The application of machine learning (ML) models to optimize antibody affinity to an antigen is gaining prominence. Unfortunately, the small and biased nature of the publicly available antibody-antigen interaction datasets makes it challenging to build an ML model that can accurately predict binding affinity changes due to mutations (ΔΔ G ). Recognizing these inherent limitations, we reformulated the problem to ask whether an ML model capable of classifying deleterious vs non-deleterious mutations can guide antibody affinity maturation in a practical setting. To test this hypothesis, we developed a Random Forest classifier (Antibody Random Forest Classifier or AbRFC) with expert-guided features and integrated it into a computational-experimental workflow. AbRFC effectively predicted non-deleterious mutations on an in-house validation dataset that is free of biases seen in the publicly available training datasets. Furthermore, experimental screening of a limited number of predictions from the model (<10^2 designs) identified affinity-enhancing mutations in two unrelated SARS-CoV-2 antibodies, resulting in constructs with up to 1000-fold increased binding to the SARS-COV-2 RBD. Our findings indicate that accurate prediction and screening of non-deleterious mutations using machine learning offers a powerful approach to improving antibody affinity.

Poliovirus can cause poliomyelitis and lifelong paralysis. Although wild poliovirus types 2 and 3 have been eradicated, wild poliovirus type 1 and vaccine-derived polioviruses are still circulating in multiple countries worldwide. In 2022, a case of paralytic polio caused by vaccine-derived poliovirus type 2 was identified in an unvaccinated young adult in New York. This case and subsequent detection of community transmission underscored the ongoing risk for importation of poliovirus into the United States and risk for poliomyelitis among unvaccinated persons. However, previous Advisory Committee on Immunization Practices (ACIP) recommendations for adult polio vaccination were limited to adults known to be at increased risk for exposure. During October 2022-June 2023, the ACIP Polio Vaccine Work Group reviewed data on poliovirus surveillance and epidemiology, safety and effectiveness of inactivated poliovirus vaccine (IPV), and other considerations outlined in the ACIP Evidence to Recommendations Framework. On June 21, 2023, ACIP voted to recommend that all U.S. adults aged ≥18 years who are known or suspected to be unvaccinated or incompletely vaccinated against polio complete a primary polio vaccination series with IPV. This report summarizes evidence considered for this recommendation and provides clinical guidance for the use of IPV in adults.

Defining predictors of antigen-binding affinity of antibodies is valuable for engineering therapeutic antibodies with high binding affinity to their targets. However, this task is challenging owing to the huge diversity in the conformations of the complementarity determining regions of antibodies and the mode of engagement between antibody and antigen. In this study, we used the structural antibody database (SAbDab) to identify features that can discriminate high- and low-binding affinity across a 5-log scale. First, we abstracted features based on previously learned representations of protein-protein interactions to derive 'complex' feature sets, which include energetic, statistical, network-based, and machine-learned features. Second, we contrasted these complex feature sets with additional 'simple' feature sets based on counts of contacts between antibody and antigen. By investigating the predictive potential of 700 features contained in the eight complex and simple feature sets, we observed that simple feature sets perform comparably to complex feature sets in classification of binding affinity. Moreover, combining features from all eight feature-sets provided the best classification performance (median cross-validation AUROC and F1-score of 0.72). Of note, classification performance is substantially improved when several sources of data leakage (e.g., homologous antibodies) are not removed from the dataset, emphasizing a potential pitfall in this task. We additionally observe a classification performance plateau across diverse featurization approaches, highlighting the need for additional affinity-labeled antibody-antigen structural data. The findings from our present study set the stage for future studies aimed at multiple-log enhancement of antibody affinity through feature-guided engineering.

Antiviral innate immunity is orchestrated by the interferon system, which appeared in ancestors of jawed vertebrates. Interferon upregulation induces hundreds of interferon-stimulated-genes (ISGs) with effector or regulatory functions. Here we investigated the evolutionary diversification of ISG responses through comparison of two salmonid fishes, accounting for the impact of sequential whole genome duplications ancestral to teleosts and salmonids. We analysed the transcriptomic response of the IFN pathway in the head kidney of rainbow trout and Atlantic salmon, which separated 25–30 Mya. We identified a large set of ISGs conserved in both species and cross-referenced them with zebrafish and human ISGs. In contrast, around one-third of salmonid ISG lacked orthologs in human, mouse, chicken or frog, and often between rainbow trout and Atlantic salmon, revealing a fast-evolving, lineage-specific arm of the antiviral response. This study also provides a key resource for in-depth functional analysis of ISGs in salmonids of commercial significance.

The application of Machine Learning (ML) tools to engineer novel antibodies having predictable functional properties is gaining prominence. Herein, we present a platform that employs an ML-guided optimization of the complementarity-determining region (CDR) together with a CDR framework (FR) shuffling method to engineer affinity-enhanced and clinically developable monoclonal antibodies (mAbs) from a limited experimental screen space (order of 10^2 designs) using only two experimental iterations. Although high-complexity deep learning models like graph neural networks (GNNs) and large language models (LLMs) have shown success on protein folding with large dataset sizes, the small and biased nature of the publicly available antibody-antigen interaction datasets is not sufficient to capture the diversity of mutations virtually screened using these models in an affinity enhancement campaign. To address this key gap, we introduced inductive biases learned from extensive domain knowledge on protein-protein interactions through feature engineering and selected model hyper parameters to reduce overfitting of the limited interaction datasets. Notably we show that this platform performs better than GNNs and LLMs on an in-house validation dataset that is enriched in diverse CDR mutations that go beyond alanine-scanning. To illustrate the broad applicability of this platform, we successfully solved a challenging problem of redesigning two different anti-SARS-COV-2 mAbs to enhance affinity (up to 2 orders of magnitude) and neutralizing potency against the dynamically evolving SARS-COV-2 Omicron variants.

The Omicron variant features enhanced transmissibility and antibody escape. Here, we describe the Omicron receptor-binding domain (RBD) mutational landscape using amino acid interaction (AAI) networks, which are well suited for interrogating constellations of mutations that function in an epistatic manner. Using AAI, we map Omicron mutations directly and indirectly driving increased escape breadth and depth in class 1-4 antibody epitopes. Further, we present epitope networks for authorized therapeutic antibodies and assess perturbations to each antibody's epitope. Since our initial modeling following the identification of Omicron, these predictions have been realized by experimental findings of Omicron neutralization escape from therapeutic antibodies ADG20, AZD8895, and AZD1061. Importantly, the AAI predicted escape resulting from indirect epitope perturbations was not captured by previous sequence or point mutation analyses. Finally, for several Omicron RBD mutations, we find evidence for a plausible role in enhanced transmissibility via disruption of RBD-down conformational stability at the RBDdown- RBDdown interface.

The SARS-CoV-2 Omicron sub-variants BA.1 and BA.2 have become the dominant variants worldwide due to enhanced transmissibility and immune evasion. In response to the rise of BA.1 and BA.2, two recent studies by Liu et al. and Iketani et al. provide a detailed analysis of loss of therapeutic antibody potency through evaluation of escape by pseudotyped viruses harboring BA.1 and BA.2 receptor binding domain (RBD) point mutations. Surprisingly, Liu et al. and Iketani et al. observed a profoundly broad escape effect for the individual mutations S371L and S371F. This result cannot be explained by known escape mechanisms of the SARS-CoV-2 RBD, and conflicts with existing computational and experimental escape measurements for S371 mutations performed on monomeric RBD. Through an examination of these conflicting datasets and a structural analysis of the antibodies assayed by Liu et al. and Iketani et al., we propose a mechanism to explain S371L/F escape according to a perturbation of spike trimer conformational dynamics that has not yet been described for any SARS-CoV-2 escape mutation. The proposed mechanism is relevant to Omicron and future variant surveillance as well as therapeutic antibody design.

The dynamic interplay between virus and host plays out across many interacting surfaces as virus and host evolve continually in response to one another. In particular, epitope-paratope interactions (EPIs) between viral antigen and host antibodies drive much of this evolutionary race. In this review, we describe a series of recent studies examining aspects of epitope complexity that go beyond two interacting protein surfaces as EPIs are typically understood. To structure our discussion, we present a framework for understanding epitope complexity as a spectrum along a series of axes, focusing primarily on 1) epitope biochemical complexity (e.g., epitopes involving N-glycans) and 2) antigen conformational/dynamic complexity (e.g., epitopes with differential properties depending on antigen state or fold-axis). We highlight additional epitope complexity factors including epitope tertiary/quaternary structure, which contribute to epistatic relationships between epitope residues within- or adjacent-to a given epitope, as well as epitope overlap resulting from polyclonal antibody responses, which is relevant when assessing antigenic pressure against a given epitope. Finally, we discuss how these different forms of epitope complexity can limit EPI analyses and therapeutic antibody development, as well as recent efforts to overcome these limitations.

Complex glycans decorate viral surface proteins and play a critical role in virus-host interactions. Viral surface glycans shield vulnerable protein epitopes from host immunity yet can also present distinct "glycoepitopes" that can be targeted by host antibodies such as the potent anti-HIV antibody 2G12 that binds high-mannose glycans on gp120. Two recent publications demonstrate 2G12 binding to high mannose glycans on SARS-CoV-2 and select Influenza A (Flu) H3N2 viruses. Previously, our lab observed 2G12 binding and functional inhibition of a range of Flu viruses that include H3N2 and H1N1 lineages. In this manuscript, we present these data alongside structural analyses to offer an expanded picture of 2G12-Flu interactions. Further, based on the remarkable breadth of 2G12 N-glycan recognition and the structural factors promoting glycoprotein oligomannosylation, we hypothesize that 2G12 glycoepitopes can be defined from protein structure alone according to N-glycan site topology. We develop a model describing 2G12 glycoepitopes based on N-glycan site topology, and apply the model to identify viruses within the Protein Data Bank presenting putative 2G12 glycoepitopes for 2G12 repurposing toward analytical, diagnostic, and therapeutic applications.

As of March 2021, three COVID-19 vaccines had been authorized by the U.S. Food and Drug Administration (FDA) for use in the United States. Each has substantial efficacy in preventing COVID-19. However, as efficacy from trials was <100% for all three vaccines, disease in vaccinated people is expected to occur. We created a spreadsheet-based tool to estimate the number of symptomatic COVID-19 cases among vaccinated people (vaccine breakthrough infections) based on published vaccine efficacy (VE) data, percent of the population that has been fully vaccinated, and average number of COVID-19 cases reported per day. We estimate that approximately 199,000 symptomatic vaccine breakthrough infections (95% CI: ~183,000-214,000 cases) occurred in the United States during January-July 2021 among >156 million fully vaccinated people. With high SARS-CoV-2 transmission and increasing numbers of people vaccinated in the United States, vaccine breakthrough infections will continue to accumulate. Understanding expectations regarding number of vaccine breakthrough infections enables accurate public health messaging to help ensure that the occurrence of such cases does not negatively affect vaccine perceptions, confidence, and uptake.

Summary Nothing will ever be the same. The idea of returning to pre-COVID-19 conditions seems less plausible every day. Nearly every business model has had to transform seemingly overnight, and hospitals and health systems are at center stage in the real-time drama that will change the way we promote, deliver, finance, and engage in healthcare for years to come. This is the next normal, the starting point for the future. Planning for Avera Health’s future has taken on a new level of excitement. Emerging from the COVID-19 crisis, we are finding opportunities. We are learning how to do our work differently and better. We are exploring new partnerships and areas of business that will add to our mission work. We are focusing on the patient–consumer experience. We are shaping a new future. The notion of a new future terrifies some people—they would rather hold on to the past. At Avera, we see this as our chance to create a future to our specifications. All we have to do is let go of yesterday and dream about what tomorrow can be. Our first action was to reassess our five-year strategic plan, unveiled shortly before the pandemic. We initially thought that the plan had been stymied. What we discovered is that it has actually been accelerated. Our organization has become more agile, focused, and sustainable. Growth has been redefined as deepening our relationship with patients to increase lifetime loyalty and creating efficiencies to bend the cost curve for patients and allow Avera to expand services and service areas. This strategy puts people first, makes healthcare more affordable, and modernizes the doctor–patient relationship.

The evolution of mutations in SARS-CoV-2 at antigenic sites that impact neutralizing antibody responses in humans poses a risk to immunity developed through vaccination and natural infection. The highly successful RNA-based vaccines have enabled rapid vaccine updates that incorporate mutations from current variants of concern (VOCs). It is therefore important to anticipate future antigenic mutations as the virus navigates the heterogeneous global landscape of host immunity. Toward this goal, we survey epitope-paratope interfaces of anti-SARS-CoV-2 antibodies to map an antigenic space that captures the role of each spike protein residue within the polyclonal antibody response directed against the ACE2-receptor binding domain (RBD) or the N-terminal domain (NTD). In particular, the antigenic space map builds on recently published epitope definitions by annotating epitope overlap and orthogonality at the residue level. We employ the antigenic space map as a framework to understand how mutations on nine major variants contribute to each variant’s evasion of neutralizing antibodies. Further, we identify constellations of mutations that span the orthogonal epitope regions of the RBD and NTD on the variants with the greatest antibody escape. Finally, we apply the antigenic space map to predict which regions of antigenic space—should they mutate—may be most likely to complementarily augment antibody evasion for the most evasive and transmissible VOCs.

Background: Effective halting of outbreaks in skilled nursing facilities (SNFs) depends on the earliest recognition of cases. We assessed confirmed COVID-19 cases at an SNF impacted by COVID-19 in the United States to identify early indications of COVID-19 infection. Methods: We performed retrospective reviews of electronic health records for residents with laboratory-confirmed SARS-CoV-2 during February 28-March 16, 2020. Records were abstracted for comorbidities, signs and symptoms, and illness outcomes during the 2 weeks before and after the date of positive specimen collection. Relative risks (RRs) of hospitalization and death were calculated. Results: Of the 118 residents tested among approximately 130 residents from Facility A during February 28-March 16, 2020, 101 (86%) were found to test positive for SARS-CoV-2. At initial presentation, about two-thirds of SARS-CoV-2-positive residents had an abnormal vital sign or change in oxygen status. Most (90.2%) symptomatic residents had elevated temperature, change in mental status, lethargy, change in oxygen status, or cough; 9 (11.0%) did not have fever, cough, or shortness of breath during their clinical course. Those with change in oxygen status had an increased relative risk (RR) of 30-day mortality [51.1% vs 29.7%, RR 1.7, 95% confidence interval (CI) 1.0-3.0]. RR of hospitalization was higher for residents with underlying hepatic disease (1.6, 95% CI 1.1-2.2) or obesity (1.5, 95% CI 1.1-2.1); RR of death was not statistically significant. Conclusions and Implications: Our findings reinforce the critical role that monitoring of signs and symptoms can have in identifying COVID-19 cases early. SNFs should ensure they have a systematic approach for responding to abnormal vital signs and oxygen saturation and consider ensuring common signs and symptoms identified in Facility A are among those they monitor. Published by Elsevier Inc. on behalf of AMDA - The Society for Post-Acute and Long-Term Care Medicine.

COVID-19 vaccines are a critical tool for controlling the ongoing global pandemic. The Food and Drug Administration (FDA) has issued Emergency Use Authorizations for three COVID-19 vaccines for use in the United States.* In large, randomized-controlled trials, each vaccine was found to be safe and efficacious in preventing symptomatic, laboratory-confirmed COVID-19 (1-3). Despite the high level of vaccine efficacy, a small percentage of fully vaccinated persons (i.e. received all recommended doses of an FDA-authorized COVID-19 vaccine) will develop symptomatic or asymptomatic infections with SARS-CoV-2, the virus that causes COVID-19 (2-8).

Two coronavirus disease 2019 (COVID-19) vaccines are currently authorized for use in the United States. The Food and Drug Administration (FDA) issued Emergency Use Authorization (EUA) for the Pfizer-BioNTech COVID-19 vaccine on December 11, 2020, and for the Moderna COVID-19 vaccine on December 18, 2020; each is administered as a 2-dose series. The Advisory Committee on Immunization Practices issued interim recommendations for Pfizer-BioNTech and Moderna COVID-19 vaccines on December 12, 2020 (1), and December 19, 2020 (2), respectively; initial doses were recommended for health care personnel and long-term care facility (LTCF) residents (3). Safety monitoring for these vaccines has been the most intense and comprehensive in U.S. history, using the Vaccine Adverse Event Reporting System (VAERS), a spontaneous reporting system, and v-safe,* an active surveillance system, during the initial implementation phases of the COVID-19 national vaccination program (4). CDC conducted descriptive analyses of safety data from the first month of vaccination (December 14, 2020-January 13, 2021). During this period, 13,794,904 vaccine doses were administered, and VAERS received and processed† 6,994 reports of adverse events after vaccination, including 6,354 (90.8%) that were classified as nonserious and 640 (9.2%) as serious.§ The symptoms most frequently reported to VAERS were headache (22.4%), fatigue (16.5%), and dizziness (16.5%). A total of 113 deaths were reported to VAERS, including 78 (65%) among LTCF residents; available information from death certificates, autopsy reports, medical records, and clinical descriptions from VAERS reports and health care providers did not suggest any causal relationship between COVID-19 vaccination and death. Rare cases of anaphylaxis after receipt of both vaccines were reported (4.5 reported cases per million doses administered). Among persons who received Pfizer-BioNTech vaccine, reactions reported to the v-safe system were more frequent after receipt of the second dose than after the first. The initial postauthorization safety profiles of the two COVID-19 vaccines in current use did not indicate evidence of unexpected serious adverse events. These data provide reassurance and helpful information regarding what health care providers and vaccine recipients might expect after vaccination.

ImportanceCerebral venous sinus thrombosis (CVST) with thrombocytopenia, a rare and serious condition, has been described in Europe following receipt of the ChAdOx1 nCoV-19 vaccine (Oxford/AstraZeneca), which uses a chimpanzee adenoviral vector. A mechanism similar to autoimmune heparin-induced thrombocytopenia (HIT) has been proposed. In the US, the Ad26.COV2.S COVID-19 vaccine (Janssen/Johnson & Johnson), which uses a human adenoviral vector, received Emergency Use Authorization (EUA) on February 27, 2021. By April 12, 2021, approximately 7 million Ad26.COV2.S vaccine doses had been given in the US, and 6 cases of CVST with thrombocytopenia had been identified among the recipients, resulting in a temporary national pause in vaccination with this product on April 13, 2021.ObjectiveTo describe reports of CVST with thrombocytopenia following Ad26.COV2.S vaccine receipt.Design, Setting, and ParticipantsCase series of 12 US patients with CVST and thrombocytopenia following use of Ad26.COV2.S vaccine under EUA reported to the Vaccine Adverse Event Reporting System (VAERS) from March 2 to April 21, 2021 (with follow-up reported through April 21, 2021).ExposuresReceipt of Ad26.COV2.S vaccine.Main Outcomes and MeasuresClinical course, imaging, laboratory tests, and outcomes after CVST diagnosis obtained from VAERS reports, medical record review, and discussion with clinicians.ResultsPatients' ages ranged from 18 to younger than 60 years; all were White women, reported from 11 states. Seven patients had at least 1 CVST risk factor, including obesity (n = 6), hypothyroidism (n = 1), and oral contraceptive use (n = 1); none had documented prior heparin exposure. Time from Ad26.COV2.S vaccination to symptom onset ranged from 6 to 15 days. Eleven patients initially presented with headache; 1 patient initially presented with back pain and later developed headache. Of the 12 patients with CVST, 7 also had intracerebral hemorrhage; 8 had non-CVST thromboses. After diagnosis of CVST, 6 patients initially received heparin treatment. Platelet nadir ranged from 9 ×103/µL to 127 ×103/µL. All 11 patients tested for the heparin-platelet factor 4 HIT antibody by enzyme-linked immunosorbent assay (ELISA) screening had positive results. All patients were hospitalized (10 in an intensive care unit [ICU]). As of April 21, 2021, outcomes were death (n = 3), continued ICU care (n = 3), continued non-ICU hospitalization (n = 2), and discharged home (n = 4).Conclusions and RelevanceThe initial 12 US cases of CVST with thrombocytopenia after Ad26.COV2.S vaccination represent serious events. This case series may inform clinical guidance as Ad26.COV2.S vaccination resumes in the US as well as investigations into the potential relationship between Ad26.COV2.S vaccine and CVST with thrombocytopenia.

SARS-CoV-2 mutations with antigenic effects pose a risk to immunity developed through vaccination and natural infection. While vaccine updates for current variants of concern (VOCs) are underway, it is likewise important to prepare for further antigenic mutations as the virus navigates the heterogeneous global landscape of host immunity. Toward this end, a wealth of data and tools exist that can augment existing genetic surveillance of VOC evolution. In this study, we integrate published datasets describing genetic, structural, and functional constraints on mutation along with computational analyses of antibody-spike co-crystal structures to identify a set of potential antigenic drift sites (PADS) within the receptor binding domain (RBD) and N-terminal domain (NTD) of SARS-CoV-2 spike protein. Further, we project the PADS set into a continuous epitope-paratope space to facilitate interpretation of the degree to which newly observed mutations might be antigenically synergistic with existing VOC mutations, and this representation suggests that functionally convergent and synergistic antigenic mutations are accruing across VOC NTDs. The PADS set and synergy visualization serve as a reference as new mutations are detected on VOCs, enable proactive investigation of potentially synergistic mutations, and offer guidance to antibody and vaccine design efforts.

Many interactions between microbes and their hosts are driven or influenced by glycans, whose heterogeneous and difficult to characterize structures have led to an underappreciation of their role in these interactions compared to protein-based interactions. Glycans decorate microbe glycoproteins to enhance attachment and fusion to host cells, provide stability, and evade the host immune system. Yet, the host immune system may also target these glycans as glycoepitopes. In this review, we provide a structural perspective on the role of glycans in host-microbe interactions, focusing primarily on viral glycoproteins and their interactions with host adaptive immunity. In particular, we discuss a class of topological glycoepitopes and their interactions with topological mAbs, using the anti-HIV mAb 2G12 as the archetypical example. We further offer our view that structure-based glycan targeting strategies are ready for application to viruses beyond HIV, and present our perspective on future development in this area.

On February 27, 2021, the Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for Janssen (Ad.26.COV2.S) COVID-19 vaccine (Janssen Biotech, Inc., a Janssen Pharmaceutical company, Johnson & Johnson) (1). The Janssen COVID-19 vaccine, the third COVID-19 vaccine authorized for use in the United States, uses a replication-incompetent human adenoviral type 26 vector platform* (2) and is administered as a single intramuscular dose, whereas the first two authorized vaccines use an mRNA platform and require 2 doses. On February 28, 2021, the Advisory Committee on Immunization Practices (ACIP) issued interim recommendations for use of Janssen COVID-19 vaccine among persons aged ≥18 years (3). During April 13-23, CDC and FDA recommended a pause in use of Janssen vaccine after reports of six cases of cerebral venous sinus thrombosis (CVST) with thrombocytopenia (platelet count <150,000/μL of blood) among Janssen vaccine recipients (4). Similar thrombotic events, primarily among women aged <60 years, have been described in Europe after receipt of the AstraZeneca COVID-19 vaccine, which uses a replication-incompetent chimpanzee adenoviral vector (5-7). The U.S. CVST cases that prompted the pause in Janssen vaccination, as well as subsequently detected CVST cases, are described elsewhere (8). This report summarizes adverse events among Janssen vaccine recipients, including non-CVST cases of thrombosis with thrombocytopenia syndrome (TTS), reported to the Vaccine Adverse Events Reporting System (VAERS), a passive surveillance system, and through v-safe, an active monitoring system. As of April 21, 2021, 7.98 million doses of the Janssen COVID-19 vaccine had been administered. Among 13,725 VAERS reports reviewed, 97% were classified as nonserious and 3% as serious,† including three reports among women of cases of thrombosis in large arteries or veins accompanied by thrombocytopenia during the second week after vaccination. These three cases and the previously detected CVST cases are consistent with 17 cases of TTS,§ a newly defined condition. Approximately 338,700 Janssen COVID-19 vaccine recipients completed at least one v-safe survey during the week after vaccination; 76% reported a systemic reaction, 61% reported a local reaction, and 34% reported a health impact.¶ Fatigue and pain were commonly reported symptoms in both VAERS and v-safe. The overall safety profile is consistent with preauthorization clinical trials data. Prompt review of U.S. vaccine safety data detected three additional cases of non-CVST TTS, in addition to the previously recognized CVST cases that initiated the pause in use of the Janssen COVID-19 vaccine. Ongoing monitoring of adverse events after COVID-19 vaccination, including vaccination with the Janssen single-dose vaccine, is essential for evaluating the risks and benefits of each vaccine.

Older adults are susceptible to severe coronavirus disease 2019 (COVID-19) outcomes as a consequence of their age and, in some cases, underlying health conditions (1). A COVID-19 outbreak in a long-term care skilled nursing facility (SNF) in King County, Washington that was first identified on February 28, 2020, highlighted the potential for rapid spread among residents of these types of facilities (2). On March 1, a health care provider at a second long-term care skilled nursing facility (facility A) in King County, Washington, had a positive test result for SARS-CoV-2, the novel coronavirus that causes COVID-19, after working while symptomatic on February 26 and 28. By March 6, seven residents of this second facility were symptomatic and had positive test results for SARS-CoV-2. On March 13, CDC performed symptom assessments and SARS-CoV-2 testing for 76 (93%) of the 82 facility A residents to evaluate the utility of symptom screening for identification of COVID-19 in SNF residents. Residents were categorized as asymptomatic or symptomatic at the time of testing, based on the absence or presence of fever, cough, shortness of breath, or other symptoms on the day of testing or during the preceding 14 days. Among 23 (30%) residents with positive test results, 10 (43%) had symptoms on the date of testing, and 13 (57%) were asymptomatic. Seven days after testing, 10 of these 13 previously asymptomatic residents had developed symptoms and were recategorized as presymptomatic at the time of testing. The reverse transcription-polymerase chain reaction (RT-PCR) testing cycle threshold (Ct) values indicated large quantities of viral RNA in asymptomatic, presymptomatic, and symptomatic residents, suggesting the potential for transmission regardless of symptoms. Symptom-based screening in SNFs could fail to identify approximately half of residents with COVID-19. Long-term care facilities should take proactive steps to prevent introduction of SARS-CoV-2 (3). Once a confirmed case is identified in an SNF, all residents should be placed on isolation precautions if possible (3), with considerations for extended use or reuse of personal protective equipment (PPE) as needed (4).