Immunogenicity and safety of two-dose SARS-CoV-2 vaccination via different platforms in kidney transplantation recipients.

After kidney transplantation, patients exhibit a poor response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination. However, the efficacy and adverse effects of vaccines based on different platforms in these patients remain unclear. We prospectively analyzed both anti-spike protein antibody and cellular responses 1 month after the first and second doses of SARS-CoV-2 vaccines in 171 kidney transplant patients. Four vaccines, including one viral vector (ChAdOx1 nCov-19, n = 30), two mRNA (mRNA1273, n = 81 and BNT162b2, n = 38), and one protein subunit (MVC-COV1901, n = 22) vaccines were administered. Among the four vaccines, mRNA1273 elicited the strongest humoral response and induced the highest interferon-γ levels in patients with a positive cellular response against the spike protein. Antiproliferative agents were negatively associated with both the antibody and cellular responses. A transient elevation in creatinine levels was noted in approximately half of the patients after the first dose of mRNA1273 or ChadOx1, and only one of them presented with borderline cellular rejection without definite causality to vaccination. In conclusion, mRNA1273 had better immunogenicity than the other vaccines. Further, renal function needs to be carefully monitored after vaccination, and vaccination strategies should be tailored according to the transplant status and vaccine characteristics.

Evaluation of RT-LAMP Assay for Rapid Detection of SARS-CoV-2.

OBJECTIVE: To evaluate the accuracy of the reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in community or primary-care settings. METHOD: We systematically searched the Web of Science, Embase, PubMed, and Cochrane Library databases. We conducted quality evaluation using ReviewManager software (version 5.0). We then used MetaDisc software (version 1.4) and Stata software (version 12.0) to build forest plots, along with a Deeks funnel plot and a bivariate boxplot for analysis. RESULT: Overall, the sensitivity, specificity, and diagnostic odds ratio were 0.79, 0.97, and 328.18, respectively. The sensitivity for the subgroup with RNA extraction appeared to be higher, at 0.88 (0.86-0.90), compared to the subgroup without RNA extraction, at 0.50 (0.45-0.55), with no significant difference in specificity. CONCLUSION: RT-LAMP assay exhibited high specificity regarding current SARS-CoV-2 infection. However, its overall sensitivity was relatively moderate. Extracting RNA was found to be beneficial in improving sensitivity.

Hope Buffers the Effect of Fear of COVID-19 on Depression among College Students: Insomnia as a Mediator.

BACKGROUND: In the period of the global pandemic, psychophysical problems induced by the fear of COVID-19 among college students deserve attention since the dormitory environment in college greatly increases the possibility of COVID-19 infection. METHODS: A hypothesized mediated moderation model was to be verified using a cross-sectional study among 2453 college students. Fear of COVID-19, insomnia, hope, and depression were assessed by using the relevant scales. RESULTS: (1) The fear of COVID-19 was positively correlated to depression (ß = 0.365, t = 5.553, 95% CI = [0.236, 0.494]); (2) hope moderated the influence of the fear of COVID-19 on depression (ß = -0.093, t = -4.066, 95% CI = [-0.137, -0.048]), as well as on insomnia (ß = -0.095, t = -4.841, 95% CI = [-0.133, -0.056]); and (3) the mediated moderation model with hope as the moderator and insomnia as the full mediating variable between fear of COVID-19 and depression was verified (ß = -0.060, 95% CI = [-0.093, -0.028]). CONCLUSIONS: The findings suggest that hope is a vital mechanism to explain the relationship between the fear of COVID-19 and depression in early adulthood. In practical application, mental health practitioners should focus on boosting hope and alleviating insomnia when addressing COVID-19-related depression issues among college students.

Epidemiological investigation of the first locally acquired case of COVID-19 identified by influenza surveillance-Taiwan, February 2020.

BACKGROUND: COVID-19 and influenza have similar clinical presentations that can range from mild to severe disease. The World Health Organization recommends that countries use existing influenza surveillance to monitor COVID-19 transmission in communities. We aim to describe the surveillance and investigation of COVID-19 at the early stage of the pandemic in Taiwan. METHODS: In February 2020, the Taiwan Centers for Disease Control enhanced COVID-19 surveillance through its existing influenza surveillance. We retrospectively tested patients for SARS-CoV-2 who had symptoms of severe complicated influenza but were negative in influenza testing. We conducted an epidemiological investigation and contact tracing for the index patient and secondary cases to prevent virus transmission. RESULTS: We identified the first COVID-19 patient on February 15 through enhanced COVID-19 surveillance. He had no history of traveling abroad and an unclear history of contact with COVID-19 cases. He presented with influenza-like illness on January 27 and was hospitalized from February 3 to 15. We identified 39 close contacts of the index patient, including 11 family members and 28 healthcare workers. In total, four close family contacts of the index patient tested positive for SARS-CoV-2. An additional 84 close contacts of the four secondary cases were identified and traced; none was diagnosed with COVID-19. CONCLUSIONS: We recommend enhancing COVID-19 surveillance by testing patients with influenza-like illness. To prevent the spread of COVID-19, we recommend using appropriate personal protective equipment when in close contact with patients who present with influenza-like illness or when caring for patients with pneumonia of unknown etiology.

Defective Interfering Particles with Broad-Acting Antiviral Activity for Dengue, Zika, Yellow Fever, Respiratory Syncytial and SARS-CoV-2 Virus Infection.

More than 100 arboviruses, almost all of which have an RNA genome, cause disease in humans. RNA viruses are causing unprecedented health system challenges worldwide, many with little or no specific therapies or vaccines available. Certain species of mosquito can carry dengue virus (DENV), Zika virus (ZIKV) and yellow fever virus (YFV), where co-infection of these viruses has occurred. Here, we found that purified synthetic defective interfering particles (DIPs) derived from DENV type 2 (DENV-2) strongly suppressed replication of the aforementioned viruses, respiratory syncytial virus (RSV) and also the novel emerging virus SARS-CoV-2 in human cells. DENV DIPs produced in bioreactors, purified by column chromatography, and concentrated are virus-like particles that are about half the diameter of a typical DENV particle, but with similar ratios of the viral structural proteins envelope and capsid. Overall, DIP-treated cells inhibited DENV, ZIKV, YFV, RSV, and SARS-CoV-2 by at least 98% by mechanisms which included interferon (IFN)-dependent cellular antiviral responses. IMPORTANCE DIPs are spontaneously derived virus mutants with deletions in genes that block viral replication. DIPs play important roles in modulation of viral disease, innate immune responses, virus persistence and virus evolution. Here, we investigated the antiviral activity of highly purified synthetic DIPs derived from DENV, which were produced in bioreactors. DENV DIPs purified by column chromatography strongly inhibited five different RNA viruses, including DENV, ZIKV, YFV, RSV, and SARS-CoV-2 in human cells. DENV DIPs inhibited virus replication via delivery of a small, noninfectious viral RNA that activated cellular innate immunity, resulting in robust type 1 interferon responses. The work here presents a pathway for DIP production which is adaptable to Good Manufacturing Practice, so that their preclinical testing should be suitable for evaluation in subjects.

Immunogenicity and safety of two-dose SARS-CoV-2 vaccination via different platforms in kidney transplantation recipients

After kidney transplantation, patients exhibit a poor response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination. However, the efficacy and adverse effects of vaccines based on different platforms in these patients remain unclear. We prospectively analyzed both anti-spike protein antibody and cellular responses 1 month after the first and second doses of SARS-CoV-2 vaccines in 171 kidney transplant patients. Four vaccines, including one viral vector (ChAdOx1 nCov-19, n = 30), two mRNA (mRNA1273, n = 81 and BNT162b2, n = 38), and one protein subunit (MVC-COV1901, n = 22) vaccines were administered. Among the four vaccines, mRNA1273 elicited the strongest humoral response and induced the highest interferon-γ levels in patients with a positive cellular response against the spike protein. Antiproliferative agents were negatively associated with both the antibody and cellular responses. A transient elevation in creatinine levels was noted in approximately half of the patients after the first dose of mRNA1273 or ChadOx1, and only one of them presented with borderline cellular rejection without definite causality to vaccination. In conclusion, mRNA1273 had better immunogenicity than the other vaccines. Further, renal function needs to be carefully monitored after vaccination, and vaccination strategies should be tailored according to the transplant status and vaccine characteristics.

Political Will and the Impact Assessment of the New Crown Epidemic on Economic and Social Development and Countermeasures.

Purpose. This paper aimed to study how to analyze and study economic and social development under the new crown epidemic based on the neural network and described the BP neural network. Methodology. Economic forecasts are affected by multiple influencing factors, the relationships between these factors are complex, and it is a nonlinear system with a high degree of uncertainty. The use of traditional forecasting methods has many limitations, and neural network methods can overcome these limitations and achieve good nonlinear forecasting. Research Findings. Through the analysis and statistics of the impact of the SARS epidemic and the new crown epidemic on the economy, by 2021, the economic contribution of final consumption expenditure, total capital formation, and net exports will be 65.4%, 13.7%, and 20.9%, respectively, and the impact of the current new crown virus epidemic on the economy will be greater than that of the SARS epidemic in 2003. Research Implications. The model applied to economic forecasting based on the BP network can achieve good forecasting effect, and scientific and reasonable forecasting methods depend on the in-depth understanding of economic activities and dominance of familiarity with economic theory. Practical Implications. Through the analysis of the economy in the context of political will and the new crown epidemic, it will give more reference to more and more complex emergencies in the future.

Potential of antibody pair targeting conserved antigenic sites in diagnosis of SARS-CoV-2 variants infection.

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has become disaster for human society. As the pandemic becomes more regular, we should develop more rapid and accurate detection methods to achieve early diagnosis and treatment. Antigen detection methods based on spike protein has great potential, however, it has not been effectively developed, probably due to the torturing conformational complexity. By utilizing cross-blocking data, we clustered SARS-CoV-2 receptor binding domain (RBD)-specific monoclonal antibodies (mAbs) into 6 clusters. Subsequently, the antigenic sites for representative mAbs were identified by RBDs with designed residue substitutions. The sensitivity and specificity of selected antibody pairs was demonstrated using serial diluted samples of SARS-CoV-2 S protein and SARS-CoV S protein. Furthermore, pseudovirus system was constructed to determine the detection capability against SARS-CoV-2 and SARS-CoV. 6 RBD-specific mAbs, recognizing different antigenic sites, were identified as potential candidates for optimal antibody pairs for detection of SARS-CoV-2 S protein. By considering relative spatial position, accessibility and conservation of corresponding antigenic sites, affinity and the presence of competitive antibodies in clinical samples, 6H7-6G3 was rationally identified as optimal antibody pair for detection of both SARS-CoV-2 and SARS-CoV. Furthermore, our results showed that 6H7 and 6G3 effectively bind to SARS-CoV-2 variants of concern (VOCs). Taken together, we identified 6H7-6G3 antibody pair as a promising rapid antigen diagnostic tool in containing COVID-19 pandemic caused by multiple VOCs. Moreover, our results also provide an important reference in screening of antibody pairs detecting antigens with complex conformation.

Xiao-Chai-Hu Decoction Ameliorates Poly (I:C)-Induced Viral Pneumonia through Inhibiting Inflammatory Response and Modulating Serum Metabolism.

Viral pneumonia is widespread, progresses rapidly, and has a high mortality rate. Developing safe and effective therapies to treat viral pneumonia can minimize risks to public health and alleviate pressures on the associated health systems. Xiao-Chai-Hu (XCH) decoction can be used in the treatment of viral pneumonia. However, the mechanisms of XCH on viral pneumonia remain unclear. In this study, poly (I:C) was used to establish a mouse model of viral pneumonia, and the therapeutic effects of XCH on viral pneumonia were assessed. Furthermore, we evaluated the effects of XCH on inflammatory response. Lastly, untargeted metabolomics were used to study the metabolic regulatory mechanisms of XCH on viral pneumonia model mice. Our results showed that XCH treatment decreased the wet/dry ratio in lung tissue, total protein concentration, and total cell count in bronchoalveolar lavage fluid (BALF). H&E staining indicated that XCH treatment alleviated the pathological changes in lung. Moreover, XCH treatment decreased the levels of proinflammatory cytokines (IL-1ß, IL-6, and TNF-α) and lowered the ratio of CD86+/CD206+ macrophages and CD11b+LY6G+ neutrophils in BALF. XCH treatment also decreased the myeloperoxidase (MPO) and reduced the phosphorylations of PI3K, AKT, and NF-κB p65 in lung. Serum untargeted metabolomics analysis showed that XCH treatment could affect 18 metabolites in serum such as creatine, hydroxyproline, cortisone, hydrocortisone, corticosterone, hypotaurine, and taurine. These metabolites were associated with arginine and proline metabolism, steroid hormone biosynthesis, and taurine and hypotaurine metabolism processes. In conclusion, our study demonstrated that treatment with XCH can ameliorate viral pneumonia and reduce inflammatory response in viral pneumonia. The mechanism of action of XCH in the treatment of viral pneumonia may be associated with inhibiting the activation of PI3K/AKT/NF-κB signaling pathway in lung and regulating arginine and proline metabolism, steroid hormone biosynthesis, and taurine and hypotaurine metabolism in serum.

The Psychological Well-Being of Southeast Asian Frontline Healthcare Workers during COVID-19: A Multi-Country Study.

OBJECTIVES: This study examined the prevalence of anxiety, depression, and job burnout among frontline healthcare workers (HCWs) across six Southeast Asian countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) during the COVID-19 pandemic in 2021. We also investigated the associated risk and protective factors. METHODS: Frontline HCWs (N = 1381) from the participating countries participated between 4 January and 14 June 2021. The participants completed self-reported surveys on anxiety (GAD-7), depression (PHQ-8), and job burnout (PWLS). Multivariate logistic regressions were performed with anxiety, depression, and job burnout as outcomes and sociodemographic and job characteristics and HCW perceptions as predictors. RESULTS: The average proportion of HCWs reporting moderate anxiety, moderately severe depression, and job burnout across all countries were 10%, 4%, and 20%, respectively. Working longer hours than usual (Odds ratio [OR] = 1.82; 3.51), perceived high job risk (1.98; 2.22), and inadequate personal protective equipment (1.89; 2.11) were associated with increased odds of anxiety and job burnout while working night shifts was associated with increased risk of depression (3.23). Perceived good teamwork was associated with lower odds of anxiety (0.46), depression (0.43), and job burnout (0.39). CONCLUSION: Job burnout remains a foremost issue among HCWs. Potential opportunities to improve HCW wellness are discussed.

The Psychological Well-Being of Southeast Asian Frontline Healthcare Workers during COVID-19: A Multi-Country Study

Objectives: This study examined the prevalence of anxiety, depression, and job burnout among frontline healthcare workers (HCWs) across six Southeast Asian countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) during the COVID-19 pandemic in 2021. We also investigated the associated risk and protective factors. Methods: Frontline HCWs (N = 1381) from the participating countries participated between 4 January and 14 June 2021. The participants completed self-reported surveys on anxiety (GAD-7), depression (PHQ-8), and job burnout (PWLS). Multivariate logistic regressions were performed with anxiety, depression, and job burnout as outcomes and sociodemographic and job characteristics and HCW perceptions as predictors. Results: The average proportion of HCWs reporting moderate anxiety, moderately severe depression, and job burnout across all countries were 10%, 4%, and 20%, respectively. Working longer hours than usual (Odds ratio [OR] = 1.82;3.51), perceived high job risk (1.98;2.22), and inadequate personal protective equipment (1.89;2.11) were associated with increased odds of anxiety and job burnout while working night shifts was associated with increased risk of depression (3.23). Perceived good teamwork was associated with lower odds of anxiety (0.46), depression (0.43), and job burnout (0.39). Conclusion: Job burnout remains a foremost issue among HCWs. Potential opportunities to improve HCW wellness are discussed.

The Impact of the Infectious diseases and Commodity on Stock Markets

We investigate short and long-run effects of commodities and the EMVID indices in stocks. It pre-dominantly compares the magnitude of the effect in China and the USA and analyzes the differences utilizing the QARDL method. It becomes evident that the impacts of the EMVID and commodity indexes vary depending on the stock market developments. The short-run results reveal that the US stocks are negatively affected by the extreme quantiles, while almost all quantiles are negatively affected by commodity shocks in the long-run before pandemic. During the COVID-19 outbreak, the EMVID index is positively correlated with the stocks for both countries.

Gastronomy Tourism and Well-Being: Evidence from Taiwan and Catalonia Michelin-Starred Restaurants.

In the tourism and hospitality industry, ensuring the well-being of visitors is essential to achieving a competitive tourist destination. This objective is even more pressing in the gastronomy sector. Surprisingly, the scientific literature on this topic is scarce and relies on questionnaire surveys and interviews as a data source. After scrutinizing the 13 articles on gastronomy tourism and well-being indexed in the Web of Science or in Scopus, this study proposes two new lines of research interrelated by the concept of gastronomic image. These exploit the content shared online by consumers in order to assess subjective well-being derived from quality gastronomic experiences. The first is a framework for the customer-perceived image based on Grönroos's service quality model, and the second is a conceptual model based on Morris's semiotics to measure gastronomic image. Through mixed methodologies, i.e., qualitative in the first research line and quantitative in the second, the study applies the theoretical framework to Michelin-starred restaurants in two tourist regions with similar features but with different gastronomic cultures-Taiwan (Asia) and Catalonia (Europe)-using as a data source all the online travel reviews (OTRs) written in English about these restaurants shared on the TripAdvisor portal. Comparing the three categories of restaurants in both regions, the results show branding and marketing problems and significant differences in the popularity of restaurants and the satisfaction and well-being of diners. There is a positive relationship between the category of restaurants according to the number of Michelin stars and their popularity according to the number of OTRs, as well as with the satisfaction and well-being of diners, except for a 3-star restaurant that is the worst-rated. These outcomes from the demand side can be useful to stakeholders to design or improve gastronomic products and services.

Dengue virus-free defective interfering particles have potent and broad anti-dengue virus activity.

Dengue virus (DENV) is spread from human to human through the bite of the female Aedes aegypti mosquito and leads to about 100 million clinical infections yearly. Treatment options and vaccine availability for DENV are limited. Defective interfering particles (DIPs) are considered a promising antiviral approach but infectious virus contamination has limited their development. Here, a DENV-derived DIP production cell line was developed that continuously produced DENV-free DIPs. The DIPs contained and could deliver to cells a DENV serotype 2 subgenomic defective-interfering RNA, which was originally discovered in DENV infected patients. The DIPs released into cell culture supernatant were purified and could potently inhibit replication of all DENV serotypes in cells. Antiviral therapeutics are limited for many viral infection. The DIP system described could be re-purposed to make antiviral DIPs for many other RNA viruses such as SARS-CoV-2, yellow fever, West Nile and Zika viruses.

The diagnostic value of chest X-ray in coronavirus disease 2019: A comparative study of X-ray and CT.

As the coronavirus disease 2019 (COVID-19) epidemic spreads around the world, the demand for imaging examinations increases accordingly. The value of conventional chest radiography (CCR) remains unclear. In this study, we aimed to investigate the diagnostic value of CCR in the detection of COVID-19 through a comparative analysis of CCR and CT. This study included 49 patients with 52 CT images and chest radiographs of pathogen-confirmed COVID-19 cases and COVID-19-suspected cases that were found to be negative (non-COVID-19). The performance of CCR in detecting COVID-19 was compared to CT imaging. The major signatures that allowed for differentiation between COVID-19 and non-COVID-19 cases were also evaluated. Approximately 75% (39/52) of images had positive findings on the chest x-ray examinations, while 80.7% (42/52) had positive chest CT scans. The COVID-19 group accounted for 88.4% (23/26) of positive chest X-ray examinations and 96.1% (25/26) of positive chest CT scans. The sensitivity, specificity, and accuracy of CCR for abnormal shadows were 88%, 80%, and 87%, respectively, for all patients. For the COVID-19 group, the accuracy of CCR was 92%. The primary signature on CCR was flocculent shadows in both groups. The shadows were primarily in the bi-pulmonary, which was significantly different from non-COVID-19 patients (p = 0.008). The major CT finding of COVID-19 patients was ground-glass opacities in both lungs, while in non-COVID-19 patients, consolidations combined with ground-glass opacities were more common in one lung than both lungs (p = 0.0001). CCR showed excellent performance in detecting abnormal shadows in patients with confirmed COVID-19. However, it has limited value in differentiating COVID-19 patients from non-COVID-19 patients. Through the typical epidemiological history, laboratory examinations, and clinical symptoms, combined with the distributive characteristics of shadows, CCR may be useful to identify patients with possible COVID-19. This will allow for the rapid identification and quarantine of patients.

Optimization of a modeling platform to predict oncogenes from genome-scale metabolic networks of non-small-cell lung cancers.

Cancer cell dysregulations result in the abnormal regulation of cellular metabolic pathways. By simulating this metabolic reprogramming using constraint-based modeling approaches, oncogenes can be predicted, and this knowledge can be used in prognosis and treatment. We introduced a trilevel optimization problem describing metabolic reprogramming for inferring oncogenes. First, this study used RNA-Seq expression data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) samples and their healthy counterparts to reconstruct tissue-specific genome-scale metabolic models and subsequently build the flux distribution pattern that provided a measure for the oncogene inference optimization problem for determining tumorigenesis. The platform detected 45 genes for LUAD and 84 genes for LUSC that lead to tumorigenesis. A high level of differentially expressed genes was not an essential factor for determining tumorigenesis. The platform indicated that pyruvate kinase (PKM), a well-known oncogene with a low level of differential gene expression in LUAD and LUSC, had the highest fitness among the predicted oncogenes based on computation. By contrast, pyruvate kinase L/R (PKLR), an isozyme of PKM, had a high level of differential gene expression in both cancers. Phosphatidylserine synthase 1 (PTDSS1), an oncogene in LUAD, was inferred to have a low level of differential gene expression, and overexpression could significantly reduce survival probability. According to the factor analysis, PTDSS1 characteristics were close to those of the template, but they were unobvious in LUSC. Angiotensin-converting enzyme 2 (ACE2) has recently garnered widespread interest as the SARS-CoV-2 virus receptor. Moreover, we determined that ACE2 is an oncogene of LUSC but not of LUAD. The platform developed in this study can identify oncogenes with low levels of differential expression and be used to identify potential therapeutic targets for cancer treatment.

Prevalence and psychosocial risk factors of nonsuicidal self-injury among adolescents during the COVID-19 outbreak.

The research investigated the prevalence of nonsuicidal self-injury (NSSI) during the COVID-19 outbreak and identified the psychosocial risk factors among junior high school students in Taiwan. Cross-sectional design was applied and 1,060 participants (Mage = 14.66, SD = 0.86 years) were recruited into the study. The prevalence of NSSI was found to be 40.9% (95% confidence interval, 37.9%-43.9%) during the COVID-19 outbreak. The results suggested that the self-injurers group were mostly female, and scored significantly higher in neuroticism, depression, impulsivity, alexithymia, virtual social support, dissatisfaction with academic performance, and lower in subjective wellbeing, self-esteem, actual social support, and family function than the non-injurers group. In addition, high neuroticism, low self-esteem, high virtual social support, high impulsivity, and high alexithymia were independently predictive in the logistic regression analysis. The principal results of this study suggested that NSSI was extremely prevalent among adolescents during the COVID-19 outbreak, and in particularly, personality and virtual environment risk factors and enhancing self-esteem should be the focus of NSSI preventive strategies when targeting this age population. Our results provide a reference towards designing NSSI prevention programs geared toward the high school population during the COVID-19 pandemic.

An Interpretable Model-Based Prediction of Severity and Crucial Factors in Patients with COVID-19.

This study established an interpretable machine learning model to predict the severity of coronavirus disease 2019 (COVID-19) and output the most crucial deterioration factors. Clinical information, laboratory tests, and chest computed tomography (CT) scans at admission were collected. Two experienced radiologists reviewed the scans for the patterns, distribution, and CT scores of lung abnormalities. Six machine learning models were established to predict the severity of COVID-19. After parameter tuning and performance comparison, the optimal model was explained using Shapley Additive explanations to output the crucial factors. This study enrolled and classified 198 patients into mild (n = 162; 46.93 ± 14.49 years old) and severe (n = 36; 60.97 ± 15.91 years old) groups. The severe group had a higher temperature (37.42 ± 0.99°C vs. 36.75 ± 0.66°C), CT score at admission, neutrophil count, and neutrophil-to-lymphocyte ratio than the mild group. The XGBoost model ranked first among all models, with an AUC, sensitivity, and specificity of 0.924, 90.91%, and 97.96%, respectively. The early stage of chest CT, total CT score of the percentage of lung involvement, and age were the top three contributors to the prediction of the deterioration of XGBoost. A higher total score on chest CT had a more significant impact on the prediction. In conclusion, the XGBoost model to predict the severity of COVID-19 achieved excellent performance and output the essential factors in the deterioration process, which may help with early clinical intervention, improve prognosis, and reduce mortality.

Active Surveillance of Asymptomatic, Presymptomatic, and Oligosymptomatic SARS-CoV-2-Infected Individuals in Communities Inhabiting Closed or Semi-closed Institutions.

Background: The high COVID-19 dissemination rate demands active surveillance to identify asymptomatic, presymptomatic, and oligosymptomatic (APO) SARS-CoV-2-infected individuals. This is of special importance in communities inhabiting closed or semi-closed institutions such as residential care homes, prisons, neuropsychiatric hospitals, etc., where risk people are in close contact. Thus, a pooling approach-where samples are mixed and tested as single pools-is an attractive strategy to rapidly detect APO-infected in these epidemiological scenarios. Materials and Methods: This study was done at different pandemic periods between May 28 and August 31 2020 in 153 closed or semi-closed institutions in the Province of Buenos Aires (Argentina). We setup pooling strategy in two stages: first a pool-testing followed by selective individual-testing according to pool results. Samples included in negative pools were presumed as negative, while samples from positive pools were re-tested individually for positives identification. Results: Sensitivity in 5-sample or 10-sample pools was adequate since only 2 Ct values were increased with regard to single tests on average. Concordance between 5-sample or 10-sample pools and individual-testing was 100% in the Ct ≤ 36. We tested 4,936 APO clinical samples in 822 pools, requiring 86-50% fewer tests in low-to-moderate prevalence settings compared to individual testing. Conclusions: By this strategy we detected three COVID-19 outbreaks at early stages in these institutions, helping to their containment and increasing the likelihood of saving lives in such places where risk groups are concentrated.

Reverse Transcription Recombinase-Aided Amplification Assay With Lateral Flow Dipstick Assay for Rapid Detection of 2019 Novel Coronavirus.

Background: The emerging Coronavirus Disease-2019 (COVID-19) has challenged the public health globally. With the increasing requirement of detection for SARS-CoV-2 outside of the laboratory setting, a rapid and precise Point of Care Test (POCT) is urgently needed. Methods: Targeting the nucleocapsid (N) gene of SARS-CoV-2, specific primers, and probes for reverse transcription recombinase-aided amplification coupled with lateral flow dipstick (RT-RAA/LFD) platform were designed. For specificity evaluation, it was tested with human coronaviruses, human influenza A virus, influenza B viruses, respiratory syncytial virus, and hepatitis B virus, respectively. For sensitivity assay, it was estimated by templates of recombinant plasmid and pseudovirus of SARS-CoV-2 RNA. For clinical assessment, 100 clinical samples (13 positive and 87 negatives for SARS-CoV-2) were tested via quantitative reverse transcription PCR (RT-qPCR) and RT-RAA/LFD, respectively. Results: The limit of detection was 1 copies/µl in RT-RAA/LFD assay, which could be conducted within 30 min at 39°C, without any cross-reaction with other human coronaviruses and clinical respiratory pathogens. Compared with RT-qPCR, the established POCT assay offered 100% specificity and 100% sensitivity in the detection of clinical samples. Conclusion: This work provides a convenient POCT tool for rapid screening, diagnosis, and monitoring of suspected patients in SARS-CoV-2 endemic areas.