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At least 289 records · Page 16

The Hyperspectral Infrared Imager (HyspIRI) Public Health and Air Quality Applications

The neglected tropical diseases (NTDs), a group of chronic, debilitating, and poverty-promoting parasitic, bacterial, and some viral and fungal infections, are among the most common causes of illness of the poorest people living in developing countries. Abiotic environmental factors are important in determining the distribution of disease-causing vectors and their life-cycles. HyspIRI observations can be merged through a Land Data Assimilation System (LDAS) be used to drive spatially-explicit ecological models of NTD vectors distribution and life cycles. Assimilations will be driven by observational data LDAS and satellite-derived meteorological forcing data, parameter datasets, and assimilation observations. HyspIRI hyperspectral measurements would provide global measurements of surface mineralogy and biotic crusts important in accessing the impact of dust in human health. HyspIRI surface thermal measurements would also help identify the variability of dust sources due to surface moisture conditions and map mineralogy.

Luvall, Jeffrey C.↗

TLife-LSTM: Forecasting Future COVID-19 Progression with Topological Signatures of Atmospheric Conditions

Understanding the impact of atmospheric conditions on SARS-CoV2 is critical to model COVID-19 dynamics and sheds a light on the future spread around the world. Furthermore, geographic distri- butions of expected clinical severity of COVID-19 may be closely linked to prior history of respiratory diseases and changes in humidity, tem- perature, and air quality. In this context, we postulate that by tracking topological features of atmospheric conditions over time, we can provide a quanti?able structural distribution of atmospheric changes that are likely to be related to COVID-19 dynamics. As such, we apply the machinery of persistence homology on time series of graphs to extract topological signatures and to follow geographical changes in relative humidity and temperature. We develop an integrative machine learning framework named Topological Lifespan LSTM (TLife-LSTM) and test its predictive capabilities on forecasting the dynamics of SARS-CoV2 cases. We validate our framework using the number of con?rmed cases and hospitalization rates recorded in the states of Washington and California in the USA. Our results demonstrate the predictive potential of TLife-LSTM in forecasting the dynamics of COVID-19 and modeling its complex spatio-temporal spread dynamics.

Gel, Yulia R.↗

Clues to Coral Reef Health: Integrating Radiative Transfer Modeling and Hyperspectral Data

An important contribution to coral reef research is to improve spectral distinction between various health states of coral species in areas subject to harmful anthropogenic activity and climate change. New insights into radiative transfer properties of corals under healthy and stressed conditions can advance understandings of ecological processes on reefs and allow better assessments of the impacts of large-scale bleaching and disease events, Our objective was to examine the spectral and spatial properties of hyperspectral sensors that may be used to remotely sense changes in reef community health. We compare in situ reef environment spectra (healthy coral, stressed coral, dead coral, algae, and sand) with airborne hyperspectral data to identify important spectral characteristics and indices. Additionally, spectral measurements over a range of water depths, relief, and bottom types are compared to help quantify bottom-water column influences. In situ spectra were collected in July and August 2002 at the Long Rock site in the Andros Island, Bahamas coastal zone coral reef. Our primary emphasis was on Acropora palmata (or elkhorn coral), a major reef building coral, which is prevalent in the study area, but is suffering from white band disease. A. palmata is currently being, proposed as an endangered species because its populations have severely declined in many areas of the Caribbean. In addition to the A. palmata biotope, we have collected spectra of at least seven other coral biotopes that exist within the study area, each with different coral community composition, density of corals, relief, and size of corals. Coral spectral reflectance was then input into a radiative transfer model, CORALMOD (CM1), which is based on a leaf radiative transfer model. In CM1, input coral reflectance measurements produce modeled reflectance through an inversion at each visible wavelength to provide the absorption spectrum. Initially, we imposed a scattering baseline that is the same regardless of the coral condition and that coral is optically thick and no light is transmitted through coral. Here we will focus on methodology, experimental design, and initial findings of the in situ spectral measurements and preliminary output from the radiative transfer model.

Guild, Liane↗

Self-reported coping behavior in health and disease: assessment with a card sort game

The authors tested the hypothesis that individuals with a variety of severe chronic illnesses and the healthy elderly exhibit a loss of flexibility in their response to a variety of stressors, compared with healthy adults. A card sort game designed to assess self-reported coping behavior under different stressful life situations was used to compare healthy adults with individuals with multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus, and the elderly. The healthy adults were found to exhibit more variability than any of the illness groups or the elderly. Healthy function is marked by a complex type of variability.

Non-NASA Center↗

Remote Imaging Applied to Schistosomiasis Control: The Anning River Project

The use of satellite imaging to remotely detect areas of high risk for transmission of infectious disease is an appealing prospect for large-scale monitoring of these diseases. The detection of large-scale environmental determinants of disease risk, often called landscape epidemiology, has been motivated by several authors (Pavlovsky 1966; Meade et al. 1988). The basic notion is that large-scale factors such as population density, air temperature, hydrological conditions, soil type, and vegetation can determine in a coarse fashion the local conditions contributing to disease vector abundance and human contact with disease agents. These large-scale factors can often be remotely detected by sensors or cameras mounted on satellite or aircraft platforms and can thus be used in a predictive model to mark high risk areas of transmission and to target control or monitoring efforts. A review of satellite technologies for this purpose was recently presented by Washino and Wood (1994) and Hay (1997) and Hay et al. (1997).

Seto, Edmund Y. W.↗

Integration of Dust Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Yin 2007) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Yin 2007). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). We are modifying the DREAM model to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that health effects of pollen can better be tracked for linkage with health outcome data including asthma, respiratory effects, myocardial infarction, and lost work days. DREAM is based on the SKIRON/Eta modeling system and the Eta/NCEP regional atmospheric model. The dust modules of the entire system incorporate the state of the art parameterizations of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particle size distribution on aerosol dispersion. The dust production mechanism is based on the viscous/turbulent mixing, shear-free convection diffusion, and soil moisture. In addition to these sophisticated mechanisms, very high resolution databases, including elevation, soil properties, and vegetation cover are utilized. The DREAM model was modified to use pollen sources instead of dust (PREAM). Pollen release will be estimated based on satellite-derived phenology of Juniperus spp. communities. The MODIS surface reflectance product (MOD09) will provide information on the start of the plant growing season, growth stage, peak greenness, dry-down and pollen release. Ground based observational records of pollen release timing and quantities will be used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS. The resulting deterministic model for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. This information will be used to support the Centers for Disease Control and Prevention (CDC)'s National Environmental Public Health Tracking Program (EPHT) and the State of New Mexico environmental public health decision support for asthma and allergies alerts

Luvall, Jeffrey C.↗

Microbial Impact on Success of Human Exploration Missions

The purpose of this study is to identify microbiological risks associated with space exploration and identify potential countermeasures available. Identification of microbial risks associated with space habitation requires knowledge of the sources and expected types of microbial agents. Crew data along with environmental data from water, surfaces, air, and free condensate are utilized in risk examination. Data from terrestrial models are also used. Microbial risks to crew health include bacteria, fungi, protozoa, and viruses. Adverse effects of microbes include: infections, allergic reactions, toxin production, release of volatiles, food spoilage, plant disease, material degradation, and environmental contamination. Risk is difficult to assess because of unknown potential changes in microbes (e.g., mutation) and the human host (e.g., immune changes). Prevention of adverse microbial impacts is preferred over remediation. Preventative measures include engineering measures (e.g., air filtration), crew microbial screening, acceptability standards, and active verification by onboard monitoring. Microbiological agents are important risks to human health and performance during space flight and risks increase with mission duration. Acceptable risk level must be defined. Prevention must be given high priority. Careful screening of crewmembers and payloads is an important element of any risk mitigation plan. Improved quantitation of microbiological risks is a high priority.

Pierson, Duane L.↗

Improving Decision-Making Activities for Meningitis and Malaria

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

parasitic diseases↗

Monitoring forest land from high altitude and from space

The significant findings are reported for remote sensing of forest lands conducted during the period October 1, 1965 to December 31, 1972. Forest inventory research included the use of aircraft and space imagery for forest and nonforest land classification, and land use classification by automated procedures, multispectral scanning, and computerized mapping. Forest stress studies involved previsual detection of ponderosa pine under stress from insects and disease, bark bettle infestations in the Black Hills, and root disease impacts on forest stands. Standardization and calibration studies were made to develop a field test of an ERTS-matched four-channel spectrometer. Calibration of focal plane shutters and mathematical modeling of film characteristic curves were also studied. Documents published as a result of all forestry studies funded by NASA for the Earth Resources Survey Program from 1965 through 1972 are listed.

Source record↗

Role of Transport and Kinetics in Growth of Renal Stones

Renal stone disease is not only a concern on earth but could conceivably pose as a serious risk to the astronauts health and safety in Space. In this paper, a combined transport-kinetics model for growth of calcium oxalate crystals is presented. The model is used to parametrically investigate the growth of renal calculi in urine with a focus on the coupled effects of transport and surface reaction on the ionic concentrations at the surface of the crystal and their impact on the resulting growth rates. It is shown that under nominal conditions of low solution supersaturation and low Damkohler number that typically exist on Earth, the surface concentrations of calcium and oxalate approach their bulk solution values in the urine and the growth rate is most likely limited by the surface reaction kinetics. But for higher solution supersaturations and larger Damkohler numbers that may be prevalent in the microgravity environment of Space, the calcium and oxalate surface concentrations tend to shift more towards their equilibrium or saturation values and thus the growth process may be limited by the transport through the medium. Furthermore, parametric numerical studies suggest that changes to the renal biochemistry of astronauts due in space may promote development of renal calculi during long duration space expeditions.

Kassemi, Mohammad↗

Defining Change Thresholds: What Change Is Outside Typical Sources of Variation?

Researchers often have a difficult time defining meaningful thresholds for change. We sometimes identify subtle changes but what amount of change is beyond typical sources of variation? This is especially complicated when trying to understand new disease pathogenesis like the constellation of eye changes leading to Spaceflight-associated Neuro-ocular Syndrome (SANS). To support decision makers in defining minimal meaningful change, we used a Bayesian hierarchical model to estimate innate sources of variability such as natural day to day variation. Healthy subjects were recruited and imaged with MRI, OCT, and US on separate days and measured by several technicians. Models were developed specifying random effects for the sources of variation – between left and right eyes, within-individuals over time, between raters, and finally between individuals. This allowed us to find the posterior distribution for the total typical variation, within an eye, which we use to define a threshold where change beyond typical sources of variation is likely. This threshold is now used as our earliest indicator of systematic increase in Total Retinal Thickness (a precursor to optic disc edema).

Millennia Young↗

Evidence Report: Risk of Cardiovascular Disease and Other Degenerative Tissue Effects from Radiation Exposure

Occupational radiation exposure from the space environment may result in non-cancer or non-CNS degenerative tissue diseases, such as cardiovascular disease, cataracts, and respiratory or digestive diseases. However, the magnitude of influence and mechanisms of action of radiation leading to these diseases are not well characterized. Radiation and synergistic effects of radiation cause DNA damage, persistent oxidative stress, chronic inflammation, and accelerated tissue aging and degeneration, which may lead to acute or chronic disease of susceptible organ tissues. In particular, cardiovascular pathologies such as atherosclerosis are of major concern following gamma-ray exposure. This provides evidence for possible degenerative tissue effects following exposures to ionizing radiation in the form of the GCR or SPEs expected during long-duration spaceflight. However, the existence of low dose thresholds and dose-rate and radiation quality effects, as well as mechanisms and major risk pathways, are not well-characterized. Degenerative disease risks are difficult to assess because multiple factors, including radiation, are believed to play a role in the etiology of the diseases. As additional evidence is pointing to lower, space-relevant thresholds for these degenerative effects, particularly for cardiovascular disease, additional research with cell and animal studies is required to quantify the magnitude of this risk, understand mechanisms, and determine if additional protection strategies are required.The NASA PEL (Permissive Exposure Limit)s for cataract and cardiovascular risks are based on existing human epidemiology data. Although animal and clinical astronaut data show a significant increase in cataracts following exposure and a reassessment of atomic bomb (A-bomb) data suggests an increase in cardiovascular disease from radiation exposure, additional research is required to fully understand and quantify these adverse outcomes at lower doses (less than 0.5 gray (SI unit for ionizing radiation dosage, i.e. one joule of radiation energy per one kilogram of matter)) to facilitate risk prediction. This risk has considerable uncertainty associated with it, and no acceptable model for projecting degenerative tissue risk is currently available. In particular, risk factors such as obesity, alcohol, and tobacco use can act as confounding factors that contribute to the large uncertainties. The PELs could be violated under certain scenarios, including following a large SPE (solar proton event) or long-term GCR (galactic cosmic ray) exposure. Specifically, for a Mars mission, the accumulated dose is sufficiently high that epidemiology data and preliminary risk estimates suggest a significant risk for cardiovascular disease. Ongoing research in this area is intended to provide the evidence base for accurate risk quantification to determine criticality for extended duration missions. Data specific to the space radiation environment must be compiled to quantify the magnitude of this risk to decrease the uncertainty in current PELs and to determine if additional protection strategies are required. New research results could lead to estimates of cumulative radiation risk from CNS and degenerative tissue diseases that, when combined with the cancer risk, may have major negative impacts on mission design, costs, schedule, and crew selection. The current report amends an earlier report (Human Research Program Requirements Document, HRP-47052, Rev. C, dated Jan 2009) in order to provide an update of evidence since 2009.

Patel, Zarana↗

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney↗

The economic value of remote sensing of earth resources from space: An ERTS overview and the value of continuity of service. Volume 3: Intensive use of living resources: Agriculture. Part 1: Overview

Potential economic benefits obtainable from a state-of-the-art ERS system in the resource area of intensive use of living resources, agriculture, are studied. A spectrum of equal capability (cost saving), increased capability, and new capability benefits are quantified. These benefits are estimated via ECON developed models of the agricultural marketplace and include benefits of improved production and distribution of agricultural crops. It is shown that increased capability benefits and new capability benefits result from a reduction of losses due to disease and insect infestation given ERS's capability to distinguish crop vigor and from the improvement in world trade negotiations given ERS's worldwide surveying capability.

Kornhauser, A. L.↗

NASA Earth Observation Systems and Applications for Health and Air Quality

There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

Omar, Ali H.↗

NASA Health and Air Quality Applications

There is a growing body of evidence that the environment can affect human health in ways that are both complex and global in scope. To address some of these complexities, NASA maintains a diverse constellation of Earth observing research satellites, and sponsors research in developing satellite data applications across a wide spectrum of areas. These include environmental health; infectious disease; air quality standards, policies, and regulations; and the impact of climate change on health and air quality in a number of interrelated efforts. The Health and Air Quality Applications fosters the use of observations, modeling systems, forecast development, application integration, and the research to operations transition process to address environmental health effects. NASA has been a primary partner with Federal operational agencies over the past nine years in these areas. This talk presents the background of the Health and Air Quality Applications program, recent accomplishments, and a plan for the future.

Air Quality Remote Sensing↗

Cell and molecular biology of simian virus 40: implications for human infections and disease

Simian virus 40 (SV40), a polyomavirus of rhesus macaque origin, was discovered in 1960 as a contaminant of polio vaccines that were distributed to millions of people from 1955 through early 1963. SV40 is a potent DNA tumor virus that induces tumors in rodents and transforms many types of cells in culture, including those of human origin. This virus has been a favored laboratory model for mechanistic studies of molecular processes in eukaryotic cells and of cellular transformation. The viral replication protein, named large T antigen (T-ag), is also the viral oncoprotein. There is a single serotype of SV40, but multiple strains of virus exist that are distinguishable by nucleotide differences in the regulatory region of the viral genome and in the part of the T-ag gene that encodes the protein's carboxyl terminus. Natural infections in monkeys by SV40 are usually benign but may become pathogenic in immunocompromised animals, and multiple tissues can be infected. SV40 can replicate in certain types of simian and human cells. SV40-neutralizing antibodies have been detected in individuals not exposed to contaminated polio vaccines. SV40 DNA has been identified in some normal human tissues, and there are accumulating reports of detection of SV40 DNA and/or T-ag in a variety of human tumors. This review presents aspects of replication and cell transformation by SV40 and considers their implications for human infections and disease pathogenesis by the virus. Critical assessment of virologic and epidemiologic data suggests a probable causative role for SV40 in certain human cancers, but additional studies are necessary to prove etiology.

Review↗

Human Plague Risk: Spatial-Temporal Models

This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

Pinzon, Jorge E.↗