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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Differential Accumulation of Misfolded Prion Strains in Natural Hosts of Prion Diseases

Prion diseases, also known as transmissible spongiform encephalopathies (TSEs), are a group of neurodegenerative protein misfolding diseases that invariably cause death. TSEs occur when the endogenous cellular prion protein (PrP C ) misfolds to form the pathological prion protein (PrP Sc ), which templates further conversion of PrP C to PrP Sc , accumulates, and initiates a cascade of pathologic processes in cells and tissues. Different strains of prion disease within a species are thought to arise from the differential misfolding of the prion protein and have different clinical phenotypes. Different strains of prion disease may also result in differential accumulation of PrP Sc in brain regions and tissues of natural hosts. Here, we review differential accumulation that occurs in the retinal ganglion cells, cerebellar cortex and white matter, and plexuses of the enteric nervous system in cattle with bovine spongiform encephalopathy, sheep and goats with scrapie, cervids with chronic wasting disease, and humans with prion diseases. By characterizing TSEs in their natural host, we can better understand the pathogenesis of different prion strains. This information is valuable in the pursuit of evaluating and discovering potential biomarkers and therapeutics for prion diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Air pollution and emergency department visits for respiratory diseases: A multi-city case crossover study

Highlights: • Extensive research exists on the effects of ambient air pollution on respiratory diseases. • Emergency department visits for respiratory diseases increase after days with higher concentrations of air pollution. • Ambient pollution, even at low concentrations, appear to adversely affect the respiratory system. Increasing evidence suggests that ambient air pollution is a major risk factor for both acute and chronic respiratory disease exacerbations and emergencies. The objective of this study was to determine the association between ambient air pollutants and emergency department (ED) visits for respiratory conditions in nine districts across the province of Ontario in Canada. Health, air pollutant (PM{sub 2.5}, NO{sub 2}, O{sub 3}, and SO{sub 2}), and meteorological data were retrieved from April 2004 to December 2011. Respiratory diseases were categorized as: chronic obstructive pulmonary disease (COPD, including bronchiectasis) and acute upper respiratory diseases. A case-crossover design was used to test the associations between ED visits and ambient air pollutants, stratified by sex and season. For COPD among males, positive results were observed for NO{sub 2} with lags of 3–6 days, for PM{sub 2.5} with lags 1–8, and for SO{sub 2} with lags of 4–8 days. For COPD among females, positive results were observed for O{sub 3} with lags 2–4 days, and for SO{sub 2} among lags of 3–6 days. For upper respiratory disease emergencies among males, positive results were observed for NO{sub 2} (lags 5–8 days), for O{sub 3}, (lags 0–6 days), PM{sub 2.5} (all lags), and SO{sub 2} (lag 8), and among females, positive results were observed for NO{sub 2} for lag 8 days, for O{sub 3}, PM{sub 2.5} among all lags. Our study provides evidence of the associations between short-term exposure to air pollution and increased risk of ED visits for upper and lower respiratory diseases in an environment where air pollutant concentrations are relatively low.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Use of Multi-Site Radiation Therapy for Systemic Disease Control

Metastatic cancer is a heterogeneous entity, some of which could benefit from local consolidative radiation therapy (RT). Although randomized evidence is growing in support of using RT for oligometastatic disease, a highly active area of investigation relates to whether RT could benefit patients with polymetastatic disease. This article highlights the preclinical and clinical rationale for using RT for polymetastatic disease, proposes an exploratory framework for selecting patients best suited for these types of treatments, and briefly reviews potential challenges. The goal of this hypothesis-generating review is to address personalized multimodality systemic treatment for patients with metastatic cancer. The rationale for using high-dose RT is primarily for local control and immune activation in either oligometastatic or polymetastatic disease. However, the primary application of low-dose RT is to activate distinct antitumor immune pathways and modulate the tumor stroma in efforts to better facilitate T cell infiltration. We explore clinical cases involving high- and low-dose RT to demonstrate the potential efficacy of such treatment. We then group patients by extent of disease burden to implement high- and/or low-dose RT. Patients with low-volume disease may receive high-dose RT to all sites as part of an oligometastatic paradigm. Subjects with high-volume disease (for whom standard of care remains palliative RT only) could be treated with a combination of high-dose RT to a few sites for immune activation, while receiving low-dose RT to several remaining lesions to enhance systemic responses from high-dose RT and immunotherapy. We further discuss how emerging but speculative concepts such as immune function may be integrated into this approach and examine therapies currently under investigation that may help address immune deficiencies. The review concludes by addressing challenges in using RT for polymetastatic disease, such as concerns about treatment planning workflows, treatment times, dose constraints for multiple-isocenter treatments, and economic considerations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

An infrared spectral biomarker accurately predicts neurodegenerative disease class in the absence of overt symptoms

Although some neurodegenerative diseases can be identified by behavioral characteristics relatively late in disease progression, we currently lack methods to predict who has developed disease before the onset of symptoms, when onset will occur, or the outcome of therapeutics. New biomarkers are needed. Here we describe spectral phenotyping, a new kind of biomarker that makes disease predictions based on chemical rather than biological endpoints in cells. Spectral phenotyping uses Fourier Transform Infrared (FTIR) spectromicroscopy to produce an absorbance signature as a rapid physiological indicator of disease state. FTIR spectromicroscopy has over the past been used in differential diagnoses of manifest disease. Here, we report that the unique FTIR chemical signature accurately predicts disease class in mouse with high probability in the absence of brain pathology. In human cells, the FTIR biomarker accurately predicts neurodegenerative disease class using fibroblasts as surrogate cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effect of land use and soil organic matter quality on the structure and function of microbial communities in pastoral soils: Implications for disease suppression

Cropping soils vary in extent of natural suppression of soil-borne plant diseases. However, it is unknown whether similar variation occurs across pastoral agricultural systems. We examined soil microbial community properties known to be associated with disease suppression across 50 pastoral fields varying in management intensity. The composition and abundance of the disease-suppressive community were assessed from both taxonomic and functional perspectives. Pseudomonas bacteria were selected as a general taxonomic indicator of disease suppressive potential, while genes associated with the biosynthesis of a suite of secondary metabolites provided functional markers (GeoChip 5.0 microarray analysis). The composition of both the Pseudomonas communities and disease suppressive functional genes were responsive to land use. Underlying soil properties explained 37% of the variation in Pseudomonas community structure and up to 61% of the variation in the abundance of disease suppressive functional genes. Notably, measures of soil organic matter quality, C:P ratio, and aromaticity of the dissolved organic matter content (carbon recalcitrance), influenced both the taxonomic and functional disease suppressive potential of the pasture soils. Our results suggest that key components of the soil microbial community may be managed on-farm to enhance disease suppression and plant productivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predicting Future Disease Burden in a Rapidly Changing Climate

The interplay of a rapidly changing climate and infectious disease occurrence is emerging as a critical topic, requiring investigation of possible direct, as well as indirect, connections between disease processes and climate-related variation and phenomena. First, we introduce and overview three infectious disease exemplars (dengue, influenza, valley fever) representing different transmission classes (insect-vectored, human-to-human, environmentally-transmitted) to illuminate the complex and significant interplay between climate disease processes, as well as to motivate discussion of how Sandia can transform the field, and change our understanding of climate-driven infectious disease spread. We also review state-of-the-art epidemiological and climate modeling approaches, together with data analytics and machine learning methods, potentially relevant to climate and infectious disease studies. We synthesize the modeling and disease exemplars information, suggesting initial avenues for research and development (R&D) in this area, and propose potential sponsors for this work. Whether directly or indirectly, it is certain that a rapidly changing climate will alter global disease burden. The trajectory of climate change is an important control on this burden, from local, to regional and global scales. The efforts proposed herein respond to the National Research Councils call for the creation of a multidisciplinary institute that would address critical aspects of these interlocking, cascading crises.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Health Care Usage During the COVID-19 Pandemic and the Adoption of Telemedicine: Retrospective Study of Chronic Disease Cohorts

Background: The COVID-19 pandemic accelerated telehealth adoption across disease cohorts of patients. For many patients, routine medical care was no longer an option, and others chose not to visit medical offices in order to minimize COVID-19 exposure. In this study, we take a comprehensive multidisease approach in studying the impact of the COVID-19 pandemic on health care usage and the adoption of telemedicine through the first 12 months of the COVID-19 pandemic. Objective: We studied the impact of the COVID-19 pandemic on in-person health care usage and telehealth adoption across chronic diseases to understand differences in telehealth adoption across disease cohorts and patient demographics (such as the Social Vulnerability Index [SVI]). Methods: We conducted a retrospective cohort study of 6 different disease cohorts (anxiety: n=67,578; depression: n=45,570; diabetes: n=81,885; kidney failure: n=29,284; heart failure: n=21,152; and cancer: n=35,460). We used summary statistics to characterize changes in usage and regression analysis to study how patient characteristics relate to in-person health care and telehealth adoption and usage during the first 12 months of the pandemic. Results: We observed a reduction in in-person health care usage across disease cohorts (ranging from 10% to 24%). For most diseases we study, telehealth appointments offset the reduction in in-person visits. Furthermore, for anxiety and depression, the increase in telehealth usage exceeds the reduction in in-person visits (by up to 5%). We observed that younger patients and men have higher telehealth usage after accounting for other covariates. Patients from higher SVI areas are less likely to use telehealth; however, if they do, they have a higher number of telehealth visits, after accounting for other covariates. Conclusions: The COVID-19 pandemic affected health care usage across diseases, and the role of telehealth in replacing in-person visits varies by disease cohort. Understanding these differences can inform current practices and provides opportunities to further guide modalities of in-person and telehealth visits. Critically, further study is needed to understand barriers to telehealth service usage for patients in higher SVI areas. A better understanding of the role of social determinants of health may lead to more support for patients and help individual health care providers improve access to care for patients with chronic conditions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Spatial temporal cluster analysis to enhance awareness of disease re-emergence on a global scale

ObjectiveThe application of spatial analysis to improve the awareness and use of surveillance data.IntroductionThe re-emergence of an infectious disease is dependent on social, political, behavioral, and disease-specific factors. Global disease surveillance is a requisite of early detection that facilitates coordinated interventions to these events. Novel informatics tools developed from publicly available data are constantly evolving with the incorporation of new data streams. Re-emerging Infectious Disease (RED) Alert is an open-source tool designed to help analysts develop a contextual framework when planning for future events, given what has occurred in the past. Geospatial methods assist researchers in making informed decisions by incorporating the power of place to better explain the relationships between variables.MethodsDisease incidence and indicator data derived for the RED Alert project were analyzed for spatial associations. Using aggregate country-level data, spatial and spatiotemporal clusters were identified in ArcMap 10.5.1. The identified clusters were then used as the outcome for a series of binary logistic regression models to determine significant covariates that help explain global hotspots. These methods will continue to evolve and be incorporated into the RED Alert decision support ecosystem to provide analysts with a global perspective on potential re-emergence.ResultsHotspots of high disease incidence in relation to neighboring countries were identified for measles, cholera, dengue, and yellow fever between 2000 and 2014. Disease-specific predictors were identified using aggregate estimates from World Bank indicator dataset. Data was imputed where possible to enhance the validity of the Gi * statistic for clustering. In the future, as data streams become more readily available, hotspot modeling at a finer resolution will help to improve the precision of spatial epidemiology.ConclusionsSpatial methods enhance the capability of understanding complex population and disease relationships, which in turn improves surveillance and the ability to predict re-emergence. With tools like RED Alert, public health analysts can better prepare to respond rapidly to future re-emerging disease threats.

Altherr, Forest M.↗
NASA NTRS1973

Prodromal disease: Immune responses of the host macrophage system to humoral factors

A composite is presented of nine studies, each yielding information contributing toward an understanding of methods designed to detect disease during the prodromal stages. The data further point to new areas of study that might be useful in early diagnoses. Five of the none experiments were done in mice. Four of these involved acute infectious disease states and one involved a chronic autoimmune type disease. Of the numerous perimeters studied of the acute diseases, the uptake of H3- thymidine by peripheral blood lymphocytes appeared to yield the earliest indication of disease. This test was not useful in studying the chronic disease state. Four of the nine studies involved application of diagnostic technics to human disease. A normal baseline for H3-thymidine incorporation by human lymphocytes was determined. A subject with severe combined immunodeficiency disease was studied. A human volunteer study was done using Influenza A live attenuated vaccine. Finally, a human volunteer study of subjects infected with Influenza A was done.

Criswell, B. S.↗
NASA NTRS2001

Controlling Malaria and Other Diseases Using Remote Sensing

Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.

Kiang, Richard K.↗
NASA NTRS1997

Remote Sensing the Patterns of Vector-borne Disease in El Nino and non-El Nino Years

The relationship between El Nino and non-El Nino and the patterns of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are long term predictions of changing precipitation and temperature patterns at continental and global scales. At the opposite extreme are the local or site specific ecological changes associated with the long term events. In order to understand and address the human health consequences of El Nino events, especially the patterns of vector-borne diseases, it is necessary to combine both scales of observation. At a local or regional scale the patterns of vector-borne diseases are determined by temperature, precipitation, and habitat availability. These factors, as well as disease incidence can be altered by El Nino events. Remote sensing data such as that acquired by the NOAA AVHRR and Landsat TM sensors can be used to characterize and monitor changing ecological conditions and therefore predict vector-borne disease patterns. The authors present the results of preliminary work on the analysis of historical AVHRR and TM data acquired during El Nino and nonfatal Nino years to characterize ecological conditions in Peru on a monthly basis. This information will then be combined with disease data to determine the relationship between changes in ecological conditions and disease incidence. Our goal is to produce a sequence of remotely sensed images which can be used to show the ecological and disease patterns associated with long term El Nino events and predictions.

Wood, B. L.↗
NASA NTRS1992

Evidence for a membrane defect in Alzheimer disease brain

To determine whether neurodegeneration in Alzheimer disease brain is associated with degradation of structural cell membrane molecules, we measured tissue levels of the major membrane phospholipids and their metabolites in three cortical areas from postmortem brains of Alzheimer disease patients and matched controls. Among phospholipids, there was a significant (P less than 0.05) decrease in phosphatidylcholine and phosphatidylethanolamine. There were significant (P less than 0.05) decreases in the initial phospholipid precursors choline and ethanolamine and increases in the phospholipid deacylation product glycerophosphocholine. The ratios of glycerophosphocholine to choline and glycerophosphoethanolamine to ethanolamine were significantly increased in all examined Alzheimer disease brain regions. The activity of the glycerophosphocholine-degrading enzyme glycerophosphocholine choline-phosphodiesterase was normal in Alzheimer disease brain. There was a near stoichiometric relationship between the decrease in phospholipids and the increase of phospholipid catabolites. These data are consistent with increased membrane phospholipid degradation in Alzheimer disease brain. Similar phospholipid abnormalities were not detected in brains of patients with Huntington disease, Parkinson disease, or Down syndrome. We conclude that the phospholipid abnormalities described here are not an epiphenomenon of neurodegeneration and that they may be specific for the pathomechanism of Alzheimer disease.

NASA Discipline Regulatory Physiology↗
NASA NTRS2010

Space Radiation Heart Disease Risk Estimates for Lunar and Mars Missions

The NASA Space Radiation Program performs research on the risks of late effects from space radiation for cancer, neurological disorders, cataracts, and heart disease. For mortality risks, an aggregate over all risks should be considered as well as projection of the life loss per radiation induced death. We report on a triple detriment life-table approach to combine cancer and heart disease risks. Epidemiology results show extensive heterogeneity between populations for distinct components of the overall heart disease risks including hypertension, ischaemic heart disease, stroke, and cerebrovascular diseases. We report on an update to our previous heart disease estimates for Heart disease (ICD9 390-429) and Stroke (ICD9 430-438), and other sub-groups using recent meta-analysis results for various exposed radiation cohorts to low LET radiation. Results for multiplicative and additive risk transfer models are considered using baseline rates for US males and female. Uncertainty analysis indicated heart mortality risks as low as zero, assuming a threshold dose for deterministic effects, and projections approaching one-third of the overall cancer risk. Medan life-loss per death estimates were significantly less than that of solid cancer and leukemias. Critical research questions to improve risks estimates for heart disease are distinctions in mechanisms at high doses (>2 Gy) and low to moderate doses (<2 Gy), and data and basic understanding of radiation doserate and quality effects, and individual sensitivity.

Cucinotta, Francis A.↗
DOE OSTI2019

A Metagenomic Meta-analysis Reveals Functional Signatures of Health and Disease in the Human Gut Microbiome

While recent research indicates that human health is affected by the gut microbiome, the functional mechanisms that underlie host-microbiome interactions remain poorly resolved. Metagenomic clinical studies can address this problem by revealing specific microbial functions that stratify healthy and diseased individuals. To improve our understanding of the relationship between the gut microbiome and health, we conducted the first integrative functional analysis of nearly 2,000 publicly available fecal metagenomic samples obtained from eight clinical studies. We identified characteristics of the gut microbiome that associate generally with disease, including functional alpha-diversity, beta-diversity, and beta-dispersion. Using regression modeling, we identified specific microbial functions that robustly stratify diseased individuals from healthy controls. Many of these functions overlapped multiple diseases, suggesting a general role in host health, while others were specific to a single disease and may indicate disease-specific etiologies. Our results clarify potential microbiome-mediated mechanisms of disease and reveal features of the microbiome that may be useful for the development of microbiome-based diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Structured versus narrative reporting of pelvic MRI in perianal fistulizing disease: impact on clarity, completeness, and surgical planning

Objective: To evaluate clarity, completeness, and impact on surgical planning of MRI reporting of perianal fistulizing disease using a structured disease-specific template versus narrative reporting for planning of disease treatment by colorectal surgeons. Materials and methods: In this HIPAA-compliant, IRB-approved study with waiver of informed consent, a structured reporting template for perianal fistulizing disease MRIs was developed based on collaboration between colorectal surgeons and abdominal radiologists. The study population included 45 consecutive patients who underwent pelvic MRI for perianal fistulizing disease prior to implementation of structured reporting, and 60 consecutive patients who underwent pelvic MRI for perianal fistulizing disease after implementation of structured reporting. Objective evaluation of the reports for the presence of 12 key features was performed, as also subjective evaluation regarding the clarity and completeness of reports, and impact on surgical planning. Results: Significantly more key features were absent in narrative reports [mean: 6.3 ± 1.8 (range 3–11)] than in structured reports [mean: 0.3 ± 0.9 (range 1–5)] (p ≤ 0.001). The use of structured reporting also increased the percentage of completeness (72.5–88.3% for surgeon 1, and 61.2–81.3% for surgeon 2; p = 0.05 and 0.03, respectively), helpfulness in surgical planning (7.1 ± 1.5–7.6 ± 1.5 for surgeon 1, and 5.8 ± 1.4–7.1 ± 1.1 for surgeon 2; p = 0.05 and p < 0.001, respectively), and clarity (7.6 ± 1.3–8.3 ± 1.1 for surgeon 1, and 5.2 ± 1.4–7.1 ± 1.3 for surgeon 2; p = 0.006 and p < 0.001, respectively) of the reports. Conclusion: Structured MRI reports in patients with perianal fistulizing disease miss fewer key features than narrative reports. Moreover, structured reports were described as more complete and clear, and more helpful for treatment planning.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Insight into the Bacterial Endophytic Communities of Peach Cultivars Related to Crown Gall Disease Resistance

Crown gall disease caused by Agrobacterium tumefaciens severely impacts the production of peach and other fruit trees. Several peach cultivars are partially resistant to A. tumefaciens, but little is known about the roles of endophytic microbiota in disease resistance. In the present study, the endophytic bacterial communities of resistant and susceptible peach cultivars “Honggengansutao” and “Okinawa” were analyzed using universal 16S rRNA gene amplicon sequencing in parallel with the cultivation and characterization of bacterial isolates. A total of 1,357,088 high-quality sequences representing 3,160 distinct operational taxonomic units (OTUs; Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes) and 1,200 isolates of 20 genera and 305 distinct ribotypes were collected from peach roots and twigs. It was found that factors including plant developmental stage, cultivar, and A. tumefaciens invasion strongly influenced the peach endophytic communities. The community diversity of endophytic bacteria and the abundance of culturable bacteria were both higher in the roots of the resistant cultivar, particularly after inoculation. Strikingly, the pathogen antagonists Streptomyces and Pseudomonas in roots and Rhizobium in twigs were most frequently detected in resistant plants. Our results suggest that the higher abundance and diversity of endophytic bacteria and increased proportions of antagonistic bacteria might contribute to the natural defense of the resistant cultivar against A. tumefaciens. This work reveals the relationships between endophytic bacteria and disease resistance in peach plants and provides important information for microbiome-based biocontrol of crown gall disease in fruit trees. Agrobacterium tumefaciens as the causal agent of peach crown gall disease can be controlled by planting resistant cultivars. This study profiles the endophytic bacteria in susceptible and resistant peach cultivars, advancing our understanding of the relationships between endophytic bacterial communities and peach crown gall disease, with potential implications for other complex microbiome-plant-pathogen interactions. The resistant cultivar may defend itself by increasing the diversity and abundance of beneficial endophytic bacteria. Finally, the antagonists identified among the genera Streptomyces, Pseudomonas, and Rhizobium may have application potential for biocontrol of crown gall disease in fruit trees.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework

Infectious diseases (IDs) have a significant detrimental impact on global health. Timely and accurate ID forecasting can result in more informed implementation of control measures and prevention policies. To meet the operational decision-making needs of real-world circumstances, we aimed to build a standardized, reliable, and trustworthy ID forecasting pipeline and visualization dashboard that is generalizable across a wide range of modeling techniques, IDs, and global locations. We forecasted 6 diverse, zoonotic diseases (brucellosis, campylobacteriosis, Middle East respiratory syndrome, Q fever, tick-borne encephalitis, and tularemia) across 4 continents and 8 countries. We included a wide range of statistical, machine learning, and deep learning models (n=9) and trained them on a multitude of features (average n=2326) within the One Health landscape, including demography, landscape, climate, and socioeconomic factors. The pipeline and dashboard were created in consideration of crucial operational metrics—prediction accuracy, computational efficiency, spatiotemporal generalizability, uncertainty quantification, and interpretability—which are essential to strategic data-driven decisions. While no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. For new or emerging diseases in a region, the ensemble model can predict how the disease may behave in the new region using a pretrained model from a similar region with a history of that disease. The data visualization dashboard provides a clean interface of important analytical metrics, such as ID temporal patterns, forecasts, prediction uncertainties, and model feature importance across all geographic locations and disease combinations. As the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Transboundary determinants of avian zoonotic infectious diseases: challenges for strengthening research capacity and connecting surveillance networks

As the climate changes, global systems have become increasingly unstable and unpredictable. This is particularly true for many disease systems, including subtypes of highly pathogenic avian influenzas (HPAIs) that are circulating the world. Ecological patterns once thought stable are changing, bringing new populations and organisms into contact with one another. Wild birds continue to be hosts and reservoirs for numerous zoonotic pathogens, and strains of HPAI and other pathogens have been introduced into new regions via migrating birds and transboundary trade of wild birds. With these expanding environmental changes, it is even more crucial that regions or counties that previously did not have surveillance programs develop the appropriate skills to sample wild birds and add to the understanding of pathogens in migratory and breeding birds through research. For example, little is known about wild bird infectious diseases and migration along the Mediterranean and Black Sea Flyway (MBSF), which connects Europe, Asia, and Africa. Focusing on avian influenza and the microbiome in migratory wild birds along the MBSF, this project seeks to understand the determinants of transboundary disease propagation and coinfection in regions that are connected by this flyway. Through the creation of a threat reduction network for avian diseases (Avian Zoonotic Disease Network, AZDN) in three countries along the MBSF (Georgia, Ukraine, and Jordan), this project is strengthening capacities for disease diagnostics; microbiomes; ecoimmunology; field biosafety; proper wildlife capture and handling; experimental design; statistical analysis; and vector sampling and biology. Here, we cover what is required to build a wild bird infectious disease research and surveillance program, which includes learning skills in proper bird capture and handling; biosafety and biosecurity; permits; next generation sequencing; leading-edge bioinformatics and statistical analyses; and vector and environmental sampling. Creating connected networks for avian influenzas and other pathogen surveillance will increase coordination and strengthen biosurveillance globally in wild birds.

54 ENVIRONMENTAL SCIENCES↗