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NASA NTRS2002

Radiation Effect on Human Tissue

Predicting the occurrence of human cancer following exposure of an epidemiologic population to any agent causing genetic damage is a difficult task. To an approximation, this is because the uncertainty of uniform exposure to the damaging agent, and the uncertainty of uniform processing of that damage within a complex set of biological variables, degrade the confidence of predicting the delayed expression of cancer as a relatively rare event within clinically normal individuals. This situation begs the need for alternate controlled experimental models that are predictive for the development of human cancer following exposures to agents causing genetic damage. Such models historically have not been of substantial proven value. It is more recently encouraging, however, that developments in molecular and cell biology have led to an expanded knowledge of human carcinogenesis, and of molecular markers associated with that process. It is therefore appropriate to consider new laboratory models developed to accomodate that expanded knowledge in order to assess the cancer risks associated with exposures to genotoxic agents. When ionizing radiation of space is the genotoxic agent, then a series of additional considerations for human cancer risk assessment must also be applied. These include the dose of radiation absorbed by tissue at different locations in the body, the quality of the absorbed radiation, the rate at which absorbed dose accumulates in tissue, the way in which absorbed dose is measured and calculated, and the alterations in incident radiation caused by shielding materials. It is clear that human cancer risk assessment for damage caused by ionizing radiation is a multidisciplinary responsibility, and that within this responsibility no single discipline can hold disproportionate sway if a risk assessment model of radiation-induced human cancer is to be developed that has proven value. Biomolecular and cellular markers from the work reported here are considered for use in assessing human cancer risk related to exposure to space radiation. This potential use must be integrated within the specified multidisciplinary context in order to create a new tool of molecular epidemiology that can hopefully then realistically assess this cancer risk.

Richmond, Robert C.↗

NASA NTRS2001

Space radiation and cataracts in astronauts

For over 30 years, astronauts in Earth orbit or on missions to the moon have been exposed to space radiation comprised of high-energy protons and heavy ions and secondary particles produced in collisions with spacecraft and tissue. Large uncertainties exist in the projection of risks of late effects from space radiation such as cancer and cataracts due to the paucity [corrected] of epidemiological data. Here we present epidemiological [corrected] data linking an increased risk of cataracts for astronauts with higher lens doses (>8 mSv) of space radiation relative to other astronauts with lower lens doses (<8 mSv). Our study uses historical data for cataract incidence in the 295 astronauts participating in NASA's Longitudinal Study of Astronaut Health (LSAH) and individual occupational radiation exposure data. These results, while preliminary because of the use of subjective scoring methods, suggest that relatively low doses of space radiation may predispose crew to [corrected] an increased incidence and early appearance of cataracts.

NASA Center JSC↗

NASA NTRS2004

Malaria Modeling using Remote Sensing and GIS Technologies

Malaria has been with the human race since the ancient time. In spite of the advances of biomedical research and the completion of genomic mapping of Plasmodium falciparum, the exact mechanisms of how the various strains of parasites evade the human immune system and how they have adapted and become resistant to multiple drugs remain elusive. Perhaps because of these reasons, effective vaccines against malaria are still not available. Worldwide, approximately one to three millions deaths are attributed to malaria annually. With the increased availability of remotely sensed data, researchers in medical entomology, epidemiology and ecology have started to associate environmental and ecological variables with malaria transmission. In several studies, it has been shown that transmission correlates well with certain environmental and ecological parameters, and that remote sensing can be used to measure these determinants. In a NASA project, we have taken a holistic approach to examine how remote sensing and GIs can contribute to vector and malaria controls. To gain a better understanding of the interactions among the possible promoting factors, we have been developing a habitat model, a transmission model, and a risk prediction model, all using remote sensing data as input. Our objectives are: 1) To identify the potential breeding sites of major vector species and the locations for larvicide and insecticide applications in order to reduce costs, lessen the chance of developing pesticide resistance, and minimize the damage to the environment; 2) To develop a malaria transmission model characterizing the interactions among hosts, vectors, parasites, landcover and environment in order to identify the key factors that sustain or intensify malaria transmission, and 3) To develop a risk model to predict the occurrence of malaria and its transmission intensity using epidemiological data and satellite-derived or ground-measured environmental and meteorological data.

Kiang, Richard↗

NASA NTRS2004

Historical Study of Radiation Exposures and the Incidence of Cataracts in Astronauts

For over 35 years, astronauts in low Earth orbit or on missions to the moon have been exposed to space radiation comprised of high-energy protons, heavy ions, and secondary neutrons. We reviewed the radiation exposures received by astronauts in space and on Earth, and presented results from the first epidemiological study of cataract incidence in the astronauts. Our data suggested an increased risk for cataracts from space radiation exposures. Using parametric survival analysis and the maximum likelihood method, we estimated the dose-response and age distribution for cataract incidence in astronauts by space radiation. Considering the high-LET dose contributions on specific space missions as well as data from animal studies with neutrons and heavy ions, suggested a linear response with no dose-threshold for cataracts. However, there are unanswered questions related to the importance and the definition of clinically significant cataracts commonly used in radiation protection, especially in light of epidemiological data suggesting that the probability that sub-clinical cataracts will progress is highly dependent on the age at which cataracts appear. We briefly describe a new study that will address the measurement of cataract progression-rates in astronauts and a ground-based comparison group.

Cucinotta, F. A.↗

NASA NTRS2004

Historical Study of Radiation Exposures and the Incidence of Cataracts in Astronauts

For over 35 years, astronauts in low Earth orbit or on missions to the moon have been exposed to space radiation comprised of high-energy protons, heavy ions, and secondary neutrons. We reviewed the radiation exposures received by astronauts in space and on Earth, and presented results from the first epidemiological study of cataract incidence in the astronauts. Our data suggested an increased risk for cataracts from space radiation exposures*. Using parametric survival analysis and the maximum likelihood method, we estimated the dose-response and age distribution for cataract incidence in astronauts by space radiation. Considering the high-LET dose contributions on specific space missions as well as data from animal studies with neutrons and heavy ions, suggested a linear response with no dose-threshold for cataracts. However, there are unanswered questions related to the importance and the definition of "clinically significant" cataracts commonly used in radiation protection, especially in light of epidemiological data suggesting that the probability that "sub-clinical" cataracts will progress is highly dependent on the age at which cataracts appear. We briefly describe a new study that will address the measurement of cataract progression-rates in astronauts and a ground-based comparison group.

Cucinotta, F. A.↗

NASA NTRS2007

The Application of NASA Technology to Public Health

NASA scientists have a history of applying technologies created to handle satellite data to human health at various spatial scales. Scientists are now engaged in multiple public health application projects that integrate NASA satellite data with measures of public health. Such integration requires overcoming disparities between the environmental and the health data. Ground based sensors, satellite imagery, model outputs and other environmental sources have inconsistent spatial and temporal distributions. The MSFC team has recognized the approach used by environmental scientists to fill in the empty places can also be applied to outcomes, exposures and similar data. A revisit to the classic epidemiology study of 1854 using modern day surface modeling and GIS technology, demonstrates how spatial technology can enhance and change the future of environmental epidemiology. Thus, NASA brings to public health, not just a set of data, but an innovative way of thinking about the data.

Rickman, Douglas L.↗

NASA NTRS2007

Modeling Malaria Transmission in Thailand and Indonesia

Malaria Modeling and Surveillance is a project in the NASA Applied Sciences Public Health Applications Program. The main objectives of this project are: 1) identification of the potential breeding sites for major vector species: 2) implementation of a malaria transmission model to identify they key factors that sustain or intensify malaria transmission; and 3) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity. Remote sensing and GIs are the essential elements of this project. The NASA Earth science data sets used in this project include AVHRR Pathfinder, TRMM, MODIS, NSIPP and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of precipitation, temperatures, humidity and vegetation. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Examples for spatio-temporal modeling of malaria transmissions in Southeast Asia are given. Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to Southeast Asia. The model and techniques are equally applicable to other regions of the world, when appropriate epidemiological and vector ecological parameters are used as input.

Kiang, Richard↗

NASA NTRS2008

Space Adaptation Back Pain: A Retrospective Study

Back pain is frequently reported by astronauts during the early phase of space flight as they adapt to the microgravity environment. However, the epidemiology of space adaptation back pain has not been well defined. The purpose of this retrospective study was to develop a case definition of space adaptation back pain, determine the incidence of space adaptation back pain, and determine the effectiveness of available treatments. Medical records from the Mercury, Apollo, Apollo-Soyuz Test Project (ASTP), Skylab, Mir, International Space Station (ISS), and Shuttle programs were reviewed. All episodes of in-flight back pain that met the criteria for space adaptation back pain were recorded. Pain characteristics, including intensity, location, and duration of the pain were noted. The effectiveness of specific treatments also was recorded. The incidence of space adaptation back pain among astronauts was determined to be 53% (384/722). Most of the affected astronauts reported mild pain (85%). Moderate pain was reported by 11% of the affected astronauts and severe pain was reported by only 4% of the affected astronauts. The most effective treatments were fetal positioning (91% effective) and the use of analgesic medications (85% effective). This retrospective study aids in the development of a case definition of space adaptation back pain and examines the epidemiology of space adaptation back pain. Space adaptation back pain is usually mild and self-limited. However, there is a risk of functional impairment and mission impact in cases of moderate or severe pain that do not respond to currently available treatments. Therefore, the development of preventive measures and more effective treatments should be pursued.

Kerstman, E. L.↗

NASA NTRS2012

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model1 reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties--2010 . The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables. The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements. However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors, transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Source record↗

NASA NTRS2012

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties 2010 (Cucinotta et al., 2011). The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables cited more formally as Cucinotta et al. (2011). The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. They include, more recently: (1) The "BEIR VII Phase 2" report from the NRC's Committee on Biological Effects of Ionizing Radiation (BEIR) (NRC, 2006); (2) Studies of Radiation and Cancer from the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR, 2006), (3) The 2007 Recommendations of the International Commission on Radiological Protection (ICRP), ICRP Publication 103 (ICRP, 2007); and (4) The Environmental Protection Agency s (EPA s) report EPA Radiogenic Cancer Risk Models and Projections for the U.S. Population (EPA, 2011). The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements (NCRP, 2000, 2006). However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors (Preston et al., 2007), transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Source record↗

NASA NTRS2012

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

The overall goal of this study is to address issues of environmental health and enhance public health decision making by using NASA remotely sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) Office of Surveillance, Epidemiology and Laboratory Services. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the environmental data sets and associated public health analyses to local, state and federal end ]user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) on a 10-km grid using US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of MODIS Land Surface Temperature (LST); and (3) a 12-km grid of daily incoming solar radiation and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline, stroke and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county-level, state-level, or regional-level as per users f need and downloaded in tabular, graphical, and map formats. This provides a significant addition to the CDC WONDER online system, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER. It also substantially expands public access to NASA data, making their use by a wide range of decisionmakers feasible.

Al-Hamdan, Mohammad↗

NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗

NASA NTRS2015

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↗

NASA NTRSDate not supplied

A Thermodynamic Paradigm for Studying Disease Vector’s Habitats & Life Cycles Using NASA’s NextGen Remote Sensing Instruments

Global public health is entering a new informational age through the use of spatial models of disease vector/host ecologies driven by the use of remotely sensed data to measure environmental and structural factors critical in determining disease vector habitats, distributions, life cycles, and host interactions. The vector habitat microclimates can be quantified in terms of the surface energy budget measured by satellites. The epidemiological equations (processes) can be adapted and modified to explicitly incorporate environmental factors and interfaces required by a specific disease and its vector/host cycle. Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions). Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions) defining vector habitats. The products of remote sensing can be integrated directly into the epidemiological equations to significantly enhance our understanding of disease vector’s life cycles and habitats. The next generation of NASA’s remote sensing instruments recently operational will provide a significant enhancement in our ability to study disease vector’s life cycles and habitats. Three new instruments have become operational on the International Space Station (ISS) In June 2018, ECOSTRESS (The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station), a five channel, thermal IR instrument with 70 m resolution and approximately 4-5 day repeat cycle of day/night pairs along with DESISa hyperspectral sensor system 235 channels (between 400 and 1000 nanometers), 30 m resolution, and data only being acquired on demand. In November 2018. GEDI (Global Ecosystem Dynamics Investigation). GEDI is a high-resolution laser ranging of Earth’s forests and topography. These instruments set the stage for NASA’s new global designated observables set of remote sensing measurements collecting hyperspectral and multispectral thermal data called SBG (Surface Biology Geology). The SBG is currently in the planning stage. The availability and use of level 1-4 data products generated from these ISS instruments will be discussed.

thermodynamics↗

NASA NTRS2020

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗

NASA NTRSDate not supplied

Linking Individual Variation in Movement Behavior to Infection Dynamics in Highly Mobile Species

Animal movements are linked to infectious disease dynamics in wildlife through multiple mechanisms across various spatial and temporal scales. For example, infections can impede the movement of infected individuals, but infected hosts can also disperse infectious agents as they move. Individuals inevitably vary in their responses to infections and their roles in determining infection dynamics, which means that considering variation among individuals – whether across species, across time, or within populations – is important for understanding movement-disease relationships and their implications for epidemiology. Here, I draw on studies from multiple systems to examine how variation in movement behavior links to infectious disease epidemiology. For example, a comparative study of habitat selection across multiple waterfowl species highlights that diel behavioral patterns, rather than individual or seasonal variation, is the most important driver of the risk of overlap between waterfowl and poultry farms, and therefore for the risk of avian influenza spillover. Together, these studies show that individual traits interact with the environment to influence the roles of individuals for infectious disease ecology.

Claire Stewart Teitelbaum↗

NASA NTRS2024

Premature Deaths Due to Heat Exposure: the Potential Effects of Neighborhood-Level Versus City-Level Acclimatization Within Us Cities

For the population of a given US city, the risk of premature death associated with heat exposure increases as temperatures rise, but risks in hotter cities are generally lower than in cooler cities at equivalent temperatures due to factors such as acclimatization. Those living in especially hot neighborhoods within cities might therefore suffer much more than average if such adaptation is only at the city-wide level, whereas they might not experience greatly increased risk if adjustment is at the neighborhood level. To compare these possibilities, we use high spatial resolution temperature data to evaluated heat-related deaths assuming either adjustment at the city-wide or at the neighborhood scale in 10 large US cities. On average, we find that if inhabitants are adjusted to their local conditions, a neighborhood that was 10°C hotter than a cooler one would experience only about 1.0–1.5 excess heat deaths per year per 100,000 persons. By contrast, if inhabitants are acclimatized to city-wide temperatures, the hotter neighborhood would experience about 15 excess deaths per year per 100,000 persons. Using idealized analyses, we demonstrate that current city-wide epidemiological data do not differentiate between these differing adjustments. Given the very large effects of assumptions about neighborhood-level acclimatization found here, as well as the fact that current literature is conflicting on the spatial scale of acclimatization, more neighborhood-level epidemiological data are urgently needed to determine the health impacts of variations in heat exposure within urban areas, better constrain projected changes, and inform mitigation efforts.

heat island↗

NASA NTRSDate not supplied

Long-Term Health Risk Quantification

Astronauts face hazards during spaceflight, including space radiation exposure, isolation and confinement, traveling far distances from Earth, reduced gravity levels, and closed and hostile environments. These hazards drive the definition of human health and performance risks associated with spaceflight. NASA’s Human System Risk Board maintains the human spaceflight risk posture for in-mission risks, as well as post-flight, Long-Term Health (LTH)risks potentially occurring later in the astronaut’s life. LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. Possible LTH risk outcomes include the time and interventions needed for the astronaut to return to preflight physiological states after experiencing spaceflight hazards and recovery from any in-mission medical events that persist into the post-flight timeframe. It includes chronic complications that may arise due to experiencing in-flight medical conditions or injuries and medical conditions that occur later in life with a higher probability of occurrence or with more severity because of their spaceflight exposure. Finally, LTH risk outcomes can also include a reduction in life expectancy due to spaceflight exposures. There have been 144 medical conditions identified by NASA’s Lifetime Surveillance of Astronaut Health team to be associated with LTH risk. Epidemiological studies have been performed for some of these conditions to determine if astronauts suffer from an increased prevalence or severity of the condition due to their spaceflight experience compared to a comparable cohort .Differences in astronaut mortality or morbidity due to spaceflight experience were not detected in several of these studies. There were two cases where a modest increase in the incidence rate of astronaut LTH outcomes was detected. The first suggested an increase in the incidence of melanoma cases in astronauts, where the number of cases in astronauts were similar to the elevated number of cases observed in airplane pilots. The second provided some evidence of elevated numbers of cardiovascular disease events in astronauts compared to an appropriate healthy comparator cohort, which may warrant additional investigation. The lack of detection of LTH risk outcomes should not ease concerns about astronaut LTH. The studies highlighted here constitute only a small portion of the potential LTH conditions that could occur. Once epidemiological studies are performed on all conditions, significant findings may be detected. The analysis of astronaut LTH also suffers from limited numbers of data points because of the limited numbers of astronauts overall and the even fewer who have reached an age where LTH outcomes may begin to manifest. As shuttle and ISS astronauts begin to age and increase the feasibility of analysis, LTH outcomes may be detected. An application of risk quantification is the use of risk metrics within trade studies for resource prioritization and decision making. Trade studies regarding countermeasures to LTH risk outcomes would benefit from a quantification of LTH risk. NASA has ground-based processes in place such as astronaut screening and access to continuous medical monitoring and care during and after their astronaut career which are the main methods for mitigating LTH risk. In-mission countermeasures, such as acceptable levels of medical care and available countermeasures to counter spaceflight related physiological decrements, can mitigate a poor health and performance status immediately post-flight. Identifying appropriate risk metrics, obtaining valid quantities for them, and tying them to LTH countermeasures are necessary steps for realizing their use in trade studies. This presentation will highlight the challenges associated with the identification, quantification, and utilization of LTH risk metrics

Beth Lewandowski↗