Evolution of a globally unique SARS-CoV-2 Spike E484T monoclonal antibody escape mutation in a persistently infected, immunocompromised individual.

Prolonged infections in immunocompromised individuals may be a source for novel SARS-CoV-2 variants, particularly when both the immune system and antiviral therapy fail to clear the infection, thereby promoting adaptation. Here we describe an approximately 16-month case of SARS-CoV-2 infection in an immunocompromised individual. Following monotherapy with the monoclonal antibody Bamlanivimab, the individuals virus was resistant to this antibody via a globally unique Spike amino acid variant (E484T) that evolved from E484A earlier in infection. With the emergence and spread of the Omicron Variant of Concern, which also contains Spike E484A, E484T may arise again as an antibody-resistant derivative of E484A.

SARS-CoV-2 and other respiratory pathogens are detected in continuous air samples from congregate settings.

Two years after the emergence of SARS-CoV-2, there is still a need for better ways to assess the risk of transmission in congregate spaces. We deployed active air samplers to monitor the presence of SARS-CoV-2 in real-world settings across communities in the Upper Midwestern states of Wisconsin and Minnesota. Over 29 weeks, we collected 527 air samples from 15 congregate settings and detected 106 SARS-CoV-2 positive samples, demonstrating SARS-CoV-2 can be detected in air collected from daily and weekly sampling intervals. We expanded the utility of air surveillance to test for 40 other respiratory pathogens. Surveillance data revealed differences in timing and location of SARS-CoV-2 and influenza A virus detection in the community. In addition, we obtained SARS-CoV-2 genome sequences from air samples to identify variant lineages. Collectively, this shows air surveillance is a scalable, cost-effective, and high throughput alternative to individual testing for detecting respiratory pathogens in congregate settings.

Engaging veterans in identifying key elements of environmental cleaning and disinfection for preventing healthcare-associated infections: A qualitative study.

BACKGROUND: Environmental cleaning and disinfection are important for preventing healthcare-associated infections (HAIs) via contaminated surfaces. Hospital cleanliness plays a large role in patient perception and satisfaction regarding their healthcare. However, patient perceptions of environmental cleaning procedures remain unclear. The objective of the study was to engage patients in achieving patient-centered care and examine patient perspectives on environmental cleaning work systems in healthcare. METHODS: A qualitative descriptive study was conducted using semi-structured interviews with hospitalized patients at a Midwestern Veterans Administration Hospital. Interviews were audio recorded, transcribed, then coded to identify recurring themes. RESULTS: Fifteen patient interview were conducted. Patients reported expecting a clean hospital room. Some patients expressed feeling "in the way" during cleaning, possibly rushing cleaning procedures. Patients expressed confidence in Environmental Management Service (EMS) staff's skilled work and noted "soft skills" as desirable attributes, including camaraderie which can develop between Veteran patients and Veteran staff during room cleaning. CONCLUSIONS: Patients identified environmental cleaning as a priority for HAI patient-centered infection prevention practices. Cleaning occupied rooms may be an important entry point for intervention to address actual or perceived disruption to patients or build upon Veteran peer relationships. Cleaning procedures may become more patient-centric if cleaning procedures were explained and based on patient preferences.

Anti-membrane and anti-spike antibodies are long-lasting and together discriminate between past COVID-19 infection and vaccination

The consequences of past COVID-19 infection for personal health and long-term population immunity are only starting to be revealed. Unfortunately, detecting past infection is currently a challenge, limiting clinical and research endeavors. Widely available anti-SARS-CoV-2 antibody tests cannot differentiate between past infection and vaccination given vaccine-induced anti-spike antibodies and the rapid loss of infection-induced anti-nucleocapsid antibodies. Anti-membrane antibodies develop after COVID-19, but their long-term persistence is unknown. Here, we demonstrate that anti-membrane IgG is a sensitive and specific marker of past COVID-19 infection and persists at least one year. We also confirm that anti-receptor binding domain (RBD) Ig is a long-lasting, sensitive, and specific marker of past infection and vaccination, while anti-nucleocapsid IgG lacks specificity and quickly declines after COVID-19. Thus, a combination of anti-membrane and anti-RBD antibodies can accurately differentiate between distant COVID-19 infection, vaccination, and naive states to advance public health, individual healthcare, and research goals.

The Impact of Vaccination to Control COVID-19 Burden in the United States: A Simulation Modeling Approach

IntroductionVaccination programs aim to control the COVID-19 pandemic. However, the relative impacts of vaccine coverage, effectiveness, and capacity in the context of nonpharmaceutical interventions such as mask use and physical distancing on the spread of SARS-CoV-2 are unclear. Our objective was to examine the impact of vaccination on the control of SARS-CoV-2 using our previously developed agent-based simulation model. MethodsWe applied our agent-based model to replicate COVID-19-related events in 1) Dane County, Wisconsin; 2) Milwaukee metropolitan area, Wisconsin; 3) New York City (NYC). We evaluated the impact of vaccination considering the proportion of the population vaccinated, probability that a vaccinated individual gains immunity, vaccination capacity, and adherence to nonpharmaceutical interventions. The primary outcomes were the number of confirmed COVID-19 cases and the timing of pandemic control, defined as the date after which only a small number of new cases occur. We also estimated the number of cases without vaccination. ResultsThe timing of pandemic control depends highly on vaccination coverage, effectiveness, and adherence to nonpharmaceutical interventions. In Dane County and Milwaukee, if 50% of the population is vaccinated with a daily vaccination capacity of 0.1% of the population, vaccine effectiveness of 90%, and the adherence to nonpharmaceutical interventions is 85%, controlled spread could be achieved by July 2021 and August 2021, respectively versus in March 2022 in both regions without vaccine. If adherence to nonpharmaceutical interventions increases to 70%, controlled spread could be achieved by May 2021 and April 2021 in Dane County and Milwaukee, respectively. DiscussionIn controlling the spread of SARS-CoV-2, the impact of vaccination varies widely depending not only on effectiveness and coverage, but also concurrent adherence to nonpharmaceutical interventions. The effect of SARS-CoV-2 variants was not considered. Primary Funding SourceNational Institute of Allergy and Infectious Diseases

Viral sequencing reveals US healthcare personnel rarely become infected with SARS-CoV-2 through patient contact

BackgroundHealthcare personnel (HCP) are at increased risk of infection with the severe acute respiratory coronavirus 2019 virus (SARS-CoV-2). Between 12 March 2020 and 10 January 2021, >1,170 HCP tested positive for SARS-CoV-2 at a major academic medical institution in the Upper Midwest of the United States. We aimed to understand the sources of infections in HCP and to evaluate the efficacy of infection control procedures used at this institution to protect HCP from healthcare-associated transmission. MethodsIn this retrospective case series, we used viral genomics to investigate the likely source of SARS-CoV-2 infection in 96 HCP where epidemiological data alone could not be used to rule out healthcare-associated transmission. We obtained limited epidemiological data through informal interviews and review of the electronic health record. We combined viral sequence data and available epidemiological information to infer the most likely source of HCP infection. FindingsWe investigated 32 SARS-CoV-2 infection clusters involving 96 HCP, 140 possible patient contacts, and 1 household contact (total n = 237). Of these, 182 sequences met quality standards and were used for downstream analysis. We found the majority of HCP infections could not be linked to a patient or co-worker and therefore likely occurred in the outside community (58/96; 60.4%). We found a smaller percentage could be traced to a coworker (10/96; 10.4%) or were part of a patient-employee cluster (12/96; 12.5%). Strikingly, the smallest proportion of HCP infections could be clearly traced to a patient source (4/96; 4.2%). InterpretationInfection control procedures, consistently followed, offer significant protection to HCP caring for COVID-19 patients in a representative American academic medical institution. Rapid SARS-CoV-2 genome sequencing in healthcare settings can be used retrospectively to reconstruct the likely source of HCP infection when epidemiological data are not available or are inconclusive. Understanding the source of SARS-CoV-2 infection can then be used prospectively to adjust and improve infection control practices and guidelines. FundingThis project was funded in part through a COVID-19 Response grant from the Wisconsin Partnership Program at the University of Wisconsin School of Medicine and Public Health to T.C.F. and D.H.O. Author N.S. is supported by the National Institute of Allergy and Infectious Diseases Institute (NIAID) Grant 1DP2AI144244-01. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSOn 16 January 2021 we searched for "SARS-CoV-2" AND "healthcare workers" AND "viral sequencing" in Google Scholar. This search returned 57 results, and included a number of preprint articles. We found two studies that used viral sequencing to investigate healthcare-associated outbreaks in the Netherlands 1 and the United Kingdom 2. To our knowledge, no study has used viral sequencing to specifically investigate the source of SARS-CoV-2 infections in healthcare workers in the United States. Although we and others have written about the potential utility of sequencing as an infection control asset 3-6, few have demonstrated the practical application of such efforts. Added value of this studyOur study suggests infection control measures in place at the institution evaluated in this case series are largely protecting healthcare personnel (HCP) from healthcare-associated SARS-CoV-2 infections. Even so, the majority of healthcare-associated infections we did identify appeared to be linked to HCP-to-HCP spread so additional messaging and guidelines to reduce HCP-to-HCP spread in and out of the workplace may be warranted. In addition, we demonstrated how rapid viral sequencing can be combined with, even limited, epidemiological information to reconstruct healthcare-associated SARS-CoV-2 outbreaks. Implications of all the available evidenceHealthcare-associated SARS-CoV-2 infections negatively affect HCP, patients, and communities. Infections among HCP add further strain to the healthcare system and put patients and other HCP at risk. We found the majority of HCP infections appeared to be acquired through community exposure so measures to reduce community spread are critical. This further emphasizes the importance of mask-wearing, physical distancing, robust testing programs, and the rapid distribution of vaccines.

Population Changes in Seroprevalence among a Statewide Sample in the United States

Antibody surveillance provides essential information for public health officials to work with communities to discuss the spread and impact of COVID-19. At the start of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in the United States, diagnostic testing was limited with many asymptomatic and thus undetected cases. Irrespective of symptom severity, antibodies develop within two to three weeks after exposure and may persist 6 months or more.; Thus, antibody surveillance is an important tool for tracking trends in past infections across diverse populations. This study includes adults and children ([≥]12 years old) recruited from a statewide sample of past 2014-2020 Survey of the Health of Wisconsin (SHOW) participants. SHOW, an ongoing population-based health examination study including a randomly selected sample of households, partnered with the Wisconsin Department of Health Services and the Wisconsin State Laboratory of Hygiene to conduct longitudinal antibody surveillance using the Abbott Architect SARS-CoV-2 IgG antibody test, which detects antibodies against the nucleocapsid protein. Three WAVES of sample collection were completed in 2020-2021, tracking mid-summer, late fall, and early spring COVID-19 trends prior to vaccine availability. Crude estimates of seroprevalence in the total study population increased ten-fold from 1.4% during WAVE I to 11.5% in WAVE III. Within the statewide probability sample, weighted estimates increased from 1.6% (95% CI:0.6-2.5%), to 6.8% (95% CI:4.3-9.4%) in WAVE II and to 11.4% (95% CI:8.2, 14.6%) in WAVE III. Longitudinal trends in seroprevalence match statewide case counts. Local seroprevalence showed variation by state health region with increasing prevalence among higher income (>200% poverty income ratio), and rural health regions of the state seeing the highest increase in COVID-19 prevalence over time. Significant disparities in prevalence by racial and ethnic groups also exist, with greater than two times seroprevalence among Latino and black participants compared to non-Hispanic whites. This public health and academic partnership provides critical data for the ongoing pandemic response and lays the foundation for future research into longer-term immunity, health impacts and population-level disparities.

Prevalence and outcomes of co-infection and super-infection with SARS-CoV-2 and other pathogens: A Systematic Review and Meta-analysis

IntroductionThe recovery of other respiratory viruses in patients with SARS-CoV-2 infection has been reported, either at the time of a SARS-CoV-2 infection diagnosis (co-infection) or subsequently (superinfection). However, data on the prevalence, microbiology and outcomes of co-infection and super infection are limited. The purpose of this study was to examine occurrence of respiratory co-infections and superinfections and their outcomes among patients with SARS-CoV-2 infection. Patients and MethodsWe searched literature databases for studies published from October 1, 2019, through June 11, 2020. We included studies that reported clinical features and outcomes of co-infection or super-infection of SARS-CoV-2 and other pathogens in hospitalized and non-hospitalized patients. We followed PRISMA guidelines and we registered the protocol with PROSPERO as: CRD42020189763. ResultsOf 1310 articles screened, 48 were included in the random effects meta-analysis. The pooled prevalence of co-infection was 12% (95% confidence interval (CI): 6%-18%, n=29, I2=98%) and that of super-infection was 14% (95% CI: 9%-21%, n=18, I2=97%). Pooled prevalence of pathogen type stratified by co- or super-infection: viral co-infections, 4% (95% CI: 2%-7%); viral super-infections, 2% (95% CI: 0%-7%); bacterial co-infections, 4% (95% CI: 1%-8%); bacterial super-infections, 6% (95% CI: 2%-11%); fungal co-infections, 4% (95% CI: 1%-8%); and fungal super-infections, 4% (95% CI: 0%-11%). Compared to those with co-infections, patients with super-infections had a higher prevalence of mechanical ventilation [21% (95% CI: 13%-31%) vs. 7% (95% CI: 2%-15%)] and greater average length of hospital stay [mean=12.5 days, standard deviation (SD) =5.3 vs. mean=10.2 days, SD= 6.7]. ConclusionsOur study showed that as many as 14% of patients with COVID-19 have super-infections and 12% have co-infections. Poor outcomes were associated with super-infections. Our findings have implications for diagnostic testing and therapeutics, particularly in the upcoming respiratory virus season in the Northern Hemisphere.

Distinct patterns of SARS-CoV-2 transmission in two nearby communities in Wisconsin, USA

Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties, and limited viral transmission between counties, following the statewide "Safer at Home" public health order, which went into effect 25 March 2020. Our results suggest that early containment efforts suppressed the spread of SARS-CoV-2 within Wisconsin.

Use of face coverings by the public during the COVID-19 pandemic: an observational study

Public health agencies have recommended that the public wear face coverings, including face masks, to mitigate COVID-19 transmission. However, the extent to which the public has adopted this recommendation is unknown. An observational study of 3,271 members of the public in May and June 2020 examined face covering use at grocery stores across Wisconsin. We found that only 41.2% used face coverings. Individuals who appeared to be female or older adults had higher odds of using face coverings. Additionally, location-specific variables such as expensiveness of store, county-level population and county-level COVID-19 case prevalence were associated with increased odds of using face coverings. To our knowledge, this is the first direct observational study examining face covering behavior by the public in the U.S., and our findings have implications for public health agencies during the COVID-19 pandemic.

Impact of Timing of and Adherence to Social Distancing Measures on COVID-19 Burden in the US: A Simulation Modeling Approach

BackgroundAcross the U.S., various social distancing measures were implemented to control COVID-19 pandemic. However, there is uncertainty in the effectiveness of such measures for specific regions with varying population demographics and different levels of adherence to social distancing. The objective of this paper is to determine the impact of social distancing measures in unique regions. MethodsWe developed COVid-19 Agent-based simulation Model (COVAM), an agent-based simulation model (ABM) that represents the social network and interactions among the people in a region considering population demographics, limited testing availability, imported infections from outside of the region, asymptomatic disease transmission, and adherence to social distancing measures. We adopted COVAM to represent COVID-19-associated events in Dane County, Wisconsin, Milwaukee metropolitan area, and New York City (NYC). We used COVAM to evaluate the impact of three different aspects of social distancing: 1) Adherence to social distancing measures; 2) timing of implementing social distancing; and 3) timing of easing social distancing. ResultsWe found that the timing of social distancing and adherence level had a major effect on COVID-19 occurrence. For example, in NYC, implementing social distancing measures on March 5, 2020 instead of March 12, 2020 would have reduced the total number of confirmed cases from 191,984 to 43,968 as of May 30, whereas a 1-week delay in implementing such measures could have increased the number of confirmed cases to 1,299,420. Easing social distancing measures on June 1, 2020 instead of June 15, 2020 in NYC would increase the total number of confirmed cases from 275,587 to 379,858 as of July 31. ConclusionThe timing of implementing social distancing measures, adherence to the measures, and timing of their easing have major effects on the number of COVID-19 cases. Primary Funding SourceNational Institute of Allergy and Infectious Diseases Institute

Determining the source of transmission of SARS-CoV-2 infection in a healthcare worker

BackgroundHealthcare workers (HCWs) are at the frontlines of the COVID-19 pandemic and are at risk of exposure to SARS-CoV-2 infection from their interactions with patients and in the community (1, 2). Limited availability of recommended personal protective equipment (PPE), in particular N95 respirators, has fueled concerns about whether HCWs are adequately protected from exposure while caring for patients. Understanding the source of SARS-CoV-2 infection in a HCW - the community or the healthcare system - is critical for understanding the effectiveness of hospital infection control and PPE practices. In Dane County, Wisconsin, community prevalence of SARS-CoV-2 is relatively low (cumulative prevalence of ~0.06% - positive cases / total population in Dane county as of April 17). Although SARS-CoV-2 infections in HCWs are often presumed to be acquired during the course of patient care, there are few reports unambiguously identifying the source of acquisition. ObjectiveTo determine the source of transmission of SARS-CoV-2 in a healthcare worker.