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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

The Sufficient Component Cause Model Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at low doses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗
NASA NTRSDate not supplied

The Potential Outcome Model: Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at lowdoses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗
NASA NTRS1981

Application of the epidemiological model in studying human error in aviation

An epidemiological model is described in conjunction with the analytical process through which aviation occurrence reports are composed into the events and factors pertinent to it. The model represents a process in which disease, emanating from environmental conditions, manifests itself in symptoms that may lead to fatal illness, recoverable illness, or no illness depending on individual circumstances of patient vulnerability, preventive actions, and intervention. In the aviation system the analogy of the disease process is the predilection for error of human participants. This arises from factors in the operating or physical environment and results in errors of commission or omission that, again depending on the individual circumstances, may lead to accidents, system perturbations, or harmless corrections. A discussion of the previous investigations, each of which manifests the application of the epidemiological method, exemplifies its use and effectiveness.

Cheaney, E. S.↗
NASA NTRS1995

Resource recovery and epidemiology of anaerobic wastewater treatment process in a controlled ecological life support system

The results of work accomplished under two different areas: (1) Resource Recovery of an Anaerobic Wastewater Treatment process, and (2) Epidemiological Study of an Anaerobic Wastewater Treatment Process are documented. The first part of the work was to set up and test three anaerobic digesters and then run these three digesters with a NASA-simulated wastewater. The second part of the work was to use a multi-drug resistant strain of Salmonella choleraesuis as the indicator bacteria for the epidemiological study. Details of these two parts can be found in two master's theses and are described in Sections 3 and 4 of this report. Several important results condensed from these two parts are summarized in Section 2.

Li, Ku-Yen↗
NASA NTRS1995

Study of Resource Recovery and Epidemiology in an Anaerobic Digester

Three 4-liter packed bed anaerobic digesters were fabricated and operated at 35 degrees C, pH around 7, and hydraulic retention time (HRT) of 20, 10 and 5 days to study the resource recovery and epidemiology in a controlled ecological life support system (CELSS). A simulated wastewater, consisted of shower water, clothwash water, dishwasher water, handwash water, and urine flush water was used as the feeding solution. Under steady-state operation, chemical oxygen demand (COD), total organic carbon (TOC), pH, nitrogen, phosphorus, and potassium wer monitored in the digester input and output solutions. The volume and the CH4/CO2 ratios in the biogas produced from the anaerobic digesters were measured. The results indicate about 90 percent of TOC is converted while only 5-8 percent of N-P-K are consumed in the digester. A multi-drug resistant strain of Salmonella choleraesuis was used as the indicator bacterium in the epidemiology study. The levels of Salmonella choleraesuis in the influent and the effluent wer determined and decimal decay rate constants, k(d), were estimated. The k(d) values were greater at higher initial doses than lower doses for the same HR, and greater for batch digestion (7.89/d) than for continuous digestion (4.28, 3.82, and 3.82/d for 20, 10, and 5 d HRT, respectively).

Li, K. Y.↗
NASA NTRS2002

NASA Remote Sensing Data for Epidemiological Studies

In response to the need for improved observations of environmental factors to better understand the links between human health and the environment, NASA has established a new program to significantly improve the utilization of NASA's diverse array of data, information, and observations of the Earth for health applications. This initiative, lead by Goddard Space Flight Center (GSFC) has the following goals: (1) To encourage interdisciplinary research on the relationships between environmental parameters (e.g., rainfall, vegetation) and health, (2) Develop practical early warning systems, (3) Create a unique system for the exchange of Earth science and health data, (4) Provide an investigator field support system for customers and partners, (5) Facilitate a system for observation, identification, and surveillance of parameters relevant to environment and health issues. The NASA Environment and Health Program is conducting several interdisciplinary projects to examine applications of remote sensing data and information to a variety of health issues, including studies on malaria, Rift Valley Fever, St. Louis Encephalitis, Dengue Fever, Ebola, African Dust and health, meningitis, asthma, and filariasis. In addition, the NASA program is creating a user-friendly data system to help provide the public health community with easy and timely access to space-based environmental data for epidemiological studies. This NASA data system is being designed to bring land, atmosphere, water and ocean satellite data/products to users not familiar with satellite data/products, but who are knowledgeable in the Geographic Information Systems (GIS) environment. This paper discusses the most recent results of the interdisciplinary environment-health research projects and provides an analysis of the usefulness of the satellite data to epidemiological studies. In addition, there will be a summary of presently-available NASA Earth science data and a description of how it may be obtained.

Maynard, Nancy G.↗
NASA NTRS2009

Monitoring Bone Health after Spaceflight: Data Mining to Support an Epidemiological Analysis of Age-related Bone Loss in Astronauts

Through the epidemiological analysis of bone data, HRP is seeking evidence as to whether the prolonged exposure to microgravity of low earth orbit predisposes crewmembers to an earlier onset of osteoporosis. While this collaborative Epidemiological Project may be currently limited by the number of ISS persons providing relevant spaceflight medical data, a positive note is that it compares medical data of astronauts to data of an age-matched (not elderly) population that is followed longitudinally with similar technologies. The inclusion of data from non-ISS and non-NASA crewmembers is also being pursued. The ultimate goal of this study is to provide critical information for NASA to understand the impact of low physical or minimal weight-bearing activity on the aging process as well as to direct its development of countermeasures and rehabilitation programs to influence skeletal recovery. However, in order to optimize these results NASA needs to better define the requirements for long term monitoring and encourage both active and retired astronauts to contribute to a legacy of data that will define human health risks in space.

Baker, K. S,↗
NASA NTRS2010

Combining Epidemiologic Information Across Space Agencies

Space flight is a very unique occupational exposure with potential hazards that are not fully understood. A limited number of individuals have experienced the exposures incurred during space flight, and epidemiologic research would benefit from shared information across space agencies. However, data sharing can be problematic due to agency protection policies for personally identifiable information as well as medical records. Compliance with these protocols in the astronaut population is particularly difficult given the small, high-profile population under study. Creativity in combining data is necessary in order to overcome these difficulties and improve statistical power in research. This study presents methods in meta-analysis that may be used to combine non-attributable data across space agencies so that meaningful conclusions may be drawn about study interests. Methods for combining epidemiologic data across space agencies are presented, and the processes are demonstrated using life-time mortality data in U.S. astronauts and Russian cosmonauts. This proof of concept was found to be an acceptable way of sharing data across agencies, and will be used in the future as more relevant research interests are identified.

Minard, Charles G.↗
NASA NTRS1975

Epidemiological, clinical and sleep laboratory evaluations of insomnia

Epidemiological studies have contributed to the understanding of the total scope of the insomnia problem, both in terms of the incidence of sleep difficulties, and the extent and frequency of hypnotic drug use. Clinical studies - at the Sleep Research and Treatment Center - have been used to evaluate the medical, psychological, pharmacological and situational factors contributing to insomnia, and to evaluate the psychotherapy and chemotherapy best suited to treatment of insomnia. The sleep laboratory studies were of two types: (1) the study of sleep induction, sleep maintenance, and sleep stages, and (2) the use of hypnotic drugs, emphasizing their effectiveness in inducing and maintaining sleep, and the duration of this effectiveness.

Bixler, E. O.↗
NASA NTRS1990

Epidemiologic research in Antarctica

A study of epidemiology of respiratory viruses that was begun in the early 1960's is described. Locations selected for the study included a Wisconsin University housing village, a second grade school population, individual volunteers who associated socially, married couples, and the winter-over population at McMurdo Bay and at Scott Base in the Antarctic. It was concluded that most rhinovirus transmission is through aerosolized particles. Air filtration and careful nasal sanitation with virucidal tissues are determined to be effective in blocking rhinovirus transmission and should be useful in both isolated space colonies and in ordinary earth-bound populations.

Source record↗
NASA NTRS2003

A new dynamical atmospheric ionizing radiation (AIR) model for epidemiological studies

A new Atmospheric Ionizing Radiation (AIR) model is currently being developed for use in radiation dose evaluation in epidemiological studies targeted to atmospheric flight personnel such as civilian airlines crewmembers. The model will allow computing values for biologically relevant parameters, e.g. dose equivalent and effective dose, for individual flights from 1945. Each flight is described by its actual three dimensional flight profile, i.e. geographic coordinates and altitudes varying with time. Solar modulated primary particles are filtered with a new analytical fully angular dependent geomagnetic cut off rigidity model, as a function of latitude, longitude, arrival direction, altitude and time. The particle transport results have been obtained with a technique based on the three-dimensional Monte Carlo transport code FLUKA, with a special procedure to deal with HZE particles. Particle fluxes are transformed into dose-related quantities and then integrated all along the flight path to obtain the overall flight dose. Preliminary validations of the particle transport technique using data from the AIR Project ER-2 flight campaign of measurements are encouraging. Future efforts will deal with modeling of the effects of the aircraft structure as well as inclusion of solar particle events. Published by Elsevier Ltd on behalf of COSPAR.

Aviation↗
NASA NTRS2011

A Monitoring System for Crimean Congo Hemorrhagic Fever Epidemiology Studies in Afghanistan

In the last few years, tick-borne diseases have been reported as a resurging in the Middle East. Crimean-Congo hemorrhagic fever (CCHF) is endemic in the Middle East, including Turkey, Iran, Afghanistan and Pakistan. Recent studies have explored the causal link between environmental and disease incidence patterns by correlating remote sensing indicators (surface temperature, rainfall, and vegetation indices of plant photosynthetic activity) with spatially explicit epidemiological data. We combined the monitoring of environmental data at monthly temporal resolutions with available reports of confirmed CCHF cases to identify the environmental properties of endemic regions and quantify those properties to CCHF risk. We also conducted a sero-prevalence survey in a sample of households (human and animal specimens) in 9 villages in Engil district surrounding Herat province, in western Afghanistan. We present analysis results from our study villages and validate the associated environmental conditions as predictive for human disease occurrences. Risk prediction is critical for anticipating the type and potential impact of disease threats for timely response action.

Mustafa, M.↗
NASA NTRS2015

Assessing Disparities of Dengue Virus Transmission Risk across the US-Mexican Border Using a Climate Driven Vector-Epidemiological Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Although transmission regularly occurs along the border region in Mexico, dengue virus transmission in bordering Arizona has not occurred. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input and Daymet for temperature and supplemental precipitation input, we modeled dengue transmission along a US‐Mexico transect using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Model runs were performed for 5 cities in Sonora, Mexico and southern Arizona. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. For cities with reported dengue case data, the top model simulations that best reproduced dengue case numbers were retained and their parameter values were extracted for comparison. These parameter values were used to run simulations in areas where dengue virus transmission does not occur or where dengue fever case data was unavailable. Additional model runs were performed to reveal how changes in climate or parameter values could alter transmission risk along the transect. The relative influence of climate variability and model parameters on dengue virus transmission is assessed to help public health workers prepare location specific infection prevention strategies.

Morin, Cory↗
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 NTRS1971

Epidemiology and hygiene of air travel

Preventive medicine for air travelers in flight and at route stops, considering disease dissemination and control, international quarantinable diseases, sanitation, etc

Randel, H. W.↗
NASA NTRS1991

Satellite, environmental, and medical information applied to epidemiological monitoring

Improved communications and space-science technologies, such as remote sensing, offer hope of new, more holistic approaches to combating many arthropod-borne disease problems. The promise offered by these technologies has surfaced at a time when global and national efforts at disease control are in decline. Indeed, these programs seem to be losing ground against the arthropod-borne diseases just as rapidly as we seem to be moving forward in technological development. Given these circumstances, we can only hope that remote sensing and geographic information system (GIS) technologies can be pressed into service to help target the temporal and spatial application of control measures and to help in developing new control strategies.

Roberts, Donald R.↗
NASA NTRS1994

Remote Sensing as a Landscape Epidemiologic Tool to Identify Villages at High Risk for Malaria Transmission

A landscape approach using remote sensing and Geographic Information System (GIS) technologies was developed to discriminate between villages at high and low risk for malaria transmission, as defined by adult Anopheles albimanus abundance. Satellite data for an area in southern Chiapas, Mexico were digitally processed to generate a map of landscape elements. The GIS processes were used to determine the proportion of mapped landscape elements surrounding 40 villages where An. albimanus data had been collected. The relationships between vector abundance and landscape element proportions were investigated using stepwise discriminant analysis and stepwise linear regression. Both analyses indicated that the most important landscape elements in terms of explaining vector abundance were transitional swamp and unmanaged pasture. Discriminant functions generated for these two elements were able to correctly distinguish between villages with high ind low vector abundance, with an overall accuracy of 90%. Regression results found both transitional swamp and unmanaged pasture proportions to be predictive of vector abundance during the mid-to-late wet season. This approach, which integrates remotely sensed data and GIS capabilities to identify villages with high vector-human contact risk, provides a promising tool for malaria surveillance programs that depend on labor-intensive field techniques. This is particularly relevant in areas where the lack of accurate surveillance capabilities may result in no malaria control action when, in fact, directed action is necessary. In general, this landscape approach could be applied to other vector-borne diseases in areas where: 1. the landscape elements critical to vector survival are known and 2. these elements can be detected at remote sensing scales.

Beck, Louisa R.↗