Search Results (849)

Background/Objectives: The trajectory of influenza hospitalization burden from pre-COVID-19 pandemic baseline through post-pandemic recovery remains poorly characterized at the national level. This study characterized phase-stratified burden and seasonal structure, quantified racial and ethnic disparities, and assessed whether post-pandemic seasons represent anomalous departures from pre-pandemic expectations. Methods: Sixteen complete seasons of FluSurv-NET surveillance data (2009–2010 through 2024–2025; 509 observation weeks) were analyzed across pre-pandemic, disruption, and recovery phases using OLS regression with effect-size estimation, bootstrapped age-adjusted rate ratios, seasonal-trend decomposition (STL), Prophet time-series forecasting, and Isolation Forest anomaly detection. Results: Mean peak weekly hospitalization rate nearly doubled from pre-pandemic to recovery (5.1 to 11.1 per 100,000), cumulative seasonal burden increased from 46.3 to 87.0 per 100,000, and median peak timing advanced from MMWR week 9 to week 50. STL decomposition revealed a marked shift from weak pre-pandemic seasonality (Fs = 0.14) to substantially stronger annual regularity (Fs = 0.98) across three recovery seasons, with threefold amplitude increase. Non-Hispanic Black persons had rate ratios of 1.72, 2.16, and 1.99 relative to White persons across phases; American Indian and Alaska Native persons showed the highest disruption-phase ratio (2.24, 95% CI 1.90–3.53), based on two contributing seasons. A flat-growth Prophet model detected first exceedance in February 2020, outperforming a linear-growth specification on held-out validation. Isolation Forest identified 2017–2018, 2023–2024, and 2024–2025 as robust anomalies across all contamination thresholds. Conclusions: Post-COVID-19 pandemic influenza recovery is characterized by intensified and restructured seasonality, persistent racial and ethnic disparities, and anomalous burden exceeding pre-pandemic projections, identified independently by time-series forecasting and unsupervised anomaly detection. Full article

Background: Multiple Myeloma (MM) remains the most common indication for Autologous Stem Cell Transplant (ASCT). ASCT use is disproportionately lower in older adults, Black patients with MM, as well as those living in rural areas and of low socioeconomic status (SES). Low utilization of ASCT is linked to poor outcomes. There are numerous barriers to ASCT access and limited interventions to address disparate outcomes in patients with MM. Methods: This is an ambispective study conducted at a single institution to identify and mitigate barriers to ASCT utilization. In aim one, we retrospectively evaluated ASCT utilization and overall survival (OS) for MM patients accounting for clinical, geographic (Rural Urban Commuting Area—RUCA), and socioeconomic factors (Yost). In aim two, based on the observations of the retrospective study, we conducted a prospective feasibility study to improve access for vulnerable patients with MM (older adults, Black patients, rural and/or Appalachian residence) using a virtual ASCT consultative model with patient navigation, coordinated with local oncology centers. Poisson regression estimated the relative risk of receiving ASCT. OS was calculated from MM diagnosis to the date of death censoring survivors at last contact and analyzed using Kaplan-Meir. Cox proportional hazard models estimated the hazard ratio for risk of death. The multivariable model was built including significant risk factors from the univariable models to estimate the independent effect of each risk factor. Results: Among 1799 patients, median age of diagnosis was 61 (range 17–87), race was self-identified as White (85.6%), Black (13.1%), or other (1.3%) and it was primarily metropolitan (n = 1205, 71.2%) and 1169 (65%) received a transplant. The hazard of death was lower for those who received a transplant (vs. no transplant, HR = 0.63, 95%CI 0.53–0.74, p < 0.001), patients identified as Black (vs. White, HR = 0.66, 95%CI 0.51–0.85, p = 0.001) and higher SES areas (quartile 2–4 vs. quartile 1, HR = 0.69, 95%CI 0.58–0.83, p < 0.001). Prospectively with patient navigation and virtual consultation (n = 35), half of the patients sought virtual consultation, 68% of patients were eligible for transplant, 43% went on to receive ASCT, of which 42% of patients were non-metropolitan and 15% of patients were from an Appalachian county. Using this strategy, no difference was observed in ASCT utilization by age (31% in age > 70 vs. 45% in age 65–70 vs. 78% in age < 65, p = 0.10), geographical area (47% in metro vs. 50% in non-metro, p = 0.99), or race (46% in White vs. 60% in Black, p = 0.66). Conclusions: Implementing patient navigation and virtual transplant consultation can effectively enhance access to ASCT among underserved MM populations while reducing the influence of racial and geographic differences. Full article

Background: Maternal mortality remains a major global health challenge, disproportionately affecting black and Indigenous women. Hypertensive disorders of pregnancy and postpartum hemorrhage are the leading direct causes of maternal death. Artificial intelligence (AI) tools have emerged as potential strategies for predicting these complications, yet concerns persist about their equity and validation across racial groups. Methods: A rapid review was conducted in five databases, PubMed, EMBASE, Web of Science, Scopus and LILACS, to synthesize recent evidence on the use of AI for preventing maternal mortality due to hypertension and postpartum hemorrhage. Studies published in the last five years that included racial or ethnic data were selected and analyzed narratively. Results: Ten studies met the inclusion criteria, showing high predictive accuracy of AI models (AUROC often >0.95) for severe maternal outcomes. However, few models incorporated racial variables or underwent external validation in racially diverse or low-resource populations. Evidence suggests that unrepresentative datasets may perpetuate or exacerbate existing health inequities. Conclusions: AI demonstrates strong technical performance in predicting maternal complications but limited equity in application. Broader racial representation, external validation, and ethical governance are essential for ensuring that AI-based tools reduce rather than reinforce racial disparities in maternal mortality. Full article

Background: Population-level predictors of intraocular pressure (IOP)-lowering surgery for neovascular glaucoma (NVG) are understudied. This study examines factors associated with IOP-lowering surgery in California (CA) Medicare beneficiaries with NVG. Methods: The study population included all 2019 CA Medicare beneficiaries with NVG. Covariates included age, sex, race/ethnicity, history of treatments for retinal ischemia, dual Medicare/Medicaid eligibility, Social Vulnerability Index score, and Charlson Comorbidity Index (CCI) score. Outcomes included incidence of trabeculectomy, tube shunt, minimally invasive glaucoma surgery, cyclophotocoagulation (CPC), or any IOP-lowering surgery. Results: Of 1843 beneficiaries, 264 (14.3%) had IOP-lowering surgeries. In multivariable logistic regression including all covariates, CCI ≥ 5 versus 0 was associated with lower odds of any IOP-lowering surgery and of each type of surgery except CPC (adjusted odds ratio [aOR] = 0.47, 95% confidence interval [CI] = 0.29, 0.75 for any versus no surgery; aOR = 1.35, CI = 0.51, 3.60 for CPC). Compared to Non-Hispanic White, racial and ethnic minorities had increased odds of trabeculectomy (aOR = 3.77, CI = 1.05, 13.57 for Black; aOR = 2.69, CI = 1.04, 6.92 for Hispanic) and tube shunt (aOR = 2.62, CI = 1.27, 5.41 for Other/Unknown). Beneficiaries 75–79 versus 65–69 years old had decreased odds of trabeculectomy (aOR = 0.21, CI = 0.05, 0.98). Conclusions: Among CA Medicare beneficiaries, higher systemic disease burden was associated with a decreased likelihood of surgery for NVG, while racial and ethnic minorities were more likely to undergo certain procedures. These findings suggest surgical risk stratification and treatment pattern disparities for individuals with NVG. Full article

Although apartheid ended in 1994, its legacy continues to shape South Africa’s higher education system, reinforcing disparities in access, funding, and representation. This study aims to critically examine how apartheid diplomacy has influenced higher education and asks: how do its strategies continue to shape academic practices, institutional relationships, and systemic inequalities in post-apartheid South Africa? It conceptualises apartheid diplomacy as the use of education to entrench racial hierarchies, reproduce class domination, and suppress indigenous knowledge. Grounded in Marxist and Weberian class theories and Crenshaw’s intersectionality framework, the analysis traces how apartheid-era policies institutionalised systemic inequalities and how these legacies persist within institutions. A scoping review was conducted using five databases (EMBASE, APA PsycINFO, Cochrane Library, CINAHL, and Scopus) between January 2007 and April 2025, guided by PRISMA ScR and Arksey and O’Malley’s six-stage framework. Of 75 articles retrieved, 15 met the inclusion criteria. Findings reveal that apartheid diplomacy shaped academic governance, resource distribution, and knowledge production, leaving enduring inequities despite ongoing reforms. Transformation efforts, including financial aid schemes, equity policies, and curriculum debates, have achieved progress but remain constrained by structural, cultural, and intersectional barriers. The study underscores that achieving lasting equity requires continuous policy interventions, inclusive leadership, and curriculum decolonisation, alongside advocacy and interdisciplinary research. It reframes higher education as a diplomatic arena where equity and epistemic justice are negotiated, offering an original lens for understanding and dismantling apartheid’s enduring influence on South African academia. Full article

Ductal carcinoma in situ (DCIS) is a non-invasive precursor to invasive breast cancer. DCIS incidence continues to rise, yet its clinical management remains constrained by the absence of reliable biomarkers that can adequately distinguish indolent lesions from those with high invasive potential, to circumvent over- or under-treatment. Black women with DCIS are significantly more likely to progress to invasive breast cancer, are disproportionately diagnosed with high-grade, hormone receptor-negative lesions, and experience elevated risk of recurrence and mortality relative to White women with DCIS. These disparities persist despite comparable access to screening and treatment, suggesting underlying biological and tissue microenvironmental factors. This review synthesizes emerging evidence implicating early molecular and systemic changes that may be driving the disparity in DCIS progression. We highlight racial distinctions in interconnected pathways involving Wnt/β-catenin signaling, metabolic and nutritional dysregulation, immune microenvironment remodeling, and cellular tolerance of genomic instability. We further discuss how epigenetic alterations, obesity-associated inflammation, and immune dysregulation may arise during the pre-invasive stage that intersect with social and environmental exposures to influence racial differences in lesion fate. We spotlight candidate biomarkers disproportionately associated with aggressive disease in Black women—including KIFC1, a mediator of centrosome clustering and genomic instability tolerance, and ACKR1/DARC, a regulator of chemokine gradients and immune trafficking—as potential drivers of progression-permissive states. This review advances an integrated, equity-informed framework for DCIS progression that links early tumor evolution to coordinated alterations in genomic instability, immune regulation, metabolic signaling, and stress-adaptive pathways. Importantly, we propose that DCIS progression is governed not by isolated molecular alterations but by coordinated programs that enable survival under genomic and immunologic stress. Current clinical risk assays, which primarily capture tumor-intrinsic proliferation and hormone signaling, do not fully resolve these pathways and may therefore incompletely reflect biologically meaningful racial disparities. This synthesis underscores the need for pathway-level, microenvironment-informed, and population-representative approaches to DCIS risk stratification. Advancing such frameworks will be essential for identifying actionable biomarkers, refining early intervention strategies, and ultimately reducing racial disparities in breast cancer outcomes. Full article

The COVID-19 pandemic triggered an unprecedented expansion of telehealth within the Medicare program, raising the question of whether this surge represented a temporary crisis response or a durable shift in care delivery. This study applied supervised machine learning and explainable artificial intelligence methods to national Medicare Telehealth Trends data to model nonlinear adoption dynamics and evaluate differential stabilization across demographic and geographic groups. Using state by quarter by demographic group observations from 2020 through 2025, random forest and gradient boosting models with temporally aware validation were implemented to characterize surge magnitude, peak timing, and post-surge equilibrium levels. Differential saturation was assessed using model predicted plateau estimates across age, race, dual eligibility status, and state. The results revealed a rapid and synchronous surge across demographic strata followed by stabilization into persistent but heterogeneous equilibrium levels. Age and dual eligibility status were associated with substantial divergence in plateau magnitude, while racial differences were comparatively modest after accounting for temporal and geographic factors. Geographic heterogeneity exceeded demographic variation, indicating that state level structural environments exert the strongest influence on long-term telehealth equilibrium. These findings suggest that telehealth has transitioned from emergency expansion to partial institutional embedding within Medicare preventive care delivery. However, uneven stabilization across states highlights structural disparities that may influence continuity of chronic disease management, behavioral health access, and routine preventive services. Strengthening digital infrastructure and policy alignment may therefore be necessary to ensure that telehealth functions as an equitable and durable component of preventive medicine beyond the pandemic period. Full article

Background: Ventricular arrhythmias (VAs) represent a high-risk complication of acute myocardial infarction (AMI) and are associated with high morbidity and mortality. Racial and ethnic disparities in the management and in-hospital outcomes of AMI with VAs remain incompletely understood. Methods: Using the National Inpatient Sample, we conducted a retrospective analysis of hospitalizations in which AMI was complicated by VAs from 2002 to 2022. Hospitalizations were stratified by race/ethnicity including White, Black, Hispanic, and other racial/ethnic groups. Baseline characteristics and in-hospital outcomes were compared across groups. Results: We identified 902,398 hospitalizations in which AMI was complicated by VAs, of which 78.2% occurred among White, 9.6% among Black, 6.3% among Hispanic, and 5.9% among patients of other racial/ethnic groups. Compared with White patients, Hispanic (aOR 1.21; CI 1.14–1.28) and patients in other racial/ethnic groups (aOR 1.31; CI 1.24–1.39) had higher odds of in-hospital mortality while Black patients had similar odds. In terms of procedural utilization, Black (aOR 0.65; CI 0.62–0.68), Hispanic (aOR 0.82; CI 0.77–0.86), and other racial/ethnic groups (aOR 0.89; CI 0.85–0.94) all had lower odds of percutaneous coronary intervention (PCI) relative to White patients. Black patients also had lower odds of coronary artery bypass grafting (CABG) (aOR 0.69; CI 0.64–0.74) and implantable cardioverter-defibrillator (ICD) insertion (aOR 0.84; CI 0.74–0.96) compared with White patients during admission. Conclusions: Racial and ethnic disparities exist in the prevalence, management, and in-hospital outcomes of AMI complicated by VAs. Further efforts are needed to address differences in care in this high-risk population. Full article

Preterm birth (PTB) remains a leading cause of neonatal morbidity and mortality and disproportionately affects Black women in the United States. While racial disparities in PTB are well documented, the molecular pathways underlying these differences remain incompletely understood. Extracellular vesicles (EVs) are circulating lipid-bound particles that carry coding and non-coding RNAs reflecting cellular stress states and may serve as integrative molecular indicators of pregnancy biology. In this hypothesis-generating pilot study, EVs were isolated from maternal plasma collected at delivery from non-Hispanic Black and non-Hispanic White women with preterm and full-term births. EV concentration and size were assessed, and EV-associated mRNA and miRNA cargo were profiled by next-generation sequencing (n = 5 per group), enabling differential expression and pathway enrichment analyses stratified by gestational outcome. EV concentrations were significantly elevated in PTB compared with full-term deliveries (p < 0.0001), with a greater increase among Black participants. Analysis of EV-associated mRNA transcripts identified a shared signature enriched for platelet activation and coagulation pathways across racial groups. Race-stratified analyses revealed distinct EV miRNA profiles in PTB, with enrichment of cytokine-mediated signaling pathways among Black participants and apoptosis-related pathways among White participants, while a subset of miRNAs differed by race independent of gestational outcome. These findings support EV profiling as a framework to investigate biological pathways contributing to PTB disparities. Full article

Background: Out-of-hospital cardiac arrest is a major cause of mortality, and survival depends heavily on rapid defibrillation. Automated external defibrillators (AEDs) can significantly improve outcomes when used before emergency medical services (EMS) arrive, yet access to and use of these devices remain uneven across communities. This study investigates racial and geographic disparities in AED use during EMS encounters in the United States, evaluating differences across racial groups, geographic settings, cardiac arrest status, and patient acuity, irrespective of whether a bystander or EMS personnel applied the device. Methods: This descriptive study used aggregated data from the National Emergency Medical Services Information System (NEMSIS) Public Release Data Cube to compare AED use across racial, geographic, cardiac arrest, and acuity categories. AED use was defined as any documented application during the EMS encounter. Results: The dataset included 106,246 EMS encounters across six racial and ethnic groups. AEDs were applied in 16,688 encounters (15.7%), with substantial variation across demographic and geographic categories. Asian, American Indian or Alaska Native, and Black or African American patients had the highest rates of AED use, while White patients had the lowest rate despite representing the largest share of encounters. Urban areas accounted for most AED deployments, whereas suburban and frontier regions showed markedly lower use, while rural AED use was similar to urban rates. AED application was strongly associated with cardiac arrest and high patient acuity, yet racial differences persisted even within these clinically severe categories. Conclusions: AED use generally aligns with clinical indicators such as cardiac arrest and critical acuity, but meaningful racial and geographic differences were observed, reflecting descriptive patterns rather than confirmed disparities. These patterns should be interpreted cautiously, as the aggregated nature of the dataset limits the ability to determine whether differences reflect inequities, incident characteristics, or EMS system factors. These findings highlight the need for targeted strategies to expand AED access, improve device placement, and strengthen community readiness in underserved areas. Integrating AED availability into broader EMS planning and community outreach may help reduce inequities and create conditions that support improved survival outcomes. Further research using individual-level data and geospatial methods is needed to clarify the drivers of these observed differences and inform equitable prehospital care policies. Full article

Background/Objectives: Racial/ethnic and regional disparities in neoplasm-related mortality remain a significant public health challenge. In this study, we aimed to evaluate long-term trends in county-level neoplasm-related mortality rates by race/ethnicity in the United States and examine associations with social determinants of health. Methods: We conducted a cross-sectional ecological study using population-based data from the Global Burden of Disease Study, including individuals residing in 50 states of the United States and the District of Columbia from 2000 to 2019. We analyzed age-standardized neoplasm-related mortality rates by ethnicity/race. Joinpoint regression analysis was used to identify significant changes in mortality trends, summarized as average annual percentage change. County-level correlations between mortality and key social determinants of health were also assessed. Results: Neoplasm-related mortality rates declined across all racial/ethnic groups from 2000 to 2019; however, disparities persisted. The age-standardized neoplasm-related mortality rates per 100,000 population decreased in all racial/ethnic subgroups. The average annual percentage change ranged from −0.94% (Hispanic and non-Hispanic American Indian or Alaska Native) to −1.90% (Black). Sex-specific analyses revealed similar trends. Southeastern states experienced slower declines than Northeastern states did. County-level smoking and poverty rates were positively correlated, whereas the primary care physician-to-population ratio, excessive alcohol consumption rate, mammography screening rate, and median household income were inversely correlated with neoplasm-related mortality rate, varying by race/ethnicity. Conclusions: Targeted, community-specific interventions are required to reduce inequities in cancer outcomes. Full article

The United States faces a worsening maternal mortality crisis that starkly contrasts with trends in other high-income nations. Maternal mortality rates (MMRs) have more than doubled over the past two decades, rising from 9.65 deaths per 100,000 live births in 1999–2002 to 23.6 in 2018–2021, with approximately 700 deaths annually. Black and American Indian/Alaska Native women experience maternal mortality rates two to three times higher than their White counterparts, reflecting persistent structural inequities rather than biological differences. This narrative review synthesizes current evidence on the underlying drivers of racial inequities in maternal mortality and evaluates evidence-based interventions and policy strategies to address these disparities. A comprehensive literature review between 2000 and 2025 was conducted using databases including PubMed, Scopus, Web of Science, and Google Scholar, focusing on studies examining clinical, social, and structural determinants of maternal health outcomes, as well as evidence-based interventions and maternal health policy. Targeted searches of policy reports and grey literature were also performed to identify relevant policy initiatives and system-level interventions. Key contributors to disparities include underlying health conditions, postpartum mental health inequities, provider shortages, and limited access to postpartum care, with pregnancy-associated breast cancer (PABC) representing a less common but clinically significant risk factor that warrants further investigation in the context of racial inequities. Structural racism and socioeconomic disparities further exacerbate inequities through differential access to care, treatment bias, and barriers to healthcare utilization. System-level challenges, including workforce shortages, maternity care deserts, and the absence of federally mandated paid maternity leave, disproportionately impact marginalized populations. Although policy initiatives such as Medicaid postpartum coverage extensions, the Maternal Health Momnibus Act, and Maternal Mortality Review Committees represent important progress, they remain insufficient without broader structural reform. Evidence-based interventions, including midwife- and doula-led care, community-based peer support, and culturally tailored mental health programs, demonstrate measurable improvements in maternal outcomes. Outcomes of this review highlight the need for a comprehensive, equity-centered approach to reducing maternal mortality disparities, emphasizing structural reform, expanded access to care, strengthened data systems, and community-driven solutions. Full article

Background: Prostate cancer remains a major cause of cancer morbidity and mortality among men in the United States. Differences in diagnosis and survival across racial and socioeconomic groups continue to raise concern in clinical and public health research. Population-based datasets provide an opportunity to examine patterns of advanced disease and survival outcomes across diverse demographic groups. Objective: This study evaluated racial and socioeconomic disparities in cancer-specific survival among patients with metastatic prostate cancer using a national population-based dataset. Methods: A retrospective population-based study was conducted using data from the Surveillance, Epidemiology, and End Results (SEER) program. Patients diagnosed with malignant prostate cancer between 2004 and 2020 with distant stage disease were included. The final analytic sample consisted of 54,062 patients. Variables included race and ethnicity, age group, metastatic sites at diagnosis, treatment variables, and median household income. Descriptive analyses compared characteristics by cancer-specific death using chi-square tests for categorical variables and t tests for continuous variables. Survival patterns were examined using Kaplan–Meier methods and log-rank tests. Multivariable Cox proportional hazards model was used to estimate adjusted hazard ratios for factors associated with cancer-specific mortality. Results: Cancer-specific mortality differed across racial and socioeconomic groups. Higher mortality was observed among non-Hispanic Black patients (aHR = 1.15, 95% CI: 1.00 to 1.31, p = 0.046) and non-Hispanic American Indian or Alaska Native patients (aHR = 1.15, 95% CI: 1.10 to 1.20, p < 0.001) compared with non-Hispanic White patients, while Hispanic and non-Hispanic Asian or Pacific Islander patients showed lower mortality risk. Older age groups demonstrated higher mortality. Liver, lung, and brain metastases were associated with increased risk of prostate cancer death. Patients in higher income groups showed lower mortality compared with patients in lower income groups (aHR = 0.83, 95% CI: 0.80 to 0.87, p < 0.001). Conclusions: This study highlights persistent racial and socioeconomic differences in cancer-specific survival among patients with advanced prostate cancer in the United States. These findings support continued efforts to address disparities in early detection, access to care, and treatment pathways. Future research should further explore clinical and structural factors that influence survival differences across population groups. Full article

Background: Sleep apnea is identified and treated less frequently among racial and ethnic minorities. Objective: The purpose of this systematic review was to examine disparities among racial and ethnic minorities and to understand the reasons for poor sleep health. Methods: The authors conducted a literature search using PubMed and Cochrane Library databases, last accessed in September 2025, using regular and MeSH keywords. A total of 123 articles were identified. PRISMA guidelines were followed, the PICO framework was applied, and the inclusion criteria were based on studies conducted in the past 10 years. After quality assessment, 18 studies were included for in-depth analysis. Results: The 18 studies included meta-analyses and observational cohort studies. In total, 51,489 patients were represented. Studies revealed that sleep apnea is underdiagnosed and undertreated in ethnic minority populations. Resident location, gender, economic status, and marital status also play an important role. One study noted clinically insignificant differences in positive airway pressure requirements between black and white populations. Nocturnal hypertension and increased left ventricle size are also observed in untreated sleep apnea. Given the heterogenous nature of the studies, quality risk assessment was not possible, which is a limitation of this study. Conclusions: Sleep apnea is underdiagnosed and undertreated among ethnic minorities. Factors such as ancestry, comorbidities, social determinants, geography, and healthcare access drive global inequities. Further sleep apnea phenotyping may be of value in planning treatment strategies. Full article

Heating, ventilation, and air conditioning (HVAC) systems struggle to maintain optimal thermal comfort because perception is subjective and varies significantly across individuals. Traditional uniform cooling strategies often overlook demographic diversity, leading to inequitable comfort outcomes and inefficient building operations. To address this limitation, this study analyzed a web-based survey of 366 university occupants using a partial proportional odds model with multiple imputation and inverse-frequency weighting. Interaction terms, specifically Age–Activity, Gender–Clothing, and Age–Clothing, were included to assess combined effects that reflect demographic disparities in adaptive capacity. The results show that clothing insulation, activity, age, gender, race/ethnicity, and space type significantly influence thermal responses. Notably, male occupants were more than three times as likely to report feeling too warm (odds ratio [OR] = 3.24), whereas older adults exhibited significantly lower odds of reporting feeling too warm (OR = 0.42). Substantial variation was observed across racial and ethnic groups (ORs ranging from 2.4 to 6.5). These findings highlight the limitations of traditional population-average comfort approaches and provide valuable scientific insights for demand-response-ready HVAC strategies that adjust temperature setpoints dynamically without sacrificing comfort. By offering accurate, real-time estimates across diverse thermal ranges, these occupant-centric models reduce HVAC energy use and associated emissions at the building scale while supporting ancillary services for flexible load shifting and smarter coordination within low-carbon electric grids. Ultimately, incorporating demographic and contextual diversity into building controls reduces unnecessary cooling waste while promoting thermal equity, establishing a human-centric foundation for sustainable built environments. Full article