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NASA NTRS2010

Modeling of the Orbital Debris Population of RORSAT Sodium-Potassium Droplets

A large population resident in the orbital debris environment is composed of eutectic sodium-potassium (NaK) droplets, released during the reactor core ejection of 16 nuclear-powered Radar Ocean Reconnaissance Satellites (RORSATs) launched in the 1980s by the former Soviet Union. These electrically conducting RORSAT debris objects are spherical in shape, generating highly polarized radar returns. Their diameters are mostly in the centimeter and millimeter size regimes. Since the Space Surveillance Network catalog is limited to objects greater than 5 cm in low Earth orbit, our current knowledge about this special class of orbital debris relies largely on the analysis of Haystack radar data. This paper elaborates the simulation of the RORSAT debris populations in the new NASA Orbital Debris Engineering Model ORDEM2010, which replaces ORDEM2000. The estimation of the NaK populations uses the NASA NaK-module as a benchmark. It follows the general statistical approach to developing all other ORDEM2010-required LEO populations (for various types of debris and across a wide range of object sizes). This paper describes, in detail, each major step in the NaK-population derivation, including a specific discussion on the conversion between Haystack-measured radar-cross-sections and object-size distribution for the NaK droplets. Modeling results show that the RORSAT debris population is stable for the time period under study and that Haystack data sets are fairly consistent over the observations of multiple years.

Xu, Y.-L.↗
NASA NTRS2019

Radar Cross Section of Orbital Debris Objects

This discussion is concerned with the radar-data analysis and usage involved in the building of model orbital debris (OD) populations in the near-Earth environment, focusing on radar cross section (RCS). While varying with radar wavelength, physical dimension, material composition, overall shape and structure, the RCS of an irregular object is also strongly dependent on its spatial orientation. The historical records of observed RCSs for cataloged OD objects in the Space Surveillance Network are usually distributed over an RCS range, forming respective characteristic patterns. The National Aeronautics and Space Administration (NASA) Size Estimation Model provides an empirical probability-density function of RCS as a function of “effective diameter” (or “characteristic length”), which makes it feasible to predict possible RCS distributions for a given model OD population and to link data with model from a statistical perspective. The discussion also includes application of the widely used method of moments (MoM) and the Generalized Multi-particle Mie-solution (GMM) in the prediction of the RCS of arbitrarily shaped objects. Theoretical calculation results for an aluminum cube are compared with corresponding experimental measurements.

Xu, Yu-Lin↗
NASA NTRS2015

Cubesat Constellation Design for Air Traffic Monitoring

Suitably equipped global and local air traffic can be tracked. The tracking information may then be used for control from ground-based stations by receiving the Automatic Dependent Surveillance-Broadcast (ADS-B) signal. The ADS-B signal, emitted from the aircraft's Mode-S transponder, is currently tracked by terrestrial based receivers but not over remote oceans or sparsely populated regions such as Alaska or the Pacific Ocean. Lack of real-time aircraft time/location information in remote areas significantly hinders optimal planning and control because bigger "safety bubbles" (lateral and vertical separation) are required around the aircraft until they reach radar-controlled airspace. Moreover, it presents a search-and-rescue bottleneck. Aircraft in distress, e.g. Air France AF449 that crashed in 2009, take days to be located or cannot be located at all, e.g. Malaysia Airlines MH370 in 2014. In this paper, we describe a tool for designing a constellation of small satellites which demonstrates, through high-fidelity modeling based on simulated air traffic data, the value of space-based ADS-B monitoring and provides recommendations for cost-efficient deployment of a constellation of small satellites to increase safety and situational awareness in the currently poorly-served surveillance area of Alaska. Air traffic data has been obtained from the Future ATM Concepts Evaluation Tool (FACET), developed at NASA Ames Research Center, simulated over the Alaskan airspace over a period of one day. The simulation is driven by MATLAB with satellites propagated and coverage calculated using AGI's Satellite ToolKit(STK10).

cubesats↗
DOE OSTI2024

Evaluating disease surveillance strategies for early outbreak detection in contact networks with varying community structure

Disease surveillance systems allow public health agencies to respond to emerging diseases before they become widespread. Developing such systems requires identifying optimal ways to monitor in the context of an epidemic outbreak; this problem is known as sensor selection. Contact networks represent the dynamics of interaction in a population and are used to model how a disease spreads in a population and to explore strategies of sensor selection. We evaluated five sensor selection strategies on their ability to provide an early warning of a COVID-like outbreak in synthetic contact networks encapsulated in four network scenarios. Three of these scenarios assessed different aspects of community structure. The fourth scenario employed a contact network representing the population and interactions of 6.8 million people in New York City, constructed from an agent-based simulation using census and transportation data. This scenario exemplifies how sensor selection strategies may perform in a real-world, urban context. Our findings suggest that the choice of the optimal strategy depends heavily on the community structure of the network. Strategies that select highly connected nodes or maximize network coverage are the optimal surveillance strategy for outbreak detection in many network community structures. However, a naive implementation of these strategies may fail to provide an early warning at all—including in the New York City scenario. Moreover, these methods are impractical for real-world use as they require knowledge of the underlying contact network. Instead, a selection strategy that starts with a set of random nodes and then performs a random walk through a chain of neighbors reliably provides early warnings without requiring prior knowledge of the network. We find this method, called “random chain”, to be the most pragmatic for implementation in a real-world disease surveillance context.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2010

Bone Health Monitoring in Astronauts: Recommended Use of Quantitative Computed Tomography [QCT] for Clinical and Operational Decisions

This slide presentation reviews the concerns that astronauts in long duration flights might have a greater risk of bone fracture as they age than the general population. A panel of experts was convened to review the information and recommend mechanisms to monitor the health of bones in astronauts. The use of Quantitative Computed Tomography (QCT) scans for risk surveillance to detect the clinical trigger and to inform countermeasure evaluation is reviewed. An added benefit of QCT is that it facilitates an individualized estimation of bone strength by Finite Element Modeling (FEM), that can inform approaches for bone rehabilitation. The use of FEM is reviewed as a process that arrives at a composite number to estimate bone strength, because it integrates multiple factors.

Sibonga, J. D.↗
NASA NTRS2012

Observations of GEO Debris with the Magellan 6.5-m Telescopes

Optical observations of geosynchronous orbit (GEO) debris are important to address two questions: 1. What is the distribution function of objects at GEO as a function of brightness? With some assumptions, this can be used to infer a size distribution. 2. Can we determine what the likely composition of individual GEO debris pieces is from studies of the spectral reflectance of these objects? In this paper we report on optical observations with the 6.5-m Magellan telescopes at Las Campanas Observatory in Chile that attempt to answer both questions. Imaging observations over a 0.5 degree diameter field-of-view have detected a significant population of optically faint debris candidates with R > 19th magnitude, corresponding to a size smaller than 20 cm assuming an albedo of 0.175. Many of these objects show brightness variations larger than a factor of 2, suggesting either irregular shapes or albedo variations or both. The object detection rate (per square degree per hour) shows an increase over the rate measured in the 0.6-m MODEST observations, implying an increase in the population at optically fainter levels. Assuming that the albedo distribution is the same for both samples, this corresponds to an increase in the population of smaller size debris. To study the second issue, calibrated reflectance spectroscopy has been obtained of a sample of GEO and near GEO objects with orbits in the public U.S. Space Surveillance Network catalog. With a 6.5-m telescope, the exposures times are short (30 seconds or less), and provide simultaneous wavelength coverage from 4500 to 8000 Angstroms. If the observed objects are tumbling, then simultaneous coverage and short exposure times are essential for a realistic assessment of the object fs spectral signature. We will compare the calibrated spectra with lab-based measurements of simple spacecraft surfaces composed of a single material.

Seitzer, Patrick↗
NASA NTRS2007

Alaska at the Crossroads of Migration: Space Based Ornithology

Understanding bird migration on a global scale is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Revolutionary advances in remote sensing now provide us with near real-time measurements of atmospheric and land surface conditions at high spatial resolution over entire continents. We use spatially-explicit, individual based bird migration models driven by numerical weather prediction models of atmospheric conditions, dynamic habitat suitability maps derived from remotely sensed land surface conditions, biophysiological models, and biological field data to simulate migration routes, timing, energy budgets, and survival of individual birds and populations. Long-distance migratory birds travel annually between breeding grounds in Alaska and wintering grounds in Latin Amierica. Approximately 25% of these species are potential vectors of Avian Influenza. Alaska is at the crossroads of Asian and New World migratory flyways and is likely to be a point of introduction of Asian H5N1 AI into the western hemisphere. If/when an infected bird is detected, a pressing question will be where was this bird several days ago, and where is it likely to go after it was released from the survey site? Answers to such questions will increase effectiveness of AI surveillance and mitigation measures. From a conservation perspective, Alaska's diverse landscape provides breeding sites for many migrants, and climatic and land surface changes along migratory flyways in the western hemisphere may reduce bird survival and physical condition upon arrival at Alaskan breeding territories, success and migrant populations.

Deppe, Jill↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗
NASA NTRS2016

Surveillance in a Telemedicine Setting: Application of Epidemiologic Methods at NASA Johnson Space Center Adriana

Space medicine presents unique challenges and opportunities for epidemiologists, such as the use of telemedicine during spaceflight. Medical capabilities aboard the International Space Station (ISS) are limited due to severe restrictions on power, volume, and mass. Consequently, inflight health information is based heavily on crewmember (CM) self-report of signs and symptoms, rather than formal diagnoses. While CM's are in flight, the primary source of crew health information is verbal communication between physicians and crewmembers. In 2010 NASA implemented the Lifetime Surveillance of Astronaut Health, an occupational surveillance program for the U.S. Astronaut corps. This has shifted the epidemiological paradigm from tracking diagnoses based on traditional terrestrial clinical practice to one that incorporates symptomatology and may gain a more population-based understanding of early detection of disease process.

Babiak-Vazquez, Adriana↗
NASA NTRS2016

Colonoscopy Screening in the US Astronaut Corps

BACKGROUND: Historically, colonoscopy screenings for astronauts have been conducted to ensure that astronauts are in good health for space missions. Recently this historical data has been identified as being useful for developing an occupational surveillance requirement. It can be used to assess overall colon health and to have a point of reference for future tests in current and former astronauts, as well as to follow-up and track rates of colorectal cancer and polyps. These rates can be compared to military and other terrestrial populations. In 2003, the active astronaut colonoscopy requirements changed to require less frequent colonoscopies. Since polyp removal during a colonoscopy is an intervention that prevents the polyp from potentially developing into cancer, the procedure decreases the individual's risk for colon cancer. The objective of this study is to evaluate the possible effect of increased follow-up times between colonoscopies on the number and severity of polyps identified during the procedures among both current and former NASA astronauts. Initial results and forward work regarding astronaut colonoscopy screenings will be presented. METHODS: A retrospective study of all colonoscopy procedures performed on NASA astronauts between 1962 and 2015 (both during active career and retirement) was conducted by review of the JSC Clinic Electronic Medical Record and Lifetime Surveillance of Astronaut Health (LSAH) database for colonoscopy screening procedures and pathology reports. The timeframe of interest was from the time of selection into the Astronaut Corps through May 2015 or death. For each colonoscopy report, the following data were captured: date of procedure, age at time of procedure, reason for procedure, quality of bowel prep, completion of procedure and/or reason for termination of procedure, findings of procedure, subsequent treatment (if any), recommended follow-up interval, actual follow up interval, family history of polyps or colon cancer, and other significant items or discrepancies. The population consisted of 338 astronauts: 52 females, 286 males. Of these, 56 were deceased, and 11 astronauts had no record of any colonoscopies. Because of a screening requirement change in 2003, analyses were conducted to determine if there were differences between the two time periods. One-sided Wilcoxon rank sum tests were used to identify statistically significant differences between the two time periods. RESULTS: There was a combined total of 1,964 colonoscopy screenings identified. The average follow-up intervals between colonoscopies were indeed longer after the screening requirement change than before the change. The mean follow-up interval pre -2003 was 3.59 years, while post-2003 it increased to 4.35 years. The statistical significance of this difference was confirmed using a one sided Wilcoxon rank sum test which yielded p<.001. Colonoscopies performed after the requirement change tended to have a higher incidence and greater severity of polyps. From pre-2003 to post-2003 the percentage of colonoscopy procedures yielding no polyps decreased from 83.77% to 74.70%. Not only did post-2003 procedures yield more polyp findings, but the polyps recorded were more often of severe pathology. Before 2003 3.62% of colonoscopy findings were polyps of the hyperplastic type (the least severe polyp type) and only 3.35% were of greater severity. Post-2003, 4.21% of findings were hyperplastic polyps while 11.44% were of greater severity. Upon the investigation of other possible contributing factors to these results, we also found that mean age post-2003 was 54.55 years which was significantly higher than during the pre-2003 timeframe (47.32 years). This was observed with a one-sided Wilcoxon rank sum test, resulting in a p<0.001. The increased average age of astronauts could also be a contributing factor to the greater number of polyps found since the risk of developing polyps increases with age. Further work is needed to better understand the increased incidence and greater severity of polyps found in astronaut colonoscopy outcomes.

Masterova, K.↗
NASA NTRSDate not supplied

Using A Guided Interview to Create an Individual Exposure Profile for The Lifetime Surveillance of Astronaut Health (LSAH)

BACKGROUND To support NASA’s Lifetime Surveillance of Astronaut Health (LSAH) project, Individual Exposure Profiles (IEPs) were developed to record an astronaut’s pre-, in-, and post-NASA exposures. NASA astronauts were invited to participate in a one-time guided interview to review known hazard exposures and medical history documented in NASA records and to add new information not otherwise reported. The purpose of the IEP project was to determine if any significant information was gained from these interviews and identify potential trends in long-term health. METHODOLOGY The pre-filled exposure profile data was extracted from several sources including medical records, biographies, and LSAH records. The information that was pre-filled before the interview included occupational exposures prior to selection to the Astronaut Corps, during active astronaut career (e.g., EVA and ground-based training, on-orbit exposures), and after active career. The IEPs also contained relevant medical history (e.g., audiometry, illnesses, injuries) and significant non-occupational exposures. 189 interviews were conducted from 2012-2014. A Microsoft Access database was created to store the information collected in the IEPs before and after the interviews. The database houses the information from the IEPs to track the updates made to the original data. By analyzing which astronauts supplied additional information and which kinds of data were consistently added, potential gaps and trends in missing data may be identified. In designing the database, an efficient structure was implemented for ease of inputting data and to create variables that would generate quantifiable data. Creating standardized variables within the structure helped ease the process of inputting, organizing data, and analyzing data. Additional updates/data were denoted and were categorized by type of update. The categories identified were “Confirmed”, “Confirmed & Supplemented”, “Supplemented”, “Denied”, “Denied & Supplemented”, and “Other”. STATISTICAL ANALYSIS AND RESULTS To assess frequency of exposure updates, descriptive statistics will be generated and stratified by relevant factors such as astronaut selection decade, age at selection, and program/era. Hypothesis testing will be performed to understand the associations between updates to exposure information and population characteristics.

Astronaut health↗
DOE OSTI2022

Obstructive Sleep Apnea Among Army Aircrew

INTRODUCTION: Obstructive sleep apnea (OSA) is a condition characterized by disrupted sleep and excessive daytime fatigue. Associated cognitive and psychomotor decrements pose a threat to aviators’ performance and flight safety. Additionally, the longer term health effects associated with the disease can jeopardize an aviator’s career and negatively impact operational outputs. This study reviews OSA prevalence, related comorbid conditions in Army aviators, and analyzes the aeromedical dispositions of affected individuals. METHODS: The U.S. Army Aeromedical Electronic Resource Office (AERO) database was interrogated for all cases of OSA from June 2005 through June 2015 using ICD-9 code 327.23. Prevalence rates for OSA and other comorbid conditions were then calculated using the total number of aviators in the AERO database. RESULTS: A total of 663 unique instances of OSA were found among the aviator population ( N = 24,568), giving a point prevalence of 2.69%. Four cases affected women. Mean age of initial presentation was 42.62 yr and mean Body Mass Index was 28.69. The top five most prevalent comorbid conditions were hypertension, lumbago, degeneration of a lumbar or lumbosacral intervertebral disc, PTSD, and testicular hypofunction. DISCUSSION: Prevalence of OSA among aviators is lower than the general population but is not uncommon. A positive diagnosis requires a waiver or can result in suspension if not managed effectively, potentially leading to a reduction in aviator numbers. Aggressive health promotion and robust medical surveillance and aeromedical disposition management by the aeromedical community is essential to reduce OSA numbers, maintain aviator health, and maximize flight safety. Goldie C, Stork B, Bernhardt K, Gaydos SJ, Kelley AM. Obstructive sleep apnea among army aircrew . Aerosp Med Hum Perform. 2022; 93(5):415–420.

Biophysics↗
NASA NTRS2008

Characterization of the Catalog Fengyun-1C Fragments and Their Long-term Effect on the LEO Environment

The intentional breakup of Fengyun-1C on 11 January 2007 created the most severe orbital debris cloud in history. More than 2500 large fragments were identified and tracked by the U.S. Space Surveillance Network by the end of the year. The altitude where the event occurred was probably the worst location for a major breakup in the low Earth orbit (LEO) region, since it was already highly populated with operational satellites and debris generated from previous breakups. The addition of so many fragments not only poses a realistic threat to operational satellites in the region, but also increases the instability (i.e., collision cascade effect) of the debris population there. Preliminary analysis of the large Fengyun-1C fragments indicates that their size and area-to-mass ratio (A/M) distributions are very different from those of other known events. About half of the fragments appear to be composed of light-weight materials and more than 100 of them have A/M values exceeding 1 square meter per kilogram, consistent with thermal blanket pieces. In addition, the orbital elements of the fragments suggest nontrivial velocity gain by the fragment cloud during the impact. These important characteristics were incorporated into a numerical simulation to assess the long-term impact of the Fengyun-1C fragments to the LEO debris environment. The main objectives of the simulation were to evaluate (1) the collision probabilities between the Fengyun-1C fragments and the rest of the catalog population and (2) the collision activities and population growth in the region in the next 100 years.

Liou, J.-C.↗
DOE OSTI2020

Cell fusing agent virus (Flavivirus) infection in Aedes aegypti in Texas: seasonality, comparison by trap type, and individual viral loads

Abstract South Texas has experienced local transmission of Zika virus and of other mosquito-borne viruses such as chikungunya virus and dengue virus in the last decades. Using a mosquito surveillance program in the Lower Rio Grande Valley (LRGV) and San Antonio, TX, from 2016 to 2018, we detected the presence of an insect-specific virus, cell fusing agent virus (CFAV), in the Aedes aegypti mosquito population. We tested 6,326 females and 1,249 males from the LRGV and 659 females from San Antonio for CFAV by RT-PCR using specific primers. Infection rates varied from 0 to 261 per 1,000 mosquitoes in the LRGV and 115 to 208 per 1,000 in San Antonio depending on the month of collection. Infection rates per 1,000 individuals appeared higher in females collected from BG Sentinel 2 traps compared to Autocidal Gravid Ovitraps, but the ratio of the percentage of infected pools did not differ by trap type. The natural viral load in individual males ranged from 1.25 x 10 2 to 5.50 x 10 6 RNA copies and in unfed females from 5.42 x 10 3 to 8.70 x 10 6 RNA copies. Gravid females were found to harbor fewer viral particles than males and unfed females.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Impact of including second and later cancers in cause-specific survival estimates using population-based registry data

Background. Second or later primary cancers account for approximately 20% of incident cases in the United States. Currently, cause-specific survival (CSS) analyses exclude these cancers because the cause of death (COD) classification algorithm was available only for first cancers. The authors added rules for later cancers to the Surveillance, Epidemiology, and End Results cause-specific death classification algorithm and evaluated CSS to include individuals with prior tumors. Methods. The authors constructed 2 cohorts: 1) the first ever primary cohort, including patients whose first cancer was diagnosed during 2000 through 2016) and 2) the earliest matching primary cohort, including patients with any cancer who matched the selection criteria irrespective of whether it was the first or a later cancer diagnosed during 2000 through 2016. The cohorts' CSS estimates were compared using follow-up through December 31, 2017. The new rules were used in the second cohort for patients whose first cancers during 2000 through 2016 were their second or later cancers. Results. Overall, there were no statistically significant differences in CSS estimates between the 2 cohorts. Estimates were similar by age, stage, race, and time since diagnosis, except for patients with leukemia and those aged 65 to 74 years (3.4 percentage point absolute difference). Conclusions. The absolute difference in CSS estimates for the first cancer ever cohort versus earliest of any cancers cohort in the study period was small for most cancer types. As the number of newly diagnosed patients with prior cancers increases, the algorithm will make CSS more inclusive and enable estimating survival for a group of patients with cancer for whom life tables are not available or life tables are available but do not capture other-cause mortality appropriately.

Survival Analysis↗
DOE OSTI2021

Sequence Analysis of 20,453 Severe Acute Respiratory Syndrome Coronavirus 2 Genomes from the Houston Metropolitan Area Identifies the Emergence and Widespread Distribution of Multiple Isolates of All Major Variants of Concern

Since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there has been international concern about the emergence of virus variants with mutations that increase transmissibility, enhance escape from the human immune response, or otherwise alter biologically important phenotypes. In late 2020, several variants of concern emerged globally, including the UK variant (B.1.1.7), the South Africa variant (B.1.351), Brazil variants (P.1 and P.2), and two related California variants of interest (B.1.429 and B.1.427). These variants are believed to have enhanced transmissibility. For the South Africa and Brazil variants, there is evidence that mutations in spike protein permit it to escape from some vaccines and therapeutic monoclonal antibodies. On the basis of our extensive genome sequencing program involving 20,453 coronavirus disease 2019 patient samples collected from March 2020 to February 2021, we report identification of all six of these SARS-CoV-2 variants among Houston Methodist Hospital (Houston, TX) patients residing in the greater metropolitan area. Although these variants are currently at relatively low frequency (aggregate of 1.1%) in the population, they are geographically widespread. Houston is the first city in the United States in which active circulation of all six current variants of concern has been documented by genome sequencing. Finally, as vaccine deployment accelerates, increased genomic surveillance of SARS-CoV-2 is essential to understanding the presence, frequency, and medical impact of consequential variants and their patterns and trajectory of dissemination.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Transmission risk of Oropouche fever across the Americas

Abstract Background Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. Methods To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. Results Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. Conclusions Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.

60 APPLIED LIFE SCIENCES↗