with fine motor and visual reception deficits in children with ASD without ID. A better understanding is needed for mechanisms that explain the association between DS and cognitive impairment in children with different disorders. LAY SUMMARY: We examined whether having more dysmorphic features (DFs) was related to developmental problems among children with autism spectrum disorder (ASD) with or without intellectual disability (ID), and children without ASD from the general population (POP). Children with ASD and ID had more language, movement, and learning issues as the number of DFs increased. Children with ASD without ID had more movement and learning issues as the number of DFs increased. These relationships were not observed in the POP group. Implications are discussed.

On March 13, 2020, the United States declared a national emergency in response to the coronavirus disease 2019 (COVID-19) pandemic. Subsequently, states enacted stay-at-home orders to slow the spread of SARS-CoV-2, the virus that causes COVID-19, and reduce the burden on the U.S. health care system. CDC* and the Centers for Medicare & Medicaid Services (CMS)(dagger) recommended that health care systems prioritize urgent visits and delay elective care to mitigate the spread of COVID-19 in health care settings. By May 2020, national syndromic surveillance data found that emergency department (ED) visits had declined 42% during the early months of the pandemic (1). This report describes trends in ED visits for three acute life-threatening health conditions (myocardial infarction [MI, also known as heart attack], stroke, and hyperglycemic crisis), immediately before and after declaration of the COVID-19 pandemic as a national emergency. These conditions represent acute events that always necessitate immediate emergency care, even during a public health emergency such as the COVID-19 pandemic. In the 10 weeks following the emergency declaration (March 15-May 23, 2020), ED visits declined 23% for MI, 20% for stroke, and 10% for hyperglycemic crisis, compared with the preceding 10-week period (January 5-March 14, 2020). EDs play a critical role in diagnosing and treating life-threatening conditions that might result in serious disability or death. Persons experiencing signs or symptoms of serious illness, such as severe chest pain, sudden or partial loss of motor function, altered mental state, signs of extreme hyperglycemia, or other life-threatening issues, should seek immediate emergency care, regardless of the pandemic. Clear, frequent, highly visible communication from public health and health care professionals is needed to reinforce the importance of timely care for medical emergencies and to assure the public that EDs are implementing infection prevention and control guidelines that help ensure the safety of their patients and health care personnel.

Ocular melanoma is a rare form of melanoma (less than 5% of melanoma cases) arising from melanocytes of the uveal tract, conjunctiva, or orbit; however, up to 50% of patients will develop metastatic disease [1, 2]. Causes of ocular melanoma are unclear, but some possible risk factors include type B ultraviolet radiation, light eye color, ocular melanocytosis, and ubiquitin carboxyl-terminal hydrolase BAP1 mutations [1]. A previously published study using National Cancer Institute’s Surveillance, Epidemiology, and End Results Program data examined 4999 cases and found a statistically significant increase of 0.5% in uveal melanoma (the most common type of ocular melanoma) incidence rates among whites from 1973 to 2013 [3]. The purpose of this study is to provide an update and overview of the incidence of ocular melanoma for the entire United States (US).

In the United States, approximately 1.4 million persons access emergency shelter or transitional housing each year (1). These settings can pose risks for communicable disease spread. In late March and early April 2020, public health teams responded to clusters (two or more cases in the preceding 2 weeks) of coronavirus disease 2019 (COVID-19) in residents and staff members from five homeless shelters in Boston, Massachusetts (one shelter); San Francisco, California (one); and Seattle, Washington (three). The investigations were performed in coordination with academic partners, health care providers, and homeless service providers. Investigations included reverse transcription-polymerase chain reaction testing at commercial and public health laboratories for SARS-CoV-2, the virus that causes COVID-19, over approximately 1-2 weeks for residents and staff members at the five shelters. During the same period, the team in Seattle, Washington, also tested residents and staff members at 12 shelters where a single case in each had been identified. In Atlanta, Georgia, a team proactively tested residents and staff members at two shelters with no known COVID-19 cases in the preceding 2 weeks. In each city, the objective was to test all shelter residents and staff members at each assessed facility, irrespective of symptoms. Persons who tested positive were transported to hospitals or predesignated community isolation areas.

BACKGROUND: Colorectal cancer (CRC) is the second leading cause of cancer death in the United States of cancers that affect both men and women. Despite strong evidence that screening for CRC reduces incidence and mortality, CRC screening prevalence is below the national target. This report describes current CRC screening prevalence by age, various demographic factors, and state. METHODS: Data from the 2018 Behavioral Risk Factor Surveillance System survey were analyzed to estimate the percentages of adults aged 50-75 years who reported CRC screening consistent with the United States Preventive Services Task Force recommendation. RESULTS: In 2018, 68.8% of adults were up to date with CRC screening. The percentage up to date was 79.2% among respondents aged 65-75 years and 63.3% among those aged 50-64 years. CRC screening prevalence was lowest among persons aged 50-54 years (50.0%) and increased with age. Among respondents aged 50-64 years, CRC screening prevalence was lowest among persons without health insurance (32.6%) and highest among those with reported annual household income of >/=$75,000 (70.8%). Among respondents aged 65-75 years, CRC screening prevalence was lowest among those without a regular health care provider (45.6%), and highest among those with reported annual household income >/=$75,000 (87.1%). Among states, CRC screening prevalence was highest in Massachusetts (76.5%) and lowest in Wyoming (57.8%). DISCUSSION: CRC screening prevalence is lower among adults aged 50-64 years, although most reported having a health care provider and health insurance. Concerted efforts are needed to inform persons aged <50 years about the benefit of screening so that screening can start at age 50 years.

Twenty percent of the US population, or about 60 million persons, live in rural areas.1 Rural and urban counties differ in their demographic, environmental, economic, and social characteristics, which influences health and the prevalence of disease risk factors. The rates of cigarette smoking, hypertension, obesity, and physical inactivity during leisure time are higher in rural areas than in urban areas.2 About 30% of persons living in rural counties live in poverty, whereas 19% of persons living in large central and large fringe metropolitan counties and 15% of persons living in medium and small metropolitan counties live in poverty.3 The availability of preventive services and health care access also differ in rural and urban areas. Residents of rural counties are more likely to report lower levels of health care access and lower-quality care than residents of urban counties.2 Urban areas generally have a higher density and diversity of health care providers than rural areas.4,5

The objectives of our study were to (a) report how many children met an autism spectrum disorder (ASD) surveillance definition but had no clinical diagnosis of ASD in health or education records and (b) evaluate differences in demographic, individual, and service factors between children with and without a documented ASD diagnosis. ASD surveillance was conducted in selected areas of Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin. Children were defined as having ASD if sufficient social and behavioral deficits and/or an ASD diagnosis were noted in health and/or education records. Among 4,498 children, 1,135 (25%) had ASD indicators without having an ASD diagnosis. Of those 1,135 children without a documented ASD diagnosis, 628 (55%) were not known to receive ASD services in public school. Factors associated with not having a clinical diagnosis of ASD were non-White race, no intellectual disability, older age at first developmental concern, older age at first developmental evaluation, special education eligibility other than ASD, and need for fewer supports. These results highlight the importance of reducing disparities in the diagnosis of children with ASD characteristics so that appropriate interventions can be promoted across communities. Autism Res 2019, 00: 1-10. (c) 2019 International Society for Autism Research,Wiley Periodicals, Inc. LAY SUMMARY: Children who did not have a clinical diagnosis of autism spectrum disorder (ASD) documented in health or education records were more likely to be non-White and have fewer developmental problems than children with a clinical diagnosis of ASD. They were brought to the attention of healthcare providers at older ages and needed fewer supports than children with a clinical diagnosis of ASD. All children with ASD symptoms who meet diagnostic criteria should be given a clinical diagnosis so they can receive treatment specific to their needs.

PROBLEM/CONDITION: A 2017 report quantified the higher percentage of potentially excess (or preventable) deaths in nonmetropolitan areas (often referred to as rural areas) compared with metropolitan areas. In that report, CDC compared national, regional, and state estimates of potentially excess deaths among the five leading causes of death in nonmetropolitan and metropolitan counties for 2010 and 2014. This report enhances the geographic detail by using the six levels of the 2013 National Center for Health Statistics (NCHS) urban-rural classification scheme for counties and extending estimates of potentially excess deaths by annual percent change (APC) and for additional years (2010-2017). Trends were tested both with linear and quadratic terms. PERIOD COVERED: 2010-2017. DESCRIPTION OF SYSTEM: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate potentially excess deaths from the five leading causes of death among persons aged <80 years. CDC's NCHS urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Potentially excess deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Potentially excess deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and District of Columbia. RESULTS: The number of potentially excess deaths among persons aged <80 years in the United States increased during 2010-2017 for unintentional injuries (APC: 11.2%), decreased for cancer (APC: -9.1%), and remained stable for heart disease (APC: 1.1%), chronic lower respiratory disease (CLRD) (APC: 1.7%), and stroke (APC: 0.3). Across the United States, percentages of potentially excess deaths from the five leading causes were higher in nonmetropolitan counties in all years during 2010-2017. When assessed by the six urban-rural county classifications, percentages of potentially excess deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan) for the study period. Potentially excess deaths from heart disease increased most in micropolitan counties (APC: 2.5%) and decreased most in large fringe metropolitan counties (APC: -1.1%). Potentially excess deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan (APC: -16.1%) and large fringe metropolitan (APC: -15.1%) counties. In all county categories, potentially excess deaths from the five leading causes increased, with the largest increases occurring in large central metropolitan (APC: 18.3%), large fringe metropolitan (APC: 17.1%), and medium metropolitan (APC: 11.1%) counties. Potentially excess deaths from CLRD decreased most in large central metropolitan counties (APC: -5.6%) and increased most in micropolitan (APC: 3.7%) and noncore (APC: 3.6%) counties. In all county categories, potentially excess deaths from stroke exhibited a quadratic trend (i.e., decreased then increased), except in micropolitan counties, where no change occurred. Percentages of potentially excess deaths also differed among and within public health regions and across states by urban-rural county classification during 2010-2017. INTERPRETATION: Nonmetropolitan counties had higher percentages of potentially excess deaths from the five leading causes than metropolitan counties during 2010-2017 nationwide, across public health regions, and in the majority of states. The gap between the most rural and most urban counties for potentially excess deaths increased during 2010-2017 for three causes of death (cancer, heart disease, and CLRD), decreased for unintentional injury, and remained relatively stable for stroke. Urban and suburban counties (large central metropolitan and large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in potentially excess deaths from unintentional injury during 2010-2017, leading to a narrower gap between the already high (approximately 55%) percentage of excess deaths in noncore and micropolitan counties. PUBLIC HEALTH ACTION: Routine tracking of potentially excess deaths by urban-rural county classification might help public health departments and decision-makers identify and monitor public health problems and focus interventions to reduce potentially excess deaths in these areas.

BACKGROUND: Developmental disabilities are present in a significant proportion of US children. Surveillance of developmental disabilities is crucial for monitoring population trends, guiding research into risk factors, and informing resource allocation. OBJECTIVE/HYPOTHESIS: We examined overall prevalence, prevalence by demographic characteristics, and trends over time for cerebral palsy (CP), intellectual disability (ID), moderate to severe hearing loss (MSHL), and blindness. METHODS: Data from the 2009-2016 National Health Interview Survey (NHIS) were analyzed for children 3-17 years of age. Question wording was consistent over time except for ID, which changed in 2011 to replace the term "mental retardation." Demographic differences and linear trends (over three time periods) were assessed by Chi-square tests and Wald-F tests. RESULTS: Prevalence estimates per 1000 children ages 3-17 years for CP, ID, MSHL, and blindness were 3.2 (95% CI: 2.7, 3.7), 11.1 (95% CI: 10.2, 12.1), 6.4 (95% CI: 5.6, 7.2), and 1.6 (95% CI: 1.3, 2.0), respectively. Disability prevalence was higher for children with low birthweight and from families of lower parental education, income </=200% of federal poverty level, and public insurance. Older children had higher ID prevalence; boys had significantly higher CP and ID prevalences. Only ID demonstrated a significantly increased trend over time (p=0.0002). CONCLUSIONS: We provide nationally representative prevalence estimates for four developmental disabilities; recent estimates are comparable to those from records-based studies. Prevalences were stable except for ID, which increased after 2010, coincident with the questionnaire change. A substantial number of US children continue to have these disabilities and service needs.

Uterine cancer is one of the few cancers with increasing incidence and mortality in the United States, reflecting, in part, increases in the prevalence of overweight and obesity since the 1980s (1). It is the fourth most common cancer diagnosed and the seventh most common cause of cancer death among U.S. women (1). To assess recent trends in uterine cancer incidence and mortality by race and ethnicity, CDC analyzed incidence data from CDC's National Program of Cancer Registries (NPCR) and the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program and mortality data from the National Vital Statistics System (2). Most recent data available are through 2015 for incidence and through 2016 for mortality. Uterine cancer incidence rates increased 0.7% per year during 1999-2015, and death rates increased 1.1% per year during 1999-2016, with smaller increases observed among non-Hispanic white (white) women than among women in other racial/ethnic groups. In 2015, a total of 53,911 new uterine cancer cases, corresponding to 27 cases per 100,000 women, were reported in the United States, and 10,733 uterine cancer deaths (five deaths per 100,000 women) were reported in 2016. Uterine cancer incidence was higher among non-Hispanic black (black) and white women (27 cases per 100,000) than among other racial/ethnic groups (19-23 per 100,000). Uterine cancer deaths among black women (nine per 100,000) were higher than those among other racial/ethnic groups (four to five per 100,000). Public health efforts to help women achieve and maintain a healthy weight and obtain sufficient physical activity can reduce the risk for developing cancer of the endometrium (the lining of the uterus), the most common uterine cancer. Abnormal vaginal bleeding, including bleeding between periods or after sex or any unexpected bleeding after menopause, is an important symptom of uterine cancer (3). Through programs such as CDC's Inside Knowledge* campaign, promoting awareness among women and health care providers of the need for timely evaluation of abnormal vaginal bleeding can increase the chance that uterine cancer is detected early and treated appropriately.

OBJECTIVE: The study's purpose was to investigate readiness for an increase in the congenital Zika infection (CZI) by describing the distribution of pediatric subspecialists needed for the care of children with CZI. METHODS: We applied county-level subspecialist counts to US maps, overlaying the geocoded locations of children's hospitals to assess the correlation of hospital and subspecialist locations. We calculated travel distance from census tract centroids to the nearest in-state children's hospital by state (with/without > 100 reported adult Zika virus cases) and by regions corresponding to the likely local Zika virus transmission area and to the full range of the mosquito vector. Travel distance percentiles reflect the population of children 100 miles. CONCLUSION: The travel distance to pediatric subspecialty care varies widely by state and is likely to be an access barrier in some areas, particularly states bordering the Gulf of Mexico, which may have increasing numbers of CZI cases. (Disaster Med Public Health Preparedness. 2018 page 1 of 11).

Background: Participation in epidemiologic studies has declined, raising concerns about selection bias. While estimates derived from epidemiologic studies have been shown to be robust under a wide range of scenarios, additional empiric study is needed. The Georgia Study to Explore Early Development (GA SEED), a population-based case-control study of risk factors for autism spectrum disorder (ASD), provided an opportunity to explore factors associated with non-participation and potential impacts of non-participation on association studies. Methods: GA SEED recruited preschool-aged children residing in metropolitan-Atlanta during 2007-2012. Children with ASD were identified from multiple schools and healthcare providers serving children with disabilities; children from the general population (POP) were randomly sampled from birth records. Recruitment was via mailed invitation letter with follow-up phone calls. Eligibility criteria included birth and current residence in study area and an English-speaking caregiver. Many children identified for potential inclusion could not be contacted. We used data from birth certificates to examine demographic and perinatal factors associated with participation in GA SEED and completion of the data collection protocol. We also compared ASD-risk factor associations for the final sample of children who completed the study with the initial sample of all likely ASD and POP children invited to potentially participate in the study, had they been eligible. Finally, we derived post-stratification sampling weights for participants who completed the study and compared weighted and unweighted associations between ASD and two factors collected via post-enrollment maternal interview: infertility and reproductive stoppage. Results: Maternal age and education were independently associated with participation in the POP group. Maternal education was independently associated with participation in the ASD group. Numerous other demographic and perinatal factors were not associated with participation. Moreover, unadjusted and adjusted odds ratios for associations between ASD and several demographic and perinatal factors were similar between the final sample of study completers and the total invited sample. Odds ratios for associations between ASD and infertility and reproductive stoppage were also similar in unweighted and weighted analyses of the study completion sample. Conclusions: These findings suggest that effect estimates from SEED risk factor analyses, particularly those of non-demographic factors, are likely robust.

Opioid use during pregnancy is associated with suboptimal pregnancy outcomes. Little is known about child neurodevelopmental outcomes. We examined associations between maternal opioid prescriptions preconception to delivery (peri-pregnancy) and child's risk of ASD, developmental delay/disorder (DD) with no ASD features, or ASD/DD with autism features in the Study to Explore Early Development, a case-control study of neurodevelopment. Preconception opioid prescription was associated with 2.43 times the odds of ASD [95% confidence interval (CI) 0.99, 6.02] and 2.64 times the odds of ASD/DD with autism features (95% CI 1.10, 6.31) compared to mothers without prescriptions. Odds for ASD and ASD/DD were non-significantly elevated for first trimester prescriptions. Work exploring mechanisms and timing between peri-pregnancy opioid use and child neurodevelopment is needed.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2014. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years whose parents or guardians reside within 11 ADDM sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). ADDM surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by professional service providers in the community. Staff completing record review and abstraction receive extensive training and supervision and are evaluated according to strict reliability standards to certify effective initial training, identify ongoing training needs, and ensure adherence to the prescribed methodology. Record review and abstraction occurs in a variety of data sources ranging from general pediatric health clinics to specialized programs serving children with developmental disabilities. In addition, most of the ADDM sites also review records for children who have received special education services in public schools. In the second phase of the study, all abstracted information is reviewed systematically by experienced clinicians to determine ASD case status. A child is considered to meet the surveillance case definition for ASD if he or she displays behaviors, as described on one or more comprehensive evaluations completed by community-based professional providers, consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for autistic disorder; pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism); or Asperger disorder. This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD. In 2013, the American Psychiatric Association published the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which made considerable changes to ASD diagnostic criteria. The change in ASD diagnostic criteria might influence ADDM ASD prevalence estimates; therefore, most (85%) of the records used to determine prevalence estimates based on DSM-IV-TR criteria underwent additional review under a newly operationalized surveillance case definition for ASD consistent with the DSM-5 diagnostic criteria. Children meeting this new surveillance case definition could qualify on the basis of one or both of the following criteria, as documented in abstracted comprehensive evaluations: 1) behaviors consistent with the DSM-5 diagnostic features; and/or 2) an ASD diagnosis, whether based on DSM-IV-TR or DSM-5 diagnostic criteria. Stratified comparisons of the number of children meeting either of these two case definitions also are reported. RESULTS: For 2014, the overall prevalence of ASD among the 11 ADDM sites was 16.8 per 1,000 (one in 59) children aged 8 years. Overall ASD prevalence estimates varied among sites, from 13.1-29.3 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and race/ethnicity. Males were four times more likely than females to be identified with ASD. Prevalence estimates were higher for non-Hispanic white (henceforth, white) children compared with non-Hispanic black (henceforth, black) children, and both groups were more likely to be identified with ASD compared with Hispanic children. Among the nine sites with sufficient data on intellectual ability, 31% of children with ASD were classified in the range of intellectual disability (intelligence quotient [IQ] <70), 25% were in the borderline range (IQ 71-85), and 44% had IQ scores in the average to above average range (i.e., IQ >85). The distribution of intellectual ability varied by sex and race/ethnicity. Although mention of developmental concerns by age 36 months was documented for 85% of children with ASD, only 42% had a comprehensive evaluation on record by age 36 months. The median age of earliest known ASD diagnosis was 52 months and did not differ significantly by sex or race/ethnicity. For the targeted comparison of DSM-IV-TR and DSM-5 results, the number and characteristics of children meeting the newly operationalized DSM-5 case definition for ASD were similar to those meeting the DSM-IV-TR case definition, with DSM-IV-TR case counts exceeding DSM-5 counts by less than 5% and approximately 86% overlap between the two case definitions (kappa = 0.85). INTERPRETATION: Findings from the ADDM Network, on the basis of 2014 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD among children aged 8 years in multiple communities in the United States. The overall ASD prevalence estimate of 16.8 per 1,000 children aged 8 years in 2014 is higher than previously reported estimates from the ADDM Network. Because the ADDM sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States. Consistent with reports from previous ADDM surveillance years, findings from 2014 were marked by variation in ASD prevalence when stratified by geographic area, sex, and level of intellectual ability. Differences in prevalence estimates between black and white children have diminished in most sites, but remained notable for Hispanic children. For 2014, results from application of the DSM-IV-TR and DSM-5 case definitions were similar, overall and when stratified by sex, race/ethnicity, DSM-IV-TR diagnostic subtype, or level of intellectual ability. PUBLIC HEALTH ACTION: Beginning with surveillance year 2016, the DSM-5 case definition will serve as the basis for ADDM estimates of ASD prevalence in future surveillance reports. Although the DSM-IV-TR case definition will eventually be phased out, it will be applied in a limited geographic area to offer additional data for comparison. Future analyses will examine trends in the continued use of DSM-IV-TR diagnoses, such as autistic disorder, PDD-NOS, and Asperger disorder in health and education records, documentation of symptoms consistent with DSM-5 terminology, and how these trends might influence estimates of ASD prevalence over time. The latest findings from the ADDM Network provide evidence that the prevalence of ASD is higher than previously reported estimates and continues to vary among certain racial/ethnic groups and communities. With prevalence of ASD ranging from 13.1 to 29.3 per 1,000 children aged 8 years in different communities throughout the United States, the need for behavioral, educational, residential, and occupational services remains high, as does the need for increased research on both genetic and nongenetic risk factors for ASD.

Background: One previous pilot study suggested the association of low plasma glucosylceramide (GlcCer) levels with venous thrombosis (VTE) risk. Objective: We aimed to confirm and evaluate the association of low plasma GlcCer levels with VTE and myocardial infarction (MI) occurrence, respectively. Patients and Methods: We evaluated the association of GlcCer in two independent case-control studies of Caucasian VTE populations (N = 210 and 636) and one case-control study of Caucasian MI patients (N = 345). Result: Plasma GlcCer levels in VTE patients were lower compared to controls in two independent VTE populations (5.0 vs 5.8 mug/mL, p = 0.003 for the Scripps registry, and 5.6 vs 6.0 mug/mL, p = 0.001 for the Valencia registry, respectively). A low plasma GlcCer level (below 10th percentile of controls) was associated with increased VTE occurrence [odds ratio (OR) = 3.7 (95%CI, 1.8-7.9) for Scripps registry and OR = 2.1 (95%CI, 1.3-3.3) for Valencia registry, respectively). For the MI study, the median GlcCer plasma level was lower in MI patients than in controls (4.3 vs 5.6 mug/mL, p<0.001), and a low level of GlcCer (below 10th percentile of control) was associated with higher MI occurrence [OR = 7.7, (95%CI, 4.3-13.8)]. Conclusion: Lower concentration of GlcCer was associated with VTE occurrence in two independent studies and also with MI occurrence in one study.