PURPOSE: The etiopathogenesis of coronal nonsyndromic craniosynostosis (cNCS), a congenital condition defined by premature fusion of 1 or both coronal sutures, remains largely unknown. METHODS: We conducted the largest genome-wide association study of cNCS followed by replication, fine mapping, and functional validation of the most significant region using zebrafish animal model. RESULTS: Genome-wide association study identified 6 independent genome-wide-significant risk alleles, 4 on chromosome 7q21.3 SEM1-DLX5-DLX6 locus, and their combination conferred over 7-fold increased risk of cNCS. The top variants were replicated in an independent cohort and showed pleiotropic effects on brain and facial morphology and bone mineral density. Fine mapping of 7q21.3 identified a craniofacial transcriptional enhancer (eDlx36) within the linkage region of the top variant (rs4727341; odds ratio [95% confidence interval], 0.48[0.39-0.59]; P = 1.2E-12) that was located in SEM1 intron and enriched in 4 rare risk variants. In zebrafish, the activity of the transfected human eDlx36 enhancer was observed in the frontonasal prominence and calvaria during skull development and was reduced when the 4 rare risk variants were introduced into the sequence. CONCLUSION: Our findings support a polygenic nature of cNCS risk and functional role of craniofacial enhancers in cNCS susceptibility with potential broader implications for bone health.

HIV infection is monitored through the National HIV Surveillance System (NHSS) to help improve the health of people with HIV and reduce transmission. NHSS data are routinely used at federal, state, and local levels to monitor the distribution and transmission of HIV, plan and evaluate prevention and care programs, allocate resources, inform policy development, and identify and respond to rapid transmission in the United States. We describe the expanded use of HIV surveillance data since the 2013 NHSS status update, during which time the Centers for Disease Control and Prevention (CDC) coordinated to revise the HIV surveillance case definition to support the detection of early infection and reporting of laboratory data, expanded data collection to include information on sexual orientation and gender identity, enhanced data deduplication processes to improve quality, and expanded reporting to include social determinants of health and health equity measures. CDC maximized the effects of federal funding by integrating funding for HIV prevention and surveillance into a single program; the integration of program funding has expanded the use of HIV surveillance data and strengthened surveillance, resulting in enhanced cluster response capacity and intensified data-to-care activities to ensure sustained viral suppression. NHSS data serve as the primary source for monitoring HIV trends and progress toward achieving national initiatives, including the US Department of Health and Human Services' Ending the HIV Epidemic in the United States initiative, the White House's National HIV/AIDS Strategy (2022-2025), and Healthy People 2030. The NHSS will continue to modernize, adapt, and broaden its scope as the need for high-quality HIV surveillance data remains.

BACKGROUND: Work is a key social determinant of health. Without the collection of work-related information in public health data systems, the role of social determinants in creating and reinforcing health disparities cannot be fully assessed. METHODS: The Centers for Disease Control and Prevention (CDC) maintains or supports a number of public health surveillance and health monitoring systems, including surveys, case-based disease and exposure systems, vital status records, and administrative data systems. We evaluated a convenience sample of these systems for inclusion of information in three work-related domains: employment status, industry and occupation, and working conditions. RESULTS: While 12 of 39 data systems were identified as collecting work-related data, this information was often minimal (e.g., only employment status), restricted to a subset of respondents, or only gathered periodically. Information on working conditions was particularly sparse. CONCLUSION: Historically, the limited and inconsistent collection of work-related information in public health data systems has hindered understanding of the role work plays in health disparities. Current CDC data modernization efforts present opportunities to enhance the identification and mitigation of health disparities by prioritizing inclusion of an expanded set of work-related data elements.

BACKGROUND: Clinical trials initiated during emerging infectious disease outbreaks must quickly enroll participants to identify treatments to reduce morbidity and mortality. This may be at odds with enrolling a representative study population, especially when the population affected is undefined. METHODS: We evaluated the utility of the Centers for Disease Control and Prevention's COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), the COVID-19 Case Surveillance System (CCSS), and 2020 United States (US) Census data to determine demographic representation in the 4 stages of the Adaptive COVID-19 Treatment Trial (ACTT). We compared the cumulative proportion of participants by sex, race, ethnicity, and age enrolled at US ACTT sites, with respective 95% confidence intervals, to the reference data in forest plots. RESULTS: US ACTT sites enrolled 3509 adults hospitalized with COVID-19. When compared with COVID-NET, ACTT enrolled a similar or higher proportion of Hispanic/Latino and White participants depending on the stage, and a similar proportion of African American participants in all stages. In contrast, ACTT enrolled a higher proportion of these groups when compared with US Census and CCSS. The proportion of participants aged ≥65 years was either similar or lower than COVID-NET and higher than CCSS and the US Census. The proportion of females enrolled in ACTT was lower than the proportion of females in the reference datasets. CONCLUSIONS: Although surveillance data of hospitalized cases may not be available early in an outbreak, they are a better comparator than US Census data and surveillance of all cases, which may not reflect the population affected and at higher risk of severe disease.

BACKGROUND: While the occupational risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection for healthcare personnel in the United States has been relatively well characterized, less information is available on the occupational risk for workers employed in other settings. Even fewer studies have attempted to compare risks across occupations and industries. Using differential proportionate distribution as an approximation, we evaluated excess risk of SARS-CoV-2 infection by occupation and industry among non-healthcare workers in six states. METHODS: We analyzed data on occupation and industry of employment from a six-state callback survey of adult non-healthcare workers with confirmed SARS-CoV-2 infection and population-based reference data on employment patterns, adjusted for the effect of telework, from the U.S. Bureau of Labor Statistics. We estimated the differential proportionate distribution of SARS-CoV-2 infection by occupation and industry using the proportionate morbidity ratio (PMR). RESULTS: Among a sample of 1111 workers with confirmed SARS-CoV-2 infection, significantly higher-than-expected proportions of workers were employed in service occupations (PMR 1.3, 99% confidence interval [CI] 1.1-1.5) and in the transportation and utilities (PMR 1.4, 99% CI 1.1-1.8) and leisure and hospitality industries (PMR 1.5, 99% CI 1.2-1.9). CONCLUSIONS: We found evidence of significant differences in the proportionate distribution of SARS-CoV-2 infection by occupation and industry among respondents in a multistate, population-based survey, highlighting the excess risk of SARS-CoV-2 infection borne by some worker populations, particularly those whose jobs require frequent or prolonged close contact with other people.

BACKGROUND: Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (Covid-19), no antiviral agents have yet been shown to be efficacious. METHODS: We conducted a double-blind, randomized, placebo-controlled trial of intravenous remdesivir in adults who were hospitalized with Covid-19 and had evidence of lower respiratory tract infection. Patients were randomly assigned to receive either remdesivir (200 mg loading dose on day 1, followed by 100 mg daily for up to 9 additional days) or placebo for up to 10 days. The primary outcome was the time to recovery, defined by either discharge from the hospital or hospitalization for infection-control purposes only. RESULTS: A total of 1062 patients underwent randomization (with 541 assigned to remdesivir and 521 to placebo). Those who received remdesivir had a median recovery time of 10 days (95% confidence interval [CI], 9 to 11), as compared with 15 days (95% CI, 13 to 18) among those who received placebo (rate ratio for recovery, 1.29; 95% CI, 1.12 to 1.49; P<0.001, by a log-rank test). In an analysis that used a proportional-odds model with an eight-category ordinal scale, the patients who received remdesivir were found to be more likely than those who received placebo to have clinical improvement at day 15 (odds ratio, 1.5; 95% CI, 1.2 to 1.9, after adjustment for actual disease severity). The Kaplan-Meier estimates of mortality were 6.7% with remdesivir and 11.9% with placebo by day 15 and 11.4% with remdesivir and 15.2% with placebo by day 29 (hazard ratio, 0.73; 95% CI, 0.52 to 1.03). Serious adverse events were reported in 131 of the 532 patients who received remdesivir (24.6%) and in 163 of the 516 patients who received placebo (31.6%). CONCLUSIONS: Our data show that remdesivir was superior to placebo in shortening the time to recovery in adults who were hospitalized with Covid-19 and had evidence of lower respiratory tract infection. (Funded by the National Institute of Allergy and Infectious Diseases and others; ACTT-1 ClinicalTrials.gov number, NCT04280705.).

Work is a recognized social determinant of health. This became most apparent during the COVID-19 pandemic. Workers, particularly those in certain industries and occupations, were at risk due to interaction with the public and close proximity to co-workers. The purpose of this study was to assess how states collected work and employment data on COVID-19 cases, characterizing the need for systematic collection of case-based specific work and employment data, including industry and occupation, of COVID-19 cases. A survey was distributed among state occupational health contacts and epidemiologists in all 50 states to assess current practices in state public health surveillance systems. Twenty-seven states collected some kind of work and employment information from COVID-19 cases. Most states (93%) collected industry and/or occupation information. More than half used text-only fields, a predefined reference or dropdown list, or both. Use of work and employment data included identifying high risk populations, prioritizing vaccination efforts, and assisting with reopening plans. Reported barriers to collecting industry and occupation data were lack of staffing, technology issues, and funding. Scientific understanding of work-related COVID-19 risk requires the systematic, case-based collection of specific work and employment data, including industry and occupation. While this alone does not necessarily indicate a clear workplace exposure, collection of these data elements can help to determine and further prevent workplace outbreaks, thereby ensuring the viability of the nation's critical infrastructure.

OBJECTIVES: Early in the COVID-19 pandemic, several outbreaks were linked with facilities employing essential workers, such as long-term care facilities and meat and poultry processing facilities. However, timely national data on which workplace settings were experiencing COVID-19 outbreaks were unavailable through routine surveillance systems. We estimated the number of US workplace outbreaks of COVID-19 and identified the types of workplace settings in which they occurred during August-October 2021. METHODS: The Centers for Disease Control and Prevention collected data from health departments on workplace COVID-19 outbreaks from August through October 2021: the number of workplace outbreaks, by workplace setting, and the total number of cases among workers linked to these outbreaks. Health departments also reported the number of workplaces they assisted for outbreak response, COVID-19 testing, vaccine distribution, or consultation on mitigation strategies. RESULTS: Twenty-three health departments reported a total of 12 660 workplace COVID-19 outbreaks. Among the 12 470 workplace types that were documented, 35.9% (n = 4474) of outbreaks occurred in health care settings, 33.4% (n = 4170) in educational settings, and 30.7% (n = 3826) in other work settings, including non-food manufacturing, correctional facilities, social services, retail trade, and food and beverage stores. Eleven health departments that reported 3859 workplace outbreaks provided information about workplace assistance: 3090 (80.1%) instances of assistance involved consultation on COVID-19 mitigation strategies, 1912 (49.5%) involved outbreak response, 436 (11.3%) involved COVID-19 testing, and 185 (4.8%) involved COVID-19 vaccine distribution. CONCLUSIONS: These findings underscore the continued impact of COVID-19 among workers, the potential for work-related transmission, and the need to apply layered prevention strategies recommended by public health officials.

Objectives. To explore previous COVID-19 diagnosis and COVID-19 vaccination status among US essential worker groups. Methods. We analyzed the US Census Household Pulse Survey (May 26-July 5, 2021), a nationally representative sample of adults aged 18 years and older. We compared currently employed essential workers working outside the home with those working at home using adjusted prevalence ratios. We calculated proportion vaccinated and intention to be vaccinated, stratifying by essential worker and demographic groups for those who worked or volunteered outside the home since January 1, 2021. Results. The proportion of workers with previous COVID-19 diagnosis was highest among first responders (24.9%) working outside the home compared with workers who did not (13.3%). Workers in agriculture, forestry, fishing, and hunting had the lowest vaccination rates (67.5%) compared with all workers (77.8%). Those without health insurance were much less likely to be vaccinated across all worker groups. Conclusions. This study underscores the importance of improving surveillance to monitor COVID-19 and other infectious diseases among workers and identify and implement tailored risk mitigation strategies, including vaccination campaigns, for workplaces. (Am J Public Health. 2022;112(11):1599-1610. https://doi.org/10.2105/AJPH.2022.307010).

BACKGROUND: Surveillance systems lack detailed occupational exposure information from workers with SARS-CoV-2 infection. The National Institute for Occupational Safety and Health partnered with six states to collect information from adults diagnosed with SARS-CoV-2 infection (either COVID-19 or asymptomatic infection) who worked in person (outside the home) in non-healthcare settings during the two weeks prior to illness onset. METHODS: The survey captured demographic, medical, occupational characteristics, and work- and non-work-related risk factors for SARS-CoV-2 infection. Reported close contact with a person known or suspected to have COVID-19 was categorized by setting as: exposure at work, exposure outside of work only, or no known exposure/didn't know if they had exposures. Frequencies and percentages of exposure types are compared by respondent characteristics and risk factors for SARS-CoV-2 infection. RESULTS: Of 1,111 qualified respondents, 19.4% reported exposure at work, 23.4% reported exposure outside of work only, and 57.2% reported no known exposure/didn't know if they had exposures. Workers in protective service occupations (48.8%) and public administration industries (35.6%) reported exposure at work most often. Over a third (33.7%) of respondents who experienced close contact with ≥10 coworkers per day and 28.8% of respondents who experienced close contact with ≥10 customers/clients per day reported exposures at work. CONCLUSIONS: Exposure to SARS-CoV-2 at work was common among respondents. Examining differences in exposures among different groups of workers can help identify populations with the greatest need for prevention interventions. The benefits of recording employment characteristics as standard demographic information will remain relevant as new and reemerging public health issues occur.

During the past few decades, the science of toxicology has been undergoing a transformation from observational to predictive science. New approach methodologies (NAMs), including in vitro assays, in silico models, read-across, and in vitro to in vivo extrapolation (IVIVE), are being developed to reduce, refine, or replace whole animal testing, encouraging the judicious use of time and resources. Some of these methods have advanced past the exploratory research stage and are beginning to gain acceptance for the risk assessment of chemicals. A review of the recent literature reveals a burst of IVIVE publications over the past decade. In this review, we propose operational definitions for IVIVE, present literature examples for several common toxicity endpoints, and highlight their implications in decision-making processes across various federal agencies, as well as international organizations, including those in the European Union (EU). The current challenges and future needs are also summarized for IVIVE. In addition to refining and reducing the number of animals in traditional toxicity testing protocols and being used for prioritizing chemical testing, the goal to use IVIVE to facilitate the replacement of animal models can be achieved through their continued evolution and development, including a strategic plan to qualify IVIVE methods for regulatory acceptance.

BACKGROUND: The Cybersecurity and Infrastructure Security Agency (CISA) produced an advisory list identifying essential critical infrastructure workers (ECIW) during the coronavirus disease 2019 (COVID-19) response. The CISA advisory list is the most common national definition of ECIW but has not been mapped to United States (U.S.) Census industry codes (CICs) to readily identify these worker populations in public health data sources. METHODS: We identified essential critical infrastructure industry designations corresponding to v4.0 of the CISA advisory list for all six-digit North American Industry Classification System (NAICS) codes and cross-walked NAICS codes to CICs. CICs were grouped as essential, non-essential, or mixed essential/non-essential according to component NAICS industries. We also obtained national estimated population sizes for NAICS and Census industries and cross-tabulated Census industry and occupation codes to identify industry-occupation pairs. RESULTS: We produced and made publicly available spreadsheets containing essential industry designations corresponding to v4.0 of the CISA advisory list for NAICS and Census industry titles and codes and population estimates by six-digit NAICS industry, Census industry, and Census industry-occupation pair. The CISA advisory list is highly inclusive and contains most industries and U.S. workers; 71.0% of Census industries comprising 80.6% of workers and 80.7% of NAICS industries comprising 87.1% of workers were designated as essential. CONCLUSIONS: We identified workers in essential critical infrastructure industries as defined by CISA using standardized industry codes. These classifications may support public health interventions and analyses related to the COVID-19 pandemic and future public health crises.

BACKGROUND: Health care personnel (HCP) have experienced significant SARS-CoV-2 risk, but exposure settings among HCP COVID-19 cases are poorly characterized. METHODS: We assessed exposure settings among HCP COVID-19 cases in the United States from March 2020 to March 2021 with reported exposures (n = 83,775) using national COVID-19 surveillance data. Exposure setting and reported community incidence temporal trends were described using breakpoint estimation. Among cases identified before initiation of COVID-19 vaccination programs (n = 65,650), we used separate multivariable regression models to estimate adjusted prevalence ratios (aPR) for associations of community incidence with health care and household and/or community exposures. RESULTS: Health care exposures were the most reported (52.0%), followed by household (30.8%) and community exposures (25.6%). Health care exposures and community COVID-19 incidence showed similar temporal trends. In adjusted analyses, HCP cases were more likely to report health care exposures (aPR = 1.31; 95% CI:1.26-1.36) and less likely to report household and/or community exposures (aPR = 0.73; 95% CI:0.70-0.76) under the highest vs lowest community incidence levels. DISCUSSION: These findings highlight HCP exposure setting temporal trends and workplace exposure hazards under high community incidence. Findings also underscore the need for robust collection of work-related data in infectious disease surveillance. CONCLUSIONS: Many reported HCP cases experienced occupational COVID-19 exposures, particularly during periods of higher community COVID-19 incidence.

We propose the hypothesis that small high-density lipoprotein (HDL) particles reduce the risk of Alzheimer's disease (AD) by virtue of their capacity to exchange lipids, affecting neuronal membrane composition and vascular and synaptic functions. Concentrations of small HDLs in cerebrospinal fluid (CSF) and plasma were measured in 180 individuals ≥60 years of age using ion mobility methodology. Small HDL concentrations in CSF were positively associated with performance in three domains of cognitive function independent of apolipoprotein E (APOE) ε4 status, age, sex, and years of education. Moreover, there was a significant correlation between levels of small HDLs in CSF and plasma. Further studies will be aimed at determining whether specific components of small HDL exchange across the blood, brain, and CSF barriers, and developing approaches to exploit small HDLs for therapeutic purposes.

Black/African American (Black) versus White persons are unequally burdened by human immunodeficiency virus (HIV) in the United States. Structural factors can influence social determinants of health, key components in reducing HIV-related health inequality by race. This analysis examined HIV care outcomes among Black and White persons with diagnosed HIV (PWDH) in relation to three structural factors: racial redlining, Medicaid expansion, and Ryan White HIV/AIDS Program (RWHAP) use. Using National HIV Surveillance System, U.S. Census, and Home Mortgage Disclosure Act data, we examined linkage to HIV care and viral suppression (i.e., viral load < 200 copies/mL) in relation to the structural factors among 12,996 Black and White PWDH with HIV diagnosed in 2017/alive at year-end 2018, aged ≥ 18 years, and residing in 38 U.S. jurisdictions with complete laboratory data, geocoding, and census tract-level redlining indexes. Compared to White PWDH, a lower proportion of Black PWDH were linked to HIV care within 1 month after diagnosis and were virally suppressed in 2018. Redlining was not associated with the HIV care outcomes. A higher prevalence of PWDH residing (v. not residing) in states with Medicaid expansion were linked to HIV care ≤ 1 month after diagnosis. A higher prevalence of those residing (v. not residing) in states with > 50% of PWDH in RWHAP had viral suppression. Direct exposure to redlining was not associated with poor HIV care outcomes. Structural factors that reduce the financial burden of HIV care and improve care access like Medicaid expansion and RWHAP might improve HIV care outcomes of PWDH.

OBJECTIVES: Federal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial partners. These initiatives advance understanding of health conditions and diseases by providing data to researchers, scientists, and policymakers for analysis, collaboration, and use outside the Centers for Disease Control and Prevention (CDC), particularly for emerging conditions such as COVID-19, for which data needs are constantly evolving. Since the beginning of the pandemic, CDC has collected person-level, de-identified data from jurisdictions and currently has more than 8 million records. We describe how CDC designed and produces 2 de-identified public datasets from these collected data. METHODS: We included data elements based on usefulness, public request, and privacy implications; we suppressed some field values to reduce the risk of re-identification and exposure of confidential information. We created datasets and verified them for privacy and confidentiality by using data management platform analytic tools and R scripts. RESULTS: Unrestricted data are available to the public through Data.CDC.gov, and restricted data, with additional fields, are available with a data-use agreement through a private repository on GitHub.com. PRACTICE IMPLICATIONS: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect the privacy of de-identified people allow for improved data use. Automating data-generation procedures improves the volume and timeliness of sharing data.

Certain hazard controls, including physical barriers, cloth face masks, and other personal protective equipment (PPE), are recommended to reduce coronavirus 2019 (COVID-19) transmission in the workplace (1). Evaluation of occupational hazard control use for COVID-19 prevention can identify inadequately protected workers and opportunities to improve use. CDC's National Institute for Occupational Safety and Health used data from the June 2020 SummerStyles survey to characterize required and voluntary use of COVID-19-related occupational hazard controls among U.S. non-health care workers. A survey-weighted regression model was used to estimate the association between employer provision of hazard controls and voluntary use, and stratum-specific adjusted risk differences (aRDs) among workers reporting household incomes <250% and ≥250% of national poverty thresholds were estimated to assess effect modification by income. Approximately one half (45.6%; 95% confidence interval [CI] = 41.0%-50.3%) of non-health care workers reported use of hazard controls in the workplace, 55.5% (95% CI = 48.8%-62.2%) of whom reported employer requirements to use them. After adjustment for occupational group and proximity to others at work, voluntary use was approximately double, or 22.3 absolute percentage points higher, among workers who were provided hazard controls than among those who were not. This effect was more apparent among lower-income (aRD = 31.0%) than among higher-income workers (aRD = 16.3%). Employers can help protect workers from COVID-19 by requiring and encouraging use of occupational hazard controls and providing hazard controls to employees (1).

Objectives: The study objectives were to examine U.S. long-haul truck drivers (LHTDs)' opinions on their safety needs and to assess the associations of driver reported unrealistically tight delivery schedules with: (1) their opinions on their compensation, maximum speed limits, and Hours-of-Service (HOS) regulations, and (2) their behaviors of noncompliance with these safety laws and regulations. Method(s): National Institute for Occupational Safety and Health analyzed data from its 2010 national survey of LHTD health and injury. A total of 1,265 drivers completed the survey. Logistic regression was used to examine the associations between driver reported unrealistically tight delivery schedule and their opinion on safety and unsafe driving behaviors. Result(s): Drivers who reported often receiving an unrealistically tight delivery schedule (an estimated 15.5% of LHTDs) were significantly more likely than drivers who reported never receiving an unrealistically tight delivery schedule to report that: (1) increasing the current maximum speed limit on interstate highways by 10 miles per hour (mph) would improve safety (odds ratio (OR) = 2.1); (2) strictly enforcing HOS rules would not improve safety (OR = 1.8); (3) they often drove 10 mph or more over the speed limit (OR = 7.5); (4) HOS regulations were often violated (OR = 10.9); (5) they often continued to drive despite fatigue, bad weather, or heavy traffic because their must delivery or pick up a load at a given time (OR = 7.5); and (6) their work was never adequately rewarded (OR = 4.5). When presented with 11 potential safety strategies, the largest percentage of LHTDs (95.4%) selected that building more truck stops/parking areas would improve truck driver safety. Conclusion(s): Driver reported unrealistically tight delivery schedules are associated with drivers' beliefs in safety laws/regulations and risk-taking behaviors. LHTDs see building more truck stops/rest areas as the most wanted safety need among the 11 potential safety strategies that were asked about in the survey.

Molldrem and Smith’s (2020) “Reassessing the Ethics of Molecular HIV Surveillance in the Era of Cluster Detection and Response: Toward HIV Data Justice,” outlines important considerations toward more ethical use of HIV data collected and used for public health. As both the HIV and coronavirus disease 2019 (COVID-19) pandemics have demonstrated, social justice concerns and historical struggles against inequality and oppression cannot be separated from public health (Bailey et al. 2017). Public health efforts aimed at reducing transmission of infectious disease often succeed in protecting relatively privileged groups, while allowing persons from oppressed groups to experience disproportionate harms (Jeffries and Henny 2019). Documenting these disproportionate harms is necessary, but not sufficient, to address ongoing HIV disparities.

In recent years, phylogenetic analysis of HIV sequence data has been used in research studies to investigate transmission patterns between individuals and groups, including analysis of data from HIV prevention clinical trials; in molecular epidemiology; and in public health surveillance programs. Phylogenetic analysis can provide valuable information to inform HIV prevention efforts, but it also has risks, including stigma and marginalization of groups, or potential identification of HIV transmission between individuals. In response to these concerns, an interdisciplinary working group was assembled to address ethical challenges in United States-based HIV phylogenetic research. The working group developed recommendations regarding (1) study design; (2) data security, access, and sharing; (3) community engagement; (4) legal issues; and (5) communication and dissemination. The working group also identified areas for future research and scholarship to promote ethical conduct of HIV phylogenetic research.

Our previous genome-wide association study (GWAS) for sagittal nonsyndromic craniosynostosis (sNCS) provided important insights into the genetics of midline CS. In this study, we performed a GWAS for a second midline NCS, metopic NCS (mNCS), using 215 non-Hispanic white case-parent triads. We identified six variants with genome-wide significance (P </= 5 x 10(-8)): rs781716 (P = 4.71 x 10(-9); odds ratio [OR] = 2.44) intronic to SPRY3; rs6127972 (P = 4.41 x 10(-8); OR = 2.17) intronic to BMP7; rs62590971 (P = 6.22 x 10(-9); OR = 0.34), located ~ 155 kb upstream from TGIF2LX; and rs2522623, rs2573826, and rs2754857, all intronic to PCDH11X (P = 1.76 x 10(-8), OR = 0.45; P = 3.31 x 10(-8), OR = 0.45; P = 1.09 x 10(-8), OR = 0.44, respectively). We performed a replication study of these variants using an independent non-Hispanic white sample of 194 unrelated mNCS cases and 333 unaffected controls; only the association for rs6127972 (P = 0.004, OR = 1.45; meta-analysis P = 1.27 x 10(-8), OR = 1.74) was replicated. Our meta-analysis examining single nucleotide polymorphisms common to both our mNCS and sNCS studies showed the strongest association for rs6127972 (P = 1.16 x 10(-6)). Our imputation analysis identified a linkage disequilibrium block encompassing rs6127972, which contained an enhancer overlapping a CTCF transcription factor binding site (chr20:55,798,821-55,798,917) that was significantly hypomethylated in mesenchymal stem cells derived from fused metopic compared to open sutures from the same probands. This study provides additional insights into genetic factors in midline CS.

BACKGROUND: Timely and reliable national estimates of the occurrence of occupational injury and illness are needed to monitor the burden of occupational morbidity and mortality, establish research and intervention priorities, and evaluate the progress and effectiveness of prevention efforts. METHODS: We provide updated estimates of morbidity from occupational injuries and selected illnesses, using current general population incidence rates, the proportion of the general public with a particular workplace exposure, and the relative risk of illness from that exposure. We provide estimates for the total U.S. working population and for specific industry sectors. RESULTS: We estimate that, in 2012, between 5 712 362 and 5 961 620 total occupational cases, including 0.7 to 1.0 million incident illnesses and 5.0 million injuries, occurred in the United States. CONCLUSION: The variety of disparate data sources and methods required to compile these estimates highlight the need for more comprehensive and compatible occupational health surveillance in the United States.

BACKGROUND: Data to Care (D2C) is a public health strategy that uses HIV surveillance and other data to identify persons living with HIV who are "not in care" to link them to medical care or other services. To support health department implementation of D2C, the Centers for Disease Control and Prevention supported direct technical assistance (TA) to build health department D2C capacity. METHODS: Between 2013 and 2017, 2 contracting organizations worked with the Centers for Disease Control and Prevention to provide intensive D2C TA to 20 US health departments. A requirement for applying for TA was the mandatory reporting of all CD4 T-lymphocyte and HIV viral load test results by laboratories to the health department's HIV surveillance system. Health department selection criteria included organizational factors; jurisdiction laws/policies about data confidentiality and sharing; and HIV morbidity level. RESULTS: Peer-to-peer consultation, technical consultation, training, information transfer, materials development, materials distribution, and technology transfer were methods used for delivering TA based on the health department's needs and preferences. TA supported health department progress in areas such as confidentiality and data security, stakeholder engagement, quality of HIV surveillance data, data sharing, staffing resources, creating "not-in-care" lists, and program evaluation. CONCLUSION: Developing D2C programs is not a linear process, and there is no one standardized approach. Health departments made the most rapid progress when TA included peer-to-peer support among health departments. Participation in this project facilitated, in some cases for the first time, collaboration between staff across HIV surveillance, prevention, and care programs.

BACKGROUND: "Data to Care" (D2C) is a public health strategy that uses surveillance and other data to improve continuity of HIV care for persons with HIV (PWH) by identifying those who are in need of medical care or other services and facilitating linkage to these services. The primary goal of D2C is to increase the number of PWH who are engaged in care and virally suppressed. METHODS: Data to Care can be implemented using several approaches. Surveillance-based D2C is usually initiated by health departments, using HIV surveillance and other data to identify those not in care. Health care providers may also initiate D2C by identifying patients who may have fallen out of care and working collaboratively with health departments to investigate, locate, and relink the patients to medical care or other needed services. RESULTS: Although D2C is a relatively new strategy, health department D2C programs have reported both promising results (eg, improved surveillance data quality and successful linkage to or re-engagement in care for PWH) and challenges (eg, incomplete or inaccurate data in surveillance systems, barriers to data sharing, and limitations of existing data systems). CONCLUSIONS: Data to Care is expected to enable health departments to move closer toward achieving national HIV prevention goals. However, additional information on appropriate implementation practices at each step of the D2C process is needed. This JAIDS Special Supplement explores how CDC funding to state health departments (eg, technical assistance and demonstration projects), and partnerships across federal agencies, are advancing our knowledge of D2C.

Workers in specific settings and activities are at increased risk for certain infectious diseases. When an infectious disease case occurs in a worker, investigators need to understand the mechanisms of disease propagation in the workplace. Few publications have explored these factors in the United States; a literature search yielded 66 investigations of infectious disease occurring in US workplaces during 2006-2015. Reported cases appear to be concentrated in specific industries and occupations, especially the healthcare industry, laboratory workers, animal workers, and public service workers. A hierarchy-of-controls approach can help determine how to implement effective preventive measures in workplaces. Consideration of occupational risk factors and control of occupational exposures will help prevent disease transmission in the workplace and protect workers' health.

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Relapse is the recovery of a previously suppressed response. Animal models have been useful in examining the mechanisms underlying relapse (e.g., reinstatement, renewal, reacquisition, resurgence). However, there are several challenges to analyzing relapse data using traditional approaches. For example, null hypothesis significance testing is commonly used to determine whether relapse has occurred. However, this method requires several a priori assumptions about the data, as well as a large sample size for between-subjects comparisons or repeated testing for within-subjects comparisons. Monte Carlo methods may represent an improved analytic technique, because these methods require no prior assumptions, permit smaller sample sizes, and can be tailored to account for all of the data from an experiment instead of some limited set. In the present study, we conducted reanalyses of three studies of relapse (Berry, Sweeney, & Odum, ; Galizio et al., ; Odum & Shahan, ) using Monte Carlo techniques to determine if relapse occurred and if there were differences in rate of response based on relevant independent variables (such as group membership or schedule of reinforcement). These reanalyses supported the previous findings. Finally, we provide general recommendations for using Monte Carlo methods in studies of relapse.

OBJECTIVES:: The Care and Prevention in the United States Demonstration Project included implementation of a Data to Care strategy using surveillance and other data to (1) identify people with HIV infection in need of HIV medical care or other services and (2) facilitate linkages to those services to improve health outcomes. We present the experiences of 4 state health departments: Illinois, Louisiana, Tennessee, and Virginia. METHODS:: The 4 state health departments used multiple databases to generate listings of people with diagnosed HIV infection (PWH) who were presumed not to be in HIV medical care or who had difficulty maintaining viral suppression from October 1, 2013, through September 29, 2016. Each health department prioritized the listings (eg, by length of time not in care, by viral load), reviewed them for accuracy, and then disseminated the listings to staff members to link PWH to HIV care and services. RESULTS:: Of 16 391 PWH presumed not to be in HIV medical care, 9852 (60.1%) were selected for follow-up; of those, 4164 (42.3%) were contacted, and of those, 1479 (35.5%) were confirmed to be not in care. Of 794 (53.7%) PWH who accepted services, 694 (87.4%) were linked to HIV medical care. The Louisiana Department of Health also identified 1559 PWH as not virally suppressed, 764 (49.0%) of whom were eligible for follow-up. Of the 764 PWH who were eligible for follow-up, 434 (56.8%) were contacted, of whom 269 (62.0%) had treatment adherence issues. Of 153 PWH who received treatment adherence services, 104 (68.0%) showed substantial improvement in viral suppression. CONCLUSIONS:: The 4 health departments established procedures for using surveillance and other data to improve linkage to HIV medical care and health outcomes for PWH. To be effective, health departments had to enhance coordination among surveillance, care programs, and providers; develop mechanisms to share data; and address limitations in data systems and data quality.

INTRODUCTION: Outbreaks of pertussis can occur in healthcare settings. Vaccinating healthcare personnel may be helpful in protecting healthcare personnel from pertussis and potentially limiting spread to others in healthcare settings. METHODS: Data from 21 states using the 2013 Behavioral Risk Factor Surveillance System industry/occupation module were analyzed in 2016. Tetanus, diphtheria, and acellular pertussis (Tdap) vaccination status was self-reported by healthcare personnel along with their occupation, healthcare setting/industry, demographics, and access to care factors. To compare groups, t-tests were used. The median state response rate was 44.0%. RESULTS: Among all healthcare personnel, 47.2% were vaccinated for Tdap. Physicians had higher Tdap coverage (66.8%) compared with all other healthcare personnel except nurse practitioners and registered nurses (59.5%), whose coverage did not statistically differ from that of physicians. Tdap vaccination coverage was higher among workers in hospitals (53.3%) than in long-term care facilities (33.3%) and other clinical settings, such as dentist, chiropractor, and optometrist offices (39.3%). Healthcare personnel who were younger, who had higher education, higher annual household income, a personal healthcare provider, and health insurance had higher Tdap vaccination coverage compared with reference groups. Tdap vaccination coverage among healthcare personnel in 21 states ranged from 30.6% in Mississippi to 65.9% in Washington. CONCLUSIONS: Improvement in Tdap vaccination among healthcare personnel is needed to potentially reduce opportunities for spread of pertussis in healthcare settings. On-site workplace vaccination, offering vaccines free of charge, and promoting vaccination may increase vaccination among healthcare personnel.

OBJECTIVE: To assess whether state criminal exposure laws are associated with HIV and stage 3 (AIDS) diagnosis rates in the United States. DESIGN: We assessed the relationship between HIV and stage 3 (AIDS) diagnosis data from the National HIV Surveillance System and the presence of a state criminal exposure law as identified through WestlawNext by using generalized estimating equations. METHODS: We limited analysis to persons aged ≥13 years with diagnosed HIV infection or AIDS reported to the National HIV Surveillance System of the Centers for Disease Control and Prevention. The primary outcome measures were rates of diagnosis of HIV (2001-2010 in 33 states) and AIDS (1994-2010 in 50 states) per 100,000 individuals per year. In addition to criminal exposure laws, state-level factors evaluated for inclusion in models included income, unemployment, poverty, education, urbanicity, and race/ethnicity. RESULTS: At the end of the study period, 30 states had laws criminalizing HIV exposure. In bivariate models (P < .05), unemployment, poverty, education, urbanicity, and race/ethnicity were associated with HIV and AIDS diagnoses. In final models, proportion of adults with less than a high school education and percentage of the population living in urban areas were significantly associated with HIV and AIDS diagnoses over time; criminal exposure laws were not associated with diagnosis rates. CONCLUSIONS: We found no association between HIV or AIDS diagnosis rates and criminal exposure laws across states over time, suggesting that these laws have had no detectable HIV prevention effect.