An anthropological history of Nepal's Female Community Health Volunteer program: gender, policy, and social change.

BACKGROUND: Community health workers (CHWs) are central to Primary Health Care globally. Amidst the current flourishing of work on CHWs, there often is a lack of reference to history-even in studies of programs that have been around for decades. This study examines the 35-year trajectory of Nepal's Female Community Health Volunteers (FCHVs). METHODS: We conducted a content analysis of an archive of primary and secondary research materials, grey literature and government reports collected during 1977-2019 across several regions in Nepal. Documents were coded in MAXQDA using principles of inductive coding. As questions arose from the materials, data were triangulated with published sources. RESULTS: Looking across four decades of the program's history illuminates that issues of gender, workload, and pay-hotly debated in the CHW literature now-have been topics of discussion for observers and FCHVs alike since the inception of the program. Following experiments with predominantly male community volunteers during the 1970s, Nepal scaled up the all-female FCHV program in the late 1980s and early 1990s, in part because of programmatic goals focused on maternal and child health. FCHVs gained legitimacy as health workers in part through participation in donor-funded vertical campaigns. FCHVs received a stable yet modest regular stipend during the early years, but since it was stopped in the 1990s, incentives have been a mix of activity-based payments and in-kind support. With increasing outmigration of men from villages and growing work responsibilities for women, the opportunity cost of health volunteering increased. FCHVs started voicing their dissatisfaction with remuneration, which gave rise to labor movements starting in the 2010s. Government officials have not comprehensively responded to demands by FCHVs for decent work, instead questioning the relevance of FCHVs in a modern, medicalized Nepali health system. CONCLUSIONS: Across public health, an awareness of history is useful in understanding the present and avoiding past mistakes. These histories are often not well-archived, and risk getting lost. Lessons from the history of Nepal's FCHV program have much to offer present-day debates around CHW policies, particularly around gender, workload and payment.

Country-based modelling of COVID-19 case fatality rate: A multiple regression analysis.

BACKGROUND: The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection. The determinants of mortality on a global scale cannot be fully understood due to lack of information. AIM: To identify key factors that may explain the variability in case lethality across countries. METHODS: We identified 21 Potential risk factors for coronavirus disease 2019 (COVID-19) case fatality rate for all the countries with available data. We examined univariate relationships of each variable with case fatality rate (CFR), and all independent variables to identify candidate variables for our final multiple model. Multiple regression analysis technique was used to assess the strength of relationship. RESULTS: The mean of COVID-19 mortality was 1.52 ± 1.72%. There was a statistically significant inverse correlation between health expenditure, and number of computed tomography scanners per 1 million with CFR, and significant direct correlation was found between literacy, and air pollution with CFR. This final model can predict approximately 97% of the changes in CFR. CONCLUSION: The current study recommends some new predictors explaining affect mortality rate. Thus, it could help decision-makers develop health policies to fight COVID-19.

Secondary School State Athletic Association Health and Safety Policy Development Processes.

BACKGROUND: The National Federation of State High School Associations provides recommendations regarding health and safety policies; however, policy development is governed at the state level. Given interstate differences in governance, the primary purpose was to describe processes that State High School Athletic Associations (SHSAAs) utilize to develop a new policy. The secondary objective was to determine what methods associations use to implement new policies. METHODS: A cross-sectional survey requested SHSAA (n = 51) representatives to report how athlete health and safety policies are introduced, revised, approved, and implemented within their state. The 22-question survey was developed to gather variables for the aims of the study. Descriptive statistics were calculated for each survey item. RESULTS: Of states who responded (n = 33), most reported a 2-committee (n = 24, 72.7%) process for developing and vetting policies, with initiation from the Sports Medicine Advisory Committee (n = 27, 81.8%), followed by an executive-level committee (n = 18, 66.7%). States reported total time from policy initiation to final approval ranged from 2 weeks to over 12 months. When a new policy was approved, most states indicated implementation began with an e-mail (n = 24, 72.7%) sent to Athletic Directors (n = 26, 78.8%). School principal or district superintendent were reported as the position in charge of compliance (36.4%, n = 12). CONCLUSIONS: Most SHSAAs use a 2-step process to write and review an athlete health and safety policy before approval. SHSAAs that require a longer policy development time could delay the implementation of important health measures. SHSAAs could consider additional communication methods to ensure information reaches all stakeholders.

"It's time for a change. I need to. I have to": Substance misuse recovery turning points of unhoused Alaskans.

Substance misuse is a pernicious health concern for many unhoused people. A deep understanding of turning points - what propels someone to take concrete action toward addressing substance misuse - is needed to inform recovery policies and practices. This study sought to identify common elements in turning points among unhoused people vis-à-vis a phenomenological qualitative approach. Twenty people (Mage = 47.47, SD = 9.75; 50% female) who self-identified as being in recovery while unhoused participated in semi-structured interviews in Anchorage, Alaska, a community with high rates of both houselessness and substance misuse. Survival (life- and health-sustaining), individual (intrapersonal), and relational (interpersonal) motivations all shaped turning points. Limitations include the possible underrepresentation of individuals using a harm-reduction approach or capturing differences by housing type. Programs to address substance misuse should consider these motivations. Future research should identify and refine turning points and work to understand how they interact with change processes.

RHMCD-20 dataset: Identify rapid human mental health depression during quarantine life using machine learning.

The RHMCD-20 dataset offers a thorough investigation of the dynamics of mental health in Bangladesh while under quarantine. The structured survey that was distributed to different demographic groups yielded a dataset that included a wide range of variables, such as age, gender, occupation, and stress levels. Predictive modelling, understanding the effects of quarantine on the workplace and society, and intergenerational insights are all greatly enhanced by this dataset. The dataset allows intelligent algorithms to be developed by bridging the gap between machine learning and healthcare. Although sampling bias is one of the limitations of correlation analysis, it does improve understanding. This presents opportunities for improving precision in mental health management, fostering interdisciplinary collaborations, and creating dynamic forecasting models. Researchers and policymakers can benefit greatly from the RHMCD-20 dataset, which offers nuanced insights into mental health experiences during quarantine and informs evidence-based interventions and policies. groundwork for innovative methodologies, steering the trajectory of informed decision-making in dynamic energy landscapes.

Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.

PURPOSE: This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processing (NLP) and machine learning (ML) techniques on race-related spatiotemporal social media text data. Specifically, this study establishes the extent to which Latent Dirichlet Allocation (LDA) and Gibbs Sampling Dirichlet Multinomial Mixture (GSDMM)-based topic modeling determines social determinants of health (SDOH) categories, and how adequately custom named-entity recognition (NER) detects key SDOH factors from a race/ethnicity-related Reddit data corpus. METHODS: In this study, we collected race/ethnicity-specific data from 5 location subreddits including New York City, NY; Los Angeles, CA; Chicago, IL; Philadelphia, PA; and Houston, TX from March to December 2019 (before COVID-19 pandemic) and from March to December 2020 (during COVID-19 pandemic). Next, we applied methods from natural language processing and machine learning to analyze SDOH issues from extracted Reddit comments and conversation threads using feature engineering, topic modeling, and custom named-entity recognition (NER). RESULTS: Topic modeling identified 35 SDOH-related topics. The SDOH-based custom NER analyses revealed that the COVID-19 pandemic significantly impacted SDOH issues of marginalized Black and Asian communities. On average, the Social and Community Context (SCC) category of SDOH had the highest percent increase (366%) from the pre-pandemic period to the pandemic period across all locations and population groups. Some of the detected SCC issues were racism, protests, arrests, immigration, police brutality, hate crime, white supremacy, and discrimination. CONCLUSION: Reddit social media platform can be an alternative source to assess the SDOH issues of marginalized Black and Asian communities during the COVID-19 pandemic. By employing NLP/ML techniques such as LDA/GSDMM-based topic modeling and custom NER on a race/ethnicity-specific Reddit corpus, we uncovered various SDOH issues affecting marginalized Black and Asian communities that were significantly worsened during the COVID-19 pandemic. As a result of conducting this research, we recommend that researchers, healthcare providers, and governments utilize social media and collaboratively formulate responses and policies that will address SDOH issues during public health crises.

Effects of red meat taxes and warning labels on food groups selected in a randomized controlled trial.

BACKGROUND: High consumption of red and processed meat contributes to both health and environmental harms. Warning labels and taxes for red meat reduce selection of red meat overall, but little is known about how these potential policies affect purchases of subcategories of red meat (e.g., processed versus unprocessed) or of non-red-meat foods (e.g., cheese, pulses) relevant to health and environmental outcomes. This study examined consumer responses to warning labels and taxes for red meat in a randomized controlled trial. METHODS: In October 2021, we recruited 3,518 US adults to complete a shopping task in a naturalistic online grocery store. Participants were randomly assigned to one of four arms: control (no warning labels or tax), warning labels only (health and environmental warning labels appeared next to products containing red meat), tax only (prices of products containing red meat were increased 30%) or combined warning labels + tax. Participants selected items to hypothetically purchase, which we categorized into food groups based on the presence of animal- and plant-source ingredients (e.g., beef, eggs, pulses), meat processing level (e.g., processed pork versus unprocessed pork), and meat species (e.g., beef versus pork). We assessed the effects of the warning labels and tax on selections from each food group. RESULTS: Compared to control, all three interventions led participants to select fewer items with processed meat (driven by reductions in processed pork) and (for the tax and warning labels + tax interventions only) fewer items with unprocessed meat (driven by reductions in unprocessed beef). All three interventions also led participants to select more items containing cheese, while only the combined warning labels + tax intervention led participants to select more items containing processed poultry. Except for an increase in selection of pulses in the tax arm, the interventions did not affect selections of fish or seafood (processed or unprocessed), eggs, or plant-based items (pulses, nuts & seeds, tofu, meat mimics, grains & potatoes, vegetables). CONCLUSIONS: Policies to reduce red meat consumption are also likely to affect consumption of other types of foods that are relevant to both health and environmental outcomes. TRIAL REGISTRATION: NCT04716010 on www. CLINICALTRIALS: gov .

Investigation of Factors Influencing Infant Mortality at Greater Accra Regional Hospital, Ghana.

Background: Annually, 5.4 million children under five face mortality, with 2.5 million deaths in the first month, 1.6 million between one and eleven months, and 1.3 million aged one to four. Despite global strides, sub-Saharan Africa, including Ghana, grapples with persistent high child mortality. This study employs statistical methods to pinpoint factors driving under-five mortality in the Greater Accra Regional Hospital. Methods: The data was acquired from Greater Accra Regional Hospital, Ghana, spanning January to December 2020. The data comprised all under-five deaths recorded in the hospital in 2020. The statistical tools employed were the chi-square test of association and the multinomial logistic regression model. Results: In 2020, there were 238 cases of under-five mortality recorded in the hospital, with males constituting the majority (55%). About 85% of these cases occurred within the first month of birth, primarily attributed to respiratory distress, prematurity, and sepsis. Notably, meconium aspiration was the least common among grouped diagnoses. The test of association and multinomial logistic model emphasised the child's age, birth type, and weight at birth as significant factors influencing child mortality. Conversely, attributes like sex, marital status, and mother's age displayed no notable association with the diagnosis of death. Conclusion: The study on child mortality at the Greater Accra Regional Hospital unveils key factors shaping child health outcomes, emphasising the role of age, birth type, and weight. While specific demographics show no significant association, identified predictors are vital for targeted interventions. Proposed strategies encompass education programs, improved care, birthing practices, and data-driven policies.

An Interactive Mapping and Case Discussion Seminar Introducing Medical Students to Climate Change, Environmental Justice, and Health.

Introduction: Integrating climate change and health into a medical school curriculum is critical for future physicians who will manage health crises caused by a rapidly changing climate. Although medical schools have increasingly included climate change in the curriculum, there remains a need to address the link between the climate crisis, environmental justice, and historical policies that shape environmental health disparities in local communities. Methods: In academic years 2021-2022 (AY22) and 2022-2023 (AY23), second-year medical students participated in a 2.5-hour seminar utilizing didactic teaching and small breakout groups that included interactive mapping activities and case scenarios. Learner knowledge and attitudes were self-assessed using pre- and postcurriculum surveys and a quiz. Qualitative thematic and content analysis was used to evaluate short-answer quiz responses and feedback. Results: Of 357 students who participated in the seminar, 208 (58%) completed both the precurriculum and postcurriculum surveys. Self-assessed ability increased significantly for all educational objectives across both years. Attitudes on the importance of climate change knowledge for patient health also improved from a mean of 3.5 precurriculum to 4.2 postcurriculum (difference = 0.7, p < .01) in AY22 and from 3.6 pre- to 4.3 postcurriculum (difference = 0.7, p < .01) in AY23 on a 5-point Likert scale. Discussion: This climate change and health session highlighting the link between environmental policy and climate change health vulnerability in the local context was successful in improving students' self-assessed ability across all stated educational objectives. Students cited the interactive small-group sessions as a major strength.

Impact of influenza related hospitalization in Spain: characteristics and risk factor of mortality during five influenza seasons (2016 to 2021).

Background: Estimating the global influenza burden in terms of hospitalization and death is important for optimizing prevention policies. Identifying risk factors for mortality allows for the design of strategies tailored to groups at the highest risk. This study aims to (a) describe the clinical characteristics of hospitalizations with a diagnosis of influenza over five flu seasons (2016-2017 to 2020-2021), (b) assess the associated morbidity (hospitalization rates and ICU admissions rate), mortality and cost of influenza hospitalizations in different age groups and (c) analyze the risk factors for mortality. Methods: This retrospective study included all hospital admissions with a diagnosis of influenza in Spain for five influenza seasons. Data were extracted from the Spanish National Surveillance System for Hospital Data from 1 July 2016 to 30 June 2021. We identified cases coded as having influenza as a primary or secondary diagnosis (International Classification of Diseases, 10th revision, J09-J11). The hospitalization rate was calculated relative to the general population. Independent predictors of mortality were identified using multivariable logistic regression. Results: Over the five seasons, there were 127,160 hospitalizations with a diagnosis of influenza. The mean influenza hospitalization rate varied from 5/100,000 in 2020-2021 (COVID-19 pandemic) to 92.9/100,000 in 2017-2018. The proportion of influenza hospitalizations with ICU admission was 7.4% and was highest in people aged 40-59 years (13.9%). The case fatality rate was 5.8% overall and 9.4% in those aged 80 years or older. Median length of stay was 5 days (and 6 days in the oldest age group). In the multivariable analysis, independent risk factors for mortality were male sex (odds ratio [OR] 1.14, 95% confidence interval [95% CI] 1.08-1.20), age (<5 years: OR 1; 5-19 years: OR 2.02, 95%CI 1.17-3.49; 20-39 years: OR 4.11, 95% CI 2.67-6.32; 40-59 years: OR 8.15, 95% CI 5.60-11.87; 60-79 years: OR 15.10, 95% CI 10.44-21.84; ≥80 years: OR 33.41, 95% CI 23.10-48.34), neurological disorder (OR 1.97, 95% CI 1.83-2.11), heart failure (OR 1.85, 95% CI 1.74-1.96), chronic kidney disease (OR 1.33, 95% CI 1.25-1.41), chronic liver disease (OR 2.95, 95% CI 2.68-3.27), cancer (OR 1.85, 95% CI 1.48-2.24), coinfection with SARS-CoV2 (OR 3.17, 95% CI 2.34-4.28), influenza pneumonia (OR 1.76, 95% CI 1.66-1.86) and admission to intensive care (OR 7.81, 95% CI 7.31-8.36). Conclusion: Influenza entails a major public health burden. People aged over 60-and especially those over 80-show the longest hospital stays. Age is also the most significant risk factor for mortality, along with certain associated comorbidities.

Digital psychiatry in Nigeria: A scoping review.

Background: Mental healthcare workforce shortage in Nigeria poses a major obstacle to mental health services scale-up. Digital psychiatry may provide a veritable platform to bridge treatment gaps. Aim: To provide an overview of quantity and range of peer-reviewed publications on digital psychiatry in Nigeria. Setting: A comprehensive literature search encompassed all original, peer-reviewed research articles on digital psychiatry in Nigeria. PubMed, Google Scholar, and a direct exploration of relevant journal article reference lists were utilised. Inclusion criteria covered peer-reviewed original articles conducted in Nigeria between January 2013 and January 2023, regardless of quality. Exclusions comprised case reports, reviews, dissertations, and abstracts. Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines were adhered to, while methodological framework of Arksey and O'Malley was used to describe the review. Results: Fourteen studies meeting inclusion criteria exhibited two primary research areas: implementation and intervention. Most studies focused on intervention strategies, showcasing efficacy of digital devices in enhancing outcomes in depression and clinic appointments. Implementation studies indicated favorable acceptance by both clients and healthcare practitioners. Conclusion: Digital technology seems acceptable to Nigerian patients and clinicians. Policies to operationalise provision of digital healthcare services will have positive impact in addressing unmet mental health needs. Finally, the quality of the evidence from majority of studies has to be enhanced, and additional studies are required to uncover gaps in some regions of the country. Contribution: This research demonstrates that, despite some drawbacks, digital methods of providing mental healthcare are practical in Nigeria.

Acceptability and Satisfaction of Patients and Providers With Telemedicine During the COVID-19 Pandemic: A Systematic Review.

COVID-19, also known as coronavirus disease 2019, is an extremely contagious viral sickness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). After the first cases of this primarily respiratory viral illness were recorded in Wuhan, Hubei Province, China, in late December 2019, SARS-CoV-2 rapidly disseminated across the globe. Consequently, on March 11, 2020, the World Health Organization (WHO) declared it a global pandemic. The rapid spread of the COVID-19 virus, coupled with subsequent lockdowns and social distancing measures, profoundly disrupted traditional healthcare delivery systems. Amidst the COVID-19 pandemic, telemedicine emerged as a pivotal solution for delivering healthcare services while minimizing exposure to the virus. This study aims to assess patient and provider satisfaction with telemedicine during this unprecedented period. A systematic literature search was conducted on PubMed and Google Scholar using specific MeSH terms and Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses (PRISMA) guidelines to summarize patient and provider satisfaction concerning telemedicine using all the facts, evidence, and published literature. The analysis showed that although providers were generally satisfied with telemedicine, they were less satisfied than patients due to technical issues and difficulties transmitting documents. Patients reported high satisfaction with telemedicine, citing convenience and cost savings as major benefits. However, a lack of provider compensation was identified as a potential barrier to adoption. Most providers believed that telemedicine was only necessary in emergencies while a few recognized its potential for routine care. The study concludes that telemedicine has the potential to improve healthcare access and efficiency, but more research is needed to address technical and reimbursement issues and to determine the appropriate scope of telemedicine use. Overall, the findings of this study can inform future healthcare policies and regulations to ensure that telemedicine is used effectively and to the satisfaction of both patients and providers.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

Past School Discipline Experiences: Perspectives of Disabled Adults.

BACKGROUND: School discipline has potential life-long consequences for students. Disabled youth can be misunderstood and experience harsh discipline and are at increased risk for negative outcomes, yet little research includes their voices. The aim of this study was to explore past school discipline experiences among disabled adults. METHODS: Disabled adult perspectives (N = 9) regarding past school discipline experiences were explored employing qualitative descriptive methodology framed by the Peace and Power Conceptual Model. Peace-Power versus Power-Over-Powers involve actions/behaviors reflecting critical emancipation or oppression of those in power. RESULTS: Eight peace-power versus power-over themes emerged: "humiliating," "threatening," "escaping," "observing," "avoiding," "diverging," "isolating," and "failing." IMPLICATIONS FOR SCHOOL HEALTH POLICY, PRACTICE, AND EQUITY: Disabled students can experience oppressive power-over dynamics separating them from others because they are unable to meet rigid classroom expectations. Educators may lack awareness of structural biases shaping reactions warranting need for school policies and practices promoting restorative justice, social-emotional learning, and inclusion. CONCLUSIONS: Classroom discipline can represent emancipatory peace-power or oppressive power-over powers. Not all teacher interactions represent 1 power or the other. Future research should focus on including disabled student voices informing school discipline practices. Educators' perspectives of their role fostering inclusive classrooms should also be considered.

Food insecurity and mental health among US adults during the COVID-19 pandemic: Results from National Health Interview Survey, 2020-2021.

OBJECTIVE: To examine socio-demographic disparities in food insecurity during the COVID-19 pandemic and the association between food insecurity and mental health among US adults overall and communities vulnerable to food insecurity. METHODS: A cross-sectional study was conducted using the 2020-2021 National Health Interview Survey of 57,456 US adults. Weighted multivariable logistic regression models were used to estimate the association between food insecurity and anxiety or depression symptoms in overall US adults and subgroups including young adults (18-34 years), females, Hispanic people, non-Hispanic Black people, individuals with prior COVID-19 infection, the unemployed, low-income participants, participants with children, and Supplemental Nutrition Assistance Program (SNAP) participants. RESULTS: Young or middle age, female sex, Hispanic/non-Hispanic Black/other race/ethnicity, lower education level, unmarried/other marital status, unemployment, being below the federal poverty level, and greater number of persons in the household were associated with food insecurity (AOR ranged from 1.35 to 2.70, all p < 0.05). Food insecurity was independently associated with anxiety (AOR = 2.67, 99 % CI: 2.33, 3.06) or depression (AOR = 3.04, 99 % CI: 2.60, 3.55) symptoms in the overall adults. Significant associations between food insecurity and anxiety or depression symptoms were also observed in all subgroups (AOR ranged from 1.95 to 3.28, all p < 0.0001). Compared with overall adults, the magnitude of the association was greater for participants with children, females (for depression only), and non-Hispanic Black people (for depression only). LIMITATIONS: The cross-sectional design prevents inference of causality. CONCLUSIONS: Comprehensive policies are needed to ensure accessible and affordable food resources to reduce disparities in food insecurity and improve mental health, especially for those socioeconomically disadvantaged communities.

An economic evaluation and incremental analysis of the cost effectiveness of three universal childhood varicella vaccination strategies for Ireland.

BACKGROUND: The cost effectiveness of childhood varicella vaccination is uncertain, as evidenced by variation in national health policies. Within the European Economic Area (EEA), only 10 of 30 countries offer universally funded childhood varicella vaccination. This study estimates the cost effectiveness of universal childhood varicella vaccination for one EEA country (Ireland), highlighting the difference in cost effectiveness between alternative vaccination strategies. METHODS: An age-structured dynamic transmission model, simulating varicella zoster virus transmission, was developed to analyse the impact of three vaccination strategies; one-dose at 12 months old, two-dose at 12 and 15 months old (short-interval), and two-dose at 12 months and five years old (long-interval). The analysis adopted an 80-year time horizon and considered payer and societal perspectives. Clinical effectiveness was based on cases of varicella and subsequently herpes zoster and post-herpetic neuralgia avoided, and outcomes were expressed in quality-adjusted life-years (QALYs). Costs were presented in 2022 Irish Euro and cost effectiveness was interpreted with reference to a willingness-to-pay threshold of €20,000 per QALY gained. RESULTS: From the payer perspective, the incremental cost-effectiveness ratio (ICER) for a one-dose strategy, compared with no vaccination, was estimated at €8,712 per QALY gained. The ICER for the next least expensive strategy, two-dose long-interval, compared with one-dose, was estimated at €45,090 per QALY gained. From a societal perspective, all three strategies were cost-saving compared with no vaccination; the two-dose short-interval strategy dominated, yielding the largest cost savings and health benefits. Results were stable across a range of sensitivity and scenario analyses. CONCLUSION: A one-dose strategy was highly cost effective from the payer perspective, driven by a reduction in hospitalisations. Two-dose strategies were cost saving from the societal perspective. These results should be considered alongside other factors such as acceptability of a new vaccine within the overall childhood immunisation schedule, programme objectives and budget impact.

Progress towards universal health coverage and inequalities in infant mortality: an analysis of 4·1 million births from 60 low-income and middle-income countries between 2000 and 2019.

BACKGROUND: Expanding universal health coverage (UHC) might not be inherently beneficial to poorer populations without the explicit targeting and prioritising of low-income populations. This study examines whether the expansion of UHC between 2000 and 2019 is associated with reduced socioeconomic inequalities in infant mortality in low-income and middle-income countries (LMICs). METHODS: We did a retrospective analysis of birth data compiled from Demographic and Health Surveys (DHSs). We analysed all births between 2000 and 2019 from all DHSs available for this period. The primary outcome was infant mortality, defined as death within 1 year of birth. Logistic regression models with country and year fixed effects assessed associations between country-level progress to UHC (using WHO's UHC service coverage index) and infant mortality (overall and by wealth quintile), adjusting for infant-level, mother-level, and country-level variables. FINDINGS: A total of 4 065 868 births to 1 833 011 mothers were analysed from 177 DHSs covering 60 LMICs between 2000 and 2019. A one unit increase in the UHC index was associated with a 1·2% reduction in the risk of infant death (AOR 0·988, 95% CI 0·981-0·995; absolute measure of association, 0·57 deaths per 1000 livebirths). An estimated 15·5 million infant deaths were averted between 2000 and 2019 because of increases in UHC. However, richer wealth quintiles had larger associated reductions in infant mortality from UHC (quintile 5 AOR 0·983, 95% CI 0·973-0·993) than poorer quintiles (quintile 1 0·991, 0·985-0·998). In the early stages of UHC, UHC expansion was generally beneficial to poorer populations (ie, larger reductions in infant mortality for poorer households [infant deaths per 1000 per one unit increase in UHC coverage: quintile 1 0·84 vs quintile 5 0·59]), but became less so as overall coverage increased (quintile 1 0·64 vs quintile 5 0·57). INTERPRETATION: Since UHC expansion in LMICs appears to become less beneficial to poorer populations as coverage increases, UHC policies should be explicitly designed to ensure lower income groups continue to benefit as coverage expands. FUNDING: UK National Institute for Health and Care Research.

Local government spending and mental health: Untangling the impacts using a dynamic modelling approach.

This study investigated the impact of local government spending on mental health in England between 2013 and 2019. Guided by the "Health in All Policies" vision, which encourages the integration of health in all decision-making areas, we explored how healthcare and multiple nonmedical budgeting decisions related to population mental health. We used random curve general cross-lagged modelling to dynamically partition effects into the short-run (from t to t + 1) and long-run (from t to t + 2) impacts, account for unobserved area-level heterogeneity and reverse causality from health outcomes to financial investments, and comprehensive modelling of budget items as an interconnected system. Our findings revealed that spending in adult social care, healthcare, and law & order predicted long-term mental health gains (0.004-0.081 SDs increase for each additional 10% in expenditure). However, these sectors exhibited negative short-term impulses (0.012-0.077 SDs decrease for each additional 10% in expenditure), markedly offsetting the long-term gains. In turn, infrastructural and environmental spending related to short-run mental health gains (0.005-0.031 SDs increase for each additional 10% in expenditure), while the long-run effects were predominantly negative (0.005-0.028 SDs decrease for each additional 10% in expenditure). The frequent occurrence of short-run and long-run negative links suggested that government resources may not be effectively reaching the areas that are most in need. In the short-term, negative effects could also imply temporary disruptions to service delivery largely uncompensated by later mental health improvements. Nonetheless, some non-health spending policies, such as law & order and infrastructure, can be related to long-lasting positive mental health impacts.

The overall fractions of coronary heart diseases and depression attributable to multiple dependent psychosocial work factors in Europe.

OBJECTIVES: The literature is nonexistent on the assessment of overall fractions of diseases attributable to multiple dependent psychosocial work factors. The objectives of the study were to calculate the overall fractions of coronary heart diseases (CHD) and depression attributable to multiple dependent psychosocial work factors in 35 European countries. METHODS: We used already published fractions of CHD and depression attributable to each of the following psychosocial work factors: job strain, effort-reward imbalance, job insecurity, long working hours, and workplace bullying. We took all exposures and their correlations into account to calculate overall attributable fractions. Wald tests were performed to test differences in these overall attributable fractions between genders and between countries. RESULTS: The overall fractions of CHD and depression attributable to all studied psychosocial work factors together were found to be 8.1% [95% CI: 2.0-13.9] and 26.3% [95% CI: 16.2-35.5] respectively in the 35 European countries. There was no difference between genders and between countries. CONCLUSION: Our study showed that the overall fractions attributable to all studied psychosocial work factors were substantial especially for depression. These overall attributable fractions may be particularly useful to evaluate the burden and costs attributable to psychosocial work factors, and also to inform policies makers at European level.

Examining State Licensing Requirements for Select Master's-Level Behavioral Health Providers for Children.

OBJECTIVE: The authors examined licensing requirements for select children's behavioral health care providers. METHODS: Statutes and regulations as of October 2021 were reviewed for licensed clinical social workers, licensed professional counselors, and licensed marriage and family therapists for all 50 U.S. states and the District of Columbia. RESULTS: All jurisdictions had laws regarding postgraduate training and license portability. No jurisdiction included language about specialized postgraduate training related to serving children and families or cultural competence. Other policies that related to the structure, composition, and authority of licensing boards varied across states and licensure types. CONCLUSIONS: In their efforts to address barriers to licensure, expand the workforce, and ensure that children have access to high-quality and culturally responsive care, states could consider their statutes and regulations.