Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

BACKGROUND: Physiological and biochemical processes across tissues of the body are regulated in response to the high demands of intense physical activity in several occupations, such as firefighting, law enforcement, military, and sports. A better understanding of such processes can ultimately help improve human performance and prevent illnesses in the work environment. METHODS: To study regulatory processes in intense physical activity simulating real-life conditions, we performed a multi-omics analysis of three biofluids (blood plasma, urine, and saliva) collected from 11 wildland firefighters before and after a 45 min, intense exercise regimen. Omics profiles post- versus pre-exercise were compared by Student's t-test followed by pathway analysis and comparison between the different omics modalities. RESULTS: Our multi-omics analysis identified and quantified 3835 proteins, 730 lipids and 182 metabolites combining the 3 different types of samples. The blood plasma analysis revealed signatures of tissue damage and acute repair response accompanied by enhanced carbon metabolism to meet energy demands. The urine analysis showed a strong, concomitant regulation of 6 out of 8 identified proteins from the renin-angiotensin system supporting increased excretion of catabolites, reabsorption of nutrients and maintenance of fluid balance. In saliva, we observed a decrease in 3 pro-inflammatory cytokines and an increase in 8 antimicrobial peptides. A systematic literature review identified 6 papers that support an altered susceptibility to respiratory infection. CONCLUSION: This study shows simultaneous regulatory signatures in biofluids indicative of homeostatic maintenance during intense physical activity with possible effects on increased infection susceptibility, suggesting that caution against respiratory diseases could benefit workers on highly physical demanding jobs.

OBJECTIVE: To spotlight the challenges, gaps, and opportunities to improve workforce mental health and well-being in higher education institutions (HEIs). METHODS: We convened a full-day summit of subject matter experts from academia, business, government, and practice to share research and best practices on workplace mental health. RESULTS: Highlights from the summit are presented in this paper covering the importance of leadership and culture; the mental health costs associated with being a Black STEM scholar; the role of the environment; case studies of three university mental health and well-being programs; and the future of work. CONCLUSIONS: Establishing a culture of caring requires leadership commitment; strategic planning; accountability and shared responsibility; and measurement and evaluation. HEI leaders are called to lead by example; foster community partnerships; adopt a Total Worker Health framework; and regularly evaluate progress.

A One Health approach is critical to strengthening health security at country, regional, and global levels. However, operationally its uptake remains limited. Recent momentum in assessing capacity to effectively prevent, detect, and respond to disease threats has resulted in identification of gaps that require dedicated action. This article highlights relevant tools, standards, and guidance to assist countries and institutions in meeting the collective vision articulated at the 2018 Prince Mahidol Award Conference on "Making the World Safe from the Threats of Emerging Infectious Diseases." Taking stock of assessment findings, resources, priorities, and implementation initiatives across human and animal health, environment and disaster risk reduction sectors can help expand participation in global health security, target risk drivers, and form synergies for collective action and shared gains for both emerging and endemic disease challenges. In addition to health security gains, a multisectoral, One Health approach can drive benefits for wider health sector and global development goals.

OBJECTIVES: Neonatal abstinence syndrome (NAS) is a postnatal withdrawal syndrome experienced by some infants with opioid exposure. Hospital administrative data are commonly used for research and surveillance but have not been validated for NAS. Our objectives for this study were to validate the diagnostic codes for NAS and to develop an algorithm to optimize identification. METHODS: Tennessee Medicaid claims from 2009 to 2011 (primary sample) and 2016 (secondary sample; post-International Classification of Diseases, 10th Revision, Clinical Modification [ICD-10-CM]) were obtained. Cases of NAS were identified by using International Classification of Diseases, Ninth Revision, Clinical Modification code (2009-2011) 779.5 and ICD-10-CM code (2016) P96.1. Medical record review cases were then conducted by 2 physicians using a standardized algorithm, and positive predictive value (PPV) was calculated. Algorithms were developed for optimizing the identification of NAS in administrative data. RESULTS: In our primary sample of 112 029 mother-infant dyads, 950 potential NAS cases were identified from Medicaid claims data and reviewed. Among reviewed records, 863 were confirmed as having NAS (including 628 [66.1%] cases identified as NAS requiring pharmacotherapy, 224 [23.5%] as NAS not requiring pharmacotherapy, and 11 [1.2%] as iatrogenic NAS), and 87 (9.2%) did not meet clinical criteria for NAS. The PPV of the International Classification of Diseases, Ninth Revision, Clinical Modification code for NAS in clinically confirmed NAS was 91% (95% confidence interval: 88.8%-92.5%). Similarly, the PPV for the ICD-10-CM code in the secondary sample was 98.2% (95% confidence interval: 95.4%-99.2%). Algorithms using elements from the Medicaid claims and from length of stay improved PPV. CONCLUSIONS: In a large population-based cohort of Medicaid participants, hospital administrative data had a high PPV in identifying cases of clinically diagnosed NAS.

Breastfeeding is the best source of nutrition for infants, and research emphasizes the benefits of breastfeeding for both mother and infant (American Academy of Pediatrics, 2012; Ip et al., 2007). The American Academy of Pediatrics (2012) recommends exclusive breastfeeding for about the first 6 months of life, and continued breastfeeding for 1 year or longer. In the United States, only 24.9% of infants are exclusively breastfed for 6 months and 33.7% receive any human milk at 12 months (Centers for Disease Control and Prevention [CDC], 2017a). Furthermore, there are disparities among rates of initiation and duration: Rates are lowest for infants who are non-Hispanic Black, living in rural areas, or living in the southeastern United States (CDC, 2017a).

Recent changes in policy and social norms related to marijuana use have increased its use and concern about how/where marijuana should be used. We aimed to characterize rules regarding marijuana and its use in homes. We recruited 1,567 US adults aged 18-34 years through Facebook advertisements to complete an online survey assessing marijuana use, social factors, perceptions of marijuana, and rules regarding marijuana and its use in the home, targeting tobacco and marijuana users to ensure the relevance of this topic. Overall, 648 (41.6%) were current marijuana users; 46.0% of participants reported that "marijuana of any type is not allowed in their home or on their property." Of those allowing marijuana on their property, 6.4% prohibited use of marijuana in their home. Of the remainder, 29.2% prohibited smoking marijuana, and 11.0% prohibited vaping, eating, or drinking marijuana. Correlates of more restrictive rules included younger age, being female, having <Bachelor's degree, not having parents or people living with them who use marijuana, perceiving use to be less socially acceptable and more harmful, and being a nonuser (p's <.05). Attitudes and subjective norms regarding marijuana are correlates of allowing marijuana in residential settings. Future work should examine areas of risk regarding household marijuana rules.

PURPOSE: Increasing cellular phone service and nonresponse are causing random digit dial (RDD) users to search for alternative ways of sampling geographically large populations. This study evaluated the feasibility and utility in using a modified version of respondent-driven sampling (RDS) as an alternative method. METHODS: Using RDS, 469 residents of Albany County, New York were enrolled into a telephone-based health survey. Participants answered health and RDS feasibility questions. Results were compared to a previously collected RDD sample and census data. RESULTS: Participation was high (81.4%) and participants referred at least one peer 65.9% of the time. The RDS method produced a more ethnically diverse sample, otherwise respondent demographics were similar to the RDD sample. The most common reason for participating (51.9%) was because a peer told them about the study; 44.9% would not have participated in an RDD study. Persons not willing to participate in a RDD study reported being less healthy and less likely to participate in healthy activities (e.g., have a physical exam in the past 24 months). CONCLUSIONS: Although more research is needed, RDS methods may be developed into a viable alternative for collecting health data from large general populations.