Seroepidemiology and risk factors for SARS-CoV-2 infection among household members of food processing and farm workers in North Carolina.

Background: Racial and ethnic minorities have borne a disproportionate burden from coronavirus disease 2019 (COVID-19). Certain essential occupations, including food processing and farm work, employ large numbers of Hispanic migrant workers and have been shown to carry an especially high risk of infection. Methods: This observational cohort study measured the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and assessed the risk factors for seropositivity among food processing and farm workers, and members of their households, in North Carolina, USA. Participants completed questionnaires, blood samples were collected, and an enzyme-linked immunosorbent assay was used to assess SARS-CoV-2 seropositivity. Univariate and multi-variate analyses were undertaken to identify risk factors associated with seropositivity, using generalized estimating equations to account for household clustering. Findings: Among the 218 participants, 94.5% were Hispanic, and SARS-CoV-2 seropositivity was 50.0%. Most seropositive individuals did not report a history of illness compatible with COVID-19. Attending church, having a prior history of COVID-19, having a seropositive household member, and speaking Spanish as one's primary language were associated with SARS-CoV-2 seropositivity, while preventive behaviours were not. Interpretation: These findings underscore the substantial burden of COVID-19 among a population of mostly Hispanic essential workers and their households in rural North Carolina. This study contributes to a large body of evidence showing that Hispanic Americans have suffered a disproportionate burden of COVID-19. This study also highlights the epidemiologic importance of viral transmission within the household.

SARS-CoV-2 seroprevalence and risk factors among meat packing, produce processing, and farm workers

Meat packing, produce processing, and farm workers are known to have an elevated risk of COVID-19, but occupational risk factors in this population are unclear. We performed an observational cohort study of meat packing, produce processing, and farm workers in North Carolina in fall 2020. Blood, saliva, and nasal turbinate samples were collected to assess for SARS-CoV-2 seropositivity. Risk factors for SARS-CoV-2 seropositivity were investigated using chi-square tests, two-sample t-tests, and adjusted risk ratio analyses. Among 118 enrolled workers, the baseline SARS-CoV-2 seroprevalence was 50.0%. Meat packing plant workers had the highest SARS-CoV-2 seroprevalence (64.6%), followed by farm workers (45.0%) and produce processing workers (10.0%), despite similar sociodemographic characteristics. Compared to SARS-CoV-2 seronegative workers, seropositive workers were more likely to work in loud environments that necessitated yelling to communicate (RR: 1.83, 95% CI: 1.25–2.69), work in cold environments (RR: 1.58, 95% CI: 1.12–2.24), or continue working despite developing symptoms at work (RR: 1.63, 95% CI: 1.14–2.32). After adjusting for age and working despite symptoms, high occupational noise levels were associated with a 1.72 times higher risk of SARS-CoV-2 seropositivity (95% CI: 1.16–2.55). Half of food processing workers showed evidence of past SARS-CoV-2 infection, a prevalence five times higher than most of the United States population at the time of the study. Work environments with loud ambient noise may pose elevated risks for SARS-CoV-2 transmission. Our findings also highlight the disproportionate burden of COVID-19 among underserved and economically disadvantaged Latinx communities in the United States.

Seroepidemiology and risk factors for SARS-CoV-2 infection among household members of food processing and farm workers in North Carolina

Background Racial and ethnic minorities have borne a disproportionate burden from COVID-19. Certain essential occupations, including food processing and farm work, employ large numbers of Hispanic migrant workers and have been shown to carry an especially high risk of infection. Methods We conducted an observational cohort study measuring the seroprevalence of SARS-CoV-2 and assessing risk factors for seropositivity among North Carolina food processing and farm workers and members of their households. Participants completed questionnaires and we collected blood samples and used an enzyme-linked immunosorbent assay to assess SARS-CoV-2 seropositivity. Univariate and multivariate analyses were carried out to identify risk factors associated with seropositivity, using generalized estimating equations to account for household clustering. Findings Among the 218 participants, 94.5% were Hispanic, and SARS-CoV-2 seropositivity was 50.0%. Most seropositive individuals did not report a history of illness compatible with COVID-19. Attending church, having a prior history of COVID-19, having a seropositive household member, and speaking Spanish as one's primary language were associated with SARS-CoV-2 seropositivity, while preventive behaviors were not. Interpretation These findings underscore the substantial burden of COVID-19 among a population of mostly Hispanic essential workers and their households in rural North Carolina. Our study contributes to a large body of evidence showing that Hispanic Americans have suffered a disproportionate COVID-19 burden. We also highlight the epidemiologic importance of viral transmission within the household.

Language models for the prediction of SARS-CoV-2 inhibitors

The COVID-19 pandemic highlights the need for computational tools to automate and accelerate drug design for novel protein targets. We leverage deep learning language models to generate and score drug candidates based on predicted protein binding affinity. We pre-trained a deep learning language model (BERT) on ∼9.6 billion molecules and achieved peak performance of 603 petaflops in mixed precision. Our work reduces pre-training time from days to hours, compared to previous efforts with this architecture, while also increasing the dataset size by nearly an order of magnitude. For scoring, we fine-tuned the language model using an assembled set of thousands of protein targets with binding affinity data and searched for inhibitors of specific protein targets, SARS-CoV-2 Mpro and PLpro. We utilized a genetic algorithm approach for finding optimal candidates using the generation and scoring capabilities of the language model. Our generalizable models accelerate the identification of inhibitors for emerging therapeutic targets.

Outcomes of Convalescent Plasma with Defined High versus Lower Neutralizing Antibody Titers against SARS-CoV-2 among Hospitalized Patients: CoronaVirus Inactivating Plasma (CoVIP) Study.

COVID-19 convalescent plasma (CCP) was an early and widely adopted putative therapy for severe COVID-19. Results from randomized control trials and observational studies have failed to demonstrate a clear therapeutic role for CCP for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Underlying these inconclusive findings is a broad heterogeneity in the concentrations of neutralizing antibodies (nAbs) between different CCP donors. We conducted this study to evaluate the effectiveness and safety of nAb titer-defined CCP in adults admitted to an academic referral hospital. Patients positive by a SARS-CoV-2 nucleic acid amplification test and with symptoms for <10 days were eligible. Participants received either CCP with nAb titers of >1:640 (high-titer group) or ≥1:160 to 1:640 (standard-titer group) in addition to standard of care treatments. The primary clinical outcome was time to hospital discharge, with mortality and respiratory support evaluated as secondary outcomes. Adverse events were contrasted by CCP titer. Between 28 August and 4 December 2020, 316 participants were screened, and 55 received CCP, with 14 and 41 receiving high- versus standard-titer CCP, respectively. Time to hospital discharge was shorter among participants receiving high- versus standard-titer CCP, accounting for death as a competing event (hazard ratio, 1.94; 95% confidence interval [CI], 1.05 to 3.58; Gray's P = 0.02). Severe adverse events (SAEs) (≥grade 3) occurred in 4 (29%) and 23 (56%) of participants receiving the high versus standard titer, respectively, by day 28 (risk ratio, 0.51; 95% CI, 0.21 to 1.22; Fisher's P = 0.12). There were no observed treatment-related AEs. (This study has been registered at ClinicalTrials.gov under registration no. NCT04524507). IMPORTANCE In this study, in a high-risk population of patients admitted for COVID-19, we found an earlier time to hospital discharge among participants receiving CCP with nAb titers of >1:640 compared with participants receiving CCP with a lower nAb titer and no CCP-related AEs. The significance of our research is in identifying a dose response of CCP and clinical outcomes based on nAb titer. Although limited by a small study size, these findings support further study of high-nAb-titer CCP defined as >1:640 in the treatment of COVID-19.

Ethnoracial Disparities in SARS-CoV-2 Seroprevalence in a Large Cohort of Individuals in Central North Carolina from April to December 2020.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths around the world within the past 2 years. Transmission within the United States has been heterogeneously distributed by geography and social factors with little data from North Carolina. Here, we describe results from a weekly cross-sectional study of 12,471 unique hospital remnant samples from 19 April to 26 December 2020 collected by four clinical sites within the University of North Carolina Health system, with a majority of samples from urban, outpatient populations in central North Carolina. We employed a Bayesian inference model to calculate SARS-CoV-2 spike protein immunoglobulin prevalence estimates and conditional odds ratios for seropositivity. Furthermore, we analyzed a subset of these seropositive samples for neutralizing antibodies. We observed an increase in seroprevalence from 2.9 (95% confidence interval [CI], 1.8 to 4.5) to 12.8 (95% CI, 10.6 to 15.2) over the course of the study. Latinx individuals had the highest odds ratio of SARS-CoV-2 exposure at 6.56 (95% CI, 4.66 to 9.44). Our findings aid in quantifying the degree of asymmetric SARS-CoV-2 exposure by ethnoracial grouping. We also find that 49% of a subset of seropositive individuals had detectable neutralizing antibodies, which was skewed toward those with recent respiratory infection symptoms. IMPORTANCE PCR-confirmed SARS-CoV-2 cases underestimate true prevalence. Few robust community-level SARS-CoV-2 ethnoracial and overall prevalence estimates have been published for North Carolina in 2020. Mortality has been concentrated among ethnoracial minorities and may result from a high likelihood of SARS-CoV-2 exposure, which we observe was particularly high among Latinx individuals in North Carolina. Additionally, neutralizing antibody titers are a known correlate of protection. Our observation that development of SARS-CoV-2 neutralizing antibodies may be inconsistent and dependent on severity of symptoms makes vaccination a high priority despite prior exposure.

How Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets

The emergence and rapid worldwide spread of the novel coronavirus disease, COVID-19, has prompted concerted efforts to find successful treatments. The causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), uses its spike (S) protein to gain entry into host cells. Therefore, the S protein presents a viable target to develop a directed therapy. Here, we deployed an integrated artificial intelligence with all-atom molecular dynamics simulation approach to provide new details of the S protein structure. Based on a comprehensive structural analysis of S proteins from SARS-CoV-2 and previous human coronaviruses, we found that the protomer state of S proteins is structurally flexible. Without the presence of a stabilizing beta sheet from another protomer chain, two regions in the S2 domain and the hinge connecting the S1 and S2 subunits lose their secondary structures. Interestingly, the region in the S2 domain was previously identified as an immunodominant site in the SARS-CoV-1 S protein. We anticipate that the molecular details elucidated here will assist in effective therapeutic development for COVID-19. © 2021 IEEE.

SECOND HOME TOURISM: AN INTERCESSION FOR REJUVENETION OF TOURISM DESTINATION IN COVID-19 CRISIS

This study aims to demonstrate how hedonistic Second Home Tourism (SHT) trips and eudaimonic community participation will retrieve tourist flow and revive tourist destination from the COVID-19 crisis. Q methodology was followed to measure the subjectivity of scholars, researchers and practitioners of tourism industry for the appreciation of SHT in the crisis. Q Method Software was used to conduct factor analysis. The result of the study concludes that short haul mobility/trip within periphery and/or travel bubble accelerates the % change of international tourist arrivals. The study also implores that how future SHT trips will ensure community resilience through social intuition (cultural integrity and knowledge exchange) and financial retention through economic empathy (demand-supply balance and revenue generation). © 2021 Editura Universitatii din Oradea. All rights reserved.

Sex Disparities and Neutralizing-Antibody Durability to SARS-CoV-2 Infection in Convalescent Individuals.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) has now caused over 2 million deaths worldwide and continues to expand. Currently, much is unknown about functionally neutralizing human antibody responses and durability to SARS-CoV-2 months after infection or the reason for the discrepancy in COVID-19 disease and sex. Using convalescent-phase sera collected from 101 COVID-19-recovered individuals 21 to 212 days after symptom onset with 48 additional longitudinal samples, we measured functionality and durability of serum antibodies. We also evaluated associations of individual demographic and clinical parameters with functional neutralizing antibody responses to COVID-19. We found robust antibody durability out to 6 months, as well as significant positive associations with the magnitude of the neutralizing antibody response and male sex and in individuals with cardiometabolic comorbidities. IMPORTANCE In this study, we found that neutralizing antibody responses in COVID-19-convalescent individuals vary in magnitude but are durable and correlate well with receptor binding domain (RBD) Ig binding antibody levels compared to other SARS-CoV-2 antigen responses. In our cohort, higher neutralizing antibody titers are independently and significantly associated with male sex compared to female sex. We also show for the first time that higher convalescent antibody titers in male donors are associated with increased age and symptom grade. Furthermore, cardiometabolic comorbidities are associated with higher antibody titers independently of sex. Here, we present an in-depth evaluation of serologic, demographic, and clinical correlates of functional antibody responses and durability to SARS-CoV-2 which supports the growing literature on sex discrepancies regarding COVID-19 disease morbidity and mortality, as well as functional neutralizing antibody responses to SARS-CoV-2.

Pulmonary hypertension following severe COVID-19: a case report

Persistence of symptoms or development of new symptoms, late in the course of COVID-19 puts a constant burden on our healthcare facilities. In its severe form, COVID-19 patient may present as acute respiratory distress syndrome (ARDS), shock, and multiorgan failure and other immunological disharmony. With extensive parenchymal and vascular endothelial damage to lung vasculature, some patient may develop extensive fibrosis and pulmonary hypertension. Our patient a 60-year-old male, slightly overweight (BMI = 28.3) with history of IGT suddenly developed fever, sore throat and anosmia with myalgia. At 7th day of symptom his saturation fell down and patient was admitted in Bangabandhu Sheikh Mujib Medical University (BSMMU) for advance management. Initially patient was treated in COVID-19 ward, latter he was shifted to ICU as oxygen saturation was not maintained by HFNC. After a long battle of 56 days in ICU and 19 days stay in post COVID ward patient was discharged home with intermittent oxygen therapy only to develop pulmonary hypertension as a sequelae of post COVID syndrome. A holistic approach to management of post COVID syndrome is needed for such multisystem involvement of severe COVID patients.

The palliative paradigm-a safety net hospital experience with COVID-19

Rationale: The Covid-19 pandemic is the worst healthcare event seen this century amassing a high toll of human life. Covid-19 infection is most commonly associated with acute hypoxic respiratory failure, often requiring intubation leading to multi-organ failure and death. Palliative medicine, during the pandemic, more than ever became in demand especially in ICU settings with a steep increase in consults for pain and symptom management, prognosis clarification and goals of care. We decided to analyze the effect on our palliative medicine service at a safety net hospital at the initial epicenter of the Covid-19 pandemic. Material and Methods: We conducted a retrospective analysis of the Palliative Medicine service at Brookdale University Hospital Medical Center in the months before and after the pandemic from November 2019 to May 2020. We analyzed the number of consults placed per month and the use of IV methadone, novel to our institution used to address breathlessness and pain. To assess the increase in palliative consults we used a linear regression model over time transcending the start of the Covid-19 pandemic. We also queried the orders of intravenous methadone use utilizing pharmacological records, which was only used under the discretion of palliative care and in end of life or terminal settings as is would address breathlessness. Results: Retrospective analysis revealed that in the months leading up to the pandemic including November 2019 through February 2020 there were an average of 80.25± 8.08 palliative consults placed a month. In the months during the initial peak of the Covid-19 pandemic including March and April 2020 there were an average of 162.0± 69 consults per month which then reduced to 69 consults in the month of May 2020. A linear regression calculation was performed which showed an equation of y = 30.6+21.9714X (R2= 0.7794 p=.067). Intravenous methadone was not used prior to the pandemic which was noted to have been ordered 14 times in April 2020 for breathlessness and pain management. Conclusion: We found an increase in the amount of palliative consults placed during the Covid-19 pandemic though not statistically significant with an eventual downtrend. This is thought to be due to distressing symptoms in an acutely life threatening illness and the need for early consultation due to the knowledge and unique skill set that palliative specialists possess. Physicians in acute care settings need be comfortable to consult palliative services early in management.

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.