Prevalence of covid-19 and long covid in collegiate student athletes from spring 2020 to fall 2021: a retrospective survey.

BACKGROUND: Symptomatic COVID-19 and Long COVID, also referred to as post-acute sequelae of SARS-CoV-2 (PASC) or post-COVID conditions, have been widely reported in young, healthy people, but their prevalence has not yet been determined in student athletes. We sought to estimate the prevalence of reported COVID-19, symptomatic COVID-19, and Long COVID in college athletes in the United States attending 18 schools from spring 2020 to fall 2021. METHODS: We developed an online survey to measure the prevalence of student athletes who tested positive for COVID-19, developed Long COVID, and did not return to their sport during the relevant time period. We surveyed a convenience sample of 18 collegiate school administrators, representing about 7,000 student athletes. Of those schools surveyed, 16 responded regarding the spring 2020 semester, and 18 responded regarding the full academic year of fall 2020 to spring 2021 (both semesters). RESULTS: According to the survey responses, there were 9.8% of student athletes who tested positive for COVID-19 in spring 2020 and 25.4% who tested positive in the academic year of fall 2020 to spring 2021. About 4% of student athletes who tested positive from spring 2020 to spring 2021 developed Long COVID, defined as new, recurring, or ongoing physical or mental health consequences occurring 4 or more weeks after SARS-CoV-2 infection. CONCLUSIONS: This study highlights that Long COVID occurs among young, healthy athletes and is a real consequence of COVID-19. Understanding the prevalence of Long COVID in this population requires longer follow-up and further study.

The Effect of a Shared Decision-Making Process on Acceptance of Colorectal Cancer Screening.

VISUAL ABSTRACT.

Pooling in a Pod: A Strategy for COVID-19 Testing to Facilitate a Safe Return to School.

The COVID-19 pandemic prompted widespread closures of primary and secondary schools. Routine testing of asymptomatic students and staff members, as part of a comprehensive mitigation program, can help schools open safely. "Pooling in a pod" is a public health surveillance strategy whereby testing cohorts (pods) are based on social relationships and physical proximity. Pooled testing provides a single laboratory test result for the entire pod, rather than a separate result for each person in the pod. During the 2020-2021 school year, an independent preschool-grade 12 school in Washington, DC, used pooling in a pod for weekly on-site point-of-care testing of all staff members and students. Staff members and older students self-collected anterior nares samples, and trained staff members collected samples from younger students. Overall, 12 885 samples were tested in 1737 pools for 863 students and 264 staff members from November 30, 2020, through April 30, 2021. The average pool size was 7.4 people. The average time from sample collection to pool test result was 40 minutes. The direct testing cost per person per week was $24.24, including swabs. During the study period, 4 surveillance test pools received positive test results for COVID-19. A post-launch survey found most parents (90.3%), students (93.4%), and staff members (98.8%) were willing to participate in pooled testing with confirmatory tests for pool members who received a positive test result. The proportion of students in remote learning decreased by 62.2% for students in grades 6-12 (P < .001) and by 92.4% for students in preschool to grade 5 after program initiation (P < .001). Pooling in a pod is a feasible, cost-effective surveillance strategy that may facilitate safe, sustainable, in-person schooling during a pandemic.

Implementation of a pooled surveillance testing program for asymptomatic SARS-CoV-2 infections in K-12 schools and universities.

BACKGROUND: The negative impact of continued school closures during the height of the COVID-19 pandemic warrants the establishment of cost-effective strategies for surveillance and screening to safely reopen and monitor for potential in-school transmission. Here, we present a novel approach to increase the availability of repetitive and routine COVID-19 testing that may ultimately reduce the overall viral burden in the community. METHODS: We implemented a testing program using the SalivaClear࣪ pooled surveillance method that included students, faculty and staff from K-12 schools (student age range 5-18 years) and universities (student age range >18 years) across the country (Mirimus Clinical Labs, Brooklyn, NY). The data analysis was performed using descriptive statistics, kappa agreement, and outlier detection analysis. FINDINGS: From August 27, 2020 until January 13, 2021, 253,406 saliva specimens were self-collected from students, faculty and staff from 93 K-12 schools and 18 universities. Pool sizes of up to 24 samples were tested over a 20-week period. Pooled testing did not significantly alter the sensitivity of the molecular assay in terms of both qualitative (100% detection rate on both pooled and individual samples) and quantitative (comparable cycle threshold (Ct) values between pooled and individual samples) measures. The detection of SARS-CoV-2 in saliva was comparable to the nasopharyngeal swab. Pooling samples substantially reduced the costs associated with PCR testing and allowed schools to rapidly assess transmission and adjust prevention protocols as necessary. In one instance, in-school transmission of the virus was determined within the main office and led to review and revision of heating, ventilating and air-conditioning systems. INTERPRETATION: By establishing low-cost, weekly testing of students and faculty, pooled saliva analysis for the presence of SARS-CoV-2 enabled schools to determine whether transmission had occurred, make data-driven decisions, and adjust safety protocols. We provide strong evidence that pooled testing may be a fundamental component to the reopening of schools by minimizing the risk of in-school transmission among students and faculty. FUNDING: Skoll Foundation generously provided funding to Mobilizing Foundation and Mirimus for these studies.

Neighborhood Environments and Utilitarian Walking Among Older vs. Younger Rural Adults.

Introduction: Walking has the potential to promote health across the life span, but age-specific features of the neighborhood environment (NE), especially in rural communities, linked with walking have not been adequately characterized. This study examines the relationships between NE and utilitarian walking among older vs. younger adults living in US rural towns. Methods: Data for this cross-sectional study came from telephone interviews in 2011-2012 with 2,140 randomly sampled younger (18-64 years, n = 1,398) and older (65+ years, n = 742) adults, collecting personal and NE perception variables. NE around each participant's home was also measured objectively using geographic information system techniques. Separate mixed-effects logistic regression models were estimated for the two age groups, predicting the odds of utilitarian walking at least once a week. Results: Perceived presence of crosswalks and pedestrian signals was significantly related to utilitarian walking in both age groups. Among older adults, unattended dogs, lighting at night, and religious institutions were positively while steep slope was negatively associated with their walking. For younger adults, traffic speed (negative, -), public transportation (positive, +), malls (-), cultural/recreational destinations (+), schools (+), and resource production land uses such as farms and mines (-) were significant correlates of utilitarian walking. Conclusion: Different characteristics of NE are associated with utilitarian walking among younger vs. older adults in US rural towns. Optimal modifications of NE to promote walking may need to reflect these age differences.

Identifying optimal COVID-19 testing strategies for schools and businesses: Balancing testing frequency, individual test technology, and cost.

BACKGROUND: COVID-19 test sensitivity and specificity have been widely examined and discussed, yet optimal use of these tests will depend on the goals of testing, the population or setting, and the anticipated underlying disease prevalence. We model various combinations of key variables to identify and compare a range of effective and practical surveillance strategies for schools and businesses. METHODS: We coupled a simulated data set incorporating actual community prevalence and test performance characteristics to a susceptible, infectious, removed (SIR) compartmental model, modeling the impact of base and tunable variables including test sensitivity, testing frequency, results lag, sample pooling, disease prevalence, externally-acquired infections, symptom checking, and test cost on outcomes including case reduction and false positives. FINDINGS: Increasing testing frequency was associated with a non-linear positive effect on cases averted over 100 days. While precise reductions in cumulative number of infections depended on community disease prevalence, testing every 3 days versus every 14 days (even with a lower sensitivity test) reduces the disease burden substantially. Pooling provided cost savings and made a high-frequency approach practical; one high-performing strategy, testing every 3 days, yielded per person per day costs as low as $1.32. INTERPRETATION: A range of practically viable testing strategies emerged for schools and businesses. Key characteristics of these strategies include high frequency testing with a moderate or high sensitivity test and minimal results delay. Sample pooling allowed for operational efficiency and cost savings with minimal loss of model performance.

COVID-19 Infection Control Measures in Long-Term Care Facility, Pennsylvania, USA.

Residents of long-term care facilities are at risk for coronavirus disease. We report a surveillance exercise at such a facility in Pennsylvania, USA. After introduction of a testing strategy and other measures, this facility had a 17-fold lower coronavirus disease case rate than neighboring facilities.

A comparison of health care worker-collected foam and polyester nasal swabs in convalescent COVID-19 patients.

Both polyester and foam nasal swabs were collected from convalescent COVID-19 patients at a single visit and stored in viral transport media (VTM), saline or dry. Sensitivity of each swab material and media combination were estimated, three by three tables were constructed to measure polyester and foam concordance, and cycle threshold (Ct) values were compared. 126 visits had polyester and foam swabs stored in viral transport media (VTM), 51 had swabs stored in saline, and 63 had a foam swab in VTM and a polyester swab stored in a dry tube. Polyester and foam swabs had an estimated sensitivity of 87.3% and 94.5% respectively in VTM, 87.5% and 93.8% respectively in saline, and 75.0% and 90.6% respectively for dry polyester and foam VTM. Polyester and foam Ct values were correlated, but polyester showed decreased performance for cases with a viral load near the detection threshold and higher Ct values on average.

Geographic variation in the relationship between body mass index and the built environment.

Studies examining associations between weight status and neighborhood built environment (BE) have shown inconsistent results and have generally focused on urban settings. However, many Americans do not live in metropolitan areas and BE impacts may be different outside of metropolitan areas. We sought to examine whether the relationship between body mass index (BMI) and neighborhood BE exists and varies by geographic region across small towns in the United States. We conducted telephone surveys with 2156 adults and geographic information systems data in nine towns located within three geographic regions (Northeast, Texas, Washington) in 2011 and 2012. Multiple regression models examined the relationship between individual BMI and BE measures. Most physical activity variables were significantly associated with lower BMI in all geographic regions. We saw variation across geographic region in the relationship between characteristics of the BE variables and BMI. Some perceived and objectively-measured characteristics of the BE were significantly associated with adult BMI, but significant relationships varied by geographic region. For example, in the Northeast, perceived attractiveness of the neighborhood as a reason for why they chose to live there was associated with lower BMI; in Texas, the perceived presence of a fast food restaurant was negatively associated with BMI; in Washington, perceived presence of trees along the streets was associated with lower BMI. Our findings suggest that regional variation plays a role in the relationship between adult BMI and BE characteristics in small towns. Regardless of geographic location, interventions should encourage utilitarian walking and other forms of physical activity.

Utilitarian and Recreational Walking Among Spanish- and English-Speaking Latino Adults in Micropolitan US Towns.

BACKGROUND: Walking among Latinos in US Micropolitan towns may vary by language spoken. METHODS: In 2011-2012, we collected telephone survey and built environment (BE) data from adults in six towns located within micropolitan counties from two states with sizable Latino populations. We performed mixed-effects logistic regression modeling to examine relationships between ethnicity-language group [Spanish-speaking Latinos (SSLs); English-speaking Latinos (ESLs); and English-speaking non-Latinos (ENLs)] and utilitarian walking and recreational walking, accounting for socio-demographic, lifestyle and BE characteristics. RESULTS: Low-income SSLs reported higher amounts of utilitarian walking than ENLs (p = 0.007), but utilitarian walking in this group decreased as income increased. SSLs reported lower amounts of recreational walking than ENLs (p = 0.004). ESL-ENL differences were not significant. We identified no statistically significant interactions between ethnicity-language group and BE characteristics. DISCUSSION: Approaches to increase walking in micropolitan towns with sizable SSL populations may need to account for this group's differences in walking behaviors.

Secondary GIS built environment data for health research: guidance for data development.

Built environment (BE) data in geographic information system (GIS) format are increasingly available from public agencies and private providers. These data can provide objective, low-cost BE data over large regions and are often used in public health research and surveillance. Yet challenges exist in repurposing GIS data for health research. The GIS data do not always capture desired constructs; the data can be of varying quality and completeness; and the data definitions, structures, and spatial representations are often inconsistent across sources. Using the Small Town Walkability study as an illustration, we describe (a) the range of BE characteristics measurable in a GIS that may be associated with active living, (b) the availability of these data across nine U.S. small towns, (c) inconsistencies in the GIS BE data that were available, and (d) strategies for developing accurate, complete, and consistent GIS BE data appropriate for research. Based on a conceptual framework and existing literature, objectively measurable characteristics of the BE potentially related to active living were classified under nine domains: generalized land uses, morphology, density, destinations, transportation system, traffic conditions, neighborhood behavioral conditions, economic environment, and regional location. At least some secondary GIS data were available across all nine towns for seven of the nine BE domains. Data representing high-resolution or behavioral aspects of the BE were often not available. Available GIS BE data - especially tax parcel data - often contained varying attributes and levels of detail across sources. When GIS BE data were available from multiple sources, the accuracy, completeness, and consistency of the data could be reasonable ensured for use in research. But this required careful attention to the definition and spatial representation of the BE characteristic of interest. Manipulation of the secondary source data was often required, which was facilitated through protocols.

The built environment and utilitarian walking in small U.S. towns.

OBJECTIVES: The role of the built environment on walking in rural United States (U.S.) locations is not well characterized. We examined self-reported and measured built environment correlates of walking for utilitarian purposes among adult residents of small rural towns. METHODS: In 2011-12, we collected telephone survey and geographic data from 2152 adults in 9 small towns from three U.S. regions. We performed mixed-effects logistic regression modeling to examine relationships between built environment measures and utilitarian walking ("any" versus "none"; "high" [≥150min per week] versus "low" [<150min per week]) to retail, employment and public transit destinations. RESULTS: Walking levels were lower than those reported for populations living in larger metropolitan areas. Environmental factors significantly (p<0.05) associated with higher odds of utilitarian walking in both models included self-reported presence of crosswalks and pedestrian signals and availability of park/natural recreational areas in the neighborhood, and also objectively measured manufacturing land use. CONCLUSIONS: Environmental factors associated with utilitarian walking in cities and suburbs were important in small rural towns. Moreover, manufacturing land use was associated with utilitarian walking. Modifying the built environment of small towns could lead to increased walking in a sizeable segment of the U.S. population.

Built environment change: a framework to support health-enhancing behaviour through environmental policy and health research.

As research examining the effect of the built environment on health accelerates, it is critical for health and planning researchers to conduct studies and make recommendations in the context of a robust theoretical framework. We propose a framework for built environment change (BEC) related to improving health. BEC consists of elements of the built environment, how people are exposed to and interact with them perceptually and functionally, and how this exposure may affect health-related behaviours. Integrated into this framework are the legal and regulatory mechanisms and instruments that are commonly used to effect change in the built environment. This framework would be applicable to medical research as well as to issues of policy and community planning.

Retail tobacco exposure: using geographic analysis to identify areas with excessively high retail density.

INTRODUCTION: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. METHODS: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. RESULTS: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. CONCLUSIONS: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.

Business list vs ground observation for measuring a food environment: saving time or waste of time (or worse)?

In food-environment research, an alternative to resource-intensive direct observation on the ground has been the use of commercial business lists. We sought to determine how well a frequently used commercial business list measures a dense urban food environment like the Bronx, NY. On 155 Bronx street segments, investigators compared two different levels for matches between the business list and direct ground observation: lenient (by business type) and strict (by business name). For each level of matching, researchers calculated sensitivities and positive predictive values (PPVs) for the business list overall and by broad business categories: General Grocers (eg, supermarkets), Specialty Food Stores (eg, produce markets), Restaurants, and Businesses Not Primarily Selling Food (eg, newsstands). Even after cleaning the business list (eg, for cases of multiple listings at a single location), and allowing for inexactness in listed street addresses and spellings of business names, the overall performance of the business list was poor. For strict matches, the business list had an overall sensitivity of 39.3% and PPV of 45.5%. Sensitivities and PPVs by broad business categories were not meaningfully different from overall values, although sensitivity for General Grocers and PPV for Specialty Food Stores were particularly low: 26.2% and 32%, respectively. For lenient matches, sensitivities and PPVs were somewhat higher but still poor: 52.4% to 60% and 60% to 75%, respectively. The business list is inadequate to measure the actual food environment in the Bronx. If results represent performance in other settings, findings from prior studies linking food environments to diet and diet-related health outcomes using such business lists are in question, and future studies of this type should avoid relying solely on such business lists.

Does neighborhood walkability moderate the effects of intrapersonal characteristics on amount of walking in post-menopausal women?

This study identifies factors associated with walking among postmenopausal women and tests whether neighborhood walkability moderates the influence of intrapersonal factors on walking. We used data from the Women's Health Initiative Seattle Center and linear regression models to estimate associations and interactions. Being white and healthy, having a high school education or beyond and greater non-walking exercise were significantly associated with more walking. Neighborhood walkability was not independently associated with greater walking, nor did it moderate influence of intrapersonal factors on walking. Specifying types of walking (e.g., for transportation) can elucidate the relationships among intrapersonal factors, the built environment, and walking.

Predictors of tobacco outlet density nationwide: a geographic analysis.

OBJECTIVE: To elucidate how demographics of US Census tracts are related to tobacco outlet density (TOD). METHOD: The authors conducted a nationwide assessment of the association between socio-demographic US Census indicators and the density of tobacco outlets across all 64,909 census tracts in the continental USA. Retail tobacco outlet addresses were determined through North American Industry Classification System codes, and density per 1000 population was estimated for each census tract. Independent variables included urban/rural; proportion of the population that was black, Hispanic and women with low levels of education; proportion of families living in poverty and median household size. RESULTS: In a multivariate analysis, there was a higher TOD per 1000 population in urban than in rural locations. Furthermore, higher TOD was associated with larger proportions of blacks, Hispanics, women with low levels of education and with smaller household size. Urban-rural differences in the relation between demographics and TOD were found in all socio-demographic categories, with the exception of poverty, but were particularly striking for Hispanics, for whom the relation with TOD was 10 times larger in urban compared with rural census tracts. CONCLUSIONS: The findings suggest that tobacco outlets are more concentrated in areas where people with higher risk for negative health outcomes reside. Future studies should examine the relation between TOD and smoking, smoking cessation, as well as disease rates.

A comparison of individual versus community influences on youth smoking behaviours: a cross-sectional observational study.

OBJECTIVES: To compare individual with community risk factors for adolescent smoking. DESIGN: A cross-sectional observational study with multivariate analysis. SETTING: National telephone survey. PARTICIPANTS: 3646 US adolescents aged 13-18 years in 2007 recruited through a random digit-dial survey. OUTCOME MEASURES: Ever tried smoking and, among experimental smokers, smoking intensity (based on smoking in past 30 days). RESULTS: One-third of participants (35.6%, N=1297) had tried smoking. After controlling for individual risk factors, neither tobacco outlet density nor proximity were associated with tried smoking or smoking intensity. Associations with trying smoking included age (adjusted OR (AOR)=1.23, 95% CI 1.16 to 1.31), lower socioeconomic status (AOR=0.82, 95% CI 0.74 to 0.91), sibling smoking (AOR=2.13, 95% CI 1.75 to 2.59), friend smoking (AOR=2.60, 95% CI 2.19 to 3.10 for some and AOR=7.01, 95% CI 5.05 to 9.74 for most), movie smoking exposure (AOR=2.66, 95% CI 1.95 to 3.63), team sports participation (AOR=0.69, 95% CI 0.54 to 0.89) and sensation seeking (AOR=7.72, 95% CI 5.26 to 11.34). Among experimental smokers, age (AOR=1.32, 95% CI 1.21 to 1.44), minority status (AOR=0.48, 95% CI 0.30 to 0.79 for Black; AOR=0.46, 95% CI 0.31 to 0.69 for Hispanic; AOR=0.53, 95% CI 0.43 to 0.85 for mixed race/other), friend smoking (AOR=3.37, 95% CI 2.37 to 4.81 for some; AOR=20.27, 95% CI 13.22 to 31.08 for most), team sports participation (AOR=0.38, 95% CI 0.26 to 0.55) and sensation seeking (AOR=6.57, 95% CI 3.71 to 11.64) were associated with smoking intensity. CONCLUSIONS: The study suggests that interventions and policies to prevent and reduce youth smoking should focus on individual risk factors for smoking, including supporting participation in team sports, minimising exposure to movie smoking, addressing the social influence of friend smoking and addressing experience seeking among high sensation-seekers.

End-of-life care for Medicare beneficiaries with cancer is highly intensive overall and varies widely.

Studies have shown that cancer care near the end of life is more aggressive than many patients prefer. Using a cohort of deceased Medicare beneficiaries with poor-prognosis cancer, meaning that they were likely to die within a year, we examined the association between hospital characteristics and eleven end-of-life care measures, such as hospice use and hospitalization. Our study revealed a relatively high intensity of care in the last weeks of life. At the same time, there was more than a twofold variation within hospital groups with common features, such as cancer center designation and for-profit status. We found that these hospital characteristics explained little of the observed variation in intensity of end-of-life cancer care and that none reliably predicted a specific pattern of care. These findings raise questions about what factors may be contributing to this variation. They also suggest that best practices in end-of-life cancer care can be found in many settings and that efforts to improve the quality of end-of-life care should include every hospital category.