Search NASA⌕ Search

SEARCH · Search NASA

Results for “Disease Vectors”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluation of the 2022 West Nile virus forecasting challenge, USA

Abstract Background West Nile virus (WNV) is the most common cause of mosquito-borne disease in the continental USA, with an average of ~1200 severe, neuroinvasive cases reported annually from 2005 to 2021 (range 386–2873). Despite this burden, efforts to forecast WNV disease to inform public health measures to reduce disease incidence have had limited success. Here, we analyze forecasts submitted to the 2022 WNV Forecasting Challenge, a follow-up to the 2020 WNV Forecasting Challenge. Methods Forecasting teams submitted probabilistic forecasts of annual West Nile virus neuroinvasive disease (WNND) cases for each county in the continental USA for the 2022 WNV season. We assessed the skill of team-specific forecasts, baseline forecasts, and an ensemble created from team-specific forecasts. We then characterized the impact of model characteristics and county-specific contextual factors (e.g., population) on forecast skill. Results Ensemble forecasts for 2022 anticipated a season at or below median long-term WNND incidence for nearly all (> 99%) counties. More counties reported higher case numbers than anticipated by the ensemble forecast median, but national caseload (826) was well below the 10-year median (1386). Forecast skill was highest for the ensemble forecast, though the historical negative binomial baseline model and several team-submitted forecasts had similar forecast skill. Forecasts utilizing regression-based frameworks tended to have more skill than those that did not and models using climate, mosquito surveillance, demographic, or avian data had less skill than those that did not, potentially due to overfitting. County-contextual analysis showed strong relationships with the number of years that WNND had been reported and permutation entropy (historical variability). Evaluations based on weighted interval score and logarithmic scoring metrics produced similar results. Conclusions The relative success of the ensemble forecast, the best forecast for 2022, suggests potential gains in community ability to forecast WNV, an improvement from the 2020 Challenge. Similar to the previous challenge, however, our results indicate that skill was still limited with general underprediction despite a relative low incidence year. Potential opportunities for improvement include refining mechanistic approaches, integrating additional data sources, and considering different approaches for areas with and without previous cases. Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Self-Assembling Pfs230D1-Ferritin Nanoparticle Vaccine Has Potent and Durable Malaria Transmission-Reducing Activity

Malaria is caused by eukaryotic protozoan parasites of the genus Plasmodium. There are 249 million new cases and 608,000 deaths annually, and new interventions are desperately needed. Malaria vaccines can be divided into three categories: liver stage, blood stage, or transmission-blocking vaccines. Transmission-blocking vaccines prevent the transmission of disease by the mosquito vector from one human to another. Pfs230 is one of the leading transmission-blocking vaccine antigens for malaria. Here, we describe the development of a 24-copy self-assembling nanoparticle vaccine comprising domain 1 of Pfs230 genetically fused to H. pylori ferritin. The single-component Pfs230D1-ferritin construct forms a stable and homogenous 24-copy nanoparticle with good production yields. The nanoparticle is highly immunogenic, as two low-dose vaccinations of New Zealand White rabbits elicited a potent and durable antibody response with high transmission-reducing activity when formulated in two distinct adjuvants suitable for translation to human use. This single-component 24-copy Pfs230D1-ferritin nanoparticle vaccine has the potential to improve production pipelines and the cost of manufacturing a potent and durable transmission-blocking vaccine for malaria control.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2003

Satellites as Sentinels for Climate and Health

Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring, risk mapping, and surveillance of parameters useful to such problems as vector- borne and infectious diseases, air and water quality,. harmful algal blooms, W radiation, contaminant and pathogen transport in air and water, and thermal stress. Remote sensing, geographic information systems (GIs), global positioning systems (GPS), improved computation capabilities, and interdisciplinary research between the Earth and health science communities, together with local knowledge, are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global climate and health issues. These collaborative efforts are enabling increased understanding of the relationships among changes in temperature, rainfall, wind, soil moisture, solar radiation, vegetation, and the patterns of extreme weather events and health issues. This increased understanding and improved information and data sharing, in turn, empowers local health and environmental decision-makers to better predict climate-related health problems, decrease vulnerability, take preventive measures, and improve response actions. This paper provides a number of recent examples of how satellites - from their unique vantage point in space - can serve as sentinels for climate and health.

Maynard, Nancy G.↗
DOE OSTI2021

A short hepatitis C virus NS5A peptide expression by AAV vector modulates human T cell activation and reduces vector immunogenicity

Viral vector-mediated gene therapies have the potential to treat many human diseases; however, host immune responses against the vector and/or the transgene pose a safety risk to the patients and can negatively impact product efficacy. Thus, novel strategies to reduce vector immunogenicity are critical for the advancement of these therapies. T cell activation (TCA) is required for the development of immune responses during gene therapy. We hypothesized that modulation of TCA by incorporating a novel viral immunomodulatory factor into a viral vector may reduce unwanted TCA and immune responses during gene therapy. To test this hypothesis, we identified an immunomodulatory domain of the hepatitis C virus (HCV) NS protein 5A (NS5A) protein and studied the effect of viral vectors expressing NS5A peptide on TCA. Lentiviral vector-mediated expression of a short 20-mer peptide derived from the NS5A protein in human T cells was sufficient to inhibit TCA. Synthetic 20-mer NS5A peptide also inhibited TCA in primary human T cells. Mechanistically, the NS5A protein interacted with Lck and inhibited proximal TCR signaling. Importantly, NS5A peptide expression did not cause global T cell signaling dysfunction as distal T cell signaling was not inhibited. Finally, recombinant adeno-associated virus (AAV) vector expressing the 20-mer NS5A peptide reduced both the recall antigen and the TCR-mediated activation of human T cells and did not cause global T cell signaling dysfunction. Together, these data suggest that expression of a 20-mer NS5A peptide by an AAV vector may reduce unwanted TCA and may contribute to lower vector immunogenicity during gene therapy.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

Dejection and/or prevention of human diseases through remote sensing

The use of remote sensors for the detection of probable areas of disease infestation, and possibly as a tool in the control of these diseases, is discussed. Particular attention is given to malaria, encephalitis, and Rocky Mountain Spotted Fever. The vector ecology, epidemiology, and pathogenesis of these diseases are examined. The use of remote sensors to detect the presence of Red Tide is also discussed.

Edmisten, J. A.↗
NASA NTRS2022

Spatial and Seasonal Patterns of the Mosquito Community in Central Oklahoma

Mosquitoes (Culicidae) are ubiquitous flying insects that function as vectors for several viruses that cause disease in humans. Mosquito abundance and diversity are influenced by landscape features and environmental factors such as temperature and precipitation and vary across seasons and years. The range and phenology of many mosquito species that vector viruses relevant to human health are changing. We sampled mosquito communities in central Oklahoma for four years at thirteen sites, collecting over 25,000 mosquitoes; among these, we identified 27 different species, including several that transmit human pathogens and were collected in suburban backyards. Community composition differed across the landscape and changed from early season to late season and year to year. This effort to describe mosquito communities in Oklahoma is a first step toward assessing and predicting arbovirus risk, an ongoing and dynamic public health challenge.

David Hoekman↗
NASA NTRS2015

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

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

Morin, Cory↗
NASA NTRS2001

The Effect of Regional Climate Variability on Outbreak of Bartonellosis Epidemics in Peru

Bartonellosis is a vector-borne, highly fatal, emerging infectious disease, which has been known in the Peruvian Andes since the early 1600s and has continued to be a problem in many mountain valleys in Peru and other Andean South American countries. The causative bacterium, Bartonella bacilliformis (Bb), is believed to be transmitted to humans by bites of the sand fly Lutzomyia verrucarum. According to available medical records, the transmission of infection often occurs in river valleys of the Andes Mountains at an altitude between 800 and 3500 meters above sea level. It shows a seasonal pattern, which usually begins to rise in December, peaks in February and March, and is at its lowest from July until November. The epidemics of bartonellosis also vary interannually, occurring every four to eight years, and appear to be associated with the El Nino cycle. In response to the National Oceanic and Atmospheric Administration (NOAA) announcement on climate variability and human health, which was constructed to stimulate integrated multidisciplinary research in the area of climate variability and health interactions, we have conducted a study to investigate the relationship between the El Nino induced regional climate variation and the outbreak of bartonellosis epidemics in Peru. Two test sites, Caraz and Cusco, were selected for this study. According to reports, Caraz has a long-standing history of endemic transmission and Cusco, which is located about five degrees poleward of Caraz, had no recorded epidemics until the most recent 1997/1998 El Nino event. The goal of this study is to clarify the relative importance of climatic risk factors for each area that could be predicted in advance, thus allowing implementation of cost-effective control measures, which would reduce disease morbidity and mortality.

Zhou, Jia-Yu↗
NASA NTRS1994

Purification of recombinant budgerigar fledgling disease virus VP1 capsid protein and its ability for in vitro capsid assembly

A recombinant system for the major capsid VP1 protein of budgerigar fledgling disease virus has been established. The VP1 gene was inserted into a truncated form of the pFlag-1 vector and expressed in Escherichia coli. The budgerigar fledgling disease virus VP1 protein was purified to near homogeneity by immunoaffinity chromatography. Fractions containing highly purified VP1 were pooled and found to constitute 3.3% of the original E. coli-expressed VP1 protein. Electron microscopy revealed that the VP1 protein was isolated as pentameric capsomeres. Electron microscopy also revealed that capsid-like particles were formed in vitro from purified VP1 capsomeres with the addition of Ca2+ ions and the removal of chelating and reducing agents.

NASA Discipline Developmental Biology↗
DOE OSTI2023

Identification of mosquito proteins that differentially interact with alphavirus nonstructural protein 3, a determinant of vector specificity

Chikungunya virus (CHIKV) and the closely related onyong-nyong virus (ONNV) are arthritogenic arboviruses that have caused significant, often debilitating, disease in millions of people. However, despite their kinship, they are vectored by different mosquito subfamilies that diverged 180 million years ago (anopheline versus culicine subfamilies). Previous work indicated that the nonstructural protein 3 (nsP3) of these alphaviruses was partially responsible for this vector specificity. To better understand the cellular components controlling alphavirus vector specificity, a cell culture model system of the anopheline restriction of CHIKV was developed along with a protein expression strategy. Mosquito proteins that differentially interacted with CHIKV nsP3 or ONNV nsP3 were identified. Six proteins were identified that specifically bound ONNV nsP3, ten that bound CHIKV nsP3 and eight that interacted with both. In addition to identifying novel factors that may play a role in virus/vector processing, these lists included host proteins that have been previously implicated as contributing to alphavirus replication.

Byers, Nathaniel M. (ORCID:0000000157725940)↗
DOE OSTI2021

Risk assessment of engineering diseases of embankment–bridge transition section for railway in permafrost regions

Abstract The embankment–bridge transition section (EBTS) is one of the zones where railway diseases occur frequently in permafrost regions. Disease risk assessment of EBTSs can provide guidance for maintenance. In this study, considering the engineering geological conditions, climate characteristics, and embankment structure types along the Qinghai–Tibet Railway (QTR) as well as based on the disease inventory of the QTR from 2010 to 2019, the logistic regression (LR), support vector machine (SVM), and combination‐weight‐based gay relation analysis (GRA) were used for disease risk assessment of the EBTSs along the QTR in permafrost regions. The results indicate that the LR and SVM models have a better capability for EBTS disease prediction than the GRA model, and the SVM model can select more disease samples in relatively larger regions than the LR model. Based on the SVM and LR models, the risk level of EBTSs is divided into four classes: low‐ (29.9%), moderate‐ (39.6%), high‐ (22.1%), and very high (8.4%) risk. Finally, we selected 272 EBTSs in high‐ and very‐high‐risk classes for key observation during the maintenance of the QTR in permafrost regions. This study provides a reference for the risk assessment of railways built in permafrost regions using data‐driven methods.

Zhang, Saize↗
DOE OSTI2020

Predicting Future Disease Burden in a Rapidly Changing Climate

The interplay of a rapidly changing climate and infectious disease occurrence is emerging as a critical topic, requiring investigation of possible direct, as well as indirect, connections between disease processes and climate-related variation and phenomena. First, we introduce and overview three infectious disease exemplars (dengue, influenza, valley fever) representing different transmission classes (insect-vectored, human-to-human, environmentally-transmitted) to illuminate the complex and significant interplay between climate disease processes, as well as to motivate discussion of how Sandia can transform the field, and change our understanding of climate-driven infectious disease spread. We also review state-of-the-art epidemiological and climate modeling approaches, together with data analytics and machine learning methods, potentially relevant to climate and infectious disease studies. We synthesize the modeling and disease exemplars information, suggesting initial avenues for research and development (R&D) in this area, and propose potential sponsors for this work. Whether directly or indirectly, it is certain that a rapidly changing climate will alter global disease burden. The trajectory of climate change is an important control on this burden, from local, to regional and global scales. The efforts proposed herein respond to the National Research Councils call for the creation of a multidisciplinary institute that would address critical aspects of these interlocking, cascading crises.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Transboundary determinants of avian zoonotic infectious diseases: challenges for strengthening research capacity and connecting surveillance networks

As the climate changes, global systems have become increasingly unstable and unpredictable. This is particularly true for many disease systems, including subtypes of highly pathogenic avian influenzas (HPAIs) that are circulating the world. Ecological patterns once thought stable are changing, bringing new populations and organisms into contact with one another. Wild birds continue to be hosts and reservoirs for numerous zoonotic pathogens, and strains of HPAI and other pathogens have been introduced into new regions via migrating birds and transboundary trade of wild birds. With these expanding environmental changes, it is even more crucial that regions or counties that previously did not have surveillance programs develop the appropriate skills to sample wild birds and add to the understanding of pathogens in migratory and breeding birds through research. For example, little is known about wild bird infectious diseases and migration along the Mediterranean and Black Sea Flyway (MBSF), which connects Europe, Asia, and Africa. Focusing on avian influenza and the microbiome in migratory wild birds along the MBSF, this project seeks to understand the determinants of transboundary disease propagation and coinfection in regions that are connected by this flyway. Through the creation of a threat reduction network for avian diseases (Avian Zoonotic Disease Network, AZDN) in three countries along the MBSF (Georgia, Ukraine, and Jordan), this project is strengthening capacities for disease diagnostics; microbiomes; ecoimmunology; field biosafety; proper wildlife capture and handling; experimental design; statistical analysis; and vector sampling and biology. Here, we cover what is required to build a wild bird infectious disease research and surveillance program, which includes learning skills in proper bird capture and handling; biosafety and biosecurity; permits; next generation sequencing; leading-edge bioinformatics and statistical analyses; and vector and environmental sampling. Creating connected networks for avian influenzas and other pathogen surveillance will increase coordination and strengthen biosurveillance globally in wild birds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Identification of central Kenyan Rift Valley Fever virus vector habitats with Landsat TM and evaluation of their flooding status with airborne imaging radar

Rift Valley Fever (RVF) is a mosquito-borne virus that affects livestock and humans in Africa. Landsat TM data are shown to be effective in identifying dambos, intermittently flooded areas that are potential mosquite breeding sites, in an area north of Nairobi, Kenya. Positive results were obtained from a limited test of flood detection in dambos with airborne high resolution L, C, and X band multipolarization SAR imagery. L and C bands were effective in detecting flooded dambos, but LHH was by far the best channel for discrimination between flooded and nonflooded sites in both sedge and short-grass environments. This study demonstrates the feasibility of a combined passive and active remote sensing program for monitoring the location and condition of RVF vector habitats, thus making future control of the disease more promising.

Pope, K. O.↗
DOE OSTI2020

Ribavirin targets sugar transporter 6 to suppress acquisition and transmission of rice stripe tenuivirus by its vector Laodelphax striatellus

Abstract BACKGROUND Rice stripe tenuivirus (RSV) is one of the most destructive pathogens of rice and other cereal crops. The virus is transmitted by the small brown planthopper (SBPH, Laodelphax striatellus ) in a circulative‐propagative manner. Thus, blocking transmission by the insect vector would provide an effective strategy to prevent epidemic outbreaks of the disease. RESULTS In this study, we explored the effect of ribavirin on acquisition and transmission of the virus by specifically inhibiting the expression of sugar transporter 6 (LsSt‐6), which was recently reported as a key vector component for RSV transmission. Ribavirin at the highest concentration tested (250 μmol L ‐1 ) significantly reduced RSV acquisition and transmission efficiency by SBPHs through inhibiting LsSt‐6 messenger RNA (mRNA) level. Survival of the model insect Spodoptera frugiperda cell line (Sf9) was 95.0 ± 2.2 and 85.6 ± 2.1% after exposure to 250 μmol L ‐1 ribavirin or 8‐azaguanine, respectively. Further study confirmed that 250 μmol L ‐1 ribavirin also significantly reduced LsSt‐6 mRNA and protein levels in Sf9 cells. However, 8‐azaguanine did not significantly inhibit viral infectivity and LsSt‐6 mRNA levels in SBPH or the Sf9 cell line. CONCLUSION This result provides evidence that ribavirin has the potential to disrupt LsSt‐6 expression but not others like viral RNAs to prevent acquiring RSV, which leads to less viral accumulation in SBPH tissues and thereby lower transmission efficiency. © 2020 Society of Chemical Industry

Hajano, Jamal‐U‐Ddin↗
NASA NTRS2008

Accessing and Utilizing Remote Sensing Data for Vectorborne Infectious Diseases Surveillance and Modeling

Background: The transmission of vectorborne infectious diseases is often influenced by environmental, meteorological and climatic parameters, because the vector life cycle depends on these factors. For example, the geophysical parameters relevant to malaria transmission include precipitation, surface temperature, humidity, elevation, and vegetation type. Because these parameters are routinely measured by satellites, remote sensing is an important technological tool for predicting, preventing, and containing a number of vectorborne infectious diseases, such as malaria, dengue, West Nile virus, etc. Methods: A variety of NASA remote sensing data can be used for modeling vectorborne infectious disease transmission. We will discuss both the well known and less known remote sensing data, including Landsat, AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectroradiometer), TRMM (Tropical Rainfall Measuring Mission), ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), EO-1 (Earth Observing One) ALI (Advanced Land Imager), and SIESIP (Seasonal to Interannual Earth Science Information Partner) dataset. Giovanni is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center. It provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. After remote sensing data is obtained, a variety of techniques, including generalized linear models and artificial intelligence oriented methods, t 3 can be used to model the dependency of disease transmission on these parameters. Results: The processes of accessing, visualizing and utilizing precipitation data using Giovanni, and acquiring other data at additional websites are illustrated. Malaria incidence time series for some parts of Thailand and Indonesia are used to demonstrate that malaria incidences are reasonably well modeled with generalized linear models and artificial intelligence based techniques. Conclusions: Remote sensing data relevant to the transmission of vectorborne infectious diseases can be conveniently accessed at NASA and some other websites. These data are useful for vectorborne infectious disease surveillance and modeling.

Kiang, Richard↗