Leveraging Earth Observations and Health Data to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention
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Ellen Delgado Florian↗
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The Public Health Service guidelines. Governing research involving human subjects: An analysis of the policy-making process
The policy making process which led to development of the Public Health Service Guidelines governing research involving human subjects is outlined. Part 1 examines the evolution of PHS Guidelines, tracing (1) evolution of thought and legal interpretation regarding research using human subjects; (2) initial involvement of the Federal government; (3) development of the government's research program; (4) the social-political environment in which formal government policy was developed; and (5) various policy statements issued by the government. Part 2 analyzes the process by which PHS Guidelines were developed and examines the values and other underlying factors which contributed to their development. It was concluded that the evolution of the Guidelines is best understood within the context of a mixed-scanning strategy. In such a strategy, policy makers make fundamental decisions regarding the basic direction of policy and subsequent decisions are made incrementally and within the contexts set by the original fundamental decisions.
Frankel, M. S.↗
Public health applications of remote sensing of vector borne and parasitic diseases
Results of an investigation of the potential application of remote sensing to various fields of public health are presented. Specific topics discussed include: detection of snail habitats in connection with the epidemiology of schistosomiasis; the detection of certain Anopheles breeding sites, and location of transient human populations, both in connection with malaria eradication programs; and detection of overwintering population sites for the primary screwworm (Cochliomyia americana). Emphasis was placed on the determination of ground truth data on the biological, chemical, and physical characteristics of ground waters which would or would not support the growth of significant populations of mosquitoes.
Source record↗
Synthetic TEMPO Data Products at NASA SPoRT for Air Quality and Public Health Communities
Synthetic TEMPO (Tropospheric Emissions: Monitoring of Pollution) Data Products at NASA SPoRT (Short-term Prediction Research and Transition Center) for Air Quality and Public Health Communities. O2R/R2O (Operation-to-Research/Research-to-Operation).
Naeger, Aaron↗
Urban Sustainability and Public Health: Throwing the Bath Water Out and Not the Baby
This slide presentation reviews the affect of urbanization on community health. It exams urbanization trends in the Atlanta metro area and includes information on impervious surfaces, air quality, mitigation strategies, spatial growth modeling, land use, public health surveillance and different data collection methods.
Quattrochi, Dale A.↗
Linking Asthma Exacerbation and Air Pollution Data: A Step Toward Public Health and Environmental Data Integration
Studies have shown that reducing exposure to triggers such as air pollutants can reduce symptoms and the need for medication in asthma patients. However, systems that track asthma are generally not integrated with those that track environmental hazards related to asthma. Tlvs lack of integration hinders public health awareness and responsiveness to these environmental triggers. The current study is a collaboration between health and environmental professionals to utilize NASA-derived environmental data to develop a decision support system (DSS) for asthma prediction, surveillance, and intervention. The investigators link asthma morbidity data from the University of Mississippi Medical Center (UMMC) and Mississippi Department of Health (MDH) with air quality data from the Mississippi Department of Environmental Quality (MDEQ) and remote sensing data from NASA. Daily ambient environmental hazard data for PM2.5 and ozone are obtained from the MDEQ air quality monitoring locations and are combined with remotely sensed data from NASA to develop a state-wide spatial and time series profile of environmental air quality. These data are then used to study the correlation of these measures of air quality variation with the asthma exacerbation incidence throughout the state over time. The goal is to utilize these readily available measures to allow real-time risk assessment for asthma exacerbations. GeoMedStat, a DSS previously developed for biosurveillance, will integrate these measures to monitor, analyze and report the real-time risk assessment for asthma exacerbation throughout the state.
Faruque, Fazlay↗
NASA's Systems Engineering Approaches for Addressing Public Health Surveillance Requirements
NASA's systems engineering has its heritage in space mission analysis and design, including the end-to-end approach to managing every facet of the extreme engineering required for successful space missions. NASA sensor technology, understanding of remote sensing, and knowledge of Earth system science, can be powerful new tools for improved disease surveillance and environmental public health tracking. NASA's systems engineering framework facilitates the match between facilitates the match between partner needs and decision support requirements in the areas of 1) Science/Data; 2) Technology; 3) Integration. Partnerships between NASA and other Federal agencies are diagrammed in this viewgraph presentation. NASA's role in these partnerships is to provide systemic and sustainable solutions that contribute to the measurable enhancement of a partner agency's disease surveillance efforts.
Vann, Timi↗
Applications of remote sensing in public health.
Current research concerning the determination of the habitat of mosquito vectors of disease is discussed. It is shown how advanced interpretative processes have enabled recognition of the breeding areas of salt marsh mosquitoes and the breeding sites of the mosquito responsible for the transmission of St. Louis strain of encephalitis and of human filariasis. In addition, remote sensing data have also been useful in the study of the habitat of endemic strains of Venezuelan encephalitis virus in Florida. The beginning of the application of remote sensing to such public health aspects as air, water, and urban degradation is noted.
Barnes, C. M.↗
Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study
Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.
remote sensing data↗
Assessing Land Cover Change Dynamics in the Peruvian Amazon to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention
Dengue fever and leishmaniasis are two tropical diseases prevalent in Madre de Dios Region of Peru and have been associated with urbanization and road construction. Rapid land use changes such as mining, timber harvesting, and hydroelectric dam development lead to denser human presence in previously sparsely-populated areas which increases the proximity of human settlements to zoonotic disease vectors. In partnership with the Peruvian Ministries of Health (MINSA), the Environment (MINAM), and other in-country collaborators, a NASA DEVELOP team examined Land Use Land Cover (LULC) changes and reported dengue and leishmaniasis incidence in the Madre de Dios region. This sought to help MINSA and MINAM understand the spatial relationship between land use change and zoonotic disease incidence. We created a LULC classification script using Google Earth Engine (GEE) with Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) imagery to classify land cover in 2010, 2015, and 2020 and evaluate changes over this time period. The team then compared the quantified results of the LULC assessment in conjunction with reported disease cases to evaluate disease incidence and key land cover changes across Madre de Dios’s 11 districts. Follow on work will use these products to develop more detailed outbreak risk maps. These products will allow MINSA, MINAM, and other partners to understand hotspots of land cover change in Peru and the relationship with outbreaks to inform public health decision makers and environmental policy.
Nataly Chacon-Buitrago↗
Methods for Characterizing Fine Particulate Matter Using Satellite Remote-Sensing Data and Ground Observations: Potential Use for Environmental Public Health Surveillance
This study describes and demonstrates different techniques for surfacing daily environmental / hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5) for the purpose of integrating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC s) pilot study of Health and Environment Linked for Information Exchange (HELIX)-Atlanta. It described a methodology for estimating ground-level continuous PM2.5 concentrations using B-Spline and inverse distance weighting (IDW) surfacing techniques and leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement The Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA s satellite data. Hazard data have been processed to derive the surrogate exposure PM2.5 estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM2.5 not only provides a more complete daily representation of PM2.5 than either data set alone would allow, but it also reduces the errors in the PM2.5 estimated surfaces. The results of this paper have shown that the daily IDW PM2.5 surfaces had smaller errors, with respect to observations, than those of the B-Spline surfaces in the year studied. However the IDW mean annual composite surface had more numerical artifacts, which could be due to the interpolating nature of the IDW that assumes that the maxima and minima can occur only at the observation points. Finally, the methods discussed in this paper improve temporal and spatial resolutions and establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with good accuracy levels is critical.
Al-Hamdan, Mohammad Z.↗
Integration of Airborne Aerosol Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems
The residual signal indicates that the pollen event may influence the seasonal signal to an extent that would allow detection, given accurate QA filtering and BRDF corrections. MODIS daily reflectances increased during the pollen season. The DREAM model (PREAM) was successfully modified for use with pollen and may provide 24-36 hour running pollen forecasts. Publicly available pollen forecasts are linked to general weather patterns and roughly-known species phenologies. These are too coarse for timely health interventions. PREAM addresses this key data gap so that targeting intervention measures can be determined temporally and geospatially. The New Mexico Department of Health (NMDOH) as part of its Environmental Public Health Tracking Network (EPHTN) would use PREAM a tool for alerting the public in advance of pollen bursts to intervene and reduce the health impact on asthma populations at risk.
Luvall, Jeffrey C.↗
Environmental mycology and its importance to public health
No abstract available
NASA Discipline Environmental Health↗
Pacific Northwest Health & Air Quality: Monitoring Trends in Air Quality During a Drought Case Study to Improve Public Health Response to Drought Threats
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Abby Sgan↗
Environmental Public Health Applications Using Remotely Sensed Data
No abstract available
Public Health↗
Giovanni and Public Health Research: How Easy Data Analysis and Visualization Enables Broader Usage of NASA Earth Observation Data
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Remote sensing↗
Forecasting disease risk for increased epidemic preparedness in public health
Emerging infectious diseases pose a growing threat to human populations. Many of the world's epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.
Disease Outbreaks↗
Integration of Airborne Aerosol Prediction Systems and Vegetation Phenology to Track Pollen for Asthma Alerts in Public Health Decision Support Systems
This slide presentation reviews the study that used a model to forecast pollen to assist in warning for asthma populations. Using MODIS daily reflectances to input to a model, PREAM, adapted from the Dust REgional Atmospheric Modeling (DREAM) system, a product of predicted pollen is produced. Using the pollen from Juniper the PREAM model was shown to be an assist in alerting the public of pollen bursts, and reduce the health impact on asthma populations.
Luvall, Jeffrey C.↗