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At least 559 records · Page 31

Health Analysis and Research for Public Events (HARPE) Tool (Final CRADA Report)

Based on its experience in building assessment tools, Argonne National Laboratory (Argonne) has demonstrated expertise in developing comparative methodologies and question sets that provide both a physical and cyber-based risk assessment for the commercial facilities sector. A high-level risk assessment tool can be beneficial for venues and organizations that fall under a wide array of facility characterizations, ultimately accommodating the evolving landscape of threats specific to these facilities. The Health Analysis and Research for Public Events (HARPE) Tool is an assessment that seeks to help facility managers assess and mitigate aspects of safety, security, and emergency management within their venues. With the pandemic featuring prominently in today’s landscape, we have adapted and extended the scope of the HARPE tool so that it offers users the ability to integrate assessments of their preparation for, response to, and recovery from threats faced at the venue arising from the COVID-19 pandemic. Traditional threats and hazards remain prevalent in today’s landscape, and the best defense is a proactive approach to preventing and mitigating these threats. At the very core of prevention and mitigation is the first step of conducting a risk assessment—this is the gap that HARPE fills. While it is obvious that the response to COVID-19 is health and sanitation driven, leaders within the commercial facilities sector must also know where to best extend their efforts in mitigating future threats arising from the pandemic. Public events and mass gatherings are directly impacted by COVID-19; however, with the help of HARPE, leaders can focus their attention on core impact areas related to the safety and security of returning to a new normal, as they assess their risks using the Argonne-developed tool. HARPE provides an important solution to the COVID-19 situation by assisting venue managers and health officials in identifying their risks.

59 BASIC BIOLOGICAL SCIENCES↗

SARS-CoV-2 suppresses anticoagulant and fibrinolytic gene expression in the lung

Extensive fibrin deposition in the lungs and altered levels of circulating blood coagulation proteins in COVID-19 patients imply local derangement of pathways that limit fibrin formation and/or promote its clearance. We examined transcriptional profiles of bronchoalveolar lavage fluid (BALF) samples to identify molecular mechanisms underlying these coagulopathies. mRNA levels for regulators of the kallikrein–kinin (C1-inhibitor), coagulation (thrombomodulin, endothelial protein C receptor), and fibrinolytic (urokinase and urokinase receptor) pathways were significantly reduced in COVID-19 patients. While transcripts for several coagulation proteins were increased, those encoding tissue factor, the protein that initiates coagulation and whose expression is frequently increased in inflammatory disorders, were not increased in BALF from COVID-19 patients. Our analysis implicates enhanced propagation of coagulation and decreased fibrinolysis as drivers of the coagulopathy in the lungs of COVID-19 patients.

59 BASIC BIOLOGICAL SCIENCES↗

A Quick Route to Multiple Highly Potent SARS-CoV-2 Main Protease Inhibitors**

The COVID-19 pathogen, SARS-CoV-2, requires its main protease (SC2M Pro ) to digest two of its translated long polypeptides to form a number of mature proteins that are essential for viral replication and pathogenesis. Inhibition of this vital proteolytic process is effective in preventing the virus from replicating in infected cells and therefore provides a potential COVID-19 treatment option. Guided by previous medicinal chemistry studies about SARS-CoV-1 main protease (SC1M Pro ), we have designed and synthesized a series of SC2M Pro inhibitors that contain β-(S-2-oxopyrrolidin-3-yl)-alaninal (Opal) for the formation of a reversible covalent bond with the SC2M Pro active-site cysteine C145. All inhibitors display high potency with K i values at or below 100 nM. The most potent compound, MPI3, has as a K i value of 8.3 nM. Crystallographic analyses of SC2M Pro bound to seven inhibitors indicated both formation of a covalent bond with C145 and structural rearrangement from the apoenzyme to accommodate the inhibitors. Virus inhibition assays revealed that several inhibitors have high potency in inhibiting the SARS-CoV-2-induced cytopathogenic effect in both Vero E6 and A549/ACE2 cells. Two inhibitors, MPI5 and MPI8, completely prevented the SARS-CoV-2-induced cytopathogenic effect in Vero E6 cells at 2.5-5 μM and A549/ACE2 cells at 0.16-0.31 μM. Their virus inhibition potency is much higher than that of some existing molecules that are under preclinical and clinical investigations for the treatment of COVID-19. Our study indicates that there is a large chemical space that needs to be explored for the development of SC2M Pro inhibitors with ultra-high antiviral potency.

3C-like protease↗

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin’s role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

60 APPLIED LIFE SCIENCES↗

Coordinating and Assisting Research at the SARS-CoV-2/Microbiome Nexus

Although the COVID-19 pandemic is caused by a single virus, the rest of the human microbiome appears to be involved in the disease and could influence vaccine responses while offering opportunities for microbiome-directed therapeutics. The newly formed Microbiome Centers Consortium (MCC) surveyed its membership and identified four ways to leverage the strengths and experience of microbiome centers in the response to the COVID-19 pandemic. To meet these needs, the MCC will provide a platform to coordinate clinical and environmental research, assist with practical obstacles, and help communicate the connections between the microbiome and COVID-19. We ask that microbiome researchers join us in these efforts to address the ongoing pandemic.

59 BASIC BIOLOGICAL SCIENCES↗

A Geometry-Driven Longitudal Topic Model

A simple and scalable framework for longitudinal analysis of Twitter data is developed that combines latent topic models with computational geometric methods. Dimensionality reduction tools from computational geometry are applied to learn the intrinsic manifold on which the latent, temporal topics reside. Then shortest path distances on the manifold are used to link together these topics. The proposed framework permits visualization of the low-dimensional embedding which provides clear interpretation of the complex, high-dimensional trajectories that may exist among latent topics. Practical application of the proposed framework is demonstrated through its ability to capture and effectively visualize natural progression of latent COVID-19 related topics learned from Twitter data. Interpretability of the trajectories is achieved by comparing to real-world events. In addition, the framework permits study of spatial variation in Twitter behavior for learned topics. The analysis demonstrates that the proposed framework is able to capture granular-level impact of COVID-19 on public discussions. We end by arguing that Twitter data, when analyzed within the proposed framework, can serve as a valuable supplementary data stream for COVID-related studies.

97 MATHEMATICS AND COMPUTING↗

Tracking the SARS-CoV-2 Epidemic Using the Evolutionary Rate

This project aimed to track the developing COVID-19 epidemic through measuring the virus evolutionary rate. This may give us a way to estimate the impact of prevention campaigns and other changes in the epidemiology that we otherwise would have difficulty to estimate. Based on our previous knowledge of how viruses are affected by their environment, we investigated how spread and prevention measures may affect the virus evolutionary rate. We found that SARS-CoV-2, which causes the COVID-19 epidemic, evolves relatively slow as compared to other RNA viruses. Thus, this makes it hard to see rate changes and track the spread at a fine scale. This did in fact mislead several high-profile reports in the early phases of the epidemic. We published comments and editorials in leading journals on this. Because the COVID-19 epidemic is till ongoing, and much data is still incoming, it is likely that evolutionary-epidemiological analyses will reveal important facts later on.

59 BASIC BIOLOGICAL SCIENCES↗

Science & Technology Review - July 2021 Issue

In the early weeks of the COVID-19 pandemic, Lawrence Livermore researchers mobilized to address emerging challenges and develop capabilities for detecting the SARS-CoV-2 virus and fighting COVID-19, the diseased caused by the virus. As described in the article beginning on p. 4, the Laboratory’s Innovation and Partnerships Office provided technology transfer expertise to deploy existing, in-development, and new technologies to help detect SARS-CoV-2 and treat COVID-19.

36 MATERIALS SCIENCE↗

Early Warning Signs of a Mental Health Tsunami: A Coordinated Response to Gather Initial Data Insights From Multiple Digital Services Providers

The immediate impact of coronavirus 2019 (COVID-19) on morbidity and mortality has raised the need for accurate and real-time data monitoring and communication. The aim of this study is to document the initial observations from multiple digital services providers during the COVID-19 crisis, especially those related to mental health and well-being. We used email and social media to announce an urgent call for support. Digital mental health services providers (N = 46), financial services providers (N = 4), and other relevant digital data source providers (N = 3) responded with quantitative and/or qualitative data insights. People with lived experience of distress, as service users/consumers, and carers are included as co-authors. This study provides proof-of-concept of the viability for researchers and private companies to work collaboratively toward a common good. Digital services providers reported a diverse range of mental health concerns. A recurring observation is that demand for digital mental health support has risen, and that the nature of this demand has also changed since COVID-19, with an apparent increased presentation of anxiety and loneliness. Following this study, we will continue to work with providers in more in-depth ways to capture follow-up insights at regular time points. We will also onboard new providers to address data representativeness. Looking ahead, we anticipate the need for a rigorous process to interpret insights from an even wider variety of sources in order to monitor and respond to mental health needs.

60 APPLIED LIFE SCIENCES↗

SARS-CoV-2 Monitoring in Wastewater Reveals Novel Variants and Biomarkers of Infection

Wastewater-based epidemiology (WBE) is a popular tool for the early indication of community spread of infectious diseases. WBE emerged as an effective tool during the COVID-19 pandemic and has provided meaningful information to minimize the spread of infection. Here, we present a combination of analyses using the correlation of viral gene copies with clinical cases, sequencing of wastewater-derived RNA for the viral mutants, and correlative analyses of the viral gene copies with the bacterial biomarkers. Our study provides a unique platform for potentially using the WBE-derived results to predict the spread of COVID-19 and the emergence of new variants of concern. Further, we observed a strong correlation between the presence of SARS-CoV-2 and changes in the microbial community of wastewater, particularly the significant changes in bacterial genera belonging to the families of Lachnospiraceae and Actinomycetaceae . Our study shows that microbial biomarkers could be utilized as prediction tools for future infectious disease surveillance and outbreak responses. Overall, our comprehensive analyses of viral spread, variants, and novel bacterial biomarkers will add significantly to the growing body of literature on WBE and COVID-19.

59 BASIC BIOLOGICAL SCIENCES↗

Viral Inhibitors Derived from Macroalgae, Microalgae, and Cyanobacteria: A review of antiviral potential throughout pathogenesis

Viruses are abiotic obligate parasites utilizing complex mechanisms to hijack cellular machinery and reproduce, causing multiple harmful effects in the process. Viruses represent a growing global health concern; at the time of writing, COVID-19 has killed at least two million people around the world and devastated global economies. Lingering concern regarding the virus’ prevalence yet hampers return to normalcy. While catastrophic in and of itself, COVID-19 further heralds in a new era of human-disease interaction characterized by the emergence of novel viruses from natural sources with heretofore unseen frequency. Due to deforestation, population growth, and climate change, we are encountering more viruses that can infect larger groups of people with greater ease and increasingly severe outcomes. The devastation of COVID-19 and forecasts of future human/disease interactions call for a creative reconsideration of global response to infectious disease. There is an urgent need for accessible, cost-effective antiviral (AV) drugs that can be mass-produced and widely distributed to large populations. Development of AV drugs should be informed by a thorough understanding of viral structure and function as well as human biology. To maximize efficacy, minimize cost, and reduce development of drug-resistance, these drugs would ideally operate through a varied set of mechanisms at multiple stages throughout the course of infection. Due to their abundance and diversity, natural compounds are ideal for such comprehensive therapeutic interventions. Promising sources of such drugs are found throughout nature; especially remarkable are the algae, a polyphyletic grouping of phototrophs that produce diverse bioactive compounds. While not much literature has been published on the subject, studies have shown that these compounds exert antiviral effects at different stages of viral pathogenesis. In this review, we follow the course of viral infection in the human body and evaluate the AV effects of algae-derived compounds at each stage. Specifically, we examine the AV activities of algae-derived compounds at the entry of viruses into the body, transport through the body via the lymph and blood, infection of target cells, and immune response. We discuss what is known about algae-derived compounds that may interfere with the infection pathways of SARS-CoV-2; and review which algae are promising sources for AV agents or AV precursors that, with further investigation, may yield life-saving drugs due to their diversity of mechanisms and exceptional pharmaceutical potential.

Algae, antiviral, SARS-CoV-2, seaweed, cyanobacter↗

Efficacy of antivirals and mRNA vaccination against an XBF clinical isolate

Recombination events occur frequently in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in genetic diversity. Because these events contribute to altered host immune evasion and antiviral susceptibility, it is crucial to evaluate the efficacy of COVID-19 vaccines and antivirals against recombinant variants. As of March 2023, XBB.1.5, a recombinant sublineage of XBB, is currently the dominant form globally (Fig. S1A, Supplementary Appendix). XBB emerged as a result of recombination between two BA.2 descendants, BJ.1 and BM.1.1.1 (a progeny of BA.2.75). We and other groups have shown that XBB.1.5 is resistant to several therapeutic monoclonal antibodies and effectively evades humoral immunity elicited by natural infection or COVID-19 vaccination.1, 2, 3 By March 30, 2023, an additional recombinant variant, XBF, had been sampled 8966 times in 47 countries and territories in GISAID, reaching it highest prevalence in Australia and New Zealand (Fig. S2, Supplementary Appendix). XBF is still increasing in frequency, although the prevalence of XBB.1.5 appears to be increasing at a faster pace in most regions (Fig. S1B, Supplementary Appendix). XBF is a recombinant of BA.5.2.3 (a descendant of BA.5) and CJ.1 (a descendant of BA.2.75) and, like CJ.1, has an additional three substitutions (R346T, F486P, and F490S) in the receptor-binding domain (RBD) of the consensus form of its spike protein compared to baseline BA.2.75 (Fig. S3A, Supplementary Appendix). CJ.1 and its related sublineage CJ.1.1 did not expand as extensively as XBF, being sampled in GISAID only 1589 and 142 times respectively. CJ.1 was found circulating in many countries, but most commonly sampled in South Korea, where it is still increasing and has currently reached about 5% of the sampled population. CJ.1.1 was most frequently sampled in Malaysia and Singapore, but remained rare in both nations, peaking at about 1% of the sample in December of 2022. Despite the importance of these related variants, we have no information about the antiviral efficacy and immunity induced by COVID-19 vaccines against a clinical isolate of XBF.

60 APPLIED LIFE SCIENCES↗

The DNA glycosylase NEIL2 is protective during SARS-CoV-2 infection

SARS-CoV-2 infection-induced aggravation of host innate immune response not only causes tissue damage and multiorgan failure in COVID-19 patients but also induces host genome damage and activates DNA damage response pathways. To test whether the compromised DNA repair capacity of individuals modulates the severity of COVID-19 infection, we analyze DNA repair gene expression in publicly available patient datasets and observe a lower level of the DNA glycosylase NEIL2 in the lungs of severely infected COVID-19 patients. This observation of lower NEIL2 levels is further validated in infected patients, hamsters and ACE2 receptor-expressing human A549 (A549-ACE2) cells. Furthermore, delivery of recombinant NEIL2 in A549-ACE2 cells shows decreased expression of proinflammatory genes and viral E-gene, as well as lowers the yield of viral progeny compared to mock-treated cells. Mechanistically, NEIL2 cooperatively binds to the 5’-UTR of SARS-CoV-2 genomic RNA to block viral protein synthesis. Collectively, these data strongly suggest that the maintenance of basal NEIL2 levels is critical for the protective response of hosts to viral infection and disease.

60 APPLIED LIFE SCIENCES↗

Synthetic method of analogues for emerging infectious disease forecasting

The Method of Analogues (MOA) has gained popularity in the past decade for infectious disease forecasting due to its non-parametric nature. In MOA, the local behavior observed in a time series is matched to the local behaviors of several historical time series. The known values that directly follow the historical time series that best match the observed time series are used to calculate a forecast. This non-parametric approach leverages historical trends to produce forecasts without extensive parameterization, making it highly adaptable. However, MOA is limited in scenarios where historical data is sparse. This limitation was particularly evident during the early stages of the COVID-19 pandemic, where the emerging global epidemic had little-to-no historical data. In this work, we propose a new method inspired by MOA, called the Synthetic Method of Analogues (sMOA). sMOA replaces historical disease data with a library of synthetic data that describe a broad range of possible disease trends. This model circumvents the need to estimate explicit parameter values by instead matching segments of ongoing time series data to a comprehensive library of synthetically generated segments of time series data. We demonstrate that sMOA has competitive performance with state-of-the-art infectious disease forecasting models, out-performing 78% of models from the COVID-19 Forecasting Hub in terms of averaged Mean Absolute Error and 76% of models from the COVID-19 Forecasting Hub in terms of averaged Weighted Interval Score. Additionally, we introduce a novel uncertainty quantification methodology designed for the onset of emerging epidemics. Developing versatile approaches that do not rely on historical data and can maintain high accuracy in the face of novel pandemics is critical for enhancing public health decision-making and strengthening preparedness for future outbreaks.

97 MATHEMATICS AND COMPUTING↗

Quantification of early nonpharmaceutical interventions aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. Here, we investigated these differences in disease transmission dynamics with the objective of quantifying the contributions of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission). We considered a compartmental model accounting for distinct periods of NPIs to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

60 APPLIED LIFE SCIENCES↗

SARS-CoV-2 Cases Reported on International Arriving and Domestic Flights: United States, January 2020–December 2021

Objectives. To describe trends in the number of air travelers categorized as infectious with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2; the virus that causes COVID-19) in the context of total US COVID-19 vaccinations administered, and overall case counts of SARS-CoV-2 in the United States. Methods. We searched the Quarantine Activity Reporting System (QARS) database for travelers with inbound international or domestic air travel, a positive SARS-CoV-2 lab result, and a surveillance categorization of SARS-CoV-2 infection reported during January 2020 to December 2021. Travelers were categorized as infectious during travel if they had arrival dates from 2 days before to 10 days after symptom onset or a positive viral test. Results. We identified 80 715 persons meeting our inclusion criteria; 67 445 persons (83.6%) had at least 1 symptom reported. Of 67 445 symptomatic passengers, 43 884 (65.1%) reported an initial symptom onset date after their flight arrival date. The number of infectious travelers mirrored the overall number of US SARS-CoV-2 cases. Conclusions. Most travelers in the study were asymptomatic during travel, and therefore unknowingly traveled while infectious. During periods of high community transmission, it is important for travelers to stay up to date with COVID-19 vaccinations and consider wearing a high-quality mask to decrease the risk of transmission. (Am J Public Health. 2023;113(8):904–908. https://doi.org/10.2105/AJPH.2023.307325 )

Public, Environmental & Occupational Health↗

Solar Steam on Demand

INTRODUCTION: This Report summarizes the research and development project performed by Sunvapor and the subrecipient National Renewable Energy Laboratory (NREL) during the period of 10/01/2018-9/30/2021. The work was aimed at the economic integration of solar steam with an industrial process, and in particular, the advantages that a novel type of thermal energy storage and collector design could bring to the system. The completed work includes experimental research on the storage material, design of the collector, engineering of a complete solar steam plant, and economic analysis. The plant was, in the end, not constructed, due to COVID-19 impacts to the project host. PURPOSE: The purpose of the project was to test the hypothesis that a levelized cost of heat (LCOH) of 2¢/kWh delivered to a steam-consuming process, including energy discharged from storage, could be feasibly achieved. PROJECT OBJECTIVES: For Budget Period 1 our objectives were to engineer a prototype industrial solar steam generation system, and design and test a Latent Heat Energy Storage (LHES) lab-scale system. For Budget Period 2 our objectives were to construct and test the solar steam prototype plant, and to build and factory-test a full LHES module. For Budget Period 3 our objective was to integrate the storage module with the solar steam generator, show successful long duration energy tests of the combined system, and use the results to project the LCOH of delivered steam to a second-generation plant. PROJECT OUTCOMES: Various phase change materials (PCMs) for the LHES were tested for compatibility with industrial steam uses as measured by phase change temperature, stability of latent heat of fusion, and their corrosive effects on steel (the heat exchanger material). Two of these materials (sodium formate and sodium/ potassium) showed potential to meet the technical criteria. The estimated cost of a complete LHES module with these materials did not meet economic targets. The developmental collector design builds from previous work to exploit the potential cost advantages of a spaceframe of lumber construction. Design improvements were achieved in assembly efficiency and structural performance. A complete engineering package was completed for the solar steam system without storage that included the developmental as well as commercial arrays. The plant was permitted for construction. The storage CAPEX for a reference plant was estimate to be greater than $\$ 57$/kWh. The LCOH of the system without storage and with developmental collectors of lumber construction was projected to be 2¢/kWh, assuming a FCR of 8.2% over thirty years. PROJECT MILESTONES: The Milestones fully achieved in the first Budget Period includes obtaining a Letter of Intent from an industrial steam-consuming project host, issuance of a construction permit, and corrosion resistance. The Milestone that was partly achieved was the degradation in the latent heat of fusion. Milestones associated with Budget Periods 2 and 3, related to the construction and operation of the plant were not achieved as a result of the host shutting down the plant due to COVID-19 impacts. CONCLUSIONS: Sunvapor was able to secure an agreement with a host to build a fully engineered and permitted solar steam plant that met the host’s economic goals. As a basis for comparison, the solar field design was comprised of eight commercial collector arrays and one developmental Green Parabolic Trough Collector (GPTC) array. The projected LCOH with a solar field entirely populated with a second generation GPTC met the goal of 2¢/kWh. The experimental program concerning the PCM indicated the feasibility of meeting their technical requirements for industrial steam uses. The cost of the complete LHES exceeded its $\$ 14$/kWh target, and therefore the inclusion of LHES could not be economically justified. Due to COVID-19 impacts on the host, the solar steam plant was not constructed.

14 SOLAR ENERGY↗

Interventions to Disrupt Coronavirus Disease Transmission at a University, Wisconsin, USA, August–October 2020

University settings have demonstrated potential for coronavirus disease (COVID-19) outbreaks; they combine congregate living, substantial social activity, and a young population predisposed to mild illness. Using genomic and epidemiologic data, we describe a COVID-19 outbreak at the University of Wisconsin-Madison, Madison, Wisconsin, USA. During August-October 2020, a total of 3,485 students, including 856/6,162 students living in dormitories, tested positive. Case counts began rising during move-in week, August 25–31, 2020, then rose rapidly during September 1–11, 2020. The university initiated multiple prevention efforts, including quarantining 2 dormitories; a subsequent decline in cases was observed. Genomic surveillance of cases from Dane County, in which the university is located, did not find evidence of transmission from a large cluster of cases in the 2 quarantined dorms during the outbreak. Coordinated implementation of prevention measures can reduce COVID-19 spread in university settings and may limit spillover to the surrounding community.

60 APPLIED LIFE SCIENCES↗