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Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.
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ABSTRACT: Prior studies have demonstrated that certain populations including older patients, racial/ethnic minority groups, and women are underrepresented in clinical trials. We performed a retrospective analysis of patients with non-Hodgkin lymphoma (NHL) seen at MD Anderson Cancer Center (MDACC) to investigate the association between trial participation, race/ethnicity, travel distance, and neighborhood socioeconomic status (nSES). Using patient addresses, we ascertained nSES variables on educational attainment, income, poverty, racial composition, and housing at the census tract (CT) level. We also performed geospatial analysis to determine the geographic distribution of clinical trial participants and distance from patient residence to MDACC. We examined 3146 consecutive adult patients with NHL seen between January 2017 and December 2020. The study cohort was predominantly male and non-Hispanic White (NHW). The most common insurance types were private insurance and Medicare; only 1.1% of patients had Medicaid. There was a high overall participation rate of 30.5%, with 20.9% enrolled in therapeutic trials. In univariate analyses, lower participation rates were associated with lower nSES including higher poverty rates and living in crowded households. Racial composition of CT was not associated with differences in trial participation. In multivariable analysis, trial participation varied significantly by histology, and participation declined nonlinearly with age in the overall, follicular lymphoma, and diffuse large B-cell lymphoma (DLBCL) models. In the DLBCL subset, Hispanic patients had lower odds of participation than White patients (odds ratio, 0.36; 95% confidence interval, 0.21-0.62; P = .001). In our large academic cohort, race, sex, insurance type, and nSES were not associated with trial participation, whereas age and diagnosis were.
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Ensaios Clínicos como Assunto , Linfoma não Hodgkin , Fatores Socioeconômicos , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Linfoma não Hodgkin/terapia , Idoso , Adulto , Estudos Retrospectivos , Demografia , Classe Social , Características de Residência , Participação do Paciente , Características da VizinhançaRESUMO
BACKGROUND AND AIMS: Hepatic steatosis is known to be heritable, but its genetic basis is mostly uncharacterized. Steatosis is associated with metabolic and adiposity features; recent studies hypothesize that shared genetic effects between these traits could account for some of the unexplained heritability. This study aimed to quantify these genetic associations in a family-based sample of non-Hispanic white adults. METHODS AND RESULTS: 704 participants (18-95 years, 55.8% female) from the Fels Longitudinal Study with an MRI assessment of liver fat were included. Quantitative genetic analyses estimated the age- and sex-adjusted heritability of individual traits and the genetic correlations within trait pairs. Mean liver fat was 5.95% (SE = 0.23) and steatosis (liver fat >5.56%) was present in 29.8% of participants. Heritability (h2± SE) of steatosis was 0.72 ± 0.17 (p = 6.80e-6). All other traits including liver enzymes, fasting glucose, HOMA-IR, visceral and subcutaneous adipose tissue (VAT, SAT), body mass index, body fat percent, waist circumference, lipids and blood pressure were also heritable. Significant genetic correlations were found between liver fat and all traits except aspartate aminotransferase (AST), and among most trait pairs. Highest genetic correlations were between liver fat and HOMA-IR (0.85 ± 0.08, p = 1.73e-8), fasting glucose and ALT (0.89 ± 0.26, p = 6.68e-5), and HOMA-IR with: waist circumference (0.81 ± 0.12, p = 3.76e-6), body fat percent (0.78 ± 0.12 p = 2.42e-5) and VAT (0.73 ± 0.07, p = 6.37e-8). CONCLUSIONS: Common genes may exist between liver fat accumulation, metabolic features and adiposity phenotypes.
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Adiposidade , Predisposição Genética para Doença , Fenótipo , Humanos , Feminino , Masculino , Pessoa de Meia-Idade , Adulto , Adiposidade/genética , Idoso , Estudos Longitudinais , Adolescente , Adulto Jovem , Idoso de 80 Anos ou mais , Fígado/patologia , Fígado/metabolismo , Hereditariedade , Estados Unidos/epidemiologia , Hepatopatia Gordurosa não Alcoólica/genética , Fígado Gorduroso/genética , Imageamento por Ressonância Magnética , Medição de Risco , Estudos de Associação GenéticaRESUMO
Background: Tracking infectious diseases at the community level is challenging due to asymptomatic infections and the logistical complexities of mass surveillance. Wastewater surveillance has emerged as a valuable tool for monitoring infectious disease agents including SARS-CoV-2 and Mpox virus. However, detecting the Mpox virus in wastewater is particularly challenging due to its relatively low prevalence in the community. In this study, we aim to characterize three molecular assays for detecting and tracking the Mpox virus in wastewater from El Paso, Texas, during February and March 2023. Methods: In this study, a combined approach utilizing three real-time PCR assays targeting the C22L, F3L, and F8L genes and sequencing was employed to detect and track the Mpox virus in wastewater samples. The samples were collected from four sewersheds in the City of El Paso, Texas, during February and March 2023. Wastewater data was compared with reported clinical case data in the city. Findings: Mpox virus DNA was detected in wastewater from all the four sewersheds, whereas only one Mpox case was reported during the sampling period. Positive signals were still observed in multiple sewersheds after the Mpox case was identified. Higher viral concentrations were found in the pellet than in the supernatant of wastewater. Notably, an increasing trend in viral concentration was observed approximately 1-2 weeks before the reporting of the Mpox case. Further sequencing and epidemiological analysis provided supporting evidence for unreported Mpox infections in the city. Interpretation: Our analysis suggests that the Mpox cases in the community is underestimated. The findings emphasize the value of wastewater surveillance as a public health tool for monitoring infectious diseases even in low-prevalence areas, and the need for heightened vigilance to mitigate the spread of Mpox disease for safeguarding global health. Funding: Center of Infectious Diseases at UTHealth, the University of Texas System, and the Texas Epidemic Public Health Institute. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of these funding organizations.
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BACKGROUND: Cameron County, a low-income south Texas-Mexico border county marked by severe health disparities, was consistently among the top counties with the highest COVID-19 mortality in Texas at the onset of the pandemic. The disparity in COVID-19 burden within Texas counties revealed the need for effective interventions to address the specific needs of local health departments and their communities. Publicly available COVID-19 surveillance data were not sufficiently timely or granular to deliver such targeted interventions. An agency-academic collaboration in Cameron used novel geographic information science methods to produce granular COVID-19 surveillance data. These data were used to strategically target an educational outreach intervention named "Boots on the Ground" (BOG) in the City of Brownsville (COB). OBJECTIVE: This study aimed to evaluate the impact of a spatially targeted community intervention on daily COVID-19 test counts. METHODS: The agency-academic collaboration between the COB and UTHealth Houston led to the creation of weekly COVID-19 epidemiological reports at the census tract level. These reports guided the selection of census tracts to deliver targeted BOG between April 21 and June 8, 2020. Recordkeeping of the targeted BOG tracts and the intervention dates, along with COVID-19 daily testing counts per census tract, provided data for intervention evaluation. An interrupted time series design was used to evaluate the impact on COVID-19 test counts 2 weeks before and after targeted BOG. A piecewise Poisson regression analysis was used to quantify the slope (sustained) and intercept (immediate) change between pre- and post-BOG COVID-19 daily test count trends. Additional analysis of COB tracts that did not receive targeted BOG was conducted for comparison purposes. RESULTS: During the intervention period, 18 of the 48 COB census tracts received targeted BOG. Among these, a significant change in the slope between pre- and post-BOG daily test counts was observed in 5 tracts, 80% (n=4) of which had a positive slope change. A positive slope change implied a significant increase in daily COVID-19 test counts 2 weeks after targeted BOG compared to the testing trend observed 2 weeks before intervention. In an additional analysis of the 30 census tracts that did not receive targeted BOG, significant slope changes were observed in 10 tracts, of which positive slope changes were only observed in 20% (n=2). In summary, we found that BOG-targeted tracts had mostly positive daily COVID-19 test count slope changes, whereas untargeted tracts had mostly negative daily COVID-19 test count slope changes. CONCLUSIONS: Evaluation of spatially targeted community interventions is necessary to strengthen the evidence base of this important approach for local emergency preparedness. This report highlights how an academic-agency collaboration established and evaluated the impact of a real-time, targeted intervention delivering precision public health to a small community.
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COVID-19 , Relações Comunidade-Instituição , Saúde Pública , Humanos , Setor Censitário , COVID-19/epidemiologia , Teste para COVID-19RESUMO
Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health.
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Poliovirus , Viroma , Humanos , Viroma/genética , Águas Residuárias , Cidades , Surtos de Doenças , SARS-CoV-2/genéticaRESUMO
BACKGROUND: Regulating meal timing may have efficacy for improving metabolic health for preventing or managing chronic disease. However, the reliability of measuring meal timing with commonly used dietary assessment tools needs characterization prior to investigating meal timing and health outcomes in epidemiologic studies. OBJECTIVES: To evaluate the reliability of estimating meal timing parameters, including overnight fasting duration, the midpoint of overnight fasting time, the number of daily eating episodes, the period with the largest percentage of daily caloric intake, and late last eating episode (> 09:00 pm) from repeated 24-h dietary recalls (24HRs). METHODS: Intraclass correlation coefficients (ICC), Light's Kappa estimates, and 95% CIs were calculated from repeated 24HR administered in 3 epidemiologic studies: The United States-based Interactive Diet and Activity Tracking in AARP (IDATA) study (n = 996, 6 24HR collected over 12-mo), German EPIC-Potsdam Validation Study (European Prospective Investigation into Cancer and Nutrition Potsdam Germany cohort) (n = 134, 12 24HR collected over 12-mo) and EPIC-Potsdam BMBF-II Study (Federal Ministry of Education and Research, "Bundesministerium für Bildung und Forschung") (n = 725, 4 24HR collected over 36 mo). RESULTS: Measurement reliability of overnight fasting duration based on a single 24HR was "poor" in all studies [ICC range: 0.27; 95% CI: 0.23, 0.32 - 0.46; 95% CI: 0.43, 0.50]. Reliability was "moderate" with 3 24HR (ICC range: 0.53; 95% CI: 0.47, 0.58 in IDATA, 0.62; 95% CI: 0.52, 0.69 in the EPIC-Potsdam Validation Study, and 0.72; 95% CI: 0.70-0.75 in the EPIC-Potsdam BMBF-II Study). Results were similar for the midpoint of overnight fasting time and the number of eating episodes. Reliability of measuring late eating was "fair" in IDATA (Light's Kappa: 0.30; 95% CI: 0.21, 0.39) and "slight" in the EPIC-Potsdam Validation study and the EPIC-Potsdam BMBF-II study (Light's Kappa: 0.19; 95% CI: 0.15, 0.25 and 0.09; 95% CI: 0.06, 0.12, respectively). Reliability estimates differed by sex, BMI, weekday, and season of 24HR administration in some studies. CONCLUSIONS: Our results show that ≥ 3 24HR over a 1-3-y period are required for reliable estimates of meal timing variables.
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Dieta , Ingestão de Energia , Humanos , Estudos Prospectivos , Reprodutibilidade dos Testes , Ingestão de Energia/fisiologia , RefeiçõesRESUMO
Importance: In 2019, the Advisory Committee on Immunization Practices (ACIP) recommended patient-clinician shared decision-making for human papillomavirus (HPV) vaccination in adults aged 27 to 45 years. Less is known about the HPV vaccine administration trends in this age group before and after this recommendation update. Objective: To examine the association between the ACIP recommendation update and the HPV vaccine administration among US adults aged 27 to 45 years. Design, Setting, and Participants: This large commercial claim-based retrospective cohort study used the Optum Clinformatics database for validated claims from January 1, 2007, through December 31, 2020. A total of 22â¯600â¯520 US adults aged 27 to 45 years without previous HPV vaccination claims during the study and enrollment period were included. Main Outcomes and Measures: The first-appearing HPV vaccination claim per individual was defined as a new HPV vaccine administration. Interrupted time-series analyses were conducted to assess the association between the ACIP update and the quarterly vaccine administration rate change. The annual rate trends across race and ethnicity groups and the proportions of vaccination cases by sub-age groups and valent types were also estimated. Vaccine administration trends were assessed by race and ethnicity in this age group because HPV vaccination trends were found to differ by race and ethnicity in the initially eligible population. Results: Among 22â¯600â¯520 final study participants, the majority were men (50.9%) and non-Hispanic White (53.4%), and the mean (SD) age when first observed was 34.6 (5.8) years. In women, the ACIP update was associated with an immediate increase in vaccine administration rate (coefficient ß2, 40.18 per 100â¯000 persons; P = .01) and an increased slope (coefficient ß3, 9.62 per 100â¯000 persons per quarter; P = .03) over time postupdate. The ACIP update was only associated with an immediate increase in vaccine administration in men (coefficient ß2, 27.54; P < .001). The annual rate trends were similar across race and ethnicity groups. Age at vaccine administration shifted over time (eg, women aged 40-45 years comprised only 4.9% of vaccinations in 2017, then 19.0% in 2019, and 22.7% in 2020). The most administered HPV vaccines in 2020 were 9 valent (women, 97.0%; men, 97.7%). Conclusions and Relevance: In this population-based cohort study, there were statistically significant increases in HPV vaccine administration in adults aged 27 to 45 years after the ACIP recommendation update. Patient-clinician shared decision-making may have been the main associated factor for this increase. Further research is warranted to explore the decision-making process in receiving HPV vaccination and to develop effective decision aids to maximize the cancer prevention benefit in this age group.
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Infecções por Papillomavirus , Vacinas contra Papillomavirus , Masculino , Adulto , Feminino , Humanos , Vacinas contra Papillomavirus/uso terapêutico , Infecções por Papillomavirus/epidemiologia , Papillomavirus Humano , Comitês Consultivos , Estudos de Coortes , Estudos Retrospectivos , VacinaçãoRESUMO
Syndemics framework describes two or more co-occurring epidemics that synergistically interact with each other and the complex structural social forces that sustain them leading to excess disease burden. The term syndemic was first used to describe the interaction between substance abuse, violence, and AIDS by Merrill Singer. A broader range of syndemic studies has since emerged describing the framework's applicability to other public health scenarios. With syndemic theory garnering significant attention, the focus is shifting towards developing robust empirical analytical approaches. Unfortunately, the complex nature of the disease-disease interactions nested within several social contexts complicates empirical analyses. In answering the call to analyze syndemics at the population level, we propose the use of spatial epidemiology as an empirical framework for syndemics research. Spatial epidemiology, which typically relies on geographic information systems (GIS) and statistics, is a discipline that studies spatial variations to understand the geographic landscape and the risk environment within which disease epidemics occur. GIS maps provide visualization aids to investigate the spatial distribution of disease outcomes, the associated social factors, and environmental exposures. Analytical inference, such as estimation of disease risks and identification of spatial disease clusters, can provide a detailed statistical view of spatial distributions of diseases. Spatial and spatiotemporal models can help us to understand, measure, and analyze disease syndemics as well as the social, biological, and structural factors associated with them in space and time. In this paper, we present a background on syndemics and spatial epidemiological theory and practice. We then present a case study focused on the HIV and HCV syndemic in West Virginia to provide an example of the use of GIS and spatial analytical methods. The concepts described in this paper can be considered to enhance understanding and analysis of other syndemics for which space-time data are available.