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At least 667 records · Page 37

Learning from the Pandemic: the Future of Meetings in HEP and Beyond

The COVID-19 pandemic has by-and-large prevented in-person meetings since March 2020. While the increasing deployment of effective vaccines around the world is a very positive development, the timeline and pathway to "normality" is uncertain and the "new normal" we will settle into is anyone's guess. Particle physics, like many other scientific fields, has more than a year of experience in holding virtual meetings, workshops, and conferences. A great deal of experimentation and innovation to explore how to execute these meetings effectively has occurred. Therefore, it is an appropriate time to take stock of what we as a community learned from running virtual meetings and discuss possible strategies for the future. Continuing to develop effective strategies for meetings with a virtual component is likely to be important for reducing the carbon footprint of our research activities, while also enabling greater diversity and inclusion for participation. This report summarizes a virtual two-day workshop on Virtual Meetings held May 5-6, 2021 which brought together experts from both inside and outside of high-energy physics to share their experiences and practices with organizing and executing virtual workshops, and to develop possible strategies for future meetings as we begin to emerge from the COVID-19 pandemic. This report outlines some of the practices and tools that have worked well which we hope will serve as a valuable resource for future virtual meeting organizers in all scientific fields.

Neubauer, Mark S.↗

The 2021 Annual CSEWG Meeting at Nuclear Data Week(s)

From November 15-19, 2021, CSEWG held its annual meeting during Brookhaven National Laboratory’s Nuclear Data Week(s)1. The combined event was held via zoom (due to COVID travel restrictions) and there were 175 registered attendees. This was CSEWG’s 3rd fully virtual meeting and, by all accounts, it was a success. The timetable and talks are available at https://indico.bnl.gov/event/13121/overview for registered participants. This meeting began with the welcoming of the new ENDF Library Manager, Gustavo Nobre, the announcement that ENDF/B-VIII.1’s release will be delayed until February 2024 due to COVID induced delays, and the adoption of a draft Code of Conduct. This last point is notable since CSEWG is known for its lively physics and engineering discussions. However, as professionals, we must endeavor to keep our discussions civil, collegial, and inclusive.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Demand Shocks and Supply Chain Resilience: An Agent Based Modelling Approach and Application to the Potato Supply Chain

The food supply chain has experienced major disruptions from both demand and supply sides during the COVID-19 pandemic. While some consequences such as food waste are directly caused by the disruption due to supply chain inefficiency, others are indirectly caused by a change in consumer’s preferences. As a result, evaluating food supply chain resilience is a difficult task. With an attempt to understand impacts of demand on the food supply chain, we developed an agent-based model based on the case of Idaho’s potato supply chain. Results showed that not only the magnitude but also the timing of the demand shock will have different impacts on various stakeholders of the supply chain. Our contribution to the literature is twofold. First, the model helps explain why food waste and shortages may occur with dramatic shifts in consumer demand. Second, this paper provides a new angle on evaluating the various mitigation strategies and policy responses to disruptions beyond COVID-19.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Rapid, Sensitive, Label-Free Electrical Detection of SARS-CoV-2 in Nasal Swab Samples

Rapid diagnosis of coronavirus disease 2019 (COVID-19) is key for the long-term control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) amid renewed threats of mutated SARS-CoV-2 around the world. Here, we report on an electrical label-free detection of SARS-CoV-2 in nasopharyngeal swab samples directly collected from outpatients or in saliva-relevant conditions by using a remote floating-gate field-effect transistor (RFGFET) with a 2-dimensional reduced graphene oxide (rGO) sensing membrane. RFGFET sensors demonstrate rapid detection (<5 min), a 90.6% accuracy from 8 nasal swab samples measured by 4 different devices for each sample, and a coefficient of variation (CV) < 6%. Also, RFGFET sensors display a limit of detection (LOD) of pseudo-SARS-CoV-2 that is 10 000-fold lower than enzyme-linked immunosorbent assays, with a comparable LOD to that of reverse transcriptionpolymerase chain reaction (RT-PCR) for patient samples. To achieve this, comprehensive systematic studies were performed regarding interactions between SARS-CoV-2 and spike proteins, neutralizing antibodies, and angiotensin-converting enzyme 2, as either a biomarker (detection target) or a sensing probe (receptor) functionalized on the rGO sensing membrane. Finally, taken together, this work may have an immense effect on positioning FET bioelectronics for rapid SARS-CoV-2 diagnostics.

60 APPLIED LIFE SCIENCES↗

Molecular Architecture of Early Dissemination and Massive Second Wave of the SARS-CoV-2 Virus in a Major Metropolitan Area

We sequenced the genomes of 5,085 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains causing two coronavirus disease 2019 (COVID-19) disease waves in metropolitan Houston, TX, an ethnically diverse region with 7 million residents. The genomes were from viruses recovered in the earliest recognized phase of the pandemic in Houston and from viruses recovered in an ongoing massive second wave of infections. The virus was originally introduced into Houston many times independently. Virtually all strains in the second wave have a Gly614 amino acid replacement in the spike protein, a polymorphism that has been linked to increased transmission and infectivity. Patients infected with the Gly614 variant strains had significantly higher virus loads in the nasopharynx on initial diagnosis. We found little evidence of a significant relationship between virus genotype and altered virulence, stressing the linkage between disease severity, underlying medical conditions, and host genetics. Some regions of the spike protein—the primary target of global vaccine efforts—are replete with amino acid replacements, perhaps indicating the action of selection. We exploited the genomic data to generate defined single amino acid replacements in the receptor binding domain of spike protein that, importantly, produced decreased recognition by the neutralizing monoclonal antibody CR3022. Our report represents the first analysis of the molecular architecture of SARS-CoV-2 in two infection waves in a major metropolitan region. The findings will help us to understand the origin, composition, and trajectory of future infection waves and the potential effect of the host immune response and therapeutic maneuvers on SARS-CoV-2 evolution.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanistic modelling of SARS-CoV-2 and other infectious diseases and the effects of therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical and modeling communities during the early days of the AIDS epidemic. Its successes lead to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV), which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus (RSV), West Nile virus (WNV), Zika virus, and SAR-CoV-2, which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. Furthermore, we then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize non-pharmaceutical and pharmaceutical interventions of the COVID-19 pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein “Everything should be made as simple as possible, but not simpler”, and this idea underlies the modeling we describe below.

60 APPLIED LIFE SCIENCES↗

Longitudinal SARS-CoV-2 seroprevalence in Portugal and antibody maintenance 12 months after infection

During the COVID-19 pandemic, Portugal has experienced three distinct SARS-CoV-2 infection waves. We previously documented the prevalence of SARS-CoV-2 immunity, measured by specific antibodies, in September 2020, 6 months after the initial moderate wave. Here, we show the seroprevalence changes 6 months later, up to the second week of March 2021, shortly following the third wave, which was one of the most severe in the world, and 2 months following the start of the vaccination campaign. A longitudinal epidemiological study was conducted, with a stratified quota sample of the Portuguese population. Serological testing was performed, including ELISA determination of antibody class and titers. The proportion of seropositives, which was 2.2% in September 2020, rose sharply to 17.3% (95% CI: 15.8–18.8%) in March 2021. Importantly, circulating IgG and IgA antibody levels were very stable 6 months after the initial determination and up to a year after initial infection, indicating long-lasting infection immunity against SARS-CoV-2. Moreover, vaccinated people had higher IgG levels from 3 weeks post-vaccination when compared with previously infected people at the same time post-infection.

60 APPLIED LIFE SCIENCES↗

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Additionally, based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10 -3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

59 BASIC BIOLOGICAL SCIENCES↗

PANDEMIC: Occupancy driven predictive ventilation control to minimize energy consumption and infection risk

During the SARS-CoV-2 (COVID-19) pandemic, governments around the world have formulated policies requiring ventilation systems to operate at a higher outdoor fresh air flow rate for a sufficient time, which has led to a sharp increase in building energy consumption. Therefore, it is necessary to identify an energy-efficient ventilation strategy to reduce the risk of infection. In this study, we developed an occupant-number-based model predictive control (OBMPC) algorithm for building ventilation systems. First, we collected the occupancy and Heating, ventilation, and air conditioning system (HVAC) data from March to July 2021. Then, four different models (Auto regression moving average-based multilayer perceptron (ARMA_MLP), Recurrent neural networks (RNN), Long short-term memory networks (LSTM), and Nonhomogeneous Markov with change points detection (NH_Markov)) were used to predict the number of room occupants from 15 min to 24 h ahead with an interval output. We found that each model could predict the number of occupants with 85% accuracy using a one-person offset. Furthermore, the accuracy of 15 min of the ahead prediction could reach 95% with a one-person offset, but none of them could track abrupt changes. The occupancy prediction results were used to calculate the ventilation demand using the Wells-Riley equation, and the upper bound can maintain an infection risk lower than 2% for 93% of the day. This OBMPC model could reduce the coil load by 52.44% and shift the peak load by 3 h up to 5 kW compared with 24 × 7 h full outdoor air (OA) system when people wear masks in the space. The occupancy prediction uncertainty could cause a 9% to 26% difference in demand ventilation, a 0.3°C to 2.4°C difference in zone temperature, a 28.5% to 44.5% difference in outdoor airflow rate, and a 10.7% to 28.2% difference in coil load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics

Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic.

60 APPLIED LIFE SCIENCES↗

Investigation of potential aerosol transmission and infectivity of SARS-CoV-2 through central ventilation systems

Here we evaluate the concentrations and probabilities of infection for both building interior and exterior exposure sources using a well-mixed model in a connected multizone building. As a central hub of many community and economic activities, buildings provide social connectivity, but the COVID-19 pandemic has reduced social connectivity due to concerns of viral spread within buildings. Although single zone models of infectious spread are well studied, the impact of aerosolized spread of SARS-CoV-2 via air handling systems in multizone buildings remains unexplored. Here we evaluate the influence of filtration, air exchange rates, and the fraction of outdoor air on the probability of infection using the well-known well-mixed modeling approach for a multizone. We find filtration lowers the concentration and probability of infection in both source and connected rooms provided at least some air is recirculated, but that probability is not zero. Filtration has no influence without recirculation or unless the outdoor air contains virus. We find that increasing the air exchange rate removes virus from the source room faster but also increases the rate of exposure to connected rooms. Therefore, slower air exchange rates reduce infectivity in connected rooms at shorter durations, but higher air exchange rates reduce infectivity at longer durations. We further find that when outdoor air is virus free, increasing the fraction of outdoor air is helpful, but, when outdoor air is infective, pathogen exposure inside can persist for hours after a short-term release.

60 APPLIED LIFE SCIENCES↗

Assessing the use of portable air cleaners for reducing exposure to airborne diseases in a conference room with thermal stratification

The COVID-19 pandemic has highlighted the need for strategies that mitigate the risk of aerosol disease transmission in indoor environments with different ventilation strategies. It is necessary for building operators to be able to estimate and compare the relative impacts of different mitigation strategies to determine suitable strategies for a particular situation. Using a validated CFD model, this study simulates the dispersion of exhaled contaminants in a thermally stratified conference room with overhead heating. The impacts of portable air-cleaners (PACs) on the room airflow and contaminant distribution were evaluated for different PAC locations and flow rates, as well as for different room setups (socially distanced or fully occupied). To obtain a holistic view of a strategy's impacts under different release scenarios, we simultaneously model the steady-state distribution of aerosolized virus contaminants from eight distinct sources in 18 cases for a total of 144 release scenarios. The simulations show that the location of the source, the PAC settings, and the room set-up can impact the average exposure and PAC effectiveness. For this studied case, the PACs reduced the room average exposure by 31%-66% relative to the baseline case. Some occupant locations were shown to have a higher-than-average exposure, particularly those seated near the airflow outlet, and occupants closest to sources tended to see the highest exposure from said source. We found that these PACs were effective at reducing the stratification caused by overhead heating, and also identified at least one sub-optimal location for placing a PAC in this space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Tradeoffs among indoor air quality, financial costs, and CO 2 emissions for HVAC operation strategies to mitigate indoor virus in U.S. office buildings

Adapting building operation during the COVID-19 pandemic to improve indoor air quality (IAQ) while ensuring sustainable solutions in terms of costs and CO 2 emissions is challenging and limited in literature. Our previous study investigated different HVAC operation strategies, including increased filtration using MERV 10, MERV 13, or HEPA filters, as well as supplying 100% outdoor air into buildings for a system initially sized for MERV 10 filtration. This paper significantly extends that research by systematically analyzing the potential financial and environmental impact for different locations in the U.S. The previous medium office building system model is improved to account for operation in different climates. New evaluation metrics are created to consider the comprehensive impact of improving IAQ on costs and CO 2 emissions, using dynamic emission factors for electricity generation depending on the location. HVAC operation strategies are studied in five different locations across the United States, with distinct climates and electricity sources. In four of the five locations, MERV 13 filtration offers the best improvement in IAQ per increase in costs and emissions relative to MERV 10. The exception is the mildest climate of San Diego, where use of 100% outdoor air provides the best IAQ with a limited increase in costs and emissions. Finally, a system not sized for HEPA filtration can lead to increased costs and emissions without much improvement in IAQ.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Structures of Human Antibodies Bound to SARS-CoV-2 Spike Reveal Common Epitopes and Recurrent Features of Antibodies

Neutralizing antibody responses to coronaviruses mainly target the receptor-binding domain (RBD) of the trimeric spike. Here, we characterized polyclonal immunoglobulin Gs (IgGs) and Fabs from COVID-19 convalescent individuals for recognition of coronavirus spikes. Plasma IgGs differed in their focus on RBD epitopes, recognition of alpha- and beta-coronaviruses, and contributions of avidity to increased binding/ neutralization of IgGs over Fabs. Using electron microscopy, we examined specificities of polyclonal plasma Fabs, revealing recognition of both S1 A and RBD epitopes on SARS-CoV-2 spike. Moreover, a 3.4 Å cryoelectron microscopy (cryo-EM) structure of a neutralizing monoclonal Fab-spike complex revealed an epitope that blocks ACE2 receptor binding. Modeling based on these structures suggested different potentials for inter-spike crosslinking by IgGs on viruses, and characterized IgGs would not be affected by identified SARS-CoV-2 spike mutations. Overall, our studies structurally define a recurrent anti-SARS-CoV-2 antibody class derived from VH3-53/VH3-66 and similarity to a SARS-CoV VH3-30 antibody, providing criteria for evaluating vaccine-elicited antibodies.

59 BASIC BIOLOGICAL SCIENCES↗

Mapping Neutralizing and Immunodominant Sites on the SARS-CoV-2 Spike Receptor-Binding Domain by Structure-Guided High-Resolution Serology

We report analysis of the specificity and kinetics of neutralizing antibodies (nAbs) elicited by SARS-CoV-2 infection is crucial for understanding immune protection and identifying targets for vaccine design. In a cohort of 647 SARS-CoV-2-infected subjects, we found that both the magnitude of Ab responses to SARS-CoV-2 spike (S) and nucleoprotein and nAb titers correlate with clinical scores. The receptor-binding domain (RBD) is immunodominant and the target of 90% of the neutralizing activity present in SARS-CoV-2 immune sera. Whereas overall RBD-specific serum IgG titers waned with a half-life of 49 days, nAb titers and avidity increased over time for some individuals, consistent with affinity maturation. We structurally defined an RBD antigenic map and serologically quantified serum Abs specific for distinct RBD epitopes leading to the identification of two major receptor-binding motif antigenic sites. Our results explain the immunodominance of the receptor-binding motif and will guide the design of COVID-19 vaccines and therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗

SARS-CoV-2 variant B.1.1.7 is susceptible to neutralizing antibodies elicited by ancestral spike vaccines

All current vaccines for COVID-19 utilize ancestral SARS-CoV-2 spike with the goal of generating protective neutralizing antibodies. The recent emergence and rapid spread of several SARS-CoV-2 variants carrying multiple spike mutations raise concerns about possible immune escape. One variant, first identified in the United Kingdom (B.1.1.7, also called 20I/501Y.V1), contains eight spike mutations with potential to impact antibody therapy, vaccine efficacy, and risk of reinfection. Here in this paper, we show that B.1.1.7 remains sensitive to neutralization, albeit at moderately reduced levels (~2-fold), by serum samples from convalescent individuals and recipients of an mRNA vaccine (mRNA-1273, Moderna) and a protein nanoparticle vaccine (NVX-CoV2373, Novavax). A subset of monoclonal antibodies to the receptor binding domain (RBD) of spike are less effective against the variant, while others are largely unaffected. Lastly, these findings indicate that variant B.1.1.7 is unlikely to be a major concern for current vaccines or for an increased risk of reinfection.

60 APPLIED LIFE SCIENCES↗

Resource distribution under spatiotemporal uncertainty of disease spread: Stochastic versus robust approaches

We consider the problem of optimizing locations of distribution centers (DCs) and plans for distributing resources such as test kits and vaccines, under spatiotemporal uncertainties of disease spread and demand for the resources. We aim to balance the operational cost (including costs of deploying facilities, shipping, and storage) and quality of service (reflected by demand coverage), while ensuring equity and fairness of resource distribution across multiple populations. We compare a sample-based stochastic programming (SP) approach with a distributionally robust optimization (DRO) approach using a moment-based ambiguity set. Numerical studies are conducted on instances of distributing COVID-19 vaccines in the United States and test kits, to compare SP and DRO models with a deterministic formulation using estimated demand and with the current resource distribution plans implemented in the US. We demonstrate the results over distinct phases of the pandemic to estimate the cost and speed of resource distribution depending on scale and coverage, and show the “demand-driven” properties of the SP and DRO solutions. Furthermore, our results further indicate that if the worst-case unmet demand is prioritized, then the DRO approach is preferred despite of its higher overall cost. Nevertheless, the SP approach can provide an intermediate plan under budgetary restrictions without significant compromises in demand coverage.

97 MATHEMATICS AND COMPUTING↗

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

60 APPLIED LIFE SCIENCES↗