Retrospective Analysis of Clostridioides difficile Infection Rates in Hospitalized Patients during COVID-19 Pandemic. A Unicenter Study in Reus, Spain (preprint)

.Background: Clostridioides difficile infections (CDI) vary in severity from mild diarrhea to life-threatening conditions like pseudomembranous colitis or toxic megacolon, often leading to sepsis and death. The COVID-19 pandemic prompted changes in healthcare practices, potentially affecting CDI incidence, though reported data are inconclusive. We studied factors influencing CDI incidence and outcomes at a university hospital throughout the COVID-19 pandemic years. Methods: We conducted a retrospective study on all adult hospitalized CDI cases from January 1, 2020, to December 31, 2022. We collected demographic information, comorbid conditions, and concurrent infections. Results: While overall CDI and COVID-19 rates decreased in 2022, a nota-ble increase in CDI infections was observed among oncological patients and those undergoing some aggressive treatments, such as colon or gastroscopies. The prevalence of comorbidities remained unmodified, and there were declines in prior gastrointestinal surgeries and proton pump inhibitor prescriptions. Factors associated with patient fatality or prolonged hospitaliza-tion included older age, cancer, chronic kidney disease, higher Charlson and McCabe indices, elevated C-reactive protein, and low albumin concentrations. Conclusion: Our study shows the evolving landscape of CDI during the COVID-19 pandemic and emphasizes the impact of de-layed diagnoses and treatments exacerbated by telemedicine adoption. Identified risk factors for CDI-related mortality or prolonged hospital stays underscore the importance of targeted inter-ventions in high-risk populations.

Characterization of spike processing and entry mechanisms of seasonal human coronaviruses NL63, 229E and HKU1 (preprint)

Although much has been learned about the entry mechanism of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the details of entry mechanisms of seasonal human coronaviruses (HCoVs) remain less well understood. In the present study, we established that 293T cell lines that stably express angiotensin converting enzyme (ACE2), aminopeptidase N (APN), or transmembrane serine protease 2 (TMPRSS2) support high level transduction of lentiviral pseudoviruses bearing spike proteins of seasonal HCoVs, HCoV-NL63, -229E, or -HKU1, respectively. Our results showed that entry of HCoV-NL63, -229E and -HKU1 pseudoviruses is sensitive to endosomal acidification inhibitors (chloroquine and NH4Cl), indicating virus entry via the endocytosis route. Although HCoV-HKU1 pseudovirus infection requires TMPRSS2 expression on cell surface, endocytosis-mediated HCoV-HKU1 entry requires the serine protease domain but not the serine protease activity of TMPRSS2. We also show that amino acids in the predicted S1/S2 junctions of spike proteins of HCoV-NL63, and -229E are essential for optimal entry but non-essential for spike-mediated entry of HCoV-HKU1. Our findings provide insights into entry mechanism of seasonal HCoVs that may support the development of novel treatment strategies.

Machine Learning for Affordable Diagnosis of SARS-COV-2 from Hematological and Biochemical Tests (preprint)

COVID-19, caused by the SARS-CoV-2 virus, has spread around the world and killed around 6.9 million people. Rapid and accurate diagnosis is essential for preventing and controlling the disease, reducing transmission and consequently saving lives. RT-PCR is the gold standard test used to detect the disease. However, the test is expensive and the result is time-consuming, which makes mass testing difficult, especially in countries with limited resources. In addition, the test has high analytical specificity and low diagnostic sensitivity, which leads to false-negative results. Several studies in the literature report the presence of hematological and biochemical alterations in infected patients and use these alterations with machine learning algorithms to help diagnose the disease. Therefore, this article presents the results obtained by different neural network architectures based on Adaptive Resonance Theory (ART) for the diagnosis of COVID-19. The study was conducted in two distinct stages: the first consisted of selecting the best ART network among several, using three open-access datasets and comparing the results with the literature. In the second stage, the chosen model was tested on a dataset containing patients from various hospitals in four countries. In addition, the model was subjected to external validation, including data from a country not present during the training and adjustment of the model, in order to validate the robustness and generalization capacity of the model. The results obtained by the ART networks in this study are promising, outperforming not only classical models, but also the deep learning models often used in the literature. Validation on data from different countries strengthens the model’s reliability and effectiveness.

Antigenic cartography using hamster sera identifies SARS-CoV-2 JN.1 evasion seen in human XBB.1.5 booster sera (preprint)

Antigenic assessments of SARS-CoV-2 variants inform decisions to update COVID-19 vaccines. Primary infection sera are often used for assessments, but such sera are rare due to population immunity from SARS-CoV-2 infections and COVID-19 vaccinations. Here, we show that neutralization titers and breadth of matched human and hamster pre-Omicron variant primary infection sera correlate well and generate similar antigenic maps. The hamster antigenic map shows modest antigenic drift among XBB sub-lineage variants, with JN.1 and BA.4/BA.5 variants within the XBB cluster, but with five to six-fold antigenic differences between these variants and XBB.1.5. Compared to sera following only ancestral or bivalent COVID-19 vaccinations, or with post-vaccination infections, XBB.1.5 booster sera had the broadest neutralization against XBB sub-lineage variants, although a five-fold titer difference was still observed between JN.1 and XBB.1.5 variants. These findings suggest that antibody coverage of antigenically divergent JN.1 could be improved with a matched vaccine antigen.

Identification of immune cell infiltration and biomarkers in Alzheimer's disease and COVID-19 by integrated bioinformatics analysis and machine learning (preprint)

Background: Since its emergence in late 2019, COVID-19 has become a global epidemic, resulting in numerous infections, including a significant number of critically ill patients. Several studies have suggested a possible link between Alzheimer's disease (AD) and COVID-19. For instance, a Mendelian randomization study has proposed a causal relationship between Alzheimer's disease and COVID-19 in the pathogenic mechanism. However, there are limited studies exploring the common pathogenic genes and immune infiltration between the two. Therefore, we conducted this study to identify key genes in COVID-19 associated with Alzheimer's disease, evaluate their correlation with immune cell characteristics and metabolic pathways, and investigate potential novel biomarkers. Methods: Transcriptome analyses were used to identify common biomolecular markers of AD and COVID-19. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on gene chip datasets (GSE213313, GSE5281, and GSE63060) from AD and COVID-19 patients to identify genes associated with both conditions. Common pathogenic molecular mechanisms were identified through Gene Ontology (GO) enrichment analyses. The core genes were then identified using machine learning methods. Subsequently, we evaluated the relationship between these core genes and common immune cells and metabolic pathways. Finally, our findings were validated through single-cell analysis. Results: The study identified 484 common differentially expressed genes (DEGs) by taking the intersection of genes between AD and COVID-19. The black module, containing 132 genes, showed the highest association between the two diseases according to WGCNA. GO enrichment analysis revealed that these genes mainly affect inflammation, cytokines, immune-related functions, and signaling pathways related to metal ions and cellular response to viruses. Additionally, a machine learning approach identified eight core genes. We identified links between these genes and immune cells and also found a strong association between EIF3H and oxidative phosphorylation. In addition, these results were further validated by single-cell analysis. Conclusion: This study identifies potential shared genes, signaling pathways, immune-related alterations, and changes in metabolic pathways that may collectively contribute to the pathogenesis of COVID-19 and Alzheimer's disease. These findings provide new targets for the diagnosis and treatment of both diseases.

Social isolation emanated psychological exhaustion and disconnectedness among physicians during the COVID-19 pandemic: Results of a qualitative study in Pakistan (preprint)

Background: During the COVID-19 pandemic, many healthcare providers remained on call in COVID-19 wards, isolation centres, and emergency departments, caring for both infected and non-infected patients. Physicians have faced various challenges during the pandemic, including the stress of working with limited resources, the physical burden of long work hours and fear of public abuse in terms of stigmatization. Therefore, this study focusses on social-psychological aspects of isolation period of physicians during the COVID-19 pandemic. Methods: It is a qualitative study based on responses from 14 physicians working in two hospitals located in Islamabad, which is the capital city of Pakistan (Pakistan Institute of Medical Sciences [PIMS] and PolyclinicHospital). In-depth interviews were conducted with selected physicians by using an interview guide as a tool of data collection to explore the experiences of those physicians who suffered from COVID-19 and lived in isolation as their quarantine period. The data was analyzed by using thematic analysis technique. Results: The study explored isolation experiences of physicians during the selected period of COVID-19 and significantly found that two major themes emerged, i.e. psychological exhaustion (depression, anxiety and loneliness were subthemes) and disconnectedness (relational detachment and lack of interaction were subthemes). Conclusions: This pandemic crisis has significantly resulted in having adverse impact on the ability of physicians to approach both potential and existing patients. Particularly in times of such a crisis, adequate measures have to be taken to address mental health issues of the health workforce.

Three Modes of Viral Adaption by the Heart (preprint)

Viruses elicit long-term adaptive responses in the tissues they infect. Understanding viral adaptions in humans is difficult in organs such as the heart, where primary infected material is not routinely collected. In search of asymptomatic infections with accompanying host adaptions, we mined for cardio-pathogenic viruses in the unaligned reads of nearly one thousand human hearts profiled by RNA sequencing. Among virus-positive cases (~20%), we identified three robust adaptions in the host transcriptome related to inflammatory NFkappaB signaling and post-transcriptional regulation by the p38-MK2 pathway. The adaptions are not determined by the infecting virus, and they recur in infections of human or animal hearts and cultured cardiomyocytes. Adaptions switch states when NFkappaB or p38-MK2 are perturbed in cells engineered for chronic infection by the cardio-pathogenic virus, coxsackievirus B3. Stratifying viral responses into reversible adaptions adds a targetable systems-level simplification for infections of the heart and perhaps other organs.

Humoral immune response characteristics of the susceptible populations after the infection of SARS-CoV-2 BA.5 strain (preprint)

This study compared the humoral immune characteristics of children, elderly people, pregnant women, and adults infected with BA.5 and XBB strains in Guangzhou, China. It was found that binding and neutralizing antibodies the titers against distinct SARS-CoV-2 strains were low in the acute-phase sera of BA.5 infected patients, while the corresponding titers were significantly increased in the convalescent phase, the antibody titers against the Wuhan strain were the highest. Regardless of whether they were vaccinated, BA.5 infection did not induce high neutralizing antibodies against XBB. During the recovery phase, the titers of antiviral antibodies in the vaccinated population are more robust than those in the unvaccinated population. For BA.5 infections, the specific binding and neutralizing antibody titers in the children group were lower compared to other population groups. In the convalescence period of the disease, the titers of neutralizing antibodies against Wuhan, BA.5 and XBB strains induced by BA.5 infections are significantly correlated in pairs. XBB can induce a broader and balanced antiviral humoral immune response than BA.5 as a first-time infected strain. This finding can provide a reference for the judgment of the future epidemic law of SARS-CoV-2, and provide a scientific basis for developing novel COVID-19 vaccines, especially for discovering customized vaccines and immune strategies for different populations.

COHORT PROFILE: IMMUNE RESPONSES TO SARS-COV-2 VACCINATION AND INFECTION IN A LONGITUDINAL SAMPLING AMIDST THE COVID-19 PANDEMIC (LONGTONG-SARS2) IN MALAYSIA (preprint)

Purpose: This prospective, longitudinal study aims to evaluate the durability and functionality of SARS-CoV-2 Ancestral strain (Wuhan-Hu-1)-specific immune responses induced by COVID-19 vaccination and natural infection over a 12-month period. This article reviews the study protocol, design, methodology, ongoing data collection, analysis procedures, and demographic characteristics of the cohort enrolled. Participants: Between March 2021 and May 2022, 400 participants were enrolled with a 12-month follow-up, concluding in May 2023. Two main groups of participants: (1) serologically SARS-CoV-2-naive individuals receiving the BNT162b2 primary series vaccination (referred to as VAC) and (2) those who recently recovered from COVID-19 infection within 30 days, regardless of vaccination history (referred to as COV). Additionally, a subset of 45 participants with selected COVID-19 exposure histories provided peripheral blood mononuclear cells (PBMCs) for cross-sectional analysis six months after enrollment. Findings to date: Out of 400 participants, 66.8% (n=267) completed the follow-up. Among them, 52.8% (n=141) were in VAC, and 47.2% (n=126) were in COV. As the study progressed, we acknowledged cross-over between initial groups, leading to restructuring into five revised groups based on sequential exposure events. Sociodemographic factors revealed statistically significant age distribution differences (p=0.001) in both initial and revised groups, with no significant differences observed for sex. Future plans: LONGTONG-SARS2 assesses the host-pathogen interactions central to the development of COVID-19 immunity. With enrollment spanning two years of the pandemic, most participants exhibited mixed SARS-CoV-2 exposures-via vaccination and infection-resulting in diverse subgroups of interest. Notably, the inclusion of SARS-CoV-2-naive, pre-exposure serum samples allowed for robust comparator and reduced potential biases. Ongoing analyses will include serology kinetics, memory cells ELISpots, B cells repertoire analysis, cytokine/chemokine profiling, and proteomic pathway to comprehensively examine the immune response against the SARS-CoV-2, thus informing and potentially predicting dynamic longitudinal responses against new more transmissible, immune-evasive SARS-CoV-2 variants.

An outbreak of a pathogenic canine coronavirus type 2 in captive snow leopards (Panthera uncia) in the U.S, with severe gastrointestinal signs (preprint)

The species alphacoronavirus-1 comprises a set of diverse viruses of cats, dogs, and pigs, and is highly recombinogenic. Within this species, canine coronavirus type 2 (CCoV-2) can infect multiple species of canids, causing a range of clinical outcomes. CCoV-2 is genetically related to feline coronavirus type 1 (FCoV-1) and type 2 (FCoV-2), with FCoV-2 being a recombinant genotype of FCoV-1 and CCoV-2. Recently, a novel FCoV (FCoV-23) resulting from recombination with a highly pathogenic (pantropic) CCoV-2 (pCCoV-2) has been identified as the cause of a widespread outbreak among stray/feral cats in Cyprus. To understand the origin of recombinant variants it is crucial to identify hosts that can be infected with viruses in the species alphacoronavirus-1. Experimental evidence indicates that domesticated cats likely play a central role in the emergence of recombinant variants, as they can also be infected with CCoV-2. Wild felids are genetically closely related to domestic cats and may also be susceptible to FCoV and CCoV infection; however, there have been no reports of natural infection with CCoV in domesticated or wild felids. In this study, we retrospectively investigated a localized outbreak of severe enteritis in snow leopards (Panthera uncia) housed in a zoological institute in the U.S. Molecular screening and whole genome sequencing revealed the shedding of CCoV-2 in the feces of the three sick leopards. Phylogenetic analyses of the spike gene revealed it is genetically related to pathogenic variants of CCoV-2 identified in domesticated dogs in the U.S., and to pCCoV-2 CB/05 circulating in Europe. This study provides the first genetic evidence of CCoV-2 infection in a wild felid and highlights the necessity of conducting surveillance of both FCoV and CCoV in domesticated and wild felids.

Optimizing Vaccine Site Locations While Considering Travel Inconvenience and Public Health Outcomes (preprint)

During the COVID-19 pandemic, there were over three million infections in Los Angeles County (LAC). To facilitate distribution when vaccines first became available, LAC set up six mega-sites for dispensing a large number of vaccines to the public. To understand if another choice of mega-site location would have improved accessibility and health outcomes, and to provide insight into future vaccine allocation problems, we propose a multi-objective mixed integer linear programming model that balances travel convenience, infection reduction, and equitable distribution. We provide a tractable objective formulation that effectively proxies real-world public health goals of reducing infections while considering travel inconvenience and equitable distribution of resources. Compared with the solution empirically used in LAC in 2020, we recommend more dispersed mega-site locations that result in a 28% reduction in travel inconvenience and avert an additional 1,000 infections.

Estimating COVID-19 lockdown effectiveness: Analysis of the 2020 Danish mink lockdown (preprint)

In late 2020 Denmark became the focus of the global efforts against the Covid-19 pandemic when reports of a mutated SARS-CoV-2 virus variant in the countries population of 17 million farmed mink appeared. Spillover infections between mink and humans were feared to threaten the efficacy of upcoming vaccines. In this study the ensuing short-lived yet stringent lockdowns imposed in 7 of the countries 98 municipalities are analysed for their effectiveness to reduce SARS-CoV-2 infections. Synthetic counterfactuals are created for each of these municipalities using a weighted average combination of the the 91 municipalities not targeted by the stringent measures. This allows for a clear overview regarding the development of test-positivity rates, citizen mobility behaviours and lastly daily infection numbers in response to the restrictions. The findings show that these targeted, short-term lockdowns significantly curtailed further infections, demonstrating a marked decrease, first in citizens mobility and then in daily cases when compared to their synthetic counterfactuals. Overall, the estimates indicate average reductions to infection numbers to be around 31\%. This study underscores the potential of strict, yet severe lockdowns in breaking ongoing infection dynamics, by utilising a rare quasi-experimental design case that avoids endogeneity through treatment selection.

Binding of SARS-CoV-2 nucleocapsid protein to uninfected epithelial cells induces antibody-mediated complement deposition (preprint)

SARS-CoV-2 infection triggers strong antibody response toward Nucleocapsid-Protein (NP), suggesting extracellular presence beyond its intra-virion RNA binding. Interestingly, NP was found to decorate infected and proximal uninfected cell-surfaces. Here, we propose a new mechanism through which extracellular NP on uninfected cells contributes to COVID-19 pathogenicity. We show that NP binds to cell-surface sulfated linear-glycosaminoglycans by spatial rearrangement of its RNA-binding sites facilitated by the flexible, positively charged, linker. Coating of uninfected lung-derived cells with purified NP attracted anti-NP-IgG from lung fluids and sera collected from COVID-19 patients. The magnitude of this immune recognition was significantly elevated in moderate compared to mild COVID-19 cases. Importantly, binding of anti-NP-IgG present in sera generated clusters that triggered C3b deposition by the classical complement pathway. Heparin analog enoxaparin outcompeted NP-binding, rescuing cells from anti-NP IgG-mediated complement deposition. Our findings unveil how extracellular NP may exacerbate COVID-19 tissue damage, and suggest leads for preventative therapy.

Role of the complement system in Long COVID (preprint)

Long COVID, or Post-Acute COVID Syndrome (PACS), may develop following SARS-CoV-2 infection, posing a substantial burden to society. Recently, PACS has been linked to a persistent activation of the complement system (CS), offering hope for both a diagnostic tool and targeted therapy. However, our findings indicate that, after adjusting proteomics data for age, body mass index and sex imbalances, the evidence of complement system activation disappears. Furthermore, proteomic analysis of two orthogonal cohorts-one addressing PACS following severe acute phase and another after a mild acute phase-fails to support the notion of persistent CS activation. Instead, we identify a proteomic signature indicative of either ongoing infections or sustained immune activation similar to that observed in acute COVID-19, particularly within the mild-PACS cohort.

Leukopenia of Asymptomatic COVID-19 Infections under 18 Years Old in Recovery Stage (Running head: Leukopenia of Asymptomatic COVID-19 Infections) (preprint)

Objectives In December, 2019, a type of novel coronavirus which was designated novel coronavirus 2019 (2019-nCoV) by the World Health Organization (WHO) occurred in Wuhan, Hubei, China. There is limited information available on the epidemiological and clinical characteristics of patients under 18 years old in the recovery stage. To compare the difference of epidemiological and clinical characteristics of COVID-19 involving 25 patients under 18 years old in the recovery stage between confirmed and asymptomatic infections.Methods The retrospective, single-center cohort study of COVID-19 involving 25 patients under 18 years old in the recovery stage at Guizhou Provincial Staff Hospital in Guiyang, China, from January 29 to March 31, 2020; last date of follow-up was April 22. We collected and analyzed epidemiological, demographic, clinical, laboratory, radiological, and treatment data. The researchers compared the epidemiological and clinical characteristics of confirmed COVID-19 infections and asymptomatic infections.Results Among the 25 COVID infections under 18 years old, 16 (64%) were mild or moderate confirmed cases, and 9 (36%) were asymptomatic. The shortest treatment period was 6 days, the longest 26 days, and the average treatment period was 14 days. Four cases (44.4%) had visited Wuhan or had a living story in the city. There were 9 (100%) asymptomatic cases were familial cluster outbreak, with an average infection number was 6 cases among all families. The number of asymptomatic COVID-19 infections with leukopenia was significantly more than confirmed cases (p = 0.04).Conclusions Leukopenia mostly occurred in asymptomatic COVID-19 infections under 18 years old compared with the confirmed patients.Trial registration: The Chinese Clinical Trial Register (CCTR number: ChiCTR2000032458) registered this study retrospectively on 28 April 2020.

ONE HEALTH APPROACH ON SARS-COV-2 - USING SHEEP AS SENTINEL ANIMALS TO INCREASE FUTURE PANDEMIC PREPAREDNESS - a pilot study (preprint)

Coronaviruses are a family of viruses that can infect a number of species of birds and mammals with great zoonotic potential to cross species barriers and cause spill-over events. SARS-CoV-2 has been shown to cause clinical and inapparent disease and mortality in several animals cohabitating with humans. Sheep are also susceptible to SARS-CoV-2 and have potential to harbor and spread the virus, as well as develop neutralising antibodies due to similarities of virus-receptor interactions to those in humans. The main aim of this study was to investigate the prevalence of SARS-CoV-2 neutralising antibodies in sentinel animals after natural exposure to the virus. The serum samples were collected from sheep in Central Portugal, Serra da Estrela region, both prior to and during the COVID-19 pandemic. The sheep were kept on dairy farms for production of Serra da Estrela cheese, in small herds and in constant contact with farm workers. The sera were tested using already established SARS-CoV-2 pseudovirus systems for multiple SARS-CoV-2 variants including Wuhan, Delta and Omicron. Partial neutralisation activity towards Wuhan and Delta variants was observed, while neutralisating antibody escape was observed in all Omicron variants tested due to the mutations present . Our results indicate that potential SARS-CoV-2 virus cross-species transmission could have been established through contacts between people and animals on sheep farms. Using farm animals as sentinels is of great importance for implementing One Health Approach in zoonotic virus surveillance and control towards increasing future pandemic preparedness.

Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron variant JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study (preprint)

A notable increase in severe cases of COVID-19, with significant hospitalizations due to the emergence and spread of JN.1 was observed worldwide in late 2023 and early 2024. During the study period (November 2022-January 2024), 56 JN.1- and 126 XBB-infected patients were prospectively enrolled in 40 French intensive care units. JN.1-infected patients were more likely to be obese (35.7% vs 20.8%; p=0.033) and less frequently immunosuppressed than others (20.4% vs 41.4%; p=0.010). JN.1-infected patients required invasive mechanical ventilation support in 29.1%, 87.5% of them received dexamethasone, 14.5% tocilizumab and none received monoclonal antibodies. Day-28 mortality of JN.1-infected patients was 14.6%.

The logic of coronavirus infection: revealing the heterogeneity of disease progression and treatment outcomes in COVID patients (preprint)

Pneumonia caused by coronavirus infection is a self-limiting disease. Its progression and prognosis are highly heterogeneous among people of different ages, genders, and living with different life styles. Such heterogeneity also exists in treatment outcomes of different patients. Various physiological and pathological factors, such as renewal of pulmonary cell, number of entry receptor and viral replication, have been identified linking to the development of the disease. However, it is still unclear how these factors collectively establish a causal relationship in the course of disease progression. In this study, we built a mechanistic model to explain the dynamics of infection and progression of coronavirus disease. We modeled how the interaction of pulmonary cells determine the dynamics of disease progression by characterizing the temporal dynamics of viral load, infected and health alveolar cells, and dysfuctional alveolar cells. The viral and cellular dynamics captured different stages of clinical manifestations in individual patient during disease progression: the incubation period, mild symptom period, and severe period. We further simulated clinical interference at different stages of disease progression. The results showed that some medical interventions show no improvement either in reducing the recovery rate nor shortening the recovery time. Our theoretical framework may provide a mechanistic explanation at the systems level for the progression and prognosis of coronavirus disease as well as other similar respiratory tract diseases.

COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI System (preprint)

Computer-aided diagnosis (CAD) systems stand out as potent aids for physicians in identifying the novel Coronavirus Disease 2019 (COVID-19) through medical imaging modalities. In this paper, we showcase the integration and reliable and fast deployment of a state-of-the-art AI system designed to automatically analyze CT images, offering infection probability for the swift detection of COVID-19. The suggested system, comprising both classification and segmentation components, is anticipated to reduce physicians' detection time and enhance the overall efficiency of COVID-19 detection. We successfully surmounted various challenges, such as data discrepancy and anonymisation, testing the time-effectiveness of the model, and data security, enabling reliable and scalable deployment of the system on both cloud and edge environments. Additionally, our AI system assigns a probability of infection to each 3D CT scan and enhances explainability through anchor set similarity, facilitating timely confirmation and segregation of infected patients by physicians.

SARS-CoV-2 antibody prevalence by industry, workplace characteristics, and workplace infection prevention and control measures, North Carolina, 2021 to 2022 (preprint)

Background: The COVID-19 pandemic has disproportionately affected workers in certain industries and occupations, and the workplace can be a high risk setting for SARS-CoV-2 transmission. In this study, we measured SARS-CoV-2 antibody prevalence and identified work-related risk factors in a population primarily working at industrial livestock operations. Methods: We used a multiplex salivary SARS-CoV-2 IgG antibody assay to determine infection-induced antibody prevalence among 236 adult (>=18 years) North Carolina residents between February 2021 and August 2022. We used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to classify employed participants' industry and compared infection-induced IgG prevalence by participant industry and with the North Carolina general population. We also combined antibody results with reported SARS-CoV-2 molecular test positivity and vaccination history to identify evidence of prior infection. We used logistic regression to estimate odds ratios of prior infection by potential work-related risk factors, adjusting for industry and date. Results: Most participants (55%) were infection-induced IgG positive, including 71% of animal slaughtering and processing industry workers, which is 1.5 to 4.3 times higher compared to the North Carolina general population, as well as higher than molecularly-confirmed cases and the only other serology study we identified of animal slaughtering and processing workers. Considering questionnaire results in addition to antibodies, the proportion of participants with evidence of prior infection increased slightly, to 61%, including 75% of animal slaughtering and processing workers. Participants with more than 1000 compared to 10 or fewer coworkers at their jobsite had higher odds of prior infection (adjusted odds ratio [aOR] 4.5, 95% confidence interval [CI] 1.0 to 21.0). Conclusions: This study contributes evidence of the severe and disproportionate impacts of COVID-19 on animal processing and essential workers and workers in large congregate settings. We also demonstrate the utility of combining non-invasive biomarker and questionnaire data for the study of workplace exposures.