Search NASA⌕ Search

SEARCH · Search NASA

Results for “DISEASE INCIDENCE”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Population-level incidence of human papillomavirus–positive oropharyngeal, cervical, and anal cancers, by smoking status

Abstract We estimated the population-level incidence of human papillomavirus (HPV)–positive oropharyngeal, cervical, and anal cancers by smoking status. We combined HPV DNA genotyping data from the Centers for Disease Control and Prevention’s Cancer Registry Sentinel Surveillance System with data from the Kentucky Cancer Registry and Behavioral Risk Factor Surveillance System across smoking status. During 2004-2005 and 2014-2015 in Kentucky, most cases of oropharyngeal (63.3%), anal (59.7%), and cervical (54.9%) cancer were among individuals who ever smoked. The population-level incidence rate was higher among individuals who ever smoked than among those who never smoked for HPV-positive oropharyngeal (7.8 vs 2.1; adjusted incidence rate ratio = 2.6), cervical (13.7 vs 6.8; adjusted incidence rate ratio = 2.0), and anal (3.9 vs 1.6; adjusted incidence rate ratio = 2.5) cancers. These findings indicate that smoking is associated with increased risk of HPV-positive oropharyngeal, cervical, and anal cancers, and the population-level burden of these cancers is higher among individuals who ever smoked.

Oncology↗
DOE OSTI2024

Generalizability of heat-related health risk associations observed in a large healthcare claims database of patients with commercial health insurance

Extreme ambient heat is unambiguously associated with higher risk of illness and death. The Optum Labs Data Warehouse (OLDW), a database of medical claims from US-based patients with commercial or Medicare Advantage health insurance, has been used to quantify heat-related health impacts. Whether results for the insured sub-population are generalizable to the broader population has to our knowledge not been documented. We sought to address this question, for the US population in California from 2012 to 2019. We examined changes in daily rates of emergency department (ED) encounters and in-patient hospitalization encounters for all-causes, heat-related outcomes, renal disease, mental/behavioral disorders, cardiovascular disease, and respiratory disease. OLDW was the source for health data for insured individuals in California, and health data for the broader population were gathered from the California Department of Health Care Access and Information (HCAI). We defined extreme heat exposure as any day in a group of 2 or more days with maximum temperatures exceeding the county-specific 97.5 th percentile and used a space-time-stratified case–crossover design to assess and compare the impacts of heat on health. Average incidence rates of medical encounters differed by dataset. However, rate ratios for ED encounters were similar across datasets for all causes (ratio of incidence rate ratios (rIRR) = 0.989; 95% confidence interval (CI) = 0.973, 1.011), heat-related causes (rIRR = 1.080; 95% CI = 0.999, 1.168), renal disease (rIRR = 0.963; 95% CI = 0.718, 1.292), and mental health disorders (rIRR = 1.098; 95% CI = 1.004, 1.201). Rate ratios for inpatient encounters were also similar. This work presents evidence that OLDW can continue to be a resource for estimating the health impacts of extreme heat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Pharmacologic or genetic interference with atrogene signaling protects against glucocorticoid-induced musculoskeletal and cardiac disease

Despite their beneficial actions as immunosuppressants, glucocorticoids (GC) have devastating effects on the musculoskeletal and cardiac systems, as long-term treated patients exhibit high incidence of falls, bone fractures, and cardiovascular events. Herein, we show that GC upregulate simultaneously in bone, skeletal muscle, and the heart the expression of E3 ubiquitin ligases (atrogenes), known to stimulate the proteasomal degradation of proteins. Activation of vitamin D receptor (VDR) signaling with the VDR ligands calcitriol or eldecalcitol prevented GC-induced atrogene upregulation in vivo and ex vivo in bone/muscle organ cultures and preserved tissue structure/mass and function of the 3 tissues in vivo. Direct pharmacologic inhibition of the proteasome with carfilzomib also conferred musculoskeletal protection. Genetic loss of the atrogene MuRF1-mediated protein ubiquitination in ΔRING mice afforded temporary or sustained protection from GC excess in bone or skeletal and heart muscle. We concluded that the atrogene pathway downstream of MuRF1 underlies GC action in bone, muscle, and the heart, and it can be pharmacologically or genetically targeted to confer protection against the damaging actions of GC simultaneously in the 3 tissues.

Research & Experimental Medicine↗
DOE OSTI2024

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM 2.5 , and other exposures with regression and machine learning models

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM 2.5 , may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM 2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM 2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM 2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure’s association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Combination therapy with lenvatinib and radiation significantly inhibits thyroid cancer growth by uptake of tyrosine kinase inhibitor

Highlights: • Lenvatinib combined with radiation significantly inhibits thyroid cancer growth. • Combined therapy induced apoptosis and G2/M phase cell cycle arrest. • Irradiation increased cellular uptake of lenvatinib into cancer cells. • Combined therapy suggests a new therapeutic strategy for advanced thyroid cancer. Although surgical treatment cures >90% of differentiated thyroid cancer (DTC) patients, the remaining patients, including advanced DTC cases, have poor clinical outcomes. These patients with inoperable disease have only two choices of radioactive iodine therapy and tyrosine kinase inhibitors such as lenvatinib, which have a high incidence of treatment-related adverse events and can only prolong progression free survival by approximately 5–15 months. In this study, we investigated the antitumor effects of combination therapy with lenvatinib and radiation (CTLR) for DTC. CTLR synergistically inhibited cell replication and colony formation in vitro and tumor growth in nude mice without apparent toxicities and suppressed the expression of proliferation marker (Ki-67). CTLR also induced apoptosis and G2/M phase cell cycle arrest. Moreover, quantitative analysis of the intracellular uptake of lenvatinib using liquid chromatography and mass spectrometry demonstrated that intracellular uptake of lenvatinib was significantly increased 48 h following irradiation. These data suggest that increased membrane permeability caused by irradiation increases the intracellular concentration of levatinib, contributing to the synergistic effect. This mechanism-based potential of combination therapy suggests a powerful new therapeutic strategy for advanced thyroid cancer with fewer side effects and might be a milestone for developing a regimen in clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

The Cross-sectional and Longitudinal Association Between Thyroid Function and Depression: A Population-Based Study

Abstract Context An association of thyroid function with mood disorders has been widely suggested, but very few studies have examined this association longitudinally. Objective We assessed the cross-sectional and longitudinal association between thyroid function and depression in a population-based cohort. Methods A total of 9471 individuals were included in cross-sectional analyses, of whom 8366 had longitudinal data. At baseline, we assessed thyroid function using serum samples (thyrotropin [TSH], free thyroxine (FT4), and thyroid peroxidase antibodies) and depressive symptoms using the Centre for Epidemiologic Studies Depression (CES-D) scale. Incident depressive events (n = 1366) were continuously followed up with the CES-D and clinical interviews. We analyzed the cross-sectional association of thyroid function and thyroid disease with depressive symptoms using linear and logistic regression, and the longitudinal association with Cox proportional hazard models for depressive events. Results Lower TSH levels and lower and higher FT4 levels were cross-sectionally associated with more depressive symptoms with a B value of −0.07 per 1 unit increase of natural log-transformed TSH (95% CI −0.11; −0.04). Furthermore, hypothyroidism was cross-sectionally associated with less depressive symptoms and hyperthyroidism with more depressive symptoms. Longitudinally, there was a U-shaped association between FT4 and incident depressive events but only in euthyroid participants. Conclusion We show a cross-sectional association between thyroid (dys)function with depressive symptoms, and a U-shaped association between FT4 and incident depressive events in euthyroid individuals. Our findings suggest an association of thyroid function with the risk of developing depression, albeit small. Reverse causation and additional underlying factors may also contribute to the association.

Roa Dueñas, Oscar Hernando (ORCID:0000000207522261↗
DOE OSTI2020

Google Health Trends performance reflecting dengue incidence for the Brazilian states

Abstract Background Dengue fever is a mosquito-borne infection transmitted by Aedes aegypti and mainly found in tropical and subtropical regions worldwide. Since its re-introduction in 1986, Brazil has become a hotspot for dengue and has experienced yearly epidemics. As a notifiable infectious disease, Brazil uses a passive epidemiological surveillance system to collect and report cases; however, dengue burden is underestimated. Thus, Internet data streams may complement surveillance activities by providing real-time information in the face of reporting lags. Methods We analyzed 19 terms related to dengue using Google Health Trends (GHT), a free-Internet data-source, and compared it with weekly dengue incidence between 2011 to 2016. We correlated GHT data with dengue incidence at the national and state-level for Brazil while using the adjusted R squared statistic as primary outcome measure (0/1). We used survey data on Internet access and variables from the official census of 2010 to identify where GHT could be useful in tracking dengue dynamics. Finally, we used a standardized volatility index on dengue incidence and developed models with different variables with the same objective. Results From the 19 terms explored with GHT, only seven were able to consistently track dengue. From the 27 states, only 12 reported an adjusted R squared higher than 0.8; these states were distributed mainly in the Northeast, Southeast, and South of Brazil. The usefulness of GHT was explained by the logarithm of the number of Internet users in the last 3 months, the total population per state, and the standardized volatility index. Conclusions The potential contribution of GHT in complementing traditional established surveillance strategies should be analyzed in the context of geographical resolutions smaller than countries. For Brazil, GHT implementation should be analyzed in a case-by-case basis. State variables including total population, Internet usage in the last 3 months, and the standardized volatility index could serve as indicators determining when GHT could complement dengue state level surveillance in other countries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Million Person Study Innovation: Evaluating Cognitive Impairment and other Morbidity Outcomes from Chronic Radiation Exposure Through Linkages with the Centers for Medicaid and Medicare Services Assessment and Claims Data

Here, the study of One Million U.S. Radiation Workers and Veterans, the Million Person Study (MPS), examines the health consequences, both cancer and non-cancer, of exposure to ionizing radiation received gradually over time. Recently the MPS has focused on mortality patterns from neurological and behavioral conditions, e.g., Parkinson's disease, Alzheimer's disease, dementia, and motor neuron disease such as amyotrophic lateral sclerosis. A fuller picture of radiation-related late effects comes from studying both mortality and the occurrence (incidence) of conditions not leading to death. Accordingly, the MPS is identifying neurocognitive diagnoses from fee-for-service insurance claims from the Centers for Medicare and Medicaid Services (CMS), among Medicare beneficiaries beginning in 1999 (the earliest date claims data are available). Linkages to date have identified ∼540,000 workers with available health information. Such linkages provide individual information on important co-factor and confounding variables such as smoking, alcohol consumption, blood pressure, obesity, diabetes and many other health and demographic characteristics. The total person-level set of time-dependent variables, outcomes, organ-specific dose measures, co-factors, and demographics will be massive and much too large to be evaluated with standard software. Thus, development of specialized open-source software designed for large datasets (Colossus) is nearly complete. The wealth of information available from CMS claims data, coupled with individual dose reconstructions, will thus greatly enhance the quality and precision of health evaluations for this new field of low-dose radiation and neurocognitive effects.

Dauer, Lawrence T.↗
DOE OSTI2022

A MUC 5 B Gene Polymorphism, rs35705950-T, Confers Protective Effects Against COVID-19 Hospitalization but Not Severe Disease or Mortality

A common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis (IPF), but its role in severe acute respiratory syndrome coronavirus 2 infection and disease severity is unclear. To assess whether rs35705950-T confers differential risk for clinical outcomes associated with coronavirus disease (COVID-19) infection among participants in the Million Veteran Program (MVP). The MUC5B rs35705950-T allele was directly genotyped among MVP participants; clinical events and comorbidities were extracted from the electronic health records. Associations between the incidence or severity of COVID-19 and rs35705950-T were analyzed within each ancestry group in the MVP followed by transancestry meta-analysis. Replication and joint meta-analysis were conducted using summary statistics from the COVID-19 Host Genetics Initiative (HGI). Sensitivity analyses with adjustment for additional covariates (body mass index, Charlson comorbidity index, smoking, asbestosis, rheumatoid arthritis with interstitial lung disease, and IPF) and associations with post–COVID-19 pneumonia were performed in MVP subjects. The MUC5B variant rs35705950-T may confer protection in COVID-19 hospitalizations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Surface structure studies in 2D and 3D Nb resonators using GI-XRD

Superconductor radio frequency (SRF) Nb-resonators are a key element in the development of new generations of particle accelerators as well as in the fabrication of 3D circuit QED architecture for quantum computing. Nevertheless, Niobium is extremally reactive to light elements such as C, N, O and H, and therefore to the impurities ordering under special conditions, e.g., cryogenic temperatures. Since these resonators are put through a series of metallurgical and chemical processes, the number of impurities in the solid increases in tens of ppm. Upon operational conditions ~1.6 K, Nb become vulnerable to H atoms ordering, which leads to the nucleation of secondary phases such as Nb-hydrides. Thereupon to the energy dissipation and eventually to the superconductivity breakdown known as Q-disease and potentially High-Field Q-slope. In this contribution, we present a detailed structural analysis by high-energy grazing-incidence X-ray diffraction of specimens extracted from 3D Nb resonators to shed light on the kinetic formation of the resulting secondary phases and their crystal phase identification upon cooling and heating cycles. To our knowledge, this is the first study carried out in resonators samples using a light source, shallow angles and temperatures near ~4 K. Consequently, this work opens new routes to understand the chemical and phase composition, crystal and electronic structure of the Nb surface at temperatures near the operating conditions as a strategy to improve the physical and functional properties of Nb superconducting resonators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Hypernetwork Science: From Multidimensional Networks to Computational Topology

As data structures and mathematical objects used for complex systems modeling, hypergraphs sit nicely poised between on the one hand the world of network models, and on the other that of higher-order mathematical abstractions from algebra, lattice theory, and topology. They are able to represent complex systems interactions more faithfully than graphs and networks, while also being some of the simplest classes of systems representing topological structures as collections of multidimensional objects connected in a particular pattern. In this paper we discuss the role of (undirected) hypergraphs in the science of complex networks, and provide a mathematical overview of the core concepts needed for hypernetwork modeling, including duality and the relationship to bicolored graphs, quantitative adjacency and incidence, the nature of walks in hypergraphs, and available topological relationships and properties. We close with a brief discussion of two example applications: biomedical databases for disease analysis, and domain-name system (DNS) analysis of cyber data.

Joslyn, Cliff A.↗
DOE OSTI2022

Six-Month Outcomes of Infants Born to People With SARS-CoV-2 in Pregnancy

OBJECTIVES To assess the 6-month incidence of laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, postnatal care, hospitalization, and mortality among infants born to people with laboratory-confirmed SARS-CoV-2 infection during pregnancy by timing of maternal infection. METHODS Using a cohort of liveborn infants from pregnancies with SARS-CoV-2 infections in the year 2020 from 10 United States jurisdictions in the Surveillance for Emerging Threats to Mother and Babies Network, we describe weighted estimates of infant outcomes from birth through 6 months of age from electronic health and laboratory records. RESULTS Of 6601 exposed infants with laboratory information through 6 months of age, 1.0% (95% confidence interval: 0.8–1.1) tested positive, 19.1% (17.5–20.6) tested negative, and 80.0% (78.4–81.6) were not known to be tested for SARS-CoV-2. Among those ≤14 days of age, SARS-CoV-2 infection occurred only with maternal infection ≤14 days before delivery. Of 3967 infants with medical record abstraction, breastmilk feeding initiation was lower when maternal infection occurred ≤14 days before delivery compared with >14 days (77.6% [72.5–82.6] versus 88.3% [84.7–92.0]). Six-month all-cause hospitalization was 4.1% (2.0–6.2). All-cause mortality was higher among infants born to people with infection ≤14 days (1.0% [0.4–1.6]) than >14 days (0.3% [0.1–0.5]) before delivery. CONCLUSIONS Results are reassuring, with low incidences of most health outcomes examined. Incidence of infant SARS-CoV-2, breastmilk feeding initiation, and all-cause mortality differed by timing of maternal infection. Strategies to prevent infections and support pregnant people with coronavirus disease 2019 may improve infant outcomes.

Pediatrics↗
DOE OSTI2022

Lipoprotein(a) is associated with the onset but not the progression of aortic valve calcification

Abstract Aim Lipoprotein(a) [Lp(a)] is a potential causal factor in the pathogenesis of aortic valve disease. However, the relationship of Lp(a) with new onset and progression of aortic valve calcium (AVC) has not been studied. The purpose of the study was to assess whether high serum levels of Lp(a) are associated with AVC incidence and progression. Methods and results A total of 922 individuals from the population-based Rotterdam Study (mean age 66.0±4.2 years, 47.7% men), whose Lp(a) measurements were available, underwent non-enhanced cardiac computed tomography imaging at baseline and after a median follow-up of 14.0 [interquartile range (IQR) 13.9–14.2] years. New-onset AVC was defined as an AVC score >0 on the follow-up scan in the absence of AVC on the first scan. Progression was defined as the absolute difference in AVC score between the baseline and follow-up scan. Logistic and linear regression analyses were performed to evaluate the relationship of Lp(a) with baseline, new onset, and progression of AVC. All analyses were corrected for age, sex, body mass index, smoking, hypertension, dyslipidaemia, and creatinine. AVC progression was analysed conditional on baseline AVC score expressed as restricted cubic splines. Of the 702 individuals without AVC at baseline, 415 (59.1%) developed new-onset AVC on the follow-up scan. In those with baseline AVC, median annual progression was 13.5 (IQR = 5.2–37.8) Agatston units (AU). Lipoprotein(a) concentration was independently associated with baseline AVC [odds ratio (OR) 1.43 for each 50 mg/dL higher Lp(a); 95% confidence interval (CI) 1.15–1.79] and new-onset AVC (OR 1.30 for each 50 mg/dL higher Lp(a); 95% CI 1.02–1.65), but not with AVC progression (β: −71 AU for each 50 mg/dL higher Lp(a); 95% CI −117; 35). Only baseline AVC score was significantly associated with AVC progression (P < 0.001). Conclusion In the population-based Rotterdam Study, Lp(a) is robustly associated with baseline and new-onset AVC but not with AVC progression, suggesting that Lp(a)-lowering interventions may be most effective in pre-calcific stages of aortic valve disease.

Kaiser, Yannick (ORCID:0000000168690042)↗
DOE OSTI2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Background: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance. Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. Funding: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 ( https://www.nfdi4health.de/task-force-covid-19-2 ) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

The Epidemiology of Coccidioidomycosis (Valley fever) and the Disease Ecology of Coccidioides spp. in New Mexico (2006–2023)

Coccidioidomycosis (Valley fever), caused by Coccidioides spp., is a fungal infection endemic to semi-arid regions of the Americas. Despite 80 years of disease recognition in New Mexico, there is limited disease awareness. We incorporated clinical, epidemiological, and ecological datasets to summarize the knowledge of Valley fever in New Mexico. We analyzed 1541 human cases from 2006 to 2023. On average, 86 cases were reported each year (4.1 cases per 100,000 population per year). The highest levels of incidence were in southwestern New Mexico. American Indian or Alaska Natives in New Mexico had a 1.9 times higher incidence rate of coccidioidomycosis than White people, and among age groups, older populations in New Mexico had the highest incidence rates. We analyzed 300 soil samples near Las Cruces, New Mexico, for the presence of Coccidioides and reported the first known positive soil samples collected from the state, the majority of which were from grassland-dominated sites and from animal burrows. Sequence analyses in clinical specimens, wild animals, and soil samples confirmed that Coccidioides posadasii is the main causative species of coccidioidomycosis in New Mexico. Environmental surveillance validated that locally acquired infections could occur in, but are not limited to, Catron, Doña Ana, Sierra, and Socorro Counties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Aeromonas in South Asia: genomic insights into an environmental pathogen and reservoir of antimicrobial resistance

Aeromonads are an ecologically versatile group of bacteria that cause infections in aquatic animals and are recognised as emerging human pathogens. Despite this, our understanding of Aeromonas diversity, especially the relationship between clinical and environmental strains, remains limited. Here, we present a genomic analysis of the Aeromonas genus, comprising 1853 genomes, and a detailed comparison of clinical and environmental strains from South Asia, including 996 newly sequenced genomes from Bangladesh and India. Phylogenetic analyses revealed that Aeromonas is a highly diverse genus, with no distinct clade separating clinical and environmental isolates. We identified 28 Aeromonas species and 905 novel sequence types, comprising 72.5% of the genomes. Notably, we show a high incidence of antimicrobial resistance (AMR) genes across all isolates, including against front and last-line antibiotics. Finally, we highlight frequent misidentification of Aeromonas as Vibrio cholerae, which is relevant to cholera-endemic regions where both genera co-exist and are associated with diarrhoeal disease. Our study underscores Aeromonas as an important environmental AMR reservoir and emerging multi-species pathogen capable of spilling over into human populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effect of radiation exposure on survival after first solid cancer diagnosis in A-bomb survivors

Comparison of the estimated effect of atomic bomb radiation exposure on solid cancer incidence and solid cancer mortality in the RERF Life Span Study (LSS) reveals a difference in the magnitude and shape of the excess relative risk dose response. A possible contributing factor to this difference is pre-diagnosis radiation effect on post-diagnosis survival. Pre-diagnosis radiation exposure theoretically could influence post-diagnosis survival by affecting the genetic makeup and possibly aggressiveness of cancer, or by compromising tolerance for aggressive treatment for cancer. We analyze the radiation effect on post-diagnosis survival in 20,463 LSS subjects diagnosed with first-primary solid cancer between 1958 and 2009 with particular attention to whether death was caused by the first-primary cancer, other cancer, or non-cancer diseases. From multivariable Cox regression analysis of cause-specific survival, the excess hazard at 1 Gy (EH 1Gy ) for death from the first primary cancer was not significantly different from zero – p = 0.23, EH 1Gy = 0.038 (95 % CI: –0.023, 0.104). Death from other cancer and death from non-cancer diseases both were significantly associated with radiation dose: other cancer EH 1Gy = 0.38 (95 % CI: 0.24, 0.53); non-cancer EH 1Gy = 0.24 (95 % CI: 0.13, 0.36), both p < 0.001. There is no detectable large effect of pre-diagnosis radiation exposure on post-diagnosis death from the first primary cancer in A-bomb survivors. A direct effect of pre-diagnosis radiation exposure on cancer prognosis is ruled out as an explanation for the difference in incidence and mortality dose response in A-bomb survivors.

60 APPLIED LIFE SCIENCES↗