Search NASA⌕ Search

SEARCH · Search NASA

Results for “population surveillance”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Genomic analysis of Klebsiella aerogenes circulating in New Mexico

Klebsiella aerogenes is an opportunistic pathogen and a growing cause of healthcare-associated infections, characterized by multidrug resistance and the emergence of global high-risk clones. However, regional genomic surveillance data remain limited. Here, we sought to characterize the population structure, transmission dynamics and resistance mechanisms of clinical K. aerogenes in Albuquerque, New Mexico. We sequenced 177 clinical isolates collected between 2021 and 2023. We also developed a novel, species-specific PopPUNK database to facilitate rapid, high-resolution typing. The New Mexico K. aerogenes population was diverse but dominated by two global pandemic lineages, ST93 (47.5%) and ST4 (7.9%), which were significantly enriched for the virulence factors yersiniabactin and colibactin. Genomic evidence for recent local transmission was rare, with only four putative transmission pairs identified. The resistome was characterized by intrinsic and adaptive mutations. Nearly all isolates possessed gyrA mutations associated with decreased fluoroquinolone susceptibility. Mutations in the AmpC regulator AmpD and the outer membrane porin Omp36 were common, particularly within the dominant ST93 lineage. These mutations have been associated with increased AmpC-mediated carbapenem resistance. Our findings underscore the critical importance of genomic surveillance to monitor the transmission and evolution of adaptive resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluation of a parasite-density based pooled targeted amplicon deep sequencing (TADS) method for molecular surveillance of Plasmodium falciparum drug resistance genes in Haiti

Sequencing large numbers of individual samples is often needed for countrywide antimalarial drug resistance surveillance. Pooling DNA from several individual samples is an alternative cost and time saving approach for providing allele frequency (AF) estimates at a population level. Using 100 individual patient DNA samples of dried blood spots from a 2017 nationwide drug resistance surveillance study in Haiti, we compared codon coverage of drug resistance-conferring mutations in four Plasmodium falciparum genes ( crt , dhps , dhfr , and mdr1 ), for the same deep sequenced samples run individually and pooled. Samples with similar real-time PCR cycle threshold (Ct) values (+/- 1.0 Ct value) were combined with ten samples per pool. The sequencing success for samples in pools were higher at a lower parasite density than the individual samples sequence method. The median codon coverage for drug resistance-associated mutations in all four genes were greater than 3-fold higher in the pooled samples than in individual samples. The overall codon coverage distribution for pooled samples was wider than the individual samples. The sample pools with < 40 parasites/μL blood showed more discordance in AF calls for dhfr and mdr1 between the individual and pooled samples. This discordance in AF estimation may be due to low amounts of parasite DNA, which could lead to variable PCR amplification efficiencies. Grouping samples with an estimated ≥ 40 parasites/μL blood prior to pooling and deep sequencing yielded the expected population level AF. Pooling DNA samples based on estimates of > 40 parasites/μL prior to deep sequencing can be used for rapid genotyping of a large number of samples for these four genes and possibly other drug resistant markers in population-based studies. As Haiti is a low malaria transmission country with very few mixed infections and continued chloroquine sensitivity, the pooled sequencing approach can be used for routine national molecular surveillance of resistant parasites.

Louha, Swarnali (ORCID:0000000207778507)↗
NASA NTRS2018

An Implementation Analysis of Communications, Navigation, and Surveillance (CNS) Technologies for Unmanned Air Systems (UAS)

The aviation industry and government agencies face a rapidly-emerging need for integrating large-scale populations of Unmanned Air Systems (UAS) into the worldwide controlled and uncontrolled airspace. Critical components for integration include the Communications, Navigation, and Surveillance (CNS) technologies necessary for ensuring safe UAS operations. Under NASA program NNA16BD84C, our work on CNS architectural concepts for the safe operation of UAS in controlled and uncontrolled airspace has introduced CNS architectures which must be analyzed in terms of implementation readiness.Controlled airspace operations for UAS are consistent with the needs for manned aviation in the worldwide Air Traffic Management (ATM) service. Uncontrolled airspace operations are consistent with the NASA Unmanned (air) Traffic Management (UTM) concept of operations. Implementation readiness is based on the NASA concept of Technology Readiness Levels (TRLs) ranging from TRL1 (basic principles observed and reported) to TRL9 (actual system flight proven through successful mission operations). In the architecture concepts, we have introduced a number of new CNS architectural elements which need to be correlated with TRL levels. In this paper, we present our implementation analysis for communications networks, communications data links, navigation, and surveillance. Each area has been under active research and development during the course of the current NASA program which has produced studies on UAS CNS Requirements, UAS CNS Architecture for Controlled Airspace and UAS CNS Architecture for Uncontrolled Airspace. We have published our architecture concepts in major UAS-related conferences (including iCNS2017, IEEE Aerospace 2018, and iCNS2018) and will continue to seek additional publication opportunities. We look forward to continuing our work to realize a full integration testing scenario for both controlled and uncontrolled airspace operation.

Unmanned (Air) Traffic Management (UTM) service↗
NASA NTRS2018

An Implementation Analysis of Communications, Navigation, and Surveillance (CNS) Technologies for Unmanned Air Systems (UAS)

The aviation industry and government agencies face a rapidly-emerging need for integrating large-scale populations of Unmanned Air Systems (UAS) into the worldwide controlled and uncontrolled airspace. Critical components for integration include the Communications, Navigation, and Surveillance (CNS) technologies necessary for ensuring safe UAS operations. Under NASA program NNA16BD84C, our work on CNS architectural concepts for the safe operation of UAS in controlled and uncontrolled airspace has introduced CNS architectures which must be analyzed in terms of implementation readiness.Controlled airspace operations for UAS are consistent with the needs for manned aviation in the worldwide Air Traffic Management (ATM) service. Uncontrolled airspace operations are consistent with the NASA Unmanned (air) Traffic Management (UTM) concept of operations. Implementation readiness is based on the NASA concept of Technology Readiness Levels (TRLs) ranging from TRL1 (basic principles observed and reported) to TRL9 (actual system flight proven through successful mission operations). In the architecture concepts, we have introduced a number of new CNS architectural elements which need to be correlated with TRL levels.In this paper, we present our implementation analysis for communications networks, communications data links, navigation, and surveillance. Each area has been under active research and development during the course of the current NASA program which has produced studies on UAS CNS Requirements, UAS CNS Architecture for Controlled Airspace and UAS CNS Architecture for Uncontrolled Airspace. We have published our architecture concepts in major UAS-related conferences (including iCNS2017, IEEE Aerospace 2018, and iCNS2018) and will continue to seek additional publication opportunities. We look forward to continuing our work to realize a full integration testing scenario for both controlled and uncontrolled airspace operation.

Ponchak, Denise↗
DOE OSTI2023

Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples

The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Early prediction of antigenic transitions for influenza A/H3N2

Influenza A/H3N2 is a rapidly evolving virus which experiences major antigenic transitions every two to eight years. Anticipating the timing and outcome of transitions is critical to developing effective seasonal influenza vaccines. Using a published phylodynamic model of influenza transmission, we identified indicators of future evolutionary success for an emerging antigenic cluster and quantified fundamental trade-offs in our ability to make such predictions. The eventual fate of a new cluster depends on its initial epidemiological growth rate––which is a function of mutational load and population susceptibility to the cluster––along with the variance in growth rate across co-circulating viruses. Logistic regression can predict whether a cluster at 5% relative frequency will eventually succeed with ~80% sensitivity, providing up to eight months advance warning. As a cluster expands, the predictions improve while the lead-time for vaccine development and other interventions decreases. However, attempts to make comparable predictions from 12 years of empirical influenza surveillance data, which are far sparser and more coarse-grained, achieve only 56% sensitivity. By expanding influenza surveillance to obtain more granular estimates of the frequencies of and population-wide susceptibility to emerging viruses, we can better anticipate major antigenic transitions. This provides added incentives for accelerating the vaccine production cycle to reduce the lead time required for strain selection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Orbital Debris Research at NASA

The United States has one of the most active programs of research of the orbital debris environment in the world. Much of the research is conducted by NASA s Orbital Debris Program Office at the Johnson Space Center. Past work by NASA has led to the development of national space policy which seeks to limit the growth of the debris population and limit the risk to spacecraft and humans in space and on the Earth from debris. NASA has also been instrumental in developing consistent international policies and standards. Much of NASA's efforts have been to measure and characterize the orbital debris population. The U.S. Department of Defense tracks and catalogs spacecraft and large debris with it's Space Surveillance Network while NASA concentrates on research on smaller debris. In low Earth orbit, NASA has utilized short wavelength radars such as Haystack, HAX, and Goldstone to statistically characterize the population in number, size, altitude, and inclination. For higher orbits, optical telescopes have been used. Much effort has gone into the understanding and removal of observational biases from both types of measurements. NASA is also striving to understand the material composition and shape characteristics of debris to assess these effects on the risk to operational spacecraft. All of these measurements along with data from ground tests provide the basis for near- and long-term modeling of the environment. NASA also develops tools used by spacecraft builders and operators to evaluate spacecraft and mission designs to assess compliance with debris standards and policies which limit the growth of the debris environment.

Stansbery, Eugene G.↗
DOE OSTI2023

Differential contagiousness of respiratory disease across the United States

The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, $R_0$. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific $R_0$ values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for $R_0$ range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1980

A continuation of base-line studies for environmentally monitoring Space Transportation Systems (STS) at John F. Kennedy Space Center. Volume 4: Threatened and endangered species of the Kennedy Space Center. Part 1: Marine turtle studies

The status of marine turtle populations in the KSC area was studied using data from previous results from ground and aerial surveillance conducted from 1976 to April 1979. During ground surveillance, various data were recorded on emergent turtles such as: species, weight, tag number (if previously tagged), time discovered, activity at discovery and the location of discovery. Observations were also made on nesting and reproductive characteristics, population estimates, immigration and emigration and growth rate of the turtles. Mortality studies were additionally made and autopsies performed on dead turtles found in the area. It is concluded that further mortality documentation should be done just prior to and just after a future space launch operation in order to accurately assess the cause and effect relationship of such a launch on the turtle population.

Ehrhart, L. M.↗
NASA NTRS2017

Protecting the Health of Astronauts: Enhancing Occupational Health Monitoring and Surveillance for Former NASA Astronauts to Understand Long-Term Outcomes of Spaceflight-Related Exposures

The astronaut community is unique, and may be disproportionately exposed to occupational hazards not commonly seen in other communities. The extent to which the demands of the astronaut occupation and exposure to spaceflight-related hazards affect the health of the astronaut population over the life course is not completely known. A better understanding of the individual, population, and mission impacts of astronaut occupational exposures is critical to providing clinical care, targeting occupational surveillance efforts, and planning for future space exploration. The ability to characterize the risk of latent health conditions is a significant component of this understanding. Provision of health screening services to active and former astronauts ensures individual, mission, and community health and safety. Currently, the NASA-Johnson Space Center (JSC) Flight Medicine Clinic (FMC) provides extensive medical monitoring to active astronauts throughout their careers. Upon retirement, astronauts may voluntarily return to the JSC FMC for an annual preventive exam. However, current retiree monitoring includes only selected screening tests, representing an opportunity for augmentation. The potential long-term health effects of spaceflight demand an expanded framework of testing for former astronauts. The need is two-fold: screening tests widely recommended for other aging populations are necessary to rule out conditions resulting from the natural aging process (e.g., colonoscopy, mammography); and expanded monitoring will increase NASA's ability to better characterize conditions resulting from astronaut occupational exposures. To meet this need, NASA has begun an extensive exploration of the overall approach, cost, and policy implications of e an Astronaut Occupational Health program to include expanded medical monitoring of former NASA astronauts. Increasing the breadth of monitoring services will ultimately enrich the existing evidence base of occupational health risks to astronauts. Such an expansion would therefore improve the understanding of the health of the astronaut population as a whole, and the ability to identify, mitigate, and manage such risks in preparation for deep space exploration missions.

Rossi, Meredith↗
DOE OSTI2020

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets. Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Determination of the Risk of Radiation-Associated Circulatory and Cancer Disease Mortality in a NASA Early Astronaut Cohort

Of the many possible health challenges posed during extended exploratory missions to space, the effects of space radiation on cardiovascular disease and cancer are of particular concern. There are unique challenges to estimating those radiation risks; care and appropriate and rigorous methodology should be applied when considering small cohorts such as the NASA astronaut population. The objective of this work was to determine if there was sufficient evidence for excess risk of cardiovascular disease and cancer in early NASA astronaut cohorts. NASA astronauts in selection groups 1-7 were chosen; this relatively homogeneous cohort consists of 73 white males, who unlike today's astronauts, maintained similar smoking and drinking habits to the general US population, and have published radiation doses. The participants flew in space on missions Mercury through Shuttle and received space radiation doses between 0-74.1 milligrays. Cause of death information was obtained from the Lifetime Surveillance of Astronaut Health (LSAH) program at NASA Johnson Space Center. Mortality was compared with the US male population. Trends of mortality with dose were assessed using a logistic model, fitted by maximum likelihood. Only 32 (43.84 percent) of the 73 early astronauts have died. Standard mortality ratios (SMRs) for cancer (n=7, SMR=43.4, 95 percent CI 17.8, 84.9), all circulatory disease (n=7, SMR=33.2, 95 percent CI 13.7, 65.0), and ischemic heart disease (IHD) (n=5, SMR=40.1, 95 percent CI 13.2, 89.4) were significantly lower than for the US white male population. For cerebrovascular disease, the upper confidence interval for SMR included 100, indicating it was not significantly different from the US population (n=2, SMR = 77.0, 95 percent CI 9.4, 268.2). The power of the study is low and remains below 10 percent even when risks 10 times those reported in the literature are assumed. Due to small sample size, there is currently insufficient statistical power to evaluate space radiation exposure effects on mortality in NASA astronauts. In addition to a comprehensive longitudinal study of NASA astronauts, a research strategy of low dose epidemiology data integration with cell and animal studies should be utilized for space radiation risk assessment in the astronauts.

Elgart, S. R.↗
NASA NTRS1991

NAVSPASUR orbital processing for satellite break-up events

Satellite breakups via explosion or collision can instantly increase the trackable orbiting population by up to several hundred objects, temporarily perturbing the routine space surveillance operations at U.S. Space Command (USSPACWCOM) and the Naval Space Surveillance Center (NAVSPASUR). This paper is a survey of some of the procedures and techniques used by NAVSPASUR to respond to such events. First, the overall data flow at NAVSPASUR is described highlighting the places at which human analysts may intervene with special processing. So-called manual intervention is required in a variety of non-nominal situations, including breakups. Second, a description is given of some of the orbital analysis and other software tools available to NAVSPASUR analysts. These tools were developed in-house over the past thirty years and can be employed in a highly flexible manner. The basic design philosophy for these tools was to implement simple concepts as efficiently as possible and to allow the analyst maximum use of his personal expertise. Finally, several historical breakup scenarios are discussed briefly. These scenarios provide examples of the types of questions that are fairly easy to answer in the present operational environment, as well as examples of questions that are very difficult to answer.

Schumacher, Paul W., Jr.↗
NASA NTRS2000

Updating the NASA LEO Orbital Debris Environment Model with Recent Radar and Optical Observations and in Situ Measurements

The Low Earth Orbit (LEO, between 200 and 2000 km altitudes) debris environment has been constantly measured by NASA Johnson Space Center's Liquid Mirror Telescope (LMT) since 1996 (Africano et al. 1999, NASA JSC-28826) and by Haystack and Haystack Auxiliary radars at MIT Lincoln Laboratory since 1990 (Settecerri et al. 1999, NASA JSC-28744). Debris particles as small as 3 mm can be detected by the radars and as small as 3 cm can be measured by LMT. Objects about 10 cm in diameter and greater are tracked and catalogued by the US Space Surveillance Network. Much smaller (down to several micrometers) natural and debris particle populations can be estimated based on in situ measurements, such as Long Duration Exposure Facility, and based on analyses of returned surfaces, such as Hubble Space Telescope solar arrays, European Retrievable Carrier, and Space Shuttles. To increase our understanding of the current LEO debris environment, the Orbital Debris Program Office at NASA JSC has initiated an effort to improve and update the ORDEM96 model (Kessler et al. 1996, NASA TM-104825) utilizing the recently available data. This paper gives an overview of the new NASA orbital debris engineering model, ORDEM2000.

Liou, J.-C.↗
DOE OSTI2026

Criteria for Retention of 3013 S1 Containers Based on Relative Risk and Expert Judgment

An evaluation was performed to assess the suitability of thirty-three 3013 containers proposed for retention. These containers have moisture levels greater than 0.08 wt.% – the S1 population. The remainder of the S1 population stored at SRS will be down blended and disposed of by the end of 2028. Based on field surveillance and shelf-life data available to date as well as informed technical judgment, no container is currently expected to fail in its 50-year storage period. However, corrosion risk varies across the S1 population. Relative risks were evaluated using predicted Consensus Scores and their 95% Upper Prediction Limits (UPLs). The predicted values are based on a statistical model of Consensus Score as a function of moisture, chloride, and whether the packaged material was electrorefining scrap packaged at Hanford. Consensus Score has been shown to be a useful indicator of corrosion potential, and the UPL captures uncertainty in the model predictions, providing a conservative indicator of corrosion potential. Using UPLs to determine relative risks, together with expert review, three containers were identified as not suitable for retention, and the remainder were determined to be suitable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Watching Without Seeing a Tool to Surveil Astronaut Health Outcomes While Maintaining Astronaut Medical Privacy

BACKGROUND The Privacy Act of 1974 regulates the use a nd disclosure of personally identifiable information by US Federal agencies. The Act applies to biographical, financial, a nd other identity-linked information, a s well a s personal health information (PHI). As such, the use of astronaut PHI is limited to authorized personnel for preapproved uses, with data reporting often limited to aggregated information about groups. These limitations on the use a nd reporting of astronaut PHI complicates surveillance efforts, wherein epidemiologists a t the National Aeronautics and Space Administration (NASA)monitor the incidence of targeted health conditions in the astronaut population, or to discover emerging trends of aging and disease. Stratification on one or more covariates –particularly time-period, sex, a nd mission participation –can lead to extremely small datasets such that the reporting of results is potentially attributable to individuals. An additional challenge is the small size of the astronaut population, both in terms of numbers of individuals a s well a s in terms of density of exposure time. Such small datasets yield volatile rate estimates that are difficult to interpret. To a id the epidemiological surveillance efforts, a surveillance tool is required that can (a) satisfy the need for rapid computation of condition-specific incidence and mortality rates; (b) improve the statistical estimates of these estimated rates; and (c) maintain astronaut privacy. Here we describe a nd demonstrate such a tool. METHODS We devised a system that models incidence a nd mortality rates rather than calculating them directly. This ha s the advantage of using all the available data to derive the estimates, lea ding to rates that a re not attributable to any one individual, a nd a re a s numerically stable a s they can be given the extremely limited data. The system models disease endpoints using a Poisson regression model with exposure density (measured in person-years) a s a n offset term. By doing so the model is estimating event counts per person-year, equivalent to modeling the rates directly. It uses a standard (pre-specified)set of covariates; the system does not engage in “model-building” as model parsimony is not the goa l. Instead, it is explicitly recognized that if a covariate is not statistically significant a nd not a confounder then it will likely have very little effect on the estimate of the incidence a nd mortality rates. Users are able to specify the disease endpoint of interest and the covariates over which they would like to stratify. The system then uses the resulting model to compute the estimated rates for the user-chosen configuration of variables as visualizes those either over an age range within a specified time-period, or over time for astronauts with a specified age range. RESULTS The first iteration of the tool computes incidence a nd mortality rates for cardiovascular conditions and cancers. Code ha s been developed to retrieve the appropriate data from the IMPALA analysis platform, compute the models for incidence a nd mortality, a nd then use those models to generate the corresponding rate curves. A companion graphical user interface allows the user to specify the curves and visualize the results. CONCLUSIONS It is important to note that the rapid surveillance tool described here is neither meant to be a definitive assessment of the incidence or mortality of any particular disease or condition in the astronaut population, nor is it meant to be used for research purposes. Rather, it is meant as an early indicator that in-depth investigation may be warranted. By automating a repetitive process and leveraging carefully curated astronaut health outcomes, the tool makes possible a rapid “first look” into known areas of concern, and, if used judiciously, may surface new areas of concern for long-term astronaut health. This work is supported in part by the Translational Research Institute for Space Health (TRISH) through NASA Cooperative Agreement NNX16AO69A.

R J Reynolds↗
DOE OSTI2020

Google Health Trends performance reflecting dengue incidence for the Brazilian states

Abstract Background Dengue fever is a mosquito-borne infection transmitted by Aedes aegypti and mainly found in tropical and subtropical regions worldwide. Since its re-introduction in 1986, Brazil has become a hotspot for dengue and has experienced yearly epidemics. As a notifiable infectious disease, Brazil uses a passive epidemiological surveillance system to collect and report cases; however, dengue burden is underestimated. Thus, Internet data streams may complement surveillance activities by providing real-time information in the face of reporting lags. Methods We analyzed 19 terms related to dengue using Google Health Trends (GHT), a free-Internet data-source, and compared it with weekly dengue incidence between 2011 to 2016. We correlated GHT data with dengue incidence at the national and state-level for Brazil while using the adjusted R squared statistic as primary outcome measure (0/1). We used survey data on Internet access and variables from the official census of 2010 to identify where GHT could be useful in tracking dengue dynamics. Finally, we used a standardized volatility index on dengue incidence and developed models with different variables with the same objective. Results From the 19 terms explored with GHT, only seven were able to consistently track dengue. From the 27 states, only 12 reported an adjusted R squared higher than 0.8; these states were distributed mainly in the Northeast, Southeast, and South of Brazil. The usefulness of GHT was explained by the logarithm of the number of Internet users in the last 3 months, the total population per state, and the standardized volatility index. Conclusions The potential contribution of GHT in complementing traditional established surveillance strategies should be analyzed in the context of geographical resolutions smaller than countries. For Brazil, GHT implementation should be analyzed in a case-by-case basis. State variables including total population, Internet usage in the last 3 months, and the standardized volatility index could serve as indicators determining when GHT could complement dengue state level surveillance in other countries.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2024

A Specialized Ultrasound Protocol for NASA's Renal Stone Surveillance and Clinical Practice

INTRODUCTION Ample evidence exists on the effectiveness of ultrasound in the diagnosis of kidney stones. However, terrestrial practice is mostly concerned with diagnosis of clinically significant urolithiasis. Adapting this non-irradiating, low-cost imaging modality for the asymptomatic astronaut population offers high-sensitivity screening and limits their career radiation dose. METHODS NASA developed a novel ultrasound-based detection and surveillance protocol to identify, categorize, and monitor mineralized renal material (MRM) in astronauts. The term MRM was developed to denote abnormal, presumably calcified, focal material of unknown clinical significance in the kidneys. Sonographic criteria for MRMs include measurable echogenic foci, their detectability in multiple, designated imaging plains, posterior shadowing, and “twinkle” pattern visualized in Color Doppler and/or demonstrated in Spectral Doppler modes. The mere discovery of an MRM does not trigger further imaging or intervention, unless the affected crewmember is mission-assigned, or the MRM meets actionable criteria based on size, location, and sonographic characteristics. If the threshold is met, the crew surgeon is notified, and additional diagnostic imaging and urology consultation are considered. RESULTS In total, 73 individuals have been scanned using our specialized methods, 60 have had more than one study done. As of April 2023, 282 total studies have been performed. So far, over 30 pairs of pre-and postflight studies have been obtained, and the findings are presented elsewhere in this panel. DISCUSSION A surveillance program was initiated nine years ago to screen asymptomatic members of the astronaut corps for renal calcifications, from their initial hiring, through their mission timeframes, and throughout their career. The goal is to reduce the probability that an astronaut will fly with a renal stone that may become symptomatic. This also gives NASA the information it needs to improve screening criteria for future long-duration crewed missions.

H Lyons↗