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This paper examined changes in human immunodeficiency virus (HIV)-related risk behaviors among high school students in the United States during 1991-2005. Data from 8 national Youth Risk Behavior Surveys conducted during that period were analyzed. During 1991-2005, the percentage of US high school students engaging in HIV-related sexual risk behaviors significantly decreased.

This article reports that the U.S. National Institutes of Health (NIH) has released a draft policy aimed at increasing public access to the results of NIH-funded research. In July, a congressional spending panel recommended that NIH post Mill-funded manuscripts within 6 months of publication, or immediately if NIH grants were used to pay publication costs. Librarians, patient organizations, and scientists who think taxpayers should have easier access to NIH-funded research urged NIH to follow the House language.

The Ohio Substance Abuse Monitoring Network (OSAM) is designed to provide accurate, timely, qualitatively-oriented epidemiologic descriptions of substance abuse trends and emerging problems in the state's major urban and rural areas. Use of qualitative methods in identifying and assessing substance abuse practices in local communities is one of the main assets of OSAM Network. Qualitative methods are sensitive to local contextual variability, flexible enough to capture emergent trends, and can be implemented with limited financial resources. This paper describes how qualitative epidemiologic methods, like those used by the OSAM Network, could be applied to inform substance abuse prevention activities, particularly those directed at adolescents.

Background: Social Frailty is a significant public health concern affecting the elderly, particularly with the global population aging rapidly. Older adults with social frailty are at significantly higher risk of adverse outcomes such as disability, cognitive impairment, depression, and even death. In recent years, there have been more and more studies on social frailty, but no bibliometrics has been used to analyze and understand the general situation in this field. Therefore, by using CiteSpace, VOSviewer, and Bilioshiny software programs, this study aims to analyze the general situation of the research on social frailties of the older adults and determine the research trends and hot spots. Methods: A bibliometric analysis was conducted by searching relevant literature on the social frailty of the older adults from 2003 to 2022 in the Web of Science core database, using visualization software to map publication volume, country and author cooperation networks, keyword co-occurrences, and word emergence. Results: We analyzed 415 articles from 2003 to 2022. Brazil has the highest number of articles in the field of social frailty of the older adults, and the United States has the highest number of cooperative publications. Andrew MK, from Canada, is the most published and co-cited author, with primary research interests in geriatric assessment, epidemiology, and public health. "Social Vulnerability," "Health," "Frailty," "Mortality," and "Older Adult" are among the research hotspots in this field. "Dementia," "Alzheimer's disease," "Population," and "Covid-19" are emerging research trends in social frailty among the older adults. Conclusion: This scientometric study maps the research hotspots and trends for the past 20 years in social frailty among the older adults. Our findings will enable researchers to better understand trends in this field and find suitable directions and partners for future research. [ABSTRACT FROM AUTHOR]

Climate change will cause a range of related risks, including increases in infectious and chronic disease, intensified social and economic stresses, and more frequent extreme weather events. Vulnerable groups will be disproportionately affected due to greater exposure to climate risks and lower ability to prepare, adapt, and recover from their effects. Better understanding of the intersection of vulnerability and climate change risks is required to identify the most important drivers of future climate risks and effectively build resilience and deploy targeted adaptation efforts. Incorporating community stakeholder input, we identified and integrated available public health, social, economic, environmental, and climate data in the United States (U.S.), comprising 184 indicators, to develop a Climate Vulnerability Index (CVI) composed of four baseline vulnerabilities (health, social/economic, infrastructure, and environment) and three climate change risks (health, social/economic, extreme events). We find that the vulnerability to and risks from climate change are highly heterogeneous across the U.S. at the census tract scale, and geospatially cluster into complementary areas with similar climate risks but differing baseline vulnerabilities. Our results therefore demonstrate that not only are climate change risks both broadly and variably distributed across the U.S., but also that existing disparities are often further exacerbated by climate change. The CVI thus lays a data-driven, scientific foundation for future research on the intersection of climate change risks with health and other inequalities, while also identifying health impacts of climate change as the greatest research gap. Moreover, given U.S. government initiatives surrounding climate and equity, the CVI can be instrumental in empowering communities and policymakers to better prioritize resources and target interventions, providing a template for addressing local-scale climate and environmental justice globally., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The objective of this paper is to answer the research question: in what ways is access to resources related to menstruation a public health issue in the United States (US) and Scotland? Resources will be understood to mean, for example, menstrual products, education, safe restroom facilities, and appropriate and accessible healthcare. The Social Ecological Model (SEM), a conceptual model consisting of four levels of consideration (individual, interpersonal, institutional/community, and societal), was used to structure a narrative review of the factors related to access to menstrual resources. The SEM offers a novel approach within Critical Menstruation Studies that leads to a better understanding of how access to resources affects menstrual health and the menstrual experience in the US and Scotland. This review is intended as an initial step towards collecting data about access to menstrual resources that can inform policy and legislation. It calls for advocates, activists, policymakers, and other interested stakeholders to explore opportunities for change at each of the levels of the SEM: individual, interpersonal, institutional/community, and societal. [ABSTRACT FROM AUTHOR]

After three years of global rampage, the COVID-19 epidemic, the most serious infectious disease to occur worldwide since the 1918 influenza pandemic, is nearing its end. From the global experience, medical control and social control are the two main dimensions in the prevention and control of COVID-19. From the perspective of "two types of control", namely medical control and social control, this paper finds that the political system, economic structure, and cultural values of the United States greatly limit the government's ability to impose social control, forcing it to adopt medical control to fight the virus in a single dimension. In contrast, China's political system, economic structure, and cultural values allow its government to adopt stringent, extensive, and frequent social control, as well as medical control to fight the virus. This approach departs from the traditional pathway of fighting the epidemic, i.e., "infection–treatment–immunization", thereby outpacing the evolution of the virus and controlling its spread more rapidly. This finding helps explain why the Chinese government adopted a strict "zeroing" and "dynamic zeroing" policy during the first three years, at the cost of enormous economic, social, and even political legitimacy. It was not until late 2022, when the Omicron variant with the waning virulence became prevalent, that China chose to "coexist" with the virus, thus avoiding a massive epidemic-related death. While the United States adopted a pulsed-style strategy at the beginning of the epidemic, i.e., "relaxation–suppression–relaxation–suppression", and began to "coexist" with the virus in just one year, resulting in a large number of excess deaths associated with the epidemic. The study contributes to explaining the difference in the interplay between public health priorities and COVID-19 response strategies in China and the United States, based on the specific public health context and the perspective of "medical control" and "social control". [ABSTRACT FROM AUTHOR]

In response to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021, covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all 6 surveys. Response rates varied widely among demographic groups and were lower among participants from certain racial and ethnic minority populations, participants with low income or educational attainment, and participants with a Spanish language preference. Survey modifications improved participant response rates between the first and last surveys (13.9% to 16.1%, P  < 0.001). This paper describes a data set with longitudinal COVID-19 survey data in a large, diverse population that will enable researchers to address important questions related to the pandemic, a data set that is of additional scientific value when combined with the program's other data sources. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a devastating impact on the world at large with over 750 million cases and almost 7 million deaths reported thus far. Of those, over 100 million cases and 1 million deaths have occurred in the United States of America (USA). The mental health of the general population has been impacted by several aspects of the pandemic including lockdowns, media sensationalism, social isolation, and spread of the disease. In this paper, we examine the associations that social isolation and COVID-19 infection and related death had with the prevalence of anxiety and depression in the general population of the USA in a state-by-state multiple time-series analysis. Vector Error Correction Models are estimated and we subsequently evaluated the coefficients of the estimated models and calculated their impulse response functions for further interpretation. We found that COVID-19 incidence was positively associated with anxiety across the studied period for a majority of states. Variables related to social isolation had a varied effect depending on the state being considered. [ABSTRACT FROM AUTHOR]

Introduction: The epidemic of gun violence in the United States (US) is exacerbated by frequent mass shootings. In 2021, there were 698 mass shootings in the US, resulting in 705 deaths and 2,830 injuries. This is a companion paper to a publication in JAMA Network Open, in which the nonfatal outcomes of victims of mass shootings have been only partially described. Methods: We gathered clinical and logistic information from 31 hospitals in the US about 403 survivors of 13 mass shootings, each event involving greater than 10 injuries, from 2012-19. Local champions in emergency medicine and trauma surgery provided clinical data from electronic health records within 24 hours of a mass shooting. We organized descriptive statistics of individual-level diagnoses recorded in medical records using International Classification of Diseases codes, according to the Barell Injury Diagnosis Matrix (BIDM), a standardized tool that classifies 12 types of injuries within 36 body regions. Results: Of the 403 patients who were evaluated at a hospital, 364 sustained physical injuries—252 by gunshot wound (GSW) and 112 by non-ballistic trauma—and 39 were uninjured. Fifty patients had 75 psychiatric diagnoses. Nearly 10% of victims came to the hospital for symptoms triggered by, but not directly related to, the shooting, or for exacerbations of underlying conditions. There were 362 gunshot wounds recorded in the Barell Matrix (1.44 per patient). The Emergency Severity Index (ESI) distribution was skewed toward higher acuity than typical for an emergency department (ED), with 15.1% ESI 1 and 17.6% ESI 2 patients. Semi-automatic firearms were used in 100% of these civilian public mass shootings, with 50 total weapons for 13 shootings (Route 91 Harvest Festival, Las Vegas. 24). Assailant motivations were reported to be associated with hate crimes in 23.1%. Conclusion: Survivors of mass shootings have substantial morbidity and characteristic injury distribution, but 37% of victims had no GSW. Law enforcement, emergency medical systems, and hospital and ED disaster planners can use this information for injury mitigation and public policy planning. The BIDM is useful to organize data regarding gun violence injuries. We call for additional research funding to prevent and mitigate interpersonal firearm injuries, and for the National Violent Death Reporting System to expand tracking of injuries, their sequelae, complications, and societal costs. [ABSTRACT FROM AUTHOR]

Background: Community health needs and assets assessment is a means of identifying and describing community health needs and resources, serving as a mechanism to gain the necessary information to make informed choices about community health. The current review of the literature was performed in order to shed more light on concepts, rationale, tools and uses of community health needs and assets assessment., Methods: We conducted a scoping review of the literature published in English using PubMed, Embase, Scopus, Web of Science, PDQ evidence, NIH database, Cochrane library, CDC library, Trip, and Global Health Library databases until March 2021., Results: A total of 169 articles including both empirical papers and theoretical and conceptual work were ultimately retained for analysis. Relevant concepts were examined guided by a conceptual framework. The empirical papers were dominantly conducted in the  United States. Qualitative, quantitative and mixed-method approaches were used to collect data on community health needs and assets, with an increasing trend of using mixed-method approaches. Almost half of the included empirical studies used participatory approaches to incorporate community inputs into the process., Conclusion: Our findings highlight the need for having holistic approaches to assess community's health needs focusing on physical, mental and social wellbeing, along with considering the broader systems factors and structural challenges to individual and population health. Furthermore, the findings emphasize assessing community health assets as an integral component of the process, beginning foremost with community capabilities and knowledge. There has been a trend toward using mixed-methods approaches to conduct the assessment in recent years that led to the inclusion of the voices of all community members, particularly vulnerable and disadvantaged groups. A notable gap in the existing literature is the lack of long-term or longitudinal-assessment of the community health needs assessment impacts., (© 2023. The Author(s).)

Competing Interests: We declare no competing interests. This work was funded by the Sean N Parker Center for Allergy and Asthma Research at Stanford University (Palo Alto, CA, USA). The funding source had no role in the writing of the report and in the decision to submit the paper for publication. All authors contributed equally.

PURPOSE: The liberalization of cannabis policies has the potential to affect the use of other substances and the harms from using them, particularly alcohol. Although a previous review of this literature found conflicting results regarding the relationship between cannabis policy and alcohol-related outcomes, cannabis policies have continued to evolve rapidly in the years since that review. SEARCH METHODS: The authors conducted a narrative review of studies published between January 1, 2015, and December 31, 2020, that assessed the effects of cannabis policies on the use of alcohol in the United States or Canada. SEARCH RESULTS: The initial search identified 3,446 unique monographs. Of these, 23 met all inclusion criteria and were included in the review, and five captured simultaneous or concurrent use of alcohol and cannabis. DISCUSSION AND CONCLUSIONS: Associations between cannabis policy liberalization and alcohol use, alcohol-related outcomes, and the co-use of alcohol and cannabis were inconclusive, with studies finding positive associations, no associations, and negative associations. Although several studies found that cannabis policy liberalization was associated with decreases in alcohol use measures, these same studies showed no impact of the cannabis policy on cannabis use itself. The lack of a consistent association was robust to subject age, outcome measure (e.g., use, medical utilization, driving), and type of cannabis policy; however, this may be due to the small number of studies for each type of outcome. This paper discusses several notable limitations of the evidence base and offers suggestions for improving consistency and comparability of research going forward, including a stronger classification of cannabis policy, inclusion of measures of the alcohol policy environment, verification of the impact of cannabis policy on cannabis use, and consideration of mediation effects. [ABSTRACT FROM AUTHOR]

Objective: During the COVID-19 pandemic in the United States, mitigation measures were implemented on a state-by-state basis. Governors were responsible for establishing interventions appropriate for their states and the timing of implementation. This paper evaluated the association between the presence and timing of a mask mandate and the severity of the COVID-19 epidemic by state. Methods: The states were divided into 3 categories based on when the governors of each state implemented a mask mandate: Early (mask mandate implemented between March 2020 and June 2020), Late (July 2020-December 2020), and Never (no mask mandate implemented). The rates of hospitalizations and mortality (per 100 000) were assessed at the different time points during the pandemic across these categories from March to December 2020. Results: The mortality rates across all 3 groups were observed to be highest in the beginning and toward the end of the pandemic in 2020 with the peak observed in the Early group between April and May 2020. Also, the rates of hospitalization increased steadily across all groups. The Early mask group was comprised of 86.7% and 13.3% states with Democratic and Republican governors respectively, and no states in the Never category had Democratic governors. Conclusion: These results support the benefit of implementing a mask mandate to minimize the impact of the COVID-19 pandemic and the role of political affiliation of governors on that impact. [ABSTRACT FROM AUTHOR]

The emergence of COVID-19 immediately affected higher education, and the closure of campuses at the start of the pandemic in March of 2020 forced educational institutions to quickly adapt to changing circumstances. Schools of public health faced challenges not only of shifting to remote learning and work environments, but also uniquely redirecting public health research and service efforts toward COVID-19. This paper offers a case study of how the Milken Institute School of Public Health at the George Washington University (GWSPH), the only school of public health in the nation's capital, initially adapted to the COVID-19 pandemic. Using a modified version of the Public Health Preparedness and Response Core Competency Model created by the Association of Schools and Programs of Public Health and the Centers for Disease Control and Prevention, we analyze how GWSPH worked in three areas-research, education, service/operations. We reviewed this initial response across four domains: model leadership; communication and management of information; planning and improving practice; and protecting worker (and student) health and safety. The adaptation of the model and the analysis of GWSPH's initial response to the pandemic can be useful to other schools of public health and health sciences in the United States and beyond, in preparing for all hazards. We hope that such analysis also informs the current concerns of schools such as return to in-person education as well as planning for future public health crises., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Hyder, Thorpe, Migliaccio, Kazeem and Goldman.)

The COVID-19 global pandemic has significantly impacted every aspect of life all over the world. The United States is reported to have suffered more than 20% of the global casualties from this pandemic. It is imperative to investigate the growth dynamics of the disease in the US based on varying geographical and governmental factors that best manifest itself in each State of the Country. This paper utilizes a hybrid machine learning and continuum deformation-based approach for analyzing the stability and growth rate of the pandemic. To this end, principal stress values of the pandemic continuum body are obtained using Mohr's Circle method and overlapping, moving windows of data are analysed successively. This helps in finding the correlations between the growth rate and Governments' action/Public's reaction. Government actions include "state of emergency", "shelter at place", and "phase declarations". We also consider the vaccination rate milestones, which shows us the coordinated Governments' action/Public's reaction. Finally, a number of recommendations are made to the Governments and people for better management of future pandemics. [ABSTRACT FROM AUTHOR]

Based on the latest coronavirus corpus of the English corpus collection list (English-corpora), this paper aims to do the data mining of the China-related reports reported by the media of the United States, Canada, Britain, and Australia in public health emergencies. It tries to analyze how the English world media construct China's national image on the basis of the theory of evidentiality. It is found that the national media in the English world media report on China's national image show a dynamic process of "concern-worry-stigmatization-dumping." The western media made the construction of China's national image by subjective reports, objective but negative media discourse, and "double standards.", Competing Interests: The author declares that there are no conflicts of interest regarding the present study., (Copyright © 2022 Dian Zhang.)

As coronavirus disease 2019 (COVID-19) spread through the United States in 2020, states began to set up alert systems to inform policy decisions and serve as risk communication tools for the general public. Many of these systems included indicators based on an assessment of trends in numbers of reported cases. However, when cases are indexed by date of disease onset, reporting delays complicate the interpretation of trends. Despite a foundation of statistical literature with which to address this problem, these methods have not been widely applied in practice. In this paper, we develop a Bayesian spatiotemporal nowcasting model for assessing trends in county-level COVID-19 cases in Ohio. We compare the performance of our model with the approach used in Ohio and the approach included in decision support materials from the Centers for Disease Control and Prevention. We demonstrate gains in performance while still retaining interpretability using our model. In addition, we are able to fully account for uncertainty in both the time series of cases and the reporting process. While we cannot eliminate all of the uncertainty in public health surveillance and subsequent decision-making, we must use approaches that embrace these challenges and deliver more accurate and honest assessments to policy-makers., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Presents an abstract of the paper `The Community Health Awareness Projects: CHAPs,' by Bret Edward Sherman, a semifinalist paper in the contest for the 1989 Secretary's Award for Innovations in Health Promotion and Disease Prevention.

Childhood obesity is a public health concern in the United States. Consequences of childhood obesity include metabolic disease and heart, lung, kidney, and other health-related comorbidities. Therefore, the early determination of obesity risk is needed and predicting the trend of a child's body mass index (BMI) at an early age is crucial. Early identification of obesity can lead to early prevention. Multiple methods have been tested and evaluated to assess obesity trends in children. Available growth charts help determine a child's current obesity level but do not predict future obesity risk. The present methods of predicting obesity include regression analysis and machine learning-based classifications and risk factor (threshold)-based categorizations based on specific criteria. All the present techniques, especially current machine learning-based methods, require longitudinal data and information on a large number of variables related to a child's growth (e.g., socioeconomic, family-related factors) in order to predict future obesity-risk. In this paper, we propose three different techniques for three different scenarios to predict childhood obesity based on machine learning approaches and apply them to real data. Our proposed methods predict obesity for children at five years of age using the following three data sets: (1) a single well-child visit, (2) multiple well-child visits under the age of two, and (3) multiple random well-child visits under the age of five. Our models are especially important for situations where only the current patient information is available rather than having multiple data points from regular spaced well-child visits. Our models predict obesity using basic information such as birth BMI, gestational age, BMI measures from well-child visits, and gender. Our models can predict a child's obesity category (normal, overweight, or obese) at five years of age with an accuracy of 89%, 77%, and 89%, for the three application scenarios, respectively. Therefore, our proposed models can assist healthcare professionals by acting as a decision support tool to aid in predicting childhood obesity early in order to reduce obesity-related complications, and in turn, improve healthcare. [ABSTRACT FROM AUTHOR]

Background: Maternal mortality in the United States is a public health crisis and national emergency. Missed or delayed recognition of preventable life-threatening symptoms and untimely treatment of preventable high-risk medical conditions have been cited as key contributors to the nation's worsening mortality rates. Effective strategies are urgently needed to address this maternal health crisis, particularly for Black birthing populations. Morbidity and Mortality Assessment: Lifting Outcomes Via Education (MAMA LOVE) is a web-based platform that focuses on the identification of maternal morbidity and mortality risk factors. Objective: The purpose of this paper is to present the conceptualization, development, heuristics, and utility evaluation of the web-based maternal mortality risk assessment and educational tool MAMA LOVE. Methods: A user-centered design approach was used to gain feedback from clinical experts and potential end users to ensure that the tool would be effective among groups most at risk for maternal morbidity and mortality. A heuristic evaluation was conducted to evaluate usability and need within the current market. Algorithms describing key clinical, mental health, and social conditions were designed using digital canvas software (Miro) and incorporated into the final wireframes of the revised prototype. The completed version of MAMA LOVE was designed in Figma and built with the SurveyJS platform. Results: The creation of the MAMA LOVE tool followed three distinct phases: (1) the content development and creation of an initial prototype; (2) the feedback gathering and usability assessment of the prototype; and (3) the design, development, and testing of the final tool. The tool determines the corresponding course of action using the algorithm developed by the authors. A total of 38 issues were found in the heuristic evaluation of the web tool's initial prototype. Conclusions: Maternal morbidity and mortality is a public health crisis needing immediate effective interventions. In the current market, there are few digital resources available that focus specifically on the identification of dangerous symptoms and risk factors. MAMA LOVE is a tool that can address that need by increasing knowledge and providing resources and information that can be shared with health care professionals. [ABSTRACT FROM AUTHOR]

Public health, once the gem of American social programs, has turned to dross. During the 20th century, the public-health sector wiped smallpox and polio off the U.S. map; virtually eliminated rickets, rubella, and goiter; stopped epidemic typhoid and yellow fever; and brought tuberculosis--once the leading cause of death in U.S. cities--under control. It sought, with considerable success, to reform social and economic structures so the poor would have the same chance at decent health as the wealthy. But public health seems to be a phenomenon of the past, like the Great Society or the New Deal. One testament to the failure is the activity of American health officials, the products of public-health training programs. In the past six years, Americans have seen officials redirect tax-levy funds to pay for ludicrous "biopreparedness" exercises in anticipation of wholly fabricated epidemic dangers, concocted by an administration unable to admit its mistakes after September 11. They have heard officials endorse useless "virginity pledges" for teenagers. They have seen them invoke federal quarantine law--claiming there was a hazard to the public--to arrest one man who had flown on an airplane while carrying noninfectious tuberculosis. But in the past six years, no health official has argued forcefully for social changes that would genuinely improve the public's health on a significant scale. They don't demand reforms of the sort that would make Americans more like those developed countries (Denmark, France, etc.) where infant-mortality rates are more than 20 percent lower than theirs and where life expectancy is longer--changes like more affordable housing, a guaranteed minimum income, a higher minimum wage, restoration of workplace-safety oversights emasculated by big-business-friendly government, or better and cheaper public transportation systems. The author states that health educators must revise their teaching radically and develop curricula that face the vexatious positioning of health as a moral issue.

Objectives: (i) To determine the current state of online grocery shopping, including individuals' motivations for shopping for groceries online and types of foods purchased; and (ii) to identify the potential promise and pitfalls that online grocery shopping may offer in relation to food and beverage purchases. Design: PubMed, ABI/INFORM and Google Scholar were searched to identify published research. Setting: To be included, studies must have been published between 2007 and 2017 in English, based in the USA or Europe (including the UK), and focused on: (i) motivations for online grocery shopping; (ii) the cognitive/psychosocial domain; and (iii) the community or neighbourhood food environment domain. Subjects: Our search yielded twenty-four relevant papers. Results: Findings indicate that online grocery shopping can be a double-edged sword. While it has the potential to increase healthy choices via reduced unhealthy impulse purchases, nutrition labelling strategies, and as a method to overcome food access limitations among individuals with limited access to a brick-and-mortar store, it also has the potential to increase unhealthy choices due to reasons such as consumers' hesitance to purchase fresh produce online. Conclusions: Additional research is needed to determine the most effective ways to positively engage customers to use online grocery shopping to make healthier choices. [ABSTRACT FROM AUTHOR]

This paper estimates the long-term impact of childhood exposure to a preventative public health programme on adult human capital. From 1908 to 1933, local governments in the United States instituted county-level health departments (CHDs) that provided preventative health services geared towards children. This paper estimates the long-term benefits of childhood exposure to this public programme using variation in CHD location, timing and age of exposure. CHD operation before the age of 5 increases men's later-life earnings by 2% to 5%. Exposed boys not only perform better than later- and never-treated groups, but, after adding household fixed effects, exposed men earn more than their brothers. [ABSTRACT FROM AUTHOR]

In the wake of the September 2001 attacks, the U.S. government founded the Department of Homeland Security (DHS) with responsibility to develop a National Infrastructure Protection Plan for securing critical infrastructures and key resources. DHS established interdisciplinary networks of academic expertise administered through Centers of Excellence across the country, each addressing a different aspect of homeland defense. The National Center for Food Protection and Defense (NCFPD), created in 2004, organized over 150 experts around five theme groups: Agent Behavior, Event Modeling, Systems Strategies, Risk Communication, and Educational Programs. The fifth theme group, Educational Programs, was the focus of a special library project to assist experts in delivering "high-quality education and training programs to develop a cadre of professionals equipped to deal with future threats to the food system." An initial database provided National Center for Food Protection and Defense experts with a listing of educational resources and their uniform resource locators (URLs). In 2009, NCFPD formed a team of librarians and subject experts to finalize the framework for a working collection of food protection educational resources. The framework consisted of 1) a scope of work for the database, 2) descriptive metadata elements and classification decisions, and 3) a vetting instrument to maintain the utility and currency of selected information. This paper describes the work performed by the database team to create criteria for inclusion and classification of resources consistent with NCFPD end-users' evolving needs. A content validity method is described that was used to gauge whether the team's conceptual definition of the domain of information was congruent with that of the expert community being served. (Contains 9 tables.)

The article discusses the development of the "American Journal of Public Health (AJPH)" in the U.S. The journal was first published in 1911, however, it was not the first serial publication of the American Public Health Association (APHA). During the early days of AJPH, mostly of their articles were from APHA meetings. Contributions from different sectors started in 1956. Several years after, the publication has changed in character and content. Advances in science and technology are considered the main force behind AJPH's growth.

Although there is substantial agreement how microeconomic forces—income, risk aversion—shape public health outcomes, there is substantial disagreement about the relationship between macroeconomic forces—market liberalization and economic freedom—on public health. In this paper, we investigate the relationship between public health, economic freedom, and wealth using a large sample of metropolitan‐level data from the United States. We find that economic freedom does have a statistically significant and positive impact on general, physical, and mental health, but the overall results are small in magnitude. When we disaggregate the three areas of economic freedom, we find that areas with lower government spending and freer labor markets have the strongest positive effect on physical and mental health. However, our results are strongest for the richest group of respondents, suggesting that the economic freedom‐health relationship is perhaps indirect, and shown through income. [ABSTRACT FROM AUTHOR]

Presents a list of research papers that have affected the author's way of making clinical decisions about the diagnosis and treatment of a disease. Background of the author; Reference of the research paper "A Critical Review of Adult Health Maintenance," Part 1, "Prevention of Atherosclerotic Diseases;" Establishment of theory that preventive medicine practice must be based on evidence; Growth of U.S. Preventive Services Task Force.

The Controlling Asthma in American Cities Project (CAACP) was designed to improve the control of asthma in inner-city populations of children with a disparate burden of symptoms and adverse outcomes. As with many chronic diseases, asthma is the manifestation of multiple biologic, environmental, and social determinants. In addition to appropriate medical management, individuals with asthma must have logistical, financial, and cultural access to environments that allow avoidance of asthma triggers and encourage good asthma management practices. In recognition of this complexity, the CAACP required the seven project sites to coordinate and synchronize multiple interventions (education, healthcare access, medical management, trigger reduction) at multiple levels (individual, home, school, community, and policy) through the collaboration of relevant groups, institutions, and individuals. This paper describes the 'program theory' of the CAACP project-the assumptions about how the project worked, how the components were linked, and what outcomes were anticipated. It relates the subsequent papers in the supplement to the program theory and describes how the papers can inform and guide other community-based interventions, and advance the translation of scientific knowledge to effective interventions in communities of need. [ABSTRACT FROM AUTHOR]

This analysis presents a detailed defense of my epidemiologic research in the May 17, 2003 British Medical Journal that found no significant relationship between environmental tobacco smoke (ETS) and tobacco-related mortality. In order to defend the honesty and scientific integrity of my research, I have identified and addressed in a detailed manner several unethical and erroneous attacks on this research. Specifically, I have demonstrated that this research is not "fatally flawed," that I have not made "inappropriate use" of the underlying database, and that my findings agree with other United States results on this relationship. My research suggests, contrary to popular claims, that there is not a causal relationship between ETS and mortality in the U.S. responsible for 50,000 excess annual deaths, but rather there is a weak and inconsistent relationship. The popular claims tend to damage the credibility of epidemiology. In addition, I address the omission of my research from the 2006 Surgeon General's Report on Involuntary Smoking and the inclusion of it in a massive U.S. Department of Justice racketeering lawsuit. I refute erroneous statements made by powerful U.S. epidemiologists and activists about me and my research and I defend the funding used to conduct this research. Finally, I compare many aspect of ETS epidemiology in the U.S. with pseudoscience in the Soviet Union during the period of Trofim Denisovich Lysenko. Overall, this paper is intended to defend legitimate research against illegitimate criticism by those who have attempted to suppress and discredit it because it does not support their ideological and political agendas. Hopefully, this defense will help other scientists defend their legitimate research and combat "Lysenko pseudoscience." [ABSTRACT FROM AUTHOR]

Focuses on the operation of an internal investigation on the approach to risk assessment by the U.S. Environmental Protection Agency (EPA). Conservatism in risk assessment to protect against uncertainty; Position of EPA as a public health agency; Use of technologies to improve risk assessments.

Background: Since COVID-19 first appeared in the United States (US) in January 2020, US states have pursued a wide range of policies to mitigate the spread of the virus and its economic ramifications. Without unified federal guidance, states have been the front lines of the policy response.Main Text: We created the COVID-19 US State Policy (CUSP) database ( https://statepolicies.com/ ) to document the dates and components of economic relief and public health measures issued at the state level in response to the COVID-19 pandemic. Documented interventions included school and business closures, face mask mandates, directives on vaccine eligibility, eviction moratoria, and expanded unemployment insurance benefits. By providing continually updated information, CUSP was designed to inform rapid-response, policy-relevant research in the context of the COVID-19 pandemic and has been widely used to investigate the impact of state policies on population health and health equity. This paper introduces the CUSP database and highlights how it is already informing the COVID-19 pandemic response in the US.Conclusion: CUSP is the most comprehensive publicly available policy database of health, social, and economic policies in response to the COVID-19 pandemic in the US. CUSP documents widespread variation in state policy decisions and implementation dates across the US and serves as a freely available and valuable resource to policymakers and researchers. [ABSTRACT FROM AUTHOR]

As coronavirus disease 2019 (COVID-19) spread through the United States in 2020, states began to set up alert systems to inform policy decisions and serve as risk communication tools for the general public. Many of these systems included indicators based on an assessment of trends in numbers of reported cases. However, when cases are indexed by date of disease onset, reporting delays complicate the interpretation of trends. Despite a foundation of statistical literature with which to address this problem, these methods have not been widely applied in practice. In this paper, we develop a Bayesian spatiotemporal nowcasting model for assessing trends in county-level COVID-19 cases in Ohio. We compare the performance of our model with the approach used in Ohio and the approach included in decision support materials from the Centers for Disease Control and Prevention. We demonstrate gains in performance while still retaining interpretability using our model. In addition, we are able to fully account for uncertainty in both the time series of cases and the reporting process. While we cannot eliminate all of the uncertainty in public health surveillance and subsequent decision-making, we must use approaches that embrace these challenges and deliver more accurate and honest assessments to policy-makers. [ABSTRACT FROM AUTHOR]

Background: In this paper, we conduct an analysis of the COVID-19 data in the United States in 2020 via functional data analysis methods. Through this research, we investigate the effectiveness of the practice of public health measures, and assess the correlation between infections and deaths caused by the COVID-19. Additionally, we look into the relationship between COVID-19 spread and geographical locations, and propose a forecasting method to predict the total number of confirmed cases nationwide. Methods: The functional data analysis methods include functional principal analysis methods, functional canonical correlation analysis methods, an expectation-maximization (EM) based clustering algorithm and a functional time series model used for forecasting. Results: It is evident that the practice of public health measures helps to reduce the growth rate of the epidemic outbreak over the nation. We have observed a high canonical correlation between confirmed and death cases. States that are geographically close to the hot spots are likely to be clustered together, and population density appears to be a critical factor affecting the cluster structure. The proposed functional time series model gives more reliable and accurate predictions of the total number of confirmed cases than standard time series methods. Conclusions: The results obtained by applying the functional data analysis methods provide new insights into the COVID-19 data in the United States. With our results and recommendations, the health professionals can make better decisions to reduce the spread of the epidemic, and mitigate its negative effects to the national public health. [ABSTRACT FROM AUTHOR]

The K6 scale is a shortened version of the K10, a 10-question scale originally developed to provide an efficient population-level screen for serious mental disorders (SMI) in the USA. Evidence that the six-item shortened version performed as well as the original 10-item version, coupled with strong psychometric properties, led to rapid dissemination and replicated validation of the K6 in a number of other countries around the world. Based on these results, the K6 is now often included in large general-purpose government health tracking surveys in a number of different countries. Until now, though, the scoring rules for the K6 in these surveys were inconsistent. The first paper in this special issue introduces the K6 scale and summarizes the results of a series of investigations to resolve these inconsistencies by providing optimal scoring rules for the K6 in 14 countries. Subsequent papers explore the usefulness of the K6 to screen for serious emotional disturbance among adolescents and report findings from validation efforts based on independent diagnostic assessments as well as of other measures of impairment and disability (World Health organization Disability Assessment Scale). Finally a highly innovative analysis using a Bayesian multilevel modeling approach is presented, designed to estimate the prevalence of SMI in small areas, such as cities, states, or schools, from surveys carried out in a larger population that includes only relatively small samples of respondents in each of the areas in which prevalence estimates are to be made. Taken together, these studies demonstrate that the K6 is an efficient and useful screening tool. The psychometric and methodological explorations will hopefully stimulate additional interest in the use of short screening scales in large-scale general health surveys to supplement the more in-depth information obtained in periodic psychiatric epidemiological surveys on the basis of diagnostic interviews. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article focuses on the American Public Health Association (APHA) and the "American Journal of Public Health." APHA has endured political and fiscal adversity, adopted a global public health mission, worked through staff departures and embraced a change in leadership with the appointment of Georges C. Benjamin as its newest executive director. In moving all of the opinion pieces, departments, feature articles and forums to the front section of the journal we were both radical and pragmatic. But listing the types of papers or table-of-contents is not the same as defining or developing a written concept statement for the front section of the journal. The challenge of finding a compelling image to feature on the cover effectively symbolizes the underlying tensions involved in composing the physical layout of the journal. And so, the cover of every issue of the journal serves as the rallying point for a public health topic we hope to advance through the issue. If we are to contribute to social change that eliminates health and other inequalities, we need to continue to enlist committed and devoted public health partners inside and outside the health sector to work with us.

Background: The Implementation Research Institute (IRI) provides two years of training in mental health implementation science for 10 new fellows each year. The IRI is supported by a National Institute of Mental Health (NIMH) R25 grant and the Department of Veterans Affairs (VA). Fellows attend two annual week-long trainings at Washington University in St. Louis. Training is provided through a rigorous curriculum, local and national mentoring, a 'learning site visit' to a federally funded implementation research project, pilot research, and grant writing. Methods: This paper describes the rationale, components, outcomes to date, and participant experiences with IRI. Results: IRI outcomes include 31 newly trained implementation researchers, their new grant proposals, contributions to other national dissemination and implementation research training, and publications in implementation science authored by the Core Faculty and fellows. Former fellows have obtained independent research funding in implementation science and are beginning to serve as mentors for more junior investigators. Conclusions: Based on the number of implementation research grant proposals and papers produced by fellows to date, the IRI is proving successful in preparing new researchers who can inform the process of making evidencebased mental healthcare more available through real-world settings of care and who are advancing the field of implementation science. [ABSTRACT FROM AUTHOR]

Population ageing is a phenomenon affecting developed and developing countries alike and represents a major global challenge. This paper is concerned with the impact of ageing populations, in developing countries, on the future provision of health and social care services to the growing elderly population. As well as reviewing previous research and available data, the paper presents the findings of a series of qualitative interviews with policy makers and clinicians in a small number of developing countries in various parts of the world. The paper argues that developing countries cannot expect to see major increases in financial resources available to health and social care for the foreseeable future. Thus, the key issue is establishing how best the available public funding for delivering health and social care services to the elderly can best be used to maximize public value at a time when public services around the world face ongoing austerity measures. The paper focuses on a number of key strategic themes to achieve this which are as follows: the strengthening of public health infrastructure and capabilities; the reconfiguration of existing health systems; a stronger focus on elderly medicine as a distinct specialty; a strengthened role for mobile healthcare, particularly in rural areas; the development of models of generic health and social care assistants; the promotion of community based social care; the utilization of appropriate public/ private health care partnerships. [ABSTRACT FROM AUTHOR]

The acquired immune deficiency syndrome (AIDS) epidemic was first recognized in 1981, and it quickly became a public health emergency. In a 1987 paper in the American Journal of Epidemiology (Am J Epidemiol. 1987;126(2): 310-318), Richard Kaslow et al. described the launch of the Multicenter AIDS Cohort Study (MACS), a cohort study of homosexual men in 4 US cities, the purpose of which was to better understand the natural history of AIDS and its determinants. The MACS enrolled participants through a range of community contacts. These efforts facilitated rapid recruitment, but given the targeted approaches, participants tended to comprise high-risk social networks. At baseline, 4%-26% of participants at the 4 sites reported having a sexual partner who had developed AIDS. Kaslow et al. also described baseline testing for the causative agent of AIDS, the human immunodeficiency virus (HIV). HIV sero- prevalence was remarkably high, ranging from 11 %-26% across age groups in Pittsburgh to 38%-53% in Los Angeles. The major turning point in the epidemic occurred in 1995-1996 when combination antiretroviral therapy was introduced, effectively blocking HIV replication and markedly reducing AIDS morbidity and mortality. The MACS cohort continues to be followed actively 3 decades after its launch and has proven to be an important resource for information on HIV infection and AIDS. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic precipitated catastrophic job loss, unprecedented unemployment rates, and severe economic hardship in renter households. As a result, housing precarity and the risk of eviction increased and worsened during the pandemic, especially among people of color and low-income populations. This paper considers the implications of this eviction crisis for health and health inequity, and the need for eviction prevention policies during the pandemic. Eviction and housing displacement are particularly threatening to individual and public health during a pandemic. Eviction is likely to increase COVID-19 infection rates because it results in overcrowded living environments, doubling up, transiency, limited access to healthcare, and a decreased ability to comply with pandemic mitigation strategies (e.g., social distancing, self-quarantine, and hygiene practices). Indeed, recent studies suggest that eviction may increase the spread of COVID-19 and that the absence or lifting of eviction moratoria may be associated with an increased rate of COVID-19 infection and death. Eviction is also a driver of health inequity as historic trends, and recent data demonstrate that people of color are more likely to face eviction and associated comorbidities. Black people have had less confidence in their ability to pay rent and are dying at 2.1 times the rate of non-Hispanic Whites. Indigenous Americans and Hispanic/Latinx people face an infection rate almost 3 times the rate of non-Hispanic whites. Disproportionate rates of both COVID-19 and eviction in communities of color compound negative health effects make eviction prevention a critical intervention to address racial health inequity. In light of the undisputed connection between eviction and health outcomes, eviction prevention, through moratoria and other supportive measures, is a key component of pandemic control strategies to mitigate COVID-19 spread and death.

The ability to produce timely and accurate flu forecasts in the United States can significantly impact public health. Augmenting forecasts with internet data has shown promise for improving forecast accuracy and timeliness in controlled settings, but results in practice are less convincing, as models augmented with internet data have not consistently outperformed models without internet data. In this paper, we perform a controlled experiment, taking into account data backfill, to improve clarity on the benefits and limitations of augmenting an already good flu forecasting model with internet-based nowcasts. Our results show that a good flu forecasting model can benefit from the augmentation of internet-based nowcasts in practice for all considered public health-relevant forecasting targets. The degree of forecast improvement due to nowcasting, however, is uneven across forecasting targets, with short-term forecasting targets seeing the largest improvements and seasonal targets such as the peak timing and intensity seeing relatively marginal improvements. The uneven forecasting improvements across targets hold even when “perfect” nowcasts are used. These findings suggest that further improvements to flu forecasting, particularly seasonal targets, will need to derive from other, non-nowcasting approaches. [ABSTRACT FROM AUTHOR]

Background: Assessing the consequences of research is an increasingly important task in research and innovation policy. This paper takes a broader view of those consequences than the conventional economic approach, placing researchers and their activities in the centre of the assessment process and examining results for professional practice and general education as well as contributions to knowledge.Methods: The paper uses historical and documentary analysis to illustrate the approach, focusing on U.S. biomedicine over the past century. At aggregate level, the analysis attributes portions of the change in aggregate health indicators to research and research-based institutions, through several available types of logic: either through correlations between timing of institutional changes and changes in the indicators or through direct or indirect causal connections.Results: The analysis shows that while biomedical research has certainly contributed to improved health in the United States, other factors have also contributed. In some ways the institutional structure of science-based medicine has worked against creating benefits for some groups in U.S. society.Conclusions: The paper concludes with a call for more strategic attention to dimensions of impact other than knowledge outcomes and for participatory planning for research. [ABSTRACT FROM AUTHOR]

The article presents news briefs regarding community health nursing. A report which has been released by the Centers for Disease Control and Prevention (CDC) regarding the Well-Integrated Screening and Evaluation for Women Across the Nation (WISEWOMAN) is discussed. Guidelines which have been provided by the American Nurses Association (ANA) regarding the way in which health care workers should respond to emergencies and disasters are mentioned.

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input. [ABSTRACT FROM AUTHOR]

Many countries and US states have mandatory statues that require reporting of HIV clinical data including genetic sequencing results to the public health departments. Because genetic sequencing is a part of routine care for HIV infected persons; health departments have extensive sequence collections spanning years and even decades of the HIV epidemic. How should these data be used (or not) in public health practice? This is a complex; multi-faceted question that weighs personal risks against public health benefit. The answer is neither straightforward nor universal. However; to make that judgement-of how genetic sequence data should be used in describing and combating the HIV epidemic-we need a clear image of what a phylogenetically enhanced HIV surveillance system can do and what benefit it might provide. In this paper, we present a positive case for how up-to-date analysis of HIV sequence databases managed by health departments can provide unique and actionable information of how HIV is spreading in local communities. We discuss this question broadly, with examples from the US, as it is globally relevant for all health authorities that collect HIV genetic data.

In this paper, we proposed a multi-method modeling approach to community-level spreading of COVID-19 disease. Our methodology was composed of interconnected age-stratified system dynamics models in an agent-based modeling framework that allowed for a granular examination of the scale and severity of disease spread, including metrics such as infection cases, deaths, hospitalizations, and ICU usage. Model parameters were calibrated using an optimization technique with an objective function to minimize error associated with the cumulative cases of COVID-19 during a training period between March 15 and October 31, 2020. We outlined several case studies to demonstrate the model's state- and local-level projection capabilities. We further demonstrated how model outcomes could be used to evaluate perceived levels of COVID-19 risk across different localities using a multi-criteria decision analysis framework. The model's two, three, and four week out-of-sample projection errors varied on a state-by-state basis, and generally increased as the out-of-sample projection period was extended. Additionally, the prediction error in the state-level projections was generally due to an underestimation of cases and an overestimation of deaths. The proposed modeling approach can be used as a virtual laboratory to investigate a wide range of what-if scenarios and easily adapted to future high-consequence public health threats. [ABSTRACT FROM AUTHOR]

Background: National health surveys linked to vital statistics and health care information provide a growing source of individual-level population health data. Pooling linked surveys across jurisdictions would create comprehensive datasets that are larger than most existing cohort studies, and that have a unique international and population perspective. This paper's objectives are to examine the feasibility of pooling linked population health surveys from three countries, facilitate the examination of health behaviours, and present useful information to assist in the planning of international population health surveillance and research studies., Data and Methods: The design, methodologies and content of the Canadian Community Health Survey (2003 to 2008), the United States National Health Interview Survey (2000, 2005) and the Scottish Health Survey (SHeS) (2003, 2008 to 2010) were examined for comparability and consistency. The feasibility of creating common variables for measuring smoking, alcohol consumption, physical activity and diet was assessed. Sample size and estimated mortality events were collected., Results: The surveys have comparable purposes, designs, sampling and administration methodologies, target populations, exclusions, and content. Similar health behaviour questions allow for comparable variables to be created across the surveys. However, the SHeS uses a more detailed risk factor evaluation for alcohol consumption and diet data. Therefore, comparisons of alcohol consumption and diet data between the SHeS and the other two surveys should be performed with caution. Pooling these linked surveys would create a dataset with over 350,000 participants, 28,424 deaths and over 2.4 million person-years of follow-up., Discussion: Pooling linked national population health surveys could improve population health research and surveillance. Innovative methodologies must be used to account for survey dissimilarities, and further discussion is needed on how to best access and analyze data across jurisdictions.

Objectives: This paper empirically examines whether and how COVID-19 may be activating bias and discrimination toward individuals of Asian descent., Methods: In March 2020, we used a national online survey to collect data from 1141 US residents. Using descriptive statistics and multivariate regression, we estimated the prevalence and COVID-19-related predictors of bias toward people of Asian descent., Results: We found over 40% of our sample reported they would engage in at least one discriminatory behavior toward people of Asian descent. Respondents who were fearful of COVID-19 (b = .09, p < 0.001) and had less accurate knowledge about the virus (b = - .07, p < 0.001) reported more negative attitudes toward Asians as did respondents with less trust in science (b = - .06, p < 0.001) and more trust in President Trump (b = .04, p < 0.001)., Conclusions: Public health leaders must confront fear of the virus, improve knowledge, and bolster trust in science as these factors may evoke negative attitudes toward Asians and increase prejudice and discrimination. Specifically, our findings warrant the adoption of public health campaigns that provide health information and build trust in scientific knowledge.