BACKGROUND: Because COVID-19 case data do not capture most SARS-CoV-2 infections, the actual risk of severe disease and death per infection is unknown. Integrating sociodemographic data into analysis can show consequential health disparities. METHODS: Data were merged from September 2020 to November 2021 from 6 national surveillance systems in matched geographic areas and analyzed to estimate numbers of COVID-19-associated cases, emergency department visits, and deaths per 100 000 infections. Relative risks of outcomes per infection were compared by sociodemographic factors in a data set including 1490 counties from 50 states and the District of Columbia, covering 71% of the US population. RESULTS: Per infection with SARS-CoV-2, COVID-19-related morbidity and mortality were higher among non-Hispanic American Indian and Alaska Native persons, non-Hispanic Black persons, and Hispanic or Latino persons vs non-Hispanic White persons; males vs females; older people vs younger; residents in more socially vulnerable counties vs less; those in large central metro areas vs rural; and people in the South vs the Northeast. DISCUSSION: Meaningful disparities in COVID-19 morbidity and mortality per infection were associated with sociodemography and geography. Addressing these disparities could have helped prevent the loss of tens of thousands of lives.

BACKGROUND: Transgender and gender diverse youth experience multiple disproportionate adverse sexual health outcomes. Sexual health education teaches knowledge, attitudes, and skills for promoting sexual health, including reducing risk for sexually transmitted infection, HIV acquisition, and unintended pregnancy. Provision of sexual health education may be protective, but research remains scarce. METHODS: We conducted a multi-stage thematic analysis of 33 in-depth interviews among transgender and gender diverse youth (ages 15-24) living in the southeastern United States on their sexual health education experiences. RESULTS: Our study participants described school-based sexual health education as unhelpful due to a lack of relevant information, inadequately prepared teachers, and a perceived negative tone toward sexuality. They reported relying on online sources of sexual health information, finding relevant content and community despite some limitations. Participants desired content and pedagogy that expands beyond binary and white-centric presentations of sexuality and gender and sought resources that provide relevant, accurate, and judgment-free information while holding positive framing around sexuality and gender. CONCLUSION: There is much work needed to improve the breadth, quality, and relevance of school-based sexual health education. Sexual health education can improve by strengthening critical media literacy skills of youth; raising staff cultural competency on gender, race, and sexual identity through training and supports; using culturally relevant and inclusive curricula; and partnering with community-based organizations. Transgender and gender diverse youth would benefit from sexual health education from multiple sources which is queer-friendly, affirms their existence, and provides information on gender, race, and sexuality in positive and expansive ways.

Perceived racism in school (i.e., a student's report of being treated badly or unfairly because of their race or ethnicity) is an important yet understudied determinant of adolescent health and well-being. Knowing how perceived racism influences adolescent health can help reduce health inequities. CDC's 2021 Adolescent Behaviors and Experiences Survey (ABES), an online survey of a probability-based, nationally representative sample of U.S. public- and private-school students in grades 9-12 (N = 7,705), was conducted during January-June 2021 to assess student behaviors during the COVID-19 pandemic. CDC analyzed data from ABES to measure perceived racism and the extent to which perceptions of racism are associated with demographic, mental health, and behavioral characteristics. Mental health and behavioral characteristics analyzed included mental health status; virtual connection with others outside of school; serious difficulty concentrating, remembering, or making decisions; and feeling close to persons at school. Demographic characteristics analyzed included sex, race and ethnicity, and grade. Prevalence of perceived racism and associations between perceived racism and demographic, mental health, and behavioral characteristics are reported overall and stratified by race and ethnicity. Approximately one third (35.6%) of U.S. high school students reported perceived racism. Perceived racism was highest among Asian (63.9%), Black (55.2%), and multiracial students (54.5%). Students who reported perceived racism had higher prevalences of poor mental health (38.1%); difficulty concentrating, remembering, or making decisions (44.1%); and not feeling close to persons at school (40.7%). Perceived racism was higher among those students who reported poor mental health than those who did not report poor mental health during the pandemic among Asian (67.9% versus 40.5%), Black (62.1% versus 38.5%), Hispanic (45.7% and 22.9%), and White students (24.5% versus 12.7%). A better understanding of how negative health outcomes are associated with student experiences of racism can guide training for staff and students to promote cultural awareness and antiracist and inclusivity interventions, which are critical for promoting safe school environments for all students.

Lesbian, gay, and bisexual (LGB) youths continue to experience more violence victimization and suicide risk than heterosexual youths; however, few studies have examined whether the proportion of LGB youths affected by these outcomes has varied over time, and no studies have assessed such trends in a nationally representative sample. This report analyzes national trends in violence victimization and suicide risk among high school students by self-reported sexual identity (LGB or heterosexual) and evaluates differences in these trends among LGB students by sex (male or female) and race/ethnicity (non-Hispanic black, non-Hispanic white, or Hispanic). Data for this analysis were derived from the 2015, 2017, and 2019 cycles of CDC's Youth Risk Behavior Survey (YRBS), a cross-sectional, school-based survey conducted biennially since 1991. Logistic regression models assessed linear trends in prevalence of violence victimization and indicators of suicide risk among LGB and heterosexual students during 2015-2019; in subsequent models, sex-stratified (controlling for race/ethnicity and grade) and race/ethnicity-stratified (controlling for sex and grade) linear trends were examined for students self-identifying as LGB during 2015-2019. Results demonstrated that LGB students experienced more violence victimization and reported more suicide risk behaviors than heterosexual youths. Among LGB youths, differences in the proportion reporting violence victimization and suicide risk by sex and race/ethnicity were found. Across analyses, very few linear trends in these outcomes were observed among LGB students. Results highlight the continued need for comprehensive intervention strategies within schools and communities with the express goal of reducing violence victimization and preventing suicide risk behaviors among LGB students.

During the COVID-19 vaccination rollout from March 2021- December 2022, the Centers for Disease Control and Prevention funded 110 primary and 1051 subrecipient partners at the national, state, local, and community-based level to improve COVID-19 vaccination access, confidence, demand, delivery, and equity in the United States. The partners implemented evidence-based strategies among racial and ethnic minority populations, rural populations, older adults, people with disabilities, people with chronic illness, people experiencing homelessness, and other groups disproportionately impacted by COVID-19. CDC also expanded existing partnerships with healthcare professional societies and other core public health partners, as well as developed innovative partnerships with organizations new to vaccination, including museums and libraries. Partners brought COVID-19 vaccine education into farm fields, local fairs, churches, community centers, barber and beauty shops, and, when possible, partnered with local healthcare providers to administer COVID-19 vaccines. Inclusive, hyper-localized outreach through partnerships with community-based organizations, faith-based organizations, vaccination providers, and local health departments was critical to increasing COVID-19 vaccine access and building a broad network of trusted messengers that promoted vaccine confidence. Data from monthly and quarterly REDCap reports and monthly partner calls showed that through these partnerships, more than 295,000 community-level spokespersons were trained as trusted messengers and more than 2.1 million COVID-19 vaccinations were administered at new or existing vaccination sites. More than 535,035 healthcare personnel were reached through outreach strategies. Quality improvement interventions were implemented in healthcare systems, long-term care settings, and community health centers resulting in changes to the clinical workflow to incorporate COVID-19 vaccine assessments, recommendations, and administration or referrals into routine office visits. Funded partners' activities improved COVID-19 vaccine access and addressed community concerns among racial and ethnic minority groups, as well as among people with barriers to vaccination due to chronic illness or disability, older age, lower income, or other factors.

This cross-sectional study assesses the reliability and validity of methods used to capture gender identity in Adolescent Brain Cognitive Development (ABCD) Study participants. | eng

BACKGROUND: Limited diagnostic capabilities, resources and health worker skills have deterred the advancement of birth defects surveillance systems in most low- and middle-income countries (LMICs). Empowering health workers to identify and diagnose major external birth defects (BDs) is crucial to establishing effective hospital-based BD surveillance. Makerere University-Johns Hopkins University (MU-JHU) Research Collaboration BD Surveillance System consists of three diagnostic levels: (1) surveillance midwives, (2) MU-JHU clinical team, and (3) U.S. Centers for Disease Control and Prevention (CDC) birth defects subject matter experts (SMEs) who provide confirmatory diagnosis. The diagnostic concordance of major external BDs by surveillance midwives or MU-JHU clinical team with CDC birth defects SMEs were estimated. METHODS: Study staff went through a series of trainings, including birth defects identification and confirmation, before surveillance activities were implemented. To assess the diagnostic concordance, we analyzed surveillance data from 2015 to 2021 for major external BDs: anencephaly, iniencephaly, encephalocele, spina bifida, craniorachischisis, microcephaly, anophthalmia/microphthalmia, anotia/microtia, cleft palate alone, cleft lip alone, cleft lip with cleft palate, imperforate anus, hypospadias, talipes equinovarus, limb reduction, gastroschisis, and omphalocele. Positive predictive value (PPV) as the proportion of BDs diagnosed by surveillance midwives or MU-JHU clinical team that were confirmed by CDC birth defects SMEs was computed. PPVs between 2015 and 2018 and 2019-2021 were compared to assess the accuracy of case diagnosis over time. RESULTS: Of the 204,332 infants examined during 2015-2021, 870 infants had a BD. Among the 1,245 BDs identified, 1,232 (99.0%) were confirmed by CDC birth defects SMEs. For surveillance midwives, PPV for 7 of 17 BDs was > 80%. For the MU-JHU clinical team, PPV for 13 of 17 BDs was > 80%. Among surveillance midwives, PPV improved significantly from 2015 to 2018 to 2019-2021, for microcephaly (+ 50.0%), cleft lip with cleft palate (+ 17.0%), imperforate anus (+ 30.0%), and talipes equinovarus (+ 10.8%). Improvements in PPV were also observed among MU-JHU clinical team; however, none were significant. CONCLUSION: The diagnostic accuracy of the midwives and clinical team increased, highlighting that BD surveillance, by front-line health care workers (midwives) in LMICs is possible when midwives receive comprehensive training, technical support, funding and continuous professional development.

During April 30-August 4, 2023, smoke originating from wildfires in Canada affected most of the contiguous United States. CDC used National Syndromic Surveillance Program data to assess numbers and percentages of asthma-associated emergency department (ED) visits on days with wildfire smoke, compared with days without wildfire smoke. Wildfire smoke days were defined as days when concentrations of particulate matter (particles generally ≤2.5 μm in aerodynamic diameter) (PM(2.5)) triggered an Air Quality Index ≥101, corresponding to the air quality categorization, "Unhealthy for Sensitive Groups." Changes in asthma-associated ED visits were assessed across U.S. Department of Health and Human Services regions and by age. Overall, asthma-associated ED visits were 17% higher than expected during the 19 days with wildfire smoke that occurred during the study period; larger increases were observed in regions that experienced higher numbers of continuous wildfire smoke days and among persons aged 5-17 and 18-64 years. These results can help guide emergency response planning and public health communication strategies, especially in U.S. regions where wildfire smoke exposure was previously uncommon.

INTRODUCTION: Most adults who currently use tobacco start before age 21. Comprehensive, cost-effective strategies and interventions to prevent initiation and encourage tobacco use cessation among youth are critical aspects of protecting youth from the harms of commercial tobacco. We describe changes in current tobacco product use among youth in 34 sites using data from the Global Youth Tobacco Survey (GYTS). METHODS: GYTS is a nationally representative school-based survey of students aged 13 to 15 years. The analysis included 34 sites that completed 2 survey waves during 2012-2020. Prevalence of current tobacco use was assessed for each country. Marginal effects in multivariable logistic regression models were used to estimate adjusted prevalence difference (aPD) between waves. RESULTS: The adjusted prevalence of current tobacco product use remained unchanged in more than 60% of the included sites. For any tobacco use, significant decreases were reported for Bhutan (aPD = -8.1; 95% CI, -12.9 to -3.4), Micronesia (aPD = -7.2; 95% CI, -9.7 to -4.7), San Marino (aPD = -7.0; 95% CI, -11.2 to -2.7), Togo (aPD = -2.7; 95% CI, -4.6 to -0.7), and Panama (aPD = -2.2; 95% CI, -4.1 to -0.4); significant increases were reported for Moldova, Albania, and Paraguay. Current e-cigarette use increased significantly in 7 of 10 sites. CONCLUSION: Data show that progress toward reducing tobacco use among youth stalled during 2012-2020, while e-cigarette use increased in a few sites with available data.

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information & Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information& Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

From August 2020 to June 2021, we assessed the efficacy of SumiShield 50WG (clothianidin), Fludora Fusion 56.25WP-SB (mixture of clothianidin and deltamethrin) and Actellic 300CS (pirimiphos-methyl) in experimental huts when partially sprayed against wild, free-flying populations of Anopheles gambiae s.l. in Tiassalé, Côte d'Ivoire. A one-month baseline period of mosquito collections was conducted to determine mosquito density and resting behavior in unsprayed huts, after which two treatments of partial indoor residual spraying (IRS) were tested: spraying only the top half of walls + ceilings or only the bottom half of walls + ceilings. These were compared to fully sprayed applications using the three IRS insecticide formulations, during twenty nights per month of collection for nine consecutive months. Mortality was assessed at the time of collection, and after a 24 h holding period (Actellic) or up to 120 h (SumiShield and Fludora Fusion). Unsprayed huts were used as a negative control. The efficacy of each partially sprayed treatment of each insecticide was compared monthly to the fully sprayed huts over the study period with a non-inferiority margin set at 10%. The residual efficacy of each insecticide sprayed was also monitored. A total of 2197 Anopheles gambiae s.l. were collected during the baseline and 17,835 during the 9-month period after spraying. During baseline, 42.6% were collected on the bottom half versus 24.3% collected on the top half of the walls, and 33.1% on the ceilings. Over the nine-month post treatment period, 73.5% were collected on the bottom half of the wall, 11.6% collected on the top half and 14.8% on the ceilings. For Actellic, the mean mortality over the nine-month period was 88.5% [87.7, 89.3] for fully sprayed huts, 88.3% [85.1, 91.4] for bottom half + ceiling sprayed walls and 80.8% [74.5, 87.1] for the top half + ceiling sprayed huts. For Fludora Fusion an overall mean mortality of 85.6% [81.5, 89.7] was recorded for fully sprayed huts, 83.7% [82.9, 84.5] for bottom half + ceiling sprayed huts and 81.3% [79.6, 83.0] for the top half + ceiling sprayed huts. For SumiShield, the overall mean mortality was 86.7% [85.3, 88.1] for fully sprayed huts, 85.6% [85.4, 85.8] for the bottom half + ceiling sprayed huts and 76.9% [76.6, 77.3] for the top half + ceiling sprayed huts. For Fludora Fusion, both iterations of partial IRS were non-inferior to full spraying. However, for SumiShield and Actellic, this was true only for the huts with the bottom half + ceiling, reflecting the resting site preference of the local vectors. The results of this study suggest that partial spraying may be a way to reduce the cost of IRS without substantially compromising IRS efficacy.

BACKGROUND: Centers for Disease Control recommends that the decision to provide sexually transmitted infection (STI)/human immunodeficiency virus (HIV) testing and presumptive treatment to patients who report sexual assault and abuse (SAA) be made on an individual basis. METHODS: The 2019 Centers for Medicare & Medicaid Services national Medicaid data set was used. The SAA visits were identified by International Classification of Diseases 10th Revision Clinical Modification (O9A4 for pregnancy-related sexual abuse, T74.2 for confirmed sexual abuse, and Z04.4 for alleged rape). The initial SAA visit was defined as the patient's first SAA-related visit. Medical services were identified by International Classification of Diseases 10th Revision Clinical Modification codes, Current Procedural Terminology codes, and National Drug Code codes. RESULTS: Of 55,113 patients at their initial SAA visits, 86.2% were female; 63.4% aged ≥13 years; 59.2% visited emergency department (ED); all STI/HIV tests were provided in ≤20% of visits; presumptive gonorrhea and chlamydia treatment was provided in 9.7% and 3.4% of visits, respectively; pregnancy test was provided in 15.7% of visits and contraception services was provided in 9.4% of visits; and diagnosed anxiety was provided in 6.4% of visits. Patients who visited ED were less likely to have STI testing and anxiety than those visited non-ED facilities, but more likely to receive presumptive treatment for gonorrhea, testing for pregnancy, and contraceptive services. About 14.2% of patients had follow-up SAA visits within 60 days after the initial SAA visit. Of 7821 patients with the follow-up SAA visits within 60 days, most medical services provided were chlamydia testing (13.8%), gonorrhea testing (13.5%), syphilis testing (12.8%), HIV testing (14.0%); diagnosed anxiety (15.0%), and posttraumatic stress disorder (9.8%). CONCLUSIONS: Current medical services during SAA visits for Medicaid patients are described in this evaluation. More collaboration with staff who handle SAA will improve SAA-related medical services.

The U.S. adolescent mental and behavioral health crisis is ongoing,* with high pre-COVID-19 pandemic baseline rates(†) (1) and further increases in poor mental health (2), suicide-related behaviors (3), and drug overdose deaths (4) reported during 2020-2021. CDC examined changes in U.S. emergency department (ED) visits for mental health conditions (MHCs) overall and for nine specific MHCs,(§) suicide-related behaviors (including suspected suicide attempts), and drug-involved overdoses (including opioids) among children and adolescents aged 12-17 years (adolescents) during January 2019-February 2023, overall and by sex. Compared with fall 2021, by fall 2022, decreases in weekly ED visits were reported among all adolescents, and females specifically, for MHCs overall, suicide-related behaviors, and drug overdoses; weekly ED visits among males were stable. During this same period, increases in weekly ED visits for opioid-involved overdoses were detected. Mean weekly ED visits in fall 2022 for suicide-related behaviors and MHCs overall were at or lower than the 2019 prepandemic baseline, respectively, and drug overdose visits were higher. Differences by sex were observed; levels among females were at or higher than prepandemic baselines for these conditions. These findings suggest some improvements as of fall 2022 in the trajectory of adolescent mental and behavioral health, as measured by ED visits; however, poor mental and behavioral health remains a substantial public health problem, particularly among adolescent females. Early identification and trauma-informed interventions, coupled with expanded evidence-based, comprehensive prevention efforts, are needed to support adolescents' mental and behavioral health.

In 2007, Hobfoll and coauthors described “Five Essential Elements of Immediate and Mid–Term Mass Trauma Intervention: Empirical Evidence,” a framework to guide intervention and prevention efforts in the aftermath of mass trauma. Briefly, these include promoting safety, calm, self- and community efficacy, connectedness, and hope for the future. These evidence-informed elements have been used in early disaster interventions, such as Psychological First Aid (Brymer et al., 2006), and have widely influenced international public health policy. This commentary will address whether these elements have provided guidance when applied to the setting of the COVID-19 pandemic. | | As of this writing (July 11, 2021), there have been more than 185 million confirmed cases of COVID-19 world-wide, resulting in over 4 million reported deaths (Johns Hopkins Coronavirus Resource Center). This international public health disaster, tremendous in scope and scale, has unfolded in unyielding and uneven waves, affecting different regions of the world with varied intensity over the past 18 months. Global mortality, societal and economic disruption, and the protracted nature of the crisis have overwhelmed medical facilities, health care systems, and communities. Inconsistent messaging about the transmissibility of the virus and seriousness of COVID-19 magnified uncertainty and fear. Early efforts focused on containing the spread of infection and managing serious respiratory illness. This quickly grew to include concern about the psychological trauma surrounding both the seriousness of the disease and the psychosocial and economic effect of its containment efforts. A large body of evidence reveals that during the initial phase of the pandemic, there was an increase in levels of anxiety, depression, substance misuse, and suicidal ideation in the U.S. (e.g., Czeisler et al., 2020; Ettman et al., 2020). Notably, youth, women, and those caring for young children –groups not previously identified as high risk for psychiatric disorders – experienced disproportionate psychological distress and possible increases in self-harm (Aknin et al., 2021).

INTRODUCTION: HIV disproportionally burdens adolescent men who have sex with men (AMSM) and transgender youth. This study explores barriers and facilitators that professionals face in delivering HIV preventive services and education. METHODS: Adolescent health providers (nurse practitioners, physicians, and other), school nurses, youth workers, and school educators were recruited nationally for this qualitative study. RESULTS: Thirty-four professionals participated. Common categories identified across professional group were (1) effective strategies for building trust with youth, (2) perceived barriers/facilitators to sexual health communication, (3) perceived barriers/facilitators to effective HIV prevention, and (4) preferred content for HIV prevention tools. DISCUSSION: Key elements for developing multidisciplinary resources to support AMSM and transgender youth should include (1) web-based or easily accessible sexual health educational materials, (2) resources for referrals, (3) trainings to support competence in caring for sexual and gender minority youth, and (4) guidance for navigating policies or eliciting policy change.

Transgender and gender diverse (TGD) youth experience significant risk for negative health outcomes, yet few studies exist that address TGD youth's experiences of health care. This paper explores the equitable access and utilization of health care in a sample of TGD youth of diverse gender and racial/ethnic identities. Data for this analysis are from the TGD subsample (n = 1415) of the 2018 Survey of Today's Adolescent Relationships and Transitions (START) Project. We assessed five health care experiences: being insured, having a current health care provider, being out to one's provider, believing your provider was knowledgeable about transgender issues, and barriers to accessing care due to gender identity/expression. We examined the proportion of TGD youth who reported each of these outcomes and within-group differences by gender identity and race/ethnicity using descriptive statistics, logistic regression, and predicted probabilities. When differences were examined by gender identity, barriers to equitable care were consistently more present among transgender females than youth of other gender identities. There were few significant differences by race/ethnicity; however, dual referent models demonstrated barriers to equitable care were particularly evident among Black and Hispanic transgender women. We discuss these findings through the lens of intersectionality and highlight the importance of research and intervention work focused on reducing barriers to equitable care for TGD youth.

BACKGROUND: Hepatitis E virus (HEV), the causative agent of hepatitis E, is a common but self-limiting disease. However, in immunosuppressed kidney transplant 47 recipients (KTRs), HEV infection can become chronic. We investigated risk factors associated with HEV infection among 271 KTRs at the Johns Hopkins Hospital transplanted between 1988 and 2012. METHODS: HEV infection was defined as having positive anti-HEV IgM, anti-HEV IgG, or HEV RNA. The risk factors included: age at transplant, sex, hemodialysis/peritoneal dialysis, plasmapheresis, transfusions, community urbanization, and other socioeconomic factors. Logistic regression was used to determine independent risk factors associated with HEV infection. RESULTS: Out of 271 KTRs, 43 (16%) had HEV infection though not active disease. HEV infection in KTRs was associated with older age (≥45 years; OR = 4.04; 95% CI = 1.81-57 10.03; p = 0.001) and living in communities with low proportions of minorities (OR = 0.22; 95% 58 CI = 0.04-0.90; p = 0.046). CONCLUSION: KTRs who had HEV infection may be at an increased risk of developing chronic HEV.

Early warning and response surveillance (EWARS) systems were widely used during the early COVID-19 response. Evaluating the effectiveness of EWARS systems is critical to ensuring global health security. We describe the Centers for Disease Control and Prevention (CDC) global COVID-19 EWARS (CDC EWARS) system and the resources CDC used to gather, manage, and analyze publicly available data during the prepandemic period. We evaluated data quality and validity by measuring reporting completeness and compared these with data from Johns Hopkins University, the European Centre for Disease Prevention and Control, and indicator-based data from the World Health Organization. CDC EWARS was integral in guiding CDC's early COVID-19 response but was labor-intensive and became less informative as case-level data decreased and the pandemic evolved. However, CDC EWARS data were similar to those reported by other organizations, confirming the validity of each system and suggesting collaboration could improve EWARS systems during future pandemics.

Sexual and gender minority (SGM) youth are at disproportionate risk of acquiring HIV, and as such, SGM youth should be meaningfully engaged in research aimed at developing effective, tailored HIV interventions. Youth Community Advisory Boards (YCABs) are an important element of community-engaged research and support the development of community-informed interventions. This article describes recruitment, facilitation, and retention of a YCAB composed of SGM youth in Greater Boston, to inform a national HIV prevention research project. These lessons can serve as a guide to future researchers who want to form YCABs as part of community-engaged research.

Comparing parasite genotypes to inform parasitic disease outbreak investigations involves computation of genetic distances that are typically analyzed by hierarchical clustering to identify related isolates, indicating a common source. A limitation of hierarchical clustering is that hierarchical clusters are not discrete, they are nested. Consequently, small groups of similar isolates exist within larger groups that get progressively larger as relationships become increasingly distant. Investigators must dissect hierarchical trees at a partition number ensuring grouped isolates belong to the same strain; a process typically performed subjectively, introducing bias into resultant groupings. We describe an unbiased, probabilistic framework for partition number selection that ensures partitions comprise isolates that are statistically likely to belong to the same strain. We compute distances and establish a normalized distribution of background distances that is used to demarcate a threshold below which the closeness of relationships is unlikely to be random. Distances are hierarchically clustered and the dendrogram dissected at a partition number where most within-partition distances fall below the threshold. We evaluated this framework by partitioning 1,137 clustered Cyclospora cayetanensis genotypes including 552 isolates epidemiologically linked to various outbreaks. The framework was 91% sensitive and 100% specific in assigning epidemiologically-linked isolates to the same partition.

BACKGROUND: When children and youth feel connected to their school, family, and others in their community, they are less likely to engage in risky behaviors and experience negative health. Disruptions to school operations during the COVID-19 pandemic have led many teachers and school administrators to prioritize finding ways to strengthen and re-establish a sense of connectedness among students and between students and adults in school. METHODS: We conducted a systematic search of peer-reviewed literature that reported on US-based research and were published in English from January 2010 through December 2019 to identify classroom management approaches that have been empirically tied to school connectedness-related outcomes in K-12 school settings. FINDINGS: Six categories of classroom management approaches were associated with improved school connectedness among students: (1) teacher caring and support, (2) peer connection and support, (3) student autonomy and empowerment, (4) management of classroom social dynamics, (5) teacher expectations, and (6) behavior management. IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: Prioritizing classroom management approaches that emphasize positive reinforcement of behavior, restorative discipline and communication, development of strong, trusting relationships, and explicitly emphasize fairness has potential to promote equitable disciplinary practices in schools. CONCLUSIONS: Classroom management approaches most linked to school connectedness are those that foster student autonomy and empowerment, mitigate social hierarchies and power differentials among students, prioritize positive reinforcement of behavior and restorative disciplinary practices, and emphasize equity and fairness.

CONTEXT: The Centers for Disease Control and Prevention (CDC) developed a workforce training on sexual and gender minorities (SGMs). OBJECTIVE: This article describes the evaluation of the training. DESIGN: Participants completed pre- and posttest surveys. After the pilot evaluation, some improvements were made to the curriculum and to the pre- and posttest questionnaires. Participants in subsequent (implementation) training were similarly asked to complete pre- and posttest questionnaires. SETTING: CDC. PARTICIPANTS: CDC staff. MAIN OUTCOME MEASURES: Participants' knowledge, ally identity, and perceptions of SGMs. RESULTS: Pilot and implementation training data showed increases in participant knowledge of 44% and 49%, respectively, increases in ally identity of 11% and 14%, respectively, and increases in positive perceptions of SGM of 25% and 31%, respectively. CONCLUSION: These results suggest that the CDC Ally Training may be a useful tool for improving staff knowledge and perceptions of SGM people.

Point-of-care antigen tests are an important tool for SARS-CoV-2 detection yet are less clinically sensitive than real-time reverse-transcription PCR (RT-PCR), impacting their efficacy as screening procedures. Our goal in this analysis was to see whether we could improve this sensitivity by considering antigen test results in combination with other relevant information, namely exposure status and reported symptoms. In November of 2020, we collected 3,419 paired upper respiratory specimens tested by RT-PCR and the Abbott BinaxNOW antigen test at two community testing sites in Pima County, Arizona. We used symptom, exposure, and antigen testing data to evaluate the sensitivity and specificity of various symptom definitions in predicting RT-PCR positivity. Our analysis yielded 6 novel multi-symptom case definitions with and without antigen test results, the best of which overall achieved a Youden's J index of 0.66, as compared with 0.53 for antigen testing alone. Using a random forest as a guide, we show that this definition, along with our others, does not lose the ability to generalize well to new data despite achieving optimal performance in our sample. Our methodology is broadly applicable, and our code is publicly available to aid public health practitioners in developing or fine-tuning their own case definitions.

The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and the size distributions of putative TB transmission clusters were enumerated. We fit cluster size distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproductive number) and dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, nine studies met inclusion criteria ($n=5$ all TB; $n=4$ drug resistant TB) from eight global settings. Estimated $R$ values (range: 0.10, 0.73) were below 1.0, consistent with declining epidemics in the included settings; estimated $k$ values were well below 1.0 (range: 0.02, 0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range 2-31%) drive the majority (80%) of ongoing transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.

Increases in severe respiratory illness and acute flaccid myelitis (AFM) among children and adolescents resulting from enterovirus D68 (EV-D68) infections occurred biennially in the United States during 2014, 2016, and 2018, primarily in late summer and fall. Although EV-D68 annual trends are not fully understood, EV-D68 levels were lower than expected in 2020, potentially because of implementation of COVID-19 mitigation measures (e.g., wearing face masks, enhanced hand hygiene, and physical distancing) (1). In August 2022, clinicians in several geographic areas notified CDC of an increase in hospitalizations of pediatric patients with severe respiratory illness and positive rhinovirus/enterovirus (RV/EV) test results.* Surveillance data were analyzed from multiple national data sources to characterize reported trends in acute respiratory illness (ARI), asthma/reactive airway disease (RAD) exacerbations, and the percentage of positive RV/EV and EV-D68 test results during 2022 compared with previous years. These data demonstrated an increase in emergency department (ED) visits by children and adolescents with ARI and asthma/RAD in late summer 2022. The percentage of positive RV/EV test results in national laboratory-based surveillance and the percentage of positive EV-D68 test results in pediatric sentinel surveillance also increased during this time. Previous increases in EV-D68 respiratory illness have led to substantial resource demands in some hospitals and have also coincided with increases in cases of AFM (2), a rare but serious neurologic disease affecting the spinal cord. Therefore, clinicians should consider AFM in patients with acute flaccid limb weakness, especially after respiratory illness or fever, and ensure prompt hospitalization and referral to specialty care for such cases. Clinicians should also test for poliovirus infection in patients suspected of having AFM because of the clinical similarity to acute flaccid paralysis caused by poliovirus. Ongoing surveillance for EV-D68 is critical to ensuring preparedness for possible future increases in ARI and AFM.

The articles published as part of the Frontiers in Public Health research topic, "Investigating exposures and respiratory health in coffee workers" present research findings that better characterize exposures to diacetyl and 2,3-pentanedione and inform our understanding of the health risks posed by these exposures. Although various research groups and organizations have conducted risk assessments to derive occupational exposure limits (OELs) for diacetyl, differences in the data used and assumptions made in these efforts have resulted in a wide range of recommended OELs designed to protect human health. The primary drivers of these differences include the decision to use data from human or animal studies in conducting a quantitative risk assessment, and the application of uncertainty factors (UF) to derive an OEL. This Perspectives paper will discuss the practical implications of these decisions, and present additional commentary on the potential role that the recent investigation of human exposures to relatively low concentrations of α-diketones, specifically diacetyl and 2,3-pentanedione, may play in supporting qualitative or quantitative human health risk assessments.

BACKGROUND: Marked reductions in the incidence of measles and rubella have been observed since the widespread use of the measles and rubella vaccines. Although no global goal for measles eradication has been established, all six WHO regions have set measles elimination targets. However, a gap remains between current control levels and elimination targets, as shown by large measles outbreaks between 2017 and 2019. We aimed to model the potential for measles and rubella elimination globally to inform a WHO report to the 73rd World Health Assembly on the feasibility of measles and rubella eradication. METHODS: In this study, we modelled the probability of measles and rubella elimination between 2020 and 2100 under different vaccination scenarios in 93 countries of interest. We evaluated measles and rubella burden and elimination across two national transmission models each (Dynamic Measles Immunisation Calculation Engine [DynaMICE], Pennsylvania State University [PSU], Johns Hopkins University, and Public Health England models), and one subnational measles transmission model (Institute for Disease Modeling model). The vaccination scenarios included a so-called business as usual approach, which continues present vaccination coverage, and an intensified investment approach, which increases coverage into the future. The annual numbers of infections projected by each model, country, and vaccination scenario were used to explore if, when, and for how long the infections would be below a threshold for elimination. FINDINGS: The intensified investment scenario led to large reductions in measles and rubella incidence and burden. Rubella elimination is likely to be achievable in all countries and measles elimination is likely in some countries, but not all. The PSU and DynaMICE national measles models estimated that by 2050, the probability of elimination would exceed 75% in 14 (16%) and 36 (39%) of 93 modelled countries, respectively. The subnational model of measles transmission highlighted inequity in routine coverage as a likely driver of the continuance of endemic measles transmission in a subset of countries. INTERPRETATION: To reach regional elimination goals, it will be necessary to innovate vaccination strategies and technologies that increase spatial equity of routine vaccination, in addition to investing in existing surveillance and outbreak response programmes. FUNDING: WHO, Gavi, the Vaccine Alliance, US Centers for Disease Control and Prevention, and the Bill & Melinda Gates Foundation.

PURPOSE: The purpose of this research is to explore the relationship between substance use and sexual risk behaviors among transgender youth. METHODS: Data from the transgender subsample of the Survey of Today's Adolescent Relationships and Transitions (n=1567) were analyzed to assess associations between substance misuse (binge drinking, prescription drug misuse, illicit drugs) and sexual risk behaviors (condom use during sex). Multivariate logistic regression models calculated adjusted odds ratios (AORs) for substance use by sexual risk behavior controlling for race/ethnicity, gender identity (transgender male, transgender female, genderqueer/gender nonconforming), age, sexual identity, and region. RESULTS: Among participants, lifetime marijuana use (AOR=0.45), cocaine use (AOR=0.46), prescription drug misuse (AOR=0.52), and injecting substances with a needle (AOR=0.45) were all associated with lower odds of reporting condom use during the last act of receptive anal sex. Similarly, marijuana use in the last 30 days (AOR=0.46), lifetime marijuana use (AOR=0.25), heroin use (AOR=0.29), methamphetamine use (AOR=0.32), misuse of prescription drugs (AOR=0.40), and injecting substances with a needle (AOR=0.17) were all associated with lower odds of reporting condom use during the last act of insertive anal sex. No associations between substance use and condom use during last act of receptive frontal (vaginal) sex were found. CONCLUSION: We found that transgender youth who reported any lifetime substance use were more likely to report condomless sex during receptive and insertive anal sex than those who did not report substance use. Significant differences exist among demographic groups, type of substance use, and sexual risk behaviors for respondents based on gender identity.

The early identification of clusters of persons with tuberculosis (TB) that will grow to become outbreaks creates an opportunity for intervention in preventing future TB cases. We used surveillance data (2009-2018) from the United States, statistically derived definitions of unexpected growth, and machine learning techniques to predict which clusters of genotype-matched TB cases are most likely to continue accumulating cases above expected growth within a 1-year follow-up period. We developed a model to predict which clusters are likely to grow on a training and testing dataset that was generalizable to a validation dataset. Our model shows that characteristics of clusters were more important than the social, demographic, and clinical characteristics of the patients in those clusters. For instance, the time between cases before unexpected growth was identified as the most important of our predictors. A faster accumulation of cases increased the probability of excess growth being predicted during the follow-up period. We demonstrated that combining the characteristics of clusters and cases with machine learning can add to existing tools to help prioritize which clusters may benefit most from public health interventions. For example, consideration of an entire cluster, not only an individual patient, may assist in interrupting ongoing transmission.