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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States

Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number ℛ0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ℛ0 relates to a herd immunity threshold (HIT), which is given by 1−1/ℛ0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level ℛ0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. ℛ0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21 January 2020 to 21 June 2020. Our ℛ0 estimates characterize the infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we found that no state had achieved herd immunity as of 20 September 2021.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2021

Guidance and Lessons Learned from COVID-19 for Human-Subjects Research

The goal of this effort was to identify innovative strategies, approaches, and methods that have enabled researchers to continue doing meaningful human subjects research during the COVID-19 pandemic. Many organizations and recent literature primarily focus on efforts for future research in a post-COVID environment. Additionally, there have been no systematic efforts across the agency or broader human factors community to coordinate or share strategies. Therefore, the focus was on acquiring knowledge gained by researchers from experiences during COVID that could be valuable to continue human-subjects research under existing restrictions.

Coronavirus Disease 2019↗
NASA NTRS2022

Global Fine Scale Changes in Ambient NO2 During COVID-19 Lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health(1–9) . A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19(10–20). Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Ground level NO2↗
DOE OSTI2022

Recent Drug Development and Medicinal Chemistry Approaches for the Treatment of SARS‐CoV‐2 Infection and COVID‐19

Abstract COVID‐19, caused by SARS‐CoV‐2 infection, continues to be a major public health crisis around the globe. Development of vaccines and the first cluster of antiviral drugs has brought promise and hope for prevention and treatment of severe coronavirus disease. However, continued development of newer, safer, and more effective antiviral drugs are critically important to combat COVID‐19 and counter the looming pathogenic variants. Studies of the coronavirus life cycle revealed several important biochemical targets for drug development. In the present review, we focus on recent drug design and medicinal chemistry efforts in small molecule drug discovery, including the development of nirmatrelvir that targets viral protein synthesis and remdesivir and molnupiravir that target viral RdRp. These are recent FDA approved drugs for the treatment of COVID‐19.

Pharmacology & Pharmacy↗
DOE OSTI2021

Lung Cancer and Heart Disease Risks Associated With Low-Dose Pulmonary Radiotherapy to COVID-19 Patients With Different Background Risks

The respiratory disease COVID-19 reached global pandemic status in 2020. Excessive inflammation is believed to result in the most severe symptoms and death from this disease. Because treatment options for patients with severe COVID-19 related pulmonary symptoms remain limited, whole-lung low-dose radiation therapy is being evaluated as an anti-inflammatory modality. However, there is concern about the long-term risks associated with low-dose pulmonary irradiation. To help quantify the benefit-risk balance of low-dose radiation therapy for COVID-19, we estimated radiation-induced lifetime risks of both lung cancer and heart disease (major coronary events) for patients of different sexes, treated at ages 50 to 85, with and without other relevant risk factors (cigarette smoking and baseline heart disease risk).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Identifying mitigation strategies for $\mathrm{COVID}$-$\mathrm{19}$ superspreading on flights using models that account for passenger movement

Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. Conventional models do not adequately explain superspreading patterns on flights, with infection spread wider than expected from proximity based on passenger seating. An important reason for this is that models typically do not consider the movement of passengers during the flight, boarding, or deplaning. Understanding the risks for each of these aspects could provide insight into effective mitigation measures. We modeled infection risk from seating and fine-grained movement patterns – boarding, deplaning, and inflight movement. We estimated infection model parameters from a prior superspreading event. We validated the model and the impact of interventions using available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections. Here our results show that the inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95–100%, while cloth masks would have reduced it by only 40–80%. Results indicate that leaving the middle seat vacant is effective in reducing infection, and the effectiveness increases when combined with good quality masks. However, with a good mask, the risk is quite low even without the middle seats being empty. Our results suggest the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Fast Climate Responses to Aerosol Emission Reductions During the COVID-19 Pandemic

The reduced human activities and associated decreases in aerosol emissions during the COVID-19 pandemic are expected to affect climate. Assuming emission changes during lockdown, back-to-work and post-lockdown stages of COVID-19, climate model simulations show a surface warming over continental regions of the Northern Hemisphere. In January–March, there was an anomalous warming of 0.05–0.15 K in eastern China, and the surface temperature increase was 0.04–0.07 K in Europe, eastern United States, and South Asia in March–May. The longer the emission reductions undergo, the warmer the climate would become. The emission reductions explain the observed temperature increases of 10–40% over eastern China relative to 2019. A southward shift of the ITCZ is also seen in the simulations. This study provides an insight into the impact of COVID-19 pandemic on global and regional climate and implications for immediate actions to mitigate fast global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave

Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October–19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A simple model of COVID-19 explains disease severity and the effect of treatments

Abstract Considerable effort has been made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue by focusing on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation, identifying the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and reveal conditions that can increase the likelihood of desired clinical outcome from treatment administration. In particular, the analysis suggest that antivirals need to be administered early during infection to have an impact on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Work from Home Patterns across COVID-19 Waves: Implications for Future Transportation

The unprecedented rise in work from home (WFH) during COVID-19 poses challenges for the transportation engineers and planners with the travel demand forecasting. If WFH persists post-pandemic, it could influence traffic patterns, reducing peak-hour congestion. However, the evolution of WFH decisions across pandemic phases and varying socio-economic contexts remains unclear. This study examines factors influencing WFH choices using data from the US Census Bureau’s Household Pulse Survey. Findings reveal a decline in WFH participation from 60% during the first wave to 38% by the third wave of the COVID-19 pandemic. A Geographically Weighted Regression model highlights the influence of socio-economic, household, and COVID-19-related variables, with notable spatial variability. Results show that younger individuals, females, and households with children are consistently more likely to WFH, while non-white and higher income individuals have an increasing likelihood for WFH as the pandemic progresses. These insights inform future transportation planning, emphasizing equity and decentralization strategies for post-pandemic commuting.

Patwary, Latif [ORNL] (ORCID:0000000189174928)↗
DOE OSTI2020

The Potential of Low Molecular Weight Heparin to Mitigate Cytokine Storm in Severe COVID‐19 Patients: A Retrospective Cohort Study

On March 11, 2020, the World Health Organization declared its assessment of coronavirus disease 2019 (COVID‐19) as a global pandemic. However, specific anti‐severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) drugs are still under development, and patients are managed by multiple complementary treatments. We performed a retrospective analysis to compare and evaluate the effect of low molecular weight heparin (LMWH) treatment on disease progression. For this purpose, the clinical records and laboratory indicators were extracted from electronic medical records of 42 patients with COVID‐19 (21 of whom were treated with LMWH, and 21 without LMWH) hospitalized (Union Hospital of Huazhong University of Science and Technology) from February 1 to March 15, 2020. Changes in the percentage of lymphocytes before and after LMWH treatment were significantly different from those in the control group ( P = 0.011). Likewise, changes in the levels of D‐dimer and fibrinogen degradation products in the LMWH group before and after treatment were significantly different from those in the control group ( P = 0.035). Remarkably, IL‐6 levels were significantly reduced after LMWH treatment ( P = 0.006), indicating that, besides other beneficial properties, LMWH may exert an anti‐inflammatory effect and attenuate in part the “cytokine storm” induced by the virus. Our results support the use of LMWH as a potential therapeutic drug for the treatment of COVID‐19, paving the way for a subsequent well‐controlled clinical study.

Shi, Chen↗
DOE OSTI2022

COVID-19 Exposure Assessment Tool (CEAT): Exposure quantification based on ventilation, infection prevalence, group characteristics, and behavior

The coronavirus disease 2019 (COVID-19) Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for various scenarios, providing understanding of how combinations of protective measures affect risk. CEAT incorporates mechanistic, stochastic, and epidemiological factors including the (i) emission rate of virus, (ii) viral aerosol degradation and removal, (iii) duration of activity/exposure, (iv) inhalation rates, (v) ventilation rates (indoors/outdoors), (vi) volume of indoor space, (vii) filtration, (viii) mask use and effectiveness, (ix) distance between people (taking into account both near-field and far-field effects of proximity), (x) group size, (xi) current infection rates by variant, (xii) prevalence of infection and immunity in the community, (xiii) vaccination rates, and (xiv) implementation of COVID-19 testing procedures. CEAT applied to published studies of COVID-19 transmission events demonstrates the model’s accuracy. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The relatively young and rural population may limit the spread and severity of COVID-19 in Africa: a modelling study

A novel coronavirus disease 2019 (COVID-19) has spread to all regions of the world. There is great uncertainty regarding how countries’ characteristics will affect the spread of the epidemic; to date, there are few studies that attempt to predict the spread of the epidemic in African countries. In this paper, we investigate the role of demographic patterns, urbanisation and comorbidities on the possible trajectories of COVID-19 in Ghana, Kenya and Senegal. We use an augmented deterministic Susceptible-Infected-Recovered model to predict the true spread of the disease, under the containment measures taken so far. We disaggregate the infected compartment into asymptomatic, mildly symptomatic and severely symptomatic to match observed clinical development of COVID-19. We also account for age structures, urbanisation and comorbidities (HIV, tuberculosis, anaemia). In our baseline model, we project that the peak of active cases will occur in July, subject to the effectiveness of policy measures. When accounting for the urbanisation, and factoring in comorbidities, the peak may occur between 2 June and 17 June (Ghana), 22 July and 29 August (Kenya) and, finally, 28 May and 15 June (Senegal). Successful containment policies could lead to lower rates of severe infections. While most cases will be mild, we project in the absence of policies further containing the spread, that between 0.78% and 1.03%, 0.61% and 1.22%, and 0.60% and 0.84% of individuals in Ghana, Kenya and Senegal, respectively, may develop severe symptoms at the time of the peak of the epidemic. Compared with Europe, Africa’s younger and rural population may modify the severity of the epidemic. The large youth population may lead to more infections but most of these infections will be asymptomatic or mild, and will probably go undetected. The higher prevalence of underlying conditions must be considered.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Disproportionate impacts of COVID-19 in a large US city

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5–24.8%) infection rate and 29.4% (95% CrI: 28.0–31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3–12.0%] vs 25.1% [95% CrI: 23.7–26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49–57%] vs 28% [95% CrI: 27–30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0–3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC’s social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

COVIDScholar: An automated COVID-19 research aggregation and analysis platform

The ongoing COVID-19 pandemic produced far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community’s COVID-19 response lead to the emergence of new research at the remarkable rate of more than 250 papers published per day. This posed a challenge for the scientific community as traditional methods of engagement with the literature were strained by the volume of new research being produced. Meanwhile, the urgency of response lead to an increasingly prominent role for preprint servers and a diffusion of relevant research through many channels simultaneously. These factors created a need for new tools to change the way scientific literature is organized and found by researchers. With this challenge in mind, we present an overview of COVIDScholar https://covidscholar.org/, an automated knowledge portal which utilizes natural language processing (NLP) that was built to meet these urgent needs. The search interface for this corpus of more than 260,000 research articles, patents, and clinical trials served more than 33,000 users at an average of 2,000 monthly active users and a peak of more than 8,600 weekly active users in the summer of 2020. Additionally, we include an analysis of trends in COVID-19 research over the course of the pandemic with a particular focus on the first 10 months, which represents a unique period of rapid worldwide shift in scientific attention.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Designing a dynamic vulnerability index to COVID-19 for New Mexico, USA

Motivation: Non-congregational shelters are a place where COVID-19 patients can quarantine away from their household until recovered. NM wants to establish non-congregational shelters for COVID-19 patients and first responders; Where? How many rooms? Create a decision support tool to assess which counties have the most vulnerable population to COVID-19; Socioeconomic status, community practices.

60 APPLIED LIFE SCIENCES↗