University of Maryland researchers have been awarded National Science Foundation (NSF) RAPID grants to address the current COVID-19 crisis.
NSF is working closely with the scientific research community to bolster the national response to COVID-19. The agency is funding dozens of research projects on COVID-19 to mobilize the scientific community to better understand and develop measures to respond to the virus. NSF issued a letter to researchers inviting proposals for rapid response research grants related to the virus to help inform and educate the public about virus transmission and prevention, and develop effective strategies for addressing this challenge at the local, state and national levels. Support for these efforts is made through NSF's Rapid Response Research (RAPID) funding mechanism, which enables the agency to quickly process and support research that addresses an urgent need.
Learn more about the University of Maryland recipients of NSF RAPID grants below:
Using Location-based Big-Data to Model People's Mobility Patterns During the COVID-19 Outbreak
Kathleen Stewart (Principal Investigator)
The outbreak of COVID-19 in the U.S. provides an important opportunity for researchers to study the impacts of a rapidly expanding pandemic on human mobility. This research investigates how to measure changes in collective movement of people in response to the fast-evolving COVID-19 outbreak using large datasets of passively collected location data. It examines how locations within a state respond to public policy implementation and times of critical public messaging. Detailed knowledge on movement patterns of people can help public officials identify hotspots and critically isolated populations, as well as shed light on those groups who continue to travel for work or other purposes. This research contributes to improving the public response to an emergency and contributes to bridging different stakeholder mitigation strategies.
Deb Niemeier (Principal Investigator)
The outbreak of COVID-19 in the U.S. provides an important opportunity for researchers to improve flattening curve models which can be used to assess and even spatially optimize health care during a rapidly expanding pandemic. This Rapid Response Research (RAPID) project will take advantage of the large-scale availability of location-sensing devices and apps that produce big data on mobility patterns that can be used to better optimize the use of healthcare facilities. This research brings together rapidly unfolding health data with real-time data on mobility. The researchers will examine how these two critical data resources can be linked to better inform policy, identify emerging hotspots, and target critical actions during a pandemic. This research will help public officials to better understand and adapt to changing conditions as a health emergency arises and expands.
Advanced Topic Modeling Methods to Analyze Text Responses in COVID-19 Survey Data
Philip Resnik (Principal Investigator)
As the COVID-19 pandemic continues, public and private organizations are deploying surveys to inform responses and policy choices. Survey designs using multiple choice responses are by far the most common -- "open ended" questions, where survey participants provide a longer-form written response, are used far less. This is true despite the fact that when you allow people to provide unconstrained spoken or text responses, it is possible to obtain richer, fine-grained information clarifying the other responses, as well as useful "bottom up" information that the survey designers did not know to ask for. A key problem is that analyzing the unstructured language in open-ended responses is a labor-intensive process, creating obstacles to using them especially when speedy analysis is needed and resources are limited. Computational methods can help, but they often fail to provide coherent, interpretable categories, or they can fail to do a good job connecting the text in the survey with the closed-end responses. This project will develop new computational methods for fast and effective analysis of survey data that includes text responses, and it will apply these methods to support organizations doing high-impact survey work related to COVID-19 response. This will improve these organizations' ability to understand and mitigate the impact of the COVID-19 pandemic.
Assessing the Social Consequences of COVID-19
Long Doan (Principal Investigator)
This project examines the impacts of COVID-19 and states' and local governments' social distancing directives on behavior, time spent with others, use of technology, and mental and physical wellbeing. The objective of the project is to investigate these daily life impacts in real time and to analyze how these impacts are affected by sociodemographic characteristics that affect time use and well-being. Data are leveraged from several hundred respondents' daily time use before the pandemic along with data collected during and after the pandemic to create a natural experiment that isolates the effects of the pandemic on changes in behavior. Among the products of this research are evidence-based recommendations to address the social consequences of the pandemic.
Energy-Efficient Disinfection of Viral Bioaerosols in Public Spaces: Vital for Lifting of the "Stay-at-Home" Orders During the Covid-19 Outbreak
Jelena Srebric (Principal Investigator)
This project will provide an analytical framework to assess potential reduction of infection risks from COVID-19 viral bioaerosols in public spaces, including school buses, classrooms, and retail stores. Viral bioaerosols may cause infection for occupants staying both near and far away from infected people, whether staying indoors at the same time or not. Upper-room germicidal ultraviolet (UR-GUV) light can provide a real-time air disinfection solution with a relatively small energy footprint if its light effectively interacts with the bioaerosol both in the air and on surfaces. This project will develop and disseminate an open-source numerical analytical framework including assessment of UR-GUV disinfection and make it publicly available online to provide a free resource useful for helping to control the spread of airborne COVID-19 infections in public spaces. An effective, real-time, and sustainable engineering solution for air indoor space disinfection is an important precaution to help prevent the spread of COVID-19, particularly in the context of efforts to restart the nation's economy.
Supply Chain Portal to Serve Entrepreneurs Producing Critical Items in Response to COVID-19
Louiqa Raschid (Principal Investigator)
This COVID-19 RAPID project combines the efforts of the NSF Convergence Accelerator Business Open Knowledge Network (BOKN) and Manufacturing Open Knowledge Network (MOKN) in order to develop a knowledge resource to support the discovery of manufacturers and materials suppliers to help assemble new supply chains, particularly focusing on personal protective equipment (PPE), such as ventilators. The BOKN encodes information about businesses and their capabilities, while the MOKN encodes manufacturing information about goods. By combining information and capabilities from both networks, this integrative COVID RAPID project will develop search and matching tools that will help entrepreneurs and manufacturers to adapt swiftly to the supply chains and processes needed to produce new types of products. The key information along with analysis capabilities for performing information extraction, data cleaning, and data representation will be accessible via a web portal, initially focusing on supply chains for PPE. The resources developed can be used equally well by small businesses and entrepreneurs as well as more established organizations.
A "Citizen Science" Approach to Examine COVID-19 Social Distancing Effects on Children's Language Development
Yi Ting Huang (Principal Investigator)
The COVID-19 pandemic is a significant threat to learning and language development for large numbers of children. Such challenges are compounded for those facing social and economic adversity, factors that are associated with decreased parental interactions, child development, and school achievement. This study examines the scope and magnitude of learning impacts from COVID19 pandemic by engaging families as "Citizen Scientists" who will track their children's language use during the crisis. Social-distancing policies vary by state, enabling the researchers to compare how these different decisions affect children's language development. This will help policymakers and educators make more informed decisions, both about crisis management and strategies to mitigate negative effects of crisis-related policies. More broadly, this work will make important contributions to the science of language learning, which in turn will help clinicians and educators best address the needs of children from varying demographics. Finally, by using a Citizen Science paradigm, this project establishes a conduit for science outreach and education.
Forest Productivity and Expression in a Low-emissions Present: A RAPID Response to the COVID-19 Emissions Reduction Event
Nathan Swenson (Principal Investigator)
State and federal policies have significantly limited human activities to keep the U.S. population safe during the COVID-19 pandemic. This has resulted in a significant decrease of atmospheric inputs from the reduction in automobile and air travel. The unprecedented and dramatic reduction in traffic in major metropolitan areas where emissions are consistently high is transforming the atmosphere, even at continental scales. The COVID-19 event presents a unique, ephemeral, and rare opportunity to study how forests would respond to dramatically cleaner air in the United States. This award will explore how North American forests that have experienced a life-time of the byproducts of human transportation respond by examining responses from the genetic and molecular levels to the forest scale. The research will be conducted at a large forest plot near the Washington DC metropolitan area with a long history of forest research and adjacent to a National Ecological Observatory Network (NEON) tower. These linkages provide opportunities to scale the molecular research to potential ecosystem responses to emissions reduction efforts. The Education Office at Smithsonian Environmental Research Center (SERC), which works with thousands of high school students and their teachers every year will incorporate results into classroom activities at the SERC Education Center.
Understanding and Facilitating Remote Triage and Rehabilitation During Pandemics via Visual Based Patient Physiologic Sensing
Min Wu (Principal Investigator)
This RAPID project plans to investigate visual-based physiological sensing technologies to facilitate remote triage and rehabilitation during pandemics, by using low-cost consumer-grade cameras to track such physiological conditions as respiration rate, heart rate, and blood oxygen saturation levels from videos. The physiological data can be visualized and archived, and shared by users with medical practitioners to understand and support remote triage and rehabilitation.
Accelerating Phylodynamic Analyses of SARS-CoV-2
Michael Cummings (Principal Investigator)
Evolutionary analyses using genomic data are an essential component of the scientific response to the COVID-19 pandemic, which is caused by Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). Inferring the evolutionary history, or phylogeny, of virus samples with sampling time and location information allows scientists to estimate the divergence of viral lineages in time and place. These analyses provide time estimates that predate sampling events. Information about mutations, and the rate of mutation, is inherent to these phylogenetic analyses such that specific viral linages with accelerated mutation rates, if they exist, can be identified. Furthermore, molecular phylodynamics includes not only evolutionary history but also information on viral genetic variation and viral population dynamics, again all in the context of geography and time. The software from this project will be used in SARS-CoV-2 research on: patterns of movement and migration; time of outbreak origin; rate of mutation and detection of significant mutations with potential health impact; prevalence in populations at different geographical scales; reproductive number and impact on policy; and infection-to-case reporting rates. Perhaps of most immediate impact is that software from this project will accelerate tracing and dating the origins of outbreaks in specific geographic regions where contact tracing is not effective. Contact tracing and phylogenetic analyses work on different scales, and thus are complementary. Together they provide a more comprehensive view of the transmission patterns for the current pandemic.
The Impact of COVID-19 on Job Loss and Job Creation
John Haltiwanger (Principal Investigator)
This research project will use anonymized real time cellular phone location data combined with other sources of data to investigate the employment effects of the COVID19 pandemic. The research will develop an innovative theoretical model of job destruction and job creation, at the granular level, in response to the pandemic and use the data assembled to estimate the model. The model does not only account for job destruction and creation at various locations but also changes in the types of jobs created as well as the changing industries in which the jobs are created at the various locations. The new model is likely to influence how researchers investigate the effects of pandemics on employment at various locations. The research results will provide important inputs into how to craft policies to counter the employment effects the current as well as future pandemics particularly, and economic disruptions generally. The results will also establish the US as the global leader in understanding the employment effects of pandemics and how to develop policies to reduce their effects.
Coronavirus, New Patterns in Electricity Demand, and Energy Inequality
Yueming Qiu (Principal Investigator)
The aim of this project is to advance national health and welfare through investigating the impact of the coronavirus pandemic on electricity demand. The pandemic has resulted in widespread stay-at-home policies meaning that, vulnerable populations such as those with low income, ethnic minorities, and the elderly might face a disproportionally higher increase in electricity expenditure. The likely inequitable energy impact on these groups could be a result of less energy-efficient homes, increased need for electrical appliances (i.e. school computers), and larger household sizes. The resulting higher energy expenditure burden might imply constraints of these groups to create a comfortable indoor environment, which is particularly vital to maintaining good health during a pandemic. This project will (1) quantify the electricity expenditure re-distribution and uncover how this relates to the wealth redistribution as lay-offs increase; (2) develop a deeper understanding of the pandemic's impact on the electricity grid for different consumer types. This work will inform policies that can reduce the energy burden of the most vulnerable populations whose job security, educational development, and mental health are linked to their ability to satisfy their energy demand, particularly during an international crisis.
May 10, 2020
University of Maryland Researchers Awarded NSF RAPID Grants to Bolster COVID-19 Response
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University of Maryland
College Park, MD 20742-1541
University of Maryland
College Park, MD 20742-1541
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