Molecular and Clinical Epidemiology of SARS-CoV-2 Infection Among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey (preprint)

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOC) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5,007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOC, including Alpha (n =714), Delta (n =1,877), and Omicron (n =1,802). Omicron isolates were further sub-typed as BA.1 (n =899), BA.2 (n =853), and BA.4/BA.5 (n =50); the remaining 614 isolates were classified as “Other”. Approximately 31.5% (1,577/5,007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p <0.001). Unvaccinated individuals accounted for 79.7% (268/336) of ICU admissions, 78.3% (185/236) of ventilator cases, and 74.4% (320/430) of deaths. Highly significant (p <0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease. Significant differences (p <0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact.

Three dimensions of COVID-19 risk perceptions and their socioeconomic correlates in the United States: A social media analysis.

Social media analysis provides an alternate approach to monitoring and understanding risk perceptions regarding COVID-19 over time. Our current understandings of risk perceptions regarding COVID-19 do not disentangle the three dimensions of risk perceptions (perceived susceptibility, perceived severity, and negative emotion) as the pandemic has evolved. Data are also limited regarding the impact of social determinants of health (SDOH) on COVID-19-related risk perceptions over time. To address these knowledge gaps, we extracted tweets regarding COVID-19-related risk perceptions and developed indicators for the three dimensions of risk perceptions based on over 502 million geotagged tweets posted by over 4.9 million Twitter users from January 2020 to December 2021 in the United States. We examined correlations between risk perception indicator scores and county-level SDOH. The three dimensions of risk perceptions demonstrate different trajectories. Perceived severity maintained a high level throughout the study period. Perceived susceptibility and negative emotion peaked on March 11, 2020 (COVID-19 declared global pandemic by WHO) and then declined and remained stable at lower levels until increasing once again with the Omicron period. Relative frequency of tweet posts on risk perceptions did not closely follow epidemic trends of COVID-19 (cases, deaths). Users from socioeconomically vulnerable counties showed lower attention to perceived severity and susceptibility of COVID-19 than those from wealthier counties. Examining trends in tweets regarding the multiple dimensions of risk perceptions throughout the COVID-19 pandemic can help policymakers frame in-time, tailored, and appropriate responses to prevent viral spread and encourage preventive behavior uptake in the United States.

Nanoplasmonic amplification in microfluidics enables accelerated colorimetric quantification of nucleic acid biomarkers from pathogens.

Deployment of nucleic acid amplification assays for diagnosing pathogens in point-of-care settings is a challenge due to lengthy preparatory steps. We present a molecular diagnostic platform that integrates a fabless plasmonic nano-surface into an autonomous microfluidic cartridge. The plasmonic 'hot' electron injection in confined space yields a ninefold kinetic acceleration of RNA/DNA amplification at single nucleotide resolution by one-step isothermal loop-mediated and rolling circle amplification reactions. Sequential flow actuation with nanoplasmonic accelerated microfluidic colorimetry and in conjugation with machine learning-assisted analysis (using our 'QolorEX' device) offers an automated diagnostic platform for multiplexed amplification. The versatility of QolorEX is demonstrated by detecting respiratory viruses: SARS-CoV-2 and its variants at the single nucleotide polymorphism level, H1N1 influenza A, and bacteria. For COVID-19 saliva samples, with an accuracy of 95% on par with quantitative polymerase chain reaction and a sample-to-answer time of 13 minutes, QolorEX is expected to advance the monitoring and rapid diagnosis of pathogens.

SARS-CoV-2 ORF8: A Rapidly Evolving Immune and Viral Modulator in COVID-19.

The COVID-19 pandemic has resulted in upwards of 6.8 million deaths over the past three years, and the frequent emergence of variants continues to strain global health. Although vaccines have greatly helped mitigate disease severity, SARS-CoV-2 is likely to remain endemic, making it critical to understand its viral mechanisms contributing to pathogenesis and discover new antiviral therapeutics. To efficiently infect, this virus uses a diverse set of strategies to evade host immunity, accounting for its high pathogenicity and rapid spread throughout the COVID-19 pandemic. Behind some of these critical host evasion strategies is the accessory protein Open Reading Frame 8 (ORF8), which has gained recognition in SARS-CoV-2 pathogenesis due to its hypervariability, secretory property, and unique structure. This review discusses the current knowledge on SARS-CoV-2 ORF8 and proposes actualized functional models describing its pivotal roles in both viral replication and immune evasion. A better understanding of ORF8's interactions with host and viral factors is expected to reveal essential pathogenic strategies utilized by SARS-CoV-2 and inspire the development of novel therapeutics to improve COVID-19 disease outcomes.

Risk for stillbirth among pregnant individuals with SARS-CoV-2 infection varied by gestational age.

BACKGROUND: Despite previous research findings on higher risks of stillbirth among pregnant individuals with SARS-CoV-2 infection, it is unclear whether the gestational timing of viral infection modulates this risk. OBJECTIVE: This study aimed to examine the association between timing of SARS-CoV-2 infection during pregnancy and risk of stillbirth. STUDY DESIGN: This retrospective cohort study used multilevel logistic regression analyses of nationwide electronic health records in the United States. Data were from 75 healthcare systems and institutes across 50 states. A total of 191,403 pregnancies of 190,738 individuals of reproductive age (15-49 years) who had childbirth between March 1, 2020 and May 31, 2021 were identified and included. The main outcome was stillbirth at ≥20 weeks of gestation. Exposures were the timing of SARS-CoV-2 infection: early pregnancy (<20 weeks), midpregnancy (21-27 weeks), the third trimester (28-43 weeks), any time before delivery, and never infected (reference). RESULTS: We identified 2342 (1.3%) pregnancies with COVID-19 in early pregnancy, 2075 (1.2%) in midpregnancy, and 12,697 (6.9%) in the third trimester. After adjusting for maternal and clinical characteristics, increased odds of stillbirth were observed among pregnant individuals with SARS-CoV-2 infection only in early pregnancy (odds ratio, 1.75, 95% confidence interval, 1.25-2.46) and midpregnancy (odds ratio, 2.09; 95% confidence interval, 1.49-2.93), as opposed to pregnant individuals who were never infected. Older age, Black race, hypertension, acute respiratory distress syndrome or acute respiratory failure, and placental abruption were found to be consistently associated with stillbirth across different trimesters. CONCLUSION: Increased risk of stillbirth was associated with COVID-19 only when pregnant individuals were infected during early and midpregnancy, and not at any time before the delivery or during the third trimester, suggesting the potential vulnerability of the fetus to SARS-CoV-2 infection in early pregnancy. Our findings underscore the importance of proactive COVID-19 prevention and timely medical intervention for individuals infected with SARS-CoV-2 during early and midpregnancy.

Improving mRNA vaccine safety and efficiency with cationized lipid nanoparticle formula (preprint)

The widespread use of Covid-19 mRNA vaccines has highlighted the need to address rare but concerning side effects. Systemic off-target gene expression has been identified as a primary cause of acute adverse reactions and side effects associated with nucleoside-modified mRNA vaccines. In this study, we incorporated the permanent cationic lipid Dotap component into the mRNA-LNP formula associated with the FDA-approved mRNA vaccine Comirnaty to create a novel positively charged LNP carrier for mRNA vaccine delivery. Using the optimized LNP formula to prepare SARS-Cov-2 Spike mRNA vaccines for immunogenicity testing, Balb/c mice exhibited improved immunogenicity kinetics with initial antibody titers being lower but showing a continuous upward trend, ultimately reaching levels comparable to those of control mRNA vaccines 8 weeks after boost immunization. The mRNA vaccines encapsulated in the modified LNPs have demonstrated a superior safety profile in respect to systemic delivery of LNP constituents, off-target gene expression, and the systemic pro-inflammatory stimulation. Consequently, it may represent a safer alternative of conventional mRNA-LNP vaccines.

Teicoplanin derivatives block spike protein mediated viral entry as pan-SARS-CoV-2 inhibitors.

The rapid emergence of highly transmissible SARS-CoV-2 variants poses serious threat to the efficacy of vaccines and neutralizing antibodies. Thus, there is an urgent need to develop new and effective inhibitors against SARS-CoV-2 and future outbreaks. Here, we have identified a series of glycopeptide antibiotics teicoplanin derivatives that bind to the SARS-CoV-2 spike (S) protein, interrupt its interaction with ACE2 receptor and selectively inhibit viral entry mediated by S protein. Computation modeling predicts that these compounds interact with the residues in the receptor binding domain. More importantly, these teicoplanin derivatives inhibit the entry of both pseudotyped SARS-CoV-2 Delta and Omicron variants. Our study demonstrates the feasibility of developing small molecule entry inhibitors by targeting the interaction of viral S protein and ACE2. Together, considering the proven safety and pharmacokinetics of teicoplanin as a glycopeptide antibiotic, the teicoplanin derivatives hold great promise of being repurposed as pan-SARS-CoV-2 inhibitors.

Cancer and COVID-19 Vaccines on Twitter:The Voice and Vaccine Attitude of Cancer Community.

We investigate social media discourses on the relationship between cancer and COVID-19 vaccines focusing on the key textual topics, themes reflecting the voice of cancer community, authors who contribute to the discourse, and valence toward vaccines. We analyzed 6,427 tweets about cancer and COVID-19 vaccines, posted from when vaccines were approved in the U.S. (December 2020) to the February 2022. We mixed quantitative text mining, manual coding and statistical analysis, and inductive qualitative thematic analysis. Nearly 16% of the tweets posted by a cancer community member mentioned about refusal or delay of their vaccination at the state/local level during the initial rollout despite the CDC's recommendation to prioritize adults with high-risk medical conditions. Most tweets posted by cancer patients (pro = 82.4% vs. anti = 5.1%) and caregivers (pro = 89.2% vs. anti = 4.2%) showed positive valence toward vaccines and advocated for vaccine uptake increase among cancer patients and the general population. Vaccine hesitancy, self-reported adverse events, and COVID-19 disruption of cancer treatment also appeared as key themes. The cancer community called for actions to improve vaccination procedures to become safe and accessible especially for elderly cancer patients, develop COVID-19 vaccines suitable for varying type, stage, and treatment of cancer, and advance cancer vaccines. Future research should continue surveilling conversations around continuous impacts of COVID-19 interference with the cancer control continuum, beyond vaccination, focusing on the voice and concern of cancer community.

SARS-CoV-2 hijacks cellular kinase CDK2 to promote viral RNA synthesis.

The coronavirus disease 2019 (COVID-19) pandemic has devastated global health. Identifying key host factors essential for SARS-CoV-2 RNA replication is expected to unravel cellular targets for the development of broad-spectrum antiviral drugs which have been quested for the preparedness of future viral outbreaks. Here, we have identified host proteins that associate with nonstructural protein 12 (nsp12), the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 using a mass spectrometry (MS)-based proteomic approach. Among the candidate factors, CDK2 (Cyclin-dependent kinase 2), a member of cyclin-dependent kinases, interacts with nsp12 and causes its phosphorylation at T20, thus facilitating the assembly of the RdRp complex consisting of nsp12, nsp7 and nsp8 and promoting efficient synthesis of viral RNA. The crucial role of CDK2 in viral RdRp function is further supported by our observation that CDK2 inhibitors potently impair viral RNA synthesis and SARS-CoV-2 infection. Taken together, we have discovered CDK2 as a key host factor of SARS-CoV-2 RdRp complex, thus serving a promising target for the development of SARS-CoV-2 RdRp inhibitors.

Identification of the pathogenic relationship between Long COVID and Alzheimer's disease by bioinformatics methods (preprint)

Background The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused an unprecedented global health crisis. Although many Corona Virus Disease 2019 (COVID-19) patients have recovered, the long-term consequences of SARS-CoV-2 infection are unclear. Several independent epidemiological surveys and clinical studies have found that SARS-CoV-2 infection and Long COVID are closely related to Alzheimer's disease (AD). This could lead to long-term medical challenges and social burdens following this health crisis. However, the mechanism between Long COVID and AD is unknown.Methods Genes associated with Long COVID were collected from the database. Two sets of AD-related clinical sample datasets were collected in the Gene Expression Omnibus (GEO) database by limiting screening conditions. After identifying the differentially expressed genes (DEGs) of AD, the significant overlapping genes of AD and Long COVID were obtained by taking the intersection. Then, four kinds of analyses were performed, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis, protein-protein interaction (PPI) analysis, identification of hub genes, hub gene verification and transcription factors (TFs) prediction.Results A total of 197 common genes were selected for subsequent analysis. GO and KEGG enrichment analysis showed that these genes were mainly enriched in multiple neurodegenerative disease related pathways. In addition, 20 important hub genes were identified using cytoHubba. At the same time, these hub genes were verified in another data set, where 19 hub gene expressions were significantly different in the two diseases and 6 hub genes were significantly different in AD patients of different genders. Finally, we collected 9 TFs that may regulate the expression of these hub genes in the Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRUSST) database and verified them in the current data set.Conclusion This work reveals the common pathways and hub genes of AD and Long COVID, providing new ideas for the pathogenic relationship between these two diseases and further mechanism research.

IFITM3 Inhibits SARS-CoV-2 Infection and Is Associated with COVID-19 Susceptibility.

SARS-CoV-2 has become a global threat to public health. Infected individuals can be asymptomatic or develop mild to severe symptoms, including pneumonia, respiratory distress, and death. This wide spectrum of clinical presentations of SARS-CoV-2 infection is believed in part due to the polymorphisms of key genetic factors in the population. In this study, we report that the interferon-induced antiviral factor IFITM3 inhibits SARS-CoV-2 infection by preventing SARS-CoV-2 spike-protein-mediated virus entry and cell-to-cell fusion. Analysis of a Chinese COVID-19 patient cohort demonstrates that the rs12252 CC genotype of IFITM3 is associated with SARS-CoV-2 infection risk in the studied cohort. These data suggest that individuals carrying the rs12252 C allele in the IFITM3 gene may be vulnerable to SARS-CoV-2 infection and thus may benefit from early medical intervention.

Rapid Genotyping of SARS-CoV-2 Strains Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/BA.5 Using ARMS- PCR and Molecular Beacon Technology (preprint)

Background SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/BA.5 have significant differences in transmission and immune escape ability. Currently, no effective detection methods are available for these subtypes. Routine detection methods are prone to missed detection.Methods In this study, a rapid detection method based on ARMS-PCR and molecular beacon probes was developed for the identification of SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/5. Specific primers and probes were designed and validated using gel electrophoresis, real-time fluorescence quantitative PCR, and molecular hybridization.Results ARMS-PCR and molecular beacon probe-based assays can be applied in RT-PCR and fluorescence assays to differentiate SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/5.Conclusions In the present study, we developed a simple, rapid and accurate detection method based on ARMS-PCR and molecular beacon probes for rapid genotyping of SARS-CoV-2 subtypes Alpha, Delta, Omicron BA.1, Omicron BA.2, Omicron BA.2.12.1, and Omicron BA.4/5. It can be used in real-time fluorescence quantitative PCR and molecular hybridization to identify subtypes of COVID-19, effectively improving the detection rate to provide guidance for disease prevention and treatment.

Temporal Events Detector for Pregnancy Care (TED-PC): A rule-based algorithm to infer gestational age and delivery date from electronic health records of pregnant women with and without COVID-19.

OBJECTIVE: Identifying the time of SARS-CoV-2 viral infection relative to specific gestational weeks is critical for delineating the role of viral infection timing in adverse pregnancy outcomes. However, this task is difficult when it comes to Electronic Health Records (EHR). In combating the COVID-19 pandemic for maternal health, we sought to develop and validate a clinical information extraction algorithm to detect the time of clinical events relative to gestational weeks. MATERIALS AND METHODS: We used EHR from the National COVID Cohort Collaborative (N3C), in which the EHR are normalized by the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). We performed EHR phenotyping, resulting in 270,897 pregnant women (June 1st, 2018 to May 31st, 2021). We developed a rule-based algorithm and performed a multi-level evaluation to test content validity and clinical validity, and extreme length of gestation (<150 or >300). RESULTS: The algorithm identified 296,194 pregnancies (16,659 COVID-19, 174,744 without COVID-19) in 270,897 pregnant women. For inferring gestational age, 95% cases (n = 40) have moderate-high accuracy (Cohen's Kappa = 0.62); 100% cases (n = 40) have moderate-high granularity of temporal information (Cohen's Kappa = 1). For inferring delivery dates, the accuracy is 100% (Cohen's Kappa = 1). The accuracy of gestational age detection for the extreme length of gestation is 93.3% (Cohen's Kappa = 1). Mothers with COVID-19 showed higher prevalence in obesity or overweight (35.1% vs. 29.5%), diabetes (17.8% vs. 17.0%), chronic obstructive pulmonary disease (0.2% vs. 0.1%), respiratory distress syndrome or acute respiratory failure (1.8% vs. 0.2%). DISCUSSION: We explored the characteristics of pregnant women by different gestational weeks of SARS-CoV-2 infection with our algorithm. TED-PC is the first to infer the exact gestational week linked with every clinical event from EHR and detect the timing of SARS-CoV-2 infection in pregnant women. CONCLUSION: The algorithm shows excellent clinical validity in inferring gestational age and delivery dates, which supports multiple EHR cohorts on N3C studying the impact of COVID-19 on pregnancy.

A Versatile Biomimic Nanotemplating Fluidic Assay for Multiplex Quantitative Monitoring of Viral Respiratory Infections and Immune Responses in Saliva and Blood.

The last pandemic exposed critical gaps in monitoring and mitigating the spread of viral respiratory infections at the point-of-need. A cost-effective multiplexed fluidic device (NFluidEX), as a home-test kit analogous to a glucometer, that uses saliva and blood for parallel quantitative detection of viral infection and body's immune response in an automated manner within 11 min is proposed. The technology integrates a versatile biomimetic receptor based on molecularly imprinted polymers in a core-shell structure with nano gold electrodes, a multiplexed fluidic-impedimetric readout, built-in saliva collection/preparation, and smartphone-enabled data acquisition and interpretation. NFluidEX is validated with Influenza A H1N1 and SARS-CoV-2 (original strain and variants of concern), and achieves low detection limit in saliva and blood for the viral proteins and the anti-receptor binding domain (RBD) Immunoglobulin G (IgG) and Immunoglobulin M (IgM), respectively. It is demonstrated that nanoprotrusions of gold electrodes are essential for the fine templating of antibodies and spike proteins during molecular imprinting, and differentiation of IgG and IgM in whole blood. In the clinical setting, NFluidEX achieves 100% sensitivity and 100% specificity by testing 44 COVID-positive and 25 COVID-negative saliva and blood samples on par with the real-time quantitative polymerase chain reaction (p < 0.001, 95% confidence) and the enzyme-linked immunosorbent assay.

Analysis of Residential Segregation and Racial and Ethnic Disparities in Severe Maternal Morbidity Before and During the COVID-19 Pandemic.

Importance: Persistent racial and ethnic disparities in severe maternal morbidity (SMM) in the US remain a public health concern. Structural racism leaves women of color in a disadvantaged situation especially during COVID-19, leading to disproportionate pandemic afflictions among racial and ethnic minority women. Objective: To examine racial and ethnic disparities in SMM rates before and during the COVID-19 pandemic and whether the disparities varied with level of Black residential segregation. Design, Setting, and Participants: A statewide population-based retrospective cohort study used birth certificates linked to all-payer childbirth claims data in South Carolina. Participants included women who gave birth between January 2018 and June 2021. Data were analyzed from December 2021 to February 2022. Exposures: Exposures were (1) period when women gave birth, either before the pandemic (January 2018 to February 2020) or during the pandemic (March 2020 to June 2021) and (2) Black-White residential segregation (isolation index), categorizing US Census tracts in a county as low (<40%), medium (40%-59%), and high (≥60%). Main Outcomes and Measures: SMM was identified using International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes developed by the US Centers for Disease Control and Prevention. Multilevel logistic regressions with an interrupted approach were used, adjusting for maternal-level and facility-level factors, accounting for residential county-level random effects. Results: Of 166 791 women, 95 098 (57.0%) lived in low-segregated counties (mean [SD] age, 28.1 [5.7] years; 5126 [5.4%] Hispanic; 20 523 [21.6%] non-Hispanic Black; 62 690 [65.9%] White), and 23 521 (14.1%) women (mean [SD] age, 28.1 [5.8] years; 782 [3.3%] Hispanic; 12 880 [54.8%] non-Hispanic Black; 7988 [34.0%] White) lived in high-segregated areas. Prepandemic SMM rates were decreasing, followed by monthly increasing trends after March 2020. On average, living in high-segregated communities was associated with higher odds of SMM (adjusted odds ratio [aOR], 1.61; 95% CI, 1.06-2.34). Black women regardless of residential segregation had higher odds of SMM than White women (aOR, 1.47; 95% CI, 1.11-1.96 for low-segregation; 2.12; 95% CI, 1.38-3.26 for high-segregation). Hispanic women living in low-segregated communities had lower odds of SMM (aOR, 0.48; 95% CI, 0.25-0.90) but those living in high-segregated communities had nearly twice the odds of SMM (aOR, 1.91; 95% CI, 1.07-4.17) as their White counterparts. Conclusions and Relevance: Living in high-segregated Black communities in South Carolina was associated with racial and ethnic SMM disparities. During the COVID-19 pandemic, Black vs White disparities persisted with no signs of widening gaps, whereas Hispanic vs White disparities were exacerbated. Policy reforms on reducing residential segregation or combating the corresponding structural racism are warranted to help improve maternal health.

Human coronaviruses: The emergence of SARS-CoV-2 and management of COVID-19.

To date, a total of seven human coronaviruses (HCoVs) have been identified, all of which are important respiratory pathogens. Recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has led to a global pandemic causing millions of infections and deaths. Here, we summarize the discovery and fundamental virology of HCoVs, discuss their zoonotic transmission and highlight the weak species barrier of SARS-CoV-2. We also discuss the possible origins of SARS-CoV-2 variants of concern identified to date and discuss the experimental challenges in characterizing mutations of interest and propose methods to circumvent them. As the COVID-19 treatment and prevention landscape rapidly evolves, we summarize current therapeutics and vaccines, and their implications on SARS-CoV-2 variants. Finally, we explore how interspecies transmission of SARS-CoV-2 may drive the emergence of novel strains, how disease severity may evolve and how COVID-19 will likely continue to burden healthcare systems globally.

Curating a knowledge base for individuals with coinfection of HIV and SARS-CoV-2: a study protocol of EHR-based data mining and clinical implementation.

INTRODUCTION: Despite a higher risk of severe COVID-19 disease in individuals with HIV, the interactions between SARS-CoV-2 and HIV infections remain unclear. To delineate these interactions, multicentre Electronic Health Records (EHR) hold existing promise to provide full-spectrum and longitudinal clinical data, demographics and sociobehavioural data at individual level. Presently, a comprehensive EHR-based cohort for the HIV/SARS-CoV-2 coinfection has not been established; EHR integration and data mining methods tailored for studying the coinfection are urgently needed yet remain underdeveloped. METHODS AND ANALYSIS: The overarching goal of this exploratory/developmental study is to establish an EHR-based cohort for individuals with HIV/SARS-CoV-2 coinfection and perform large-scale EHR-based data mining to examine the interactions between HIV and SARS-CoV-2 infections and systematically identify and validate factors contributing to the severe clinical course of the coinfection. We will use a nationwide EHR database in the USA, namely, National COVID Cohort Collaborative (N3C). Ultimately, collected clinical evidence will be implemented and used to pilot test a clinical decision support prototype to assist providers in screening and referral of at-risk patients in real-world clinics. ETHICS AND DISSEMINATION: The study was approved by the institutional review boards at the University of South Carolina (Pro00121828) as non-human subject study. Study findings will be presented at academic conferences and published in peer-reviewed journals. This study will disseminate urgently needed clinical evidence for guiding clinical practice for individuals with the coinfection at Prisma Health, a healthcare system in collaboration.

Immunogenicity of a vaccinia virus-based severe acute respiratory syndrome coronavirus 2 vaccine candidate

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines provide essential tools for the control of the COVID-19 pandemic. A number of technologies have been employed to develop SARS-CoV-2 vaccines, including the inactivated SARS-CoV-2 particles, mRNA to express viral spike protein, recombinant spike proteins, and viral vectors. Here, we report the use of the vaccinia virus Tiantan strain as a vector to express the SARS-CoV-2 spike protein. When it was used to inoculate mice, robust SARS-CoV-2 spike protein-specific antibody response and T-cell response were detected. Sera from the vaccinated mice showed strong neutralizing activity against the ancestral Wuhan SARS-CoV-2, the variants of concern (VOCs) B.1.351, B.1.617.2, and the emerging B.1.1.529 (omicron). This finding supports the possibility of developing a new type of SARS-CoV-2 vaccine using the vaccinia virus vector.