OBJECTIVES: To describe COVID-19-related pediatric hospitalizations during a period of B.1.617.2 (Delta) variant predominance and to determine age-specific factors associated with severe illness. PATIENTS AND METHODS: We abstracted data from medical charts to conduct a cross-sectional study of patients aged <21 years hospitalized at 6 US children's hospitals during July-August 2021 for COVID-19 or with an incidental positive SARS-CoV-2 test. Among patients with COVID-19, we assessed factors associated with severe illness by calculating age-stratified prevalence ratios (PR). We defined severe illness as receiving high-flow nasal cannula, positive airway pressure, or invasive mechanical ventilation. RESULTS: Of 947 hospitalized patients, 759 (80.1%) had COVID-19, of whom 287 (37.8%) had severe illness. Factors associated with severe illness included coinfection with RSV (PR 3.64) and bacteria (PR 1.88) in infants; RSV coinfection in patients aged 1-4 years (PR 1.96); and obesity in patients aged 5-11 (PR 2.20) and 12-17 years (PR 2.48). Having ≥2 underlying medical conditions was associated with severe illness in patients aged <1 (PR 1.82), 5-11 (PR 3.72), and 12-17 years (PR 3.19). CONCLUSIONS: Among patients hospitalized for COVID-19, factors associated with severe illness included RSV coinfection in those aged <5 years, obesity in those aged 5-17 years, and other underlying conditions for all age groups <18 years. These findings can inform pediatric practice, risk communication, and prevention strategies, including vaccination against COVID-19.

During June 2021, the highly transmissible(†) B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating strain in the United States. U.S. pediatric COVID-19-related hospitalizations increased during July-August 2021 following emergence of the Delta variant and peaked in September 2021.(§) As of May 12, 2021, CDC recommended COVID-19 vaccinations for persons aged ≥12 years,(¶) and on November 2, 2021, COVID-19 vaccinations were recommended for persons aged 5-11 years.** To date, clinical signs and symptoms, illness course, and factors contributing to hospitalizations during the period of Delta predominance have not been well described in pediatric patients. CDC partnered with six children's hospitals to review medical record data for patients aged <18 years with COVID-19-related hospitalizations during July-August 2021.(††) Among 915 patients identified, 713 (77.9%) were hospitalized for COVID-19 (acute COVID-19 as the primary or contributing reason for hospitalization), 177 (19.3%) had incidental positive SARS-CoV-2 test results (asymptomatic or mild infection unrelated to the reason for hospitalization), and 25 (2.7%) had multisystem inflammatory syndrome in children (MIS-C), a rare but serious inflammatory condition associated with COVID-19.(§§) Among the 713 patients hospitalized for COVID-19, 24.7% were aged <1 year, 17.1% were aged 1-4 years, 20.1% were aged 5-11 years, and 38.1% were aged 12-17 years. Approximately two thirds of patients (67.5%) had one or more underlying medical conditions, with obesity being the most common (32.4%); among patients aged 12-17 years, 61.4% had obesity. Among patients hospitalized for COVID-19, 15.8% had a viral coinfection(¶¶) (66.4% of whom had respiratory syncytial virus [RSV] infection). Approximately one third (33.9%) of patients aged <5 years hospitalized for COVID-19 had a viral coinfection. Among 272 vaccine-eligible (aged 12-17 years) patients hospitalized for COVID-19, one (0.4%) was fully vaccinated.*** Approximately one half (54.0%) of patients hospitalized for COVID-19 received oxygen support, 29.5% were admitted to the intensive care unit (ICU), and 1.5% died; of those requiring respiratory support, 14.5% required invasive mechanical ventilation (IMV). Among pediatric patients with COVID-19-related hospitalizations, many had severe illness and viral coinfections, and few vaccine-eligible patients hospitalized for COVID-19 were vaccinated, highlighting the importance of vaccination for those aged ≥5 years and other prevention strategies to protect children and adolescents from COVID-19, particularly those with underlying medical conditions.

What would you want to know before your children attend a day care opening in a former industrial building or adjacent to a nail salon? Are children at risk if their new preschool is located on former farmland where lead arsenate pesticide might have been used? What site-related environmental risks are most concerning for children attending early care and education (ECE) facilities? | | States involved with the Agency for Toxic Substances and Disease Registry’s (ATSDR) Choose Safe Places for Early Care and Education (CSPECE) effort are addressing site-related questions like these to help protect children from harmful environmental exposures.

Transportation investments have the potential to improve health, but readily available data to guide transportation decisions that could promote health are limited. In October 2015, the U.S. Department of Transportation (USDOT) and the Centers for Disease Control and Prevention (CDC) released the Transportation and Health Tool (THT). The tool is a resource to help transportation professionals in states and metropolitan areas access data about transportation and health in their jurisdictions and stimulate discussions on how to improve public health through transportation planning and policy. To develop the tool, a multidisciplinary team identified 190 possible data indicators. Using input from expert panel workshops and criteria that addressed data availability, geographic scale, timeliness, feasibility, validity, and topic area, the team selected 14 transportation and health indicators that covered the four priority topic areas of safety, active transportation, air quality, and connectivity. The THT contains the raw values for each indicator and a standardized score to enable comparisons. Additionally, the THT contains 25 evidence-based strategies that can help practitioners in states and metropolitan areas take action to improve health outcomes.

During September to October, 2006, state and local health departments and the Centers for Disease Control and Prevention investigated a large, multistate outbreak of Escherichia coli O157:H7 infections. Case patients were interviewed regarding specific foods consumed and other possible exposures. E. coli O157:H7 strains isolated from human and food specimens were subtyped using pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analyses (MLVA). Two hundred twenty-five cases (191 confirmed and 34 probable) were identified in 27 states; 116 (56%) case patients were hospitalized, 39 (19%) developed hemolytic uremic syndrome, and 5 (2%) died. Among 176 case patients from whom E. coli O157:H7 with the outbreak genotype (MLVA outbreak strain) was isolated and who provided details regarding spinach exposure, 161 (91%) reported fresh spinach consumption during the 10 days before illness began. Among 116 patients who provided spinach brand information, 106 (91%) consumed bagged brand A. E. coli O157:H7 strains were isolated from 13 bags of brand A spinach collected from patients' homes; isolates from 12 bags had the same MLVA pattern. Comprehensive epidemiologic and laboratory investigations associated this large multistate outbreak of E. coli O157:H7 infections with consumption of fresh bagged spinach. MLVA, as a supplement to pulsed-field gel electrophoresis genotyping of case patient isolates, was important to discern outbreak-related cases. This outbreak resulted in enhanced federal and industry guidance to improve the safety of leafy green vegetables and launched an independent collaborative approach to produce safety research in 2007.

We conducted an ecological study to determine whether parking prices are associated with active commuting across US cities. We obtained parking prices for 107 US cities from the Drexel University Central Business District Public Parking Survey, obtained city prevalence of walking and bicycling to work from the American Community Survey, and used weighted least squares linear regression to explore associations between parking prices and active commuting. After adjusting for several covariates, walking to work was 3.1% higher for every additional dollar charged for off-street daily parking, but only among more densely populated cities, and no such association was detected for bicycling to work. These preliminary results hint at the potential for parking policies to influence commuting mode choice, a link that city planners and public health officials could consider when evaluating parking policies and active transportation behaviors.

Creating environments that support all types of physical activity, including active transportation, is a public health priority. Public health surveillance that identifies the locations where community members walk and bicycle (i.e., engage in active transportation) can inform such efforts. Traditional population-representative active transportation surveillance incurs a considerable time lag between data collection and dissemination, and often lacks geographic specificity. Conversely, user-generated active transportation data from Global Positioning System (GPS)-based activity tracking devices and mobile applications can provide near real-time information, but might be subject to self-selection bias among users. CDC analyzed the association between GPS-based commuting data from a company that allows tracking of activity with a mobile application (Strava, Inc., San Francisco, California) and population-representative commuting data from the U.S. Census Bureau's American Community Survey (ACS) for four U.S. cities. The level of analysis was the Census block group. The number of GPS-tracked commuters in Strava was associated with the number of ACS active commuters (Spearman's rho = 0.60), suggesting block groups were ranked similarly based on these distinct but related measurements. The correlation was higher in high population density areas. User-generated active transportation data might complement traditional surveillance systems by providing near real-time, location-specific information on where active transportation occurs.

The Integrated Transport and Health Impact Model (ITHIM) is a comprehensive tool that estimates the hypothetical health effects of transportation mode shifts through changes to physical activity, air pollution, and injuries. The purpose of this paper is to describe the implementation of ITHIM in greater Nashville, Tennessee (USA), describe important lessons learned, and serve as an implementation guide for other practitioners and researchers interested in running ITHIM. As might be expected in other metropolitan areas in the US, not all the required calibration data was available locally. We utilized data from local, state, and federal sources to fulfill the 14 ITHIM calibration items, which include disease burdens, travel habits, physical activity participation, air pollution levels, and traffic injuries and fatalities. Three scenarios were developed that modeled stepwise increases in walking and bicycling, and one that modeled reductions in car travel. Cost savings estimates were calculated by scaling national-level, disease-specific direct treatment costs and indirect lost productivity costs to the greater Nashville population of approximately 1.5 million. Implementation required approximately one year of intermittent, part-time work. Across the range of scenarios, results suggested that 24-123 deaths per year could be averted in the region through a 1-5% reduction in the burden of several chronic diseases. This translated into $10-$63 million in estimated direct and indirect cost savings per year. Implementing ITHIM in greater Nashville has provided local decision makers with important information on the potential health effects of transportation choices. Other jurisdictions interested in ITHIM might find the Nashville example as a useful guide to streamline the effort required to calibrate and run the model. © 2016.

When most people hear “models,” they probably think about people, not transportation. Models—the people version—help predict how clothes will look when we wear them. Models—the transportation version—help predict how our transportation system will function based on current and future infrastructure investments. Neither type of model is entirely accurate; they attempt to predict the future, and the future rarely fully cooperates. Despite this, models can provide useful information for planning and predicting health outcomes. | | Environmental health practitioners already utilize model predictions. Prediction of disease risk, such as West Nile virus, may be based on models of vector spread (Harrigan, 2014). The risk of flooding in a given area is predicted based on historical stream-flow records (U.S. Geological Survey, 2008). In transportation, opportunities for environmental health professionals may arise as transportation models expand beyond predicting congestion and air pollution to predicting health impacts of walking and bicycling. | | The well-established health benefits of increased physical activity have created much interest in health impacts of the transportation built environment related to walking, bicycling, and public transit (Besser, 2005). Ideally, models could predict changes in health outcomes such as mortality or disease prevalence for a given built environment change, such as a bike path or complete street initiative. This process has two steps: first, predicting changes in travel behavior (e.g., mode shift or total distance walked/bicycled) following an environmental or policy change; second, predicting health outcomes following the change in travel behavior. In practice, the former is currently more difficult than the latter. Each is explained below.

PROBLEM/CONDITION: Physical activity is a health-enhancing behavior, and most U.S. adults do not meet the 2008 Physical Activity Guidelines for Americans. Active transportation, such as by walking or bicycling, is one way that persons can be physically active. No comprehensive, multiyear assessments of active transportation surveillance in the United States have been conducted. PERIOD COVERED: 1999-2012. DESCRIPTION OF SYSTEMS: Five surveillance systems assess one or more components of active transportation. The American Community Survey and the National Household Travel Survey (NHTS) both assess the mode of transportation to work in the past week. From these systems, the proportion of respondents who reported walking or bicycling to work can be calculated. NHTS and the American Time Use Survey include 1-day assessments of trips or activities. With that information, the proportion of respondents who report any walking or bicycling for transportation can be calculated. The National Health and Nutrition Examination Survey and the National Health Interview Survey both assess recent (i.e., in the past week or past month) habitual physical activity behaviors, including those performed during active travel. From these systems, the proportion of respondents who report any recent habitual active transportation can be calculated. RESULTS: The prevalence of active transportation as the primary commute mode to work in the past week ranged from 2.6% to 3.4%. The 1-day assessment indicated that the prevalence of any active transportation ranged from 10.5% to 18.5%. The prevalence of any habitual active transportation ranged from 23.9% to 31.4%. No consistent trends in active transportation across time periods and surveillance systems were identified. Among systems, active transportation was usually more common among men, younger respondents, and minority racial/ethnic groups. Among education groups, the highest prevalence of active transportation was usually among the least or most educated groups, and active transportation tended to be more prevalent in densely populated, urban areas. INTERPRETATION: Active transportation is assessed in a wide variety of ways in multiple surveillance systems. Different assessment techniques and construct definitions result in widely discrepant estimates of active transportation; however, some consistent patterns were detected across covariates. Although each type of assessment (i.e., transportation to work, single day, and habitual behavior) measures a different active transportation component, all can be used to monitor population trends in active transportation participation. PUBLIC HEALTH ACTION: An understanding of the strengths, limitations, and lack of comparability of active transportation assessment techniques is necessary to correctly evaluate findings from the various surveillance systems. When used appropriately, these systems can be used by public health and transportation professionals to monitor population participation in active transportation and plan and evaluate interventions that influence active transportation.

INTRODUCTION: Joint use or shared use of public school facilities provides community access to facilities for varied purposes. We examined a nationally representative sample of school districts in the United States to identify characteristics associated with having a formal joint use agreement (JUA) and with the kinds of uses to which JUAs apply. METHODS: We analyzed data from the 2012 School Health Policies and Practices Study. The response rate for the module containing questions about formal JUAs was 60.1% (N = 630). We used multivariate logistic regression models to examine the adjusted odds of having a formal JUA and chi2 analyses to examine differences in district characteristics associated with the uses of the JUA. RESULTS: Among the 61.6% of school districts with a formal JUA, more than 80% had an agreement for the use of indoor and outdoor recreation facilities; other uses also were identified. JUAs were more common in urban than rural areas, in large than small school districts, and in the West compared with the Midwest, South, and Northeast. CONCLUSION: In many districts, school facilities appear to be an untapped resource for community members. Formal JUAs provide an opportunity for shared use while addressing issues of liability, cost, and logistics.

CONTEXT: Exposure to elevated concentrations of traffic-related air pollutants in the near-road environment is associated with numerous adverse human health effects, including childhood cancer, which has been increasing since 1975. Results of individual epidemiologic studies have been inconsistent. Therefore, a meta-analysis was performed to examine the association between residential traffic exposure and childhood cancer. EVIDENCE ACQUISITION: Studies published between January 1980 and July 2011 were retrieved from a systematic search of 18 bibliographic databases. Nine studies meeting the inclusion criteria were identified. Weighted summary ORs were calculated using a random effects model for outcomes with four or more studies. Subgroup and sensitivity analyses were performed. EVIDENCE SYNTHESIS: Childhood leukemia was positively associated (summary OR=1.53, 95% CI=1.12, 2.10) with residential traffic exposure among seven studies using a postnatal exposure window (e.g., childhood period or diagnosis address) and there was no association (summary OR=0.92, 95% CI=0.78, 1.09) among four studies using a prenatal exposure window (e.g., pregnancy period or birth address). There were too few studies to analyze other childhood cancer outcomes. CONCLUSIONS: Current evidence suggests that childhood leukemia is associated with residential traffic exposure during the postnatal period, but not during the prenatal period. Additional well-designed epidemiologic studies that use complete residential history to estimate traffic exposure, examine leukemia subtypes, and control for potential confounding factors are needed to confirm these findings. As many people reside near busy roads, especially in urban areas, precautionary public health messages and interventions designed to reduce population exposure to traffic might be warranted.

OBJECTIVE: To describe the use and reporting of Health Impact Assessment (HIA) in Australia and New Zealand between 2005 and 2009. METHODS: We identified 115 HIAs undertaken in Australia and New Zealand between 2005 and 2009. We reviewed 55 HIAs meeting the study's inclusion criteria to identify characteristics and appraise the quality of the reports. RESULTS: Of the 55 HIAs, 31 were undertaken in Australia and 24 in New Zealand. The HIAs were undertaken on plans (31), projects (12), programs (6) and policies (6). Compared to Australia, a higher proportion of New Zealand HIAs were on policies and plans and were rapid assessments done voluntarily to support decision-making. In both countries, most HIAs were on land use planning proposals. Overall, 65% of HIA reports were judged to be adequate. CONCLUSION: This study is the first attempt to empirically investigate the nature of the broad range of HIAs done in Australia and New Zealand and has highlighted the emergence of HIA as a growing area of public health practice. It identifies areas where current practice could be improved and provides a baseline against which future HIA developments can be assessed. IMPLICATIONS: There is evidence that HIA is becoming a part of public health practice in Australia and New Zealand across a wide range of policies, plans and projects. The assessment of quality of reports allows the development of practical suggestions on ways current practice may be improved. The growth of HIA will depend on ongoing organisation and workforce development in both countries.

OBJECTIVES: We assessed changes in transit-associated walking in the United States from 2001 to 2009 and documented their importance to public health. METHODS: We examined transit walk times using the National Household Travel Survey, a telephone survey administered by the US Department of Transportation to examine travel behavior in the United States. RESULTS: People are more likely to transit walk if they are from lower income households, are non-White, and live in large urban areas with access to rail systems. Transit walkers in large urban areas with a rail system were 72% more likely to transit walk 30 minutes or more per day than were those without a rail system. From 2001 to 2009, the estimated number of transit walkers rose from 7.5 million to 9.6 million (a 28% increase); those whose transit-associated walking time was 30 minutes or more increased from approximately 2.6 million to 3.4 million (a 31% increase). CONCLUSIONS: Transit walking contributes to meeting physical activity recommendations. Study results may contribute to transportation-related health impact assessment studies evaluating the impact of proposed transit systems on physical activity, potentially influencing transportation planning decisions. (Am J Public Health. Published online ahead of print January 17, 2013: e1-e7. doi:10.2105/AJPH.2012.300912).

It’s 4:00 p.m., Friday afternoon, and someone unfamiliar is knocking on your office door. She introduces herself as a city | planner and asks whether you could help | her with an upcoming redevelopment decision. She knows the health department has | environmental health, chronic disease, and | injury programs, and that redevelopment | affects these issues. She came to your office | first because she perceives redevelopment as | a change in the environment. Through her | planning education she has heard of “Health | Impact Assessment” (HIA) and thinks it | would help this situation. | The practice of HIA acknowledges that decisions made outside of the health sector can | profoundly affect public health. Furthermore, | the health sector’s engagement can promote | evidence-based policy change. HIA practice is | growing and environmental health professionals frequently lead the charge. The National Prevention Strategy states that HIA can facilitate accomplishing the key strategy of building healthy | and safe community environments (National | Prevention Council, 2011). As the provided scenario implies, awareness of HIA has reached city | planners and associated professionals.

This article provides a comparison of health impact assessment (HIA) guidelines from around the world and for multiple geographic scales. We identify commonalities and differences within HIA guides to discuss the plausibility of consensus guidelines and to inform guideline development The practice of HIA has grown over the last two decades with a concurrent growth of HIA guides. This study expands on earlier review work and includes guides published since 2007 (Mindell, Boltong and Forde, 2008). From April 2010 to October 2011, 45 HIA guides were identified through an internet search and review of previous research. Common characteristics, key features, and the HIA process were analyzed. The 45 documents recommended similar but not identical processes for conducting HIAs. These analyses suggest that guidelines for HIAs are similar in many areas of the world and that new HIA practitioners can use these findings to inform their approach. Further discussion is needed to determine if the approaches established in these guidelines are followed and if one set of common guidelines could be written for use in numerous countries and regions. (C) 2012 Elsevier Inc. All rights reserved.