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Purpose: The purpose of this study is to investigate the impact of religiosity on banks' lending behavior during the COVID-19 pandemic in the USA. Design/methodology/approach: This study uses the evidence from the issuance of Paycheck Protection Program (PPP) loans to relate local religiosity to banks' participation in the PPP loan program and to banks' loan portfolio performance during the pandemic. Findings: The results of this study show that banks located in more religious counties have a higher level of lending through the PPP, supporting the ethical and moral concerns cultivated by local religious beliefs. In addition, banks' lending before the pandemic is more prudential in more religious areas, as reflected in lower losses and higher returns at the onset of the crisis, especially in areas where business activities were most disrupted, supporting the stewardship role encouraged by religiosity. Originality/value: Thanks to the structure of the PPP loans programs, the authors are able to disentangle the conflicting effects of morality and prudence on banks' behavior. © 2023, Emerald Publishing Limited.
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Comprehensive data on transmission mitigation behaviors and both SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify COVID-19 risk factors and the impact of public health measures. We conducted a longitudinal, population-based study in the East Bay Area of Northern California. From July 2020-March 2021, approximately 5,500 adults were recruited and followed over three data collection rounds to investigate the association between geographic and demographic characteristics and transmission mitigation behavior with SARS-CoV-2 prevalence. We estimated the populated-adjusted prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50–1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75–2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48–3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20–24.34) in Round 3, with White individuals having 4.35% (95% CI: 0.35–8.32) higher COVID-19 vaccine seroprevalence than individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other. No evidence for an association between transmission mitigation behavior and seroprevalence was observed. Despite >99% of participants reporting wearing masks individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other, as well as those in lower-income households, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Results demonstrate that more effective policies are needed to address these disparities and inequities.
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Background: April 11 , 2022, we learned from the public information platform that a COVID-19 close contact was tested nucleic acid in our hospital recently. This survey was performed to verify the infor-mation and timely identify high risk population of COVID 19. Methods: According to the National COVID-19 Control and Prevention Protocol ( 8th edition) , and the Emergency Response Plan for COVID-19 in our hospital, information verification, close contact investigation, indirect contact tracing, information report and close contact follow up were carried out by our team. Results: A total of 40 indirect contacts were identified. The basic information of those 40 indirect contacts was reported to the local Center for Diseases Control and Prevention. The close contact was followed up for 10 days, and the nucleic acid test results of COVID-19 of the contact were negative since then. No fever or other suspected symptoms of COVID-19 were appeared for the contact. Conclusion: Timely verify the COVID-19 related information, screening of high risk population and dynamically monitoring of the close contact will help to control the potential spread of COVID 19. 767. © 2022 Colegio Brasileiro de Patologia Animal. All rights reserved.
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Objective: The last retrospective systematic review on Miller Fisher syndrome (MFS) took place in 1992. To understand the evolving nature of the disease and to update the clinical picture, diagnostic testing, treatment, and prognosis, a retrospective systematic review of 174 cases of MFS published in the last three decades was performed. Method(s): We screened 1034 articles on the PUBMED search engine. Out of these articles, 153 met the inclusion criteria of case reports/series published in English after 1992. Each case contained at least two signs of the triad, with the presence or absence of GQ1B antibodies. The Chi-square test or Fisher's exact test was used for data analysis. Assessing the Methodological Quality of Systematic Reviews (AMSTAR 2) was used to assess the quality of the systematic reviews. Finding(s): 174 cases were included, with five case series. Sinopulmonary infection (60%) and gastrointestinal infection (18%) were the most common preceding illnesses, while eight cases occurred after the onset of a COVID-19 infection, and seven had recent exposure to monoclonal antibodies. We found that misdiagnosis was seen in 13.8% of cases, stroke being the most common misnomer. Residual symptoms were reported in 30% of cases, death in three and recurrence in twelve. IVIG was the most frequently used treatment option (51.1%). Severity score was significantly associated with treatment (p=0.0195);however, it was not associated with age (p=0.4255), gender (p=0.7893), GQ1b antibody presence/level (p=0.3870/ p=0.6891), or non-GQ1B (p=0.5426) status. The outcome with residual symptoms was favorable for younger patients (Age 1-18: p=0.0223) and not associated with treatment. Mechanical ventilation (13.8%), feeding tube placement (9.8%), autonomic insufficiency (8.6%), and a patient requiring a cardiac pacemaker were the top three complications. Conclusion(s): Physicians should recognize the protean clinical manifestation of MFS and recognize the various recent preceding factors like COVID-19 and monoclonal antibodies. The benefit provided by the treatment is unclear. Therefore, further studies will be required to identify patients who should be treated and the appropriate treatment to maximize patient outcomes.
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Comprehensive data on transmission mitigation behaviors and both SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify COVID-19 risk factors and the impact of public health measures. We conducted a longitudinal, population-based study in the East Bay Area of Northern California. From July 2020-March 2021, approximately 5,500 adults were recruited and followed over three data collection rounds to investigate the association between geographic and demographic characteristics and transmission mitigation behavior with SARS-CoV-2 prevalence. We estimated the populated-adjusted prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50-1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75-2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48-3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20-24.34) in Round 3, with White individuals having 4.35% (95% CI: 0.35-8.32) higher COVID-19 vaccine seroprevalence than individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other. No evidence for an association between transmission mitigation behavior and seroprevalence was observed. Despite >99% of participants reporting wearing masks individuals identifying as African American or Black, American Indian or Alaskan Native, Asian, Hispanic, two or more races, or other, as well as those in lower-income households, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Results demonstrate that more effective policies are needed to address these disparities and inequities.
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As vaccines have become available for COVID-19, it is important to understand factors that may impact response. The objective of this study is to describe vaccine response in a well-characterized Northern California cohort, including differences in side-effects and antibody response by vaccine type, sex, and age, as well as describe responses in subjects with pre-existing health conditions that are known risk factors for more severe COVID-19 infection. From July 2020 to March 2021, ~5,500 adults from the East Bay Area in Northern California were followed as part of a longitudinal cohort study. Comprehensive questionnaire data and biospecimens for COVID-19 antibody testing were collected at multiple time-points. All subjects were at least 18 years of age and members of the East-Bay COVID-19 cohort who answered questionnaires related to vaccination status and side-effects at two time-points. Three vaccines, Moderna (2 doses), Pfizer-BioNTech (2 doses), and Johnson & Johnson (single dose), were examined as exposures. Additionally, pre-existing health conditions were assessed. The main outcomes of interest were anti-SARS-CoV-2 Spike antibody response (measured by S/C ratio in the Ortho VITROS assay) and self-reporting of 11 potential vaccine side effects. When comparing both doses of the Moderna vaccine to respective doses of Pfizer-BioNTech, participants receiving the Moderna vaccine had higher odds of many reported side-effects. The same was true comparing the single-dose Johnson & Johnson vaccine to dose 2 of the Pfizer-BioNTech vaccine. The antibody S/C ratio also increased with each additional side-effect after the second dose. S/C ratios after vaccination were lower in participants aged 65 and older, and higher in females. At all vaccination timepoints, Moderna vaccine recipients had a higher S/C ratio. Individuals who were fully vaccinated with Pfizer-BioNTech had a 72.4% lower S/C ratio compared to those who were fully vaccinated with Moderna. Subjects with asthma, diabetes, and cardiovascular disease all demonstrated more than a 20% decrease in S/C ratio. In support of previous findings, we show that antibody response to the Moderna vaccine is higher than the Pfizer-BioNTech vaccine. We also observed that antibody response was associated with side-effects, and participants with a history of asthma, diabetes, and cardiovascular disease had lower antibody responses. This information is important to consider as further vaccines are recommended.
Subject(s)
Encephalitis, California , Cardiovascular Diseases , Diabetes Mellitus , Asthma , COVID-19ABSTRACT
Objective: To study the infection rate of secondary close contacts of COVID-19 patients, and assess the infection risk in the contacts. Methods: COVID-19 patients' close contacts (with a clear exposure time to index case) with negative nucleic acid test results and secondary close contacts were surveyed in continuous isolation and medical observation in this prospective study. The dynamic nucleic acid test results of the close contacts and secondary contacts of COVID-19 patients were collected to assess their risk of infection. Results: A total of 4 533 close contacts were surveyed, in whom 14 were confirmed as COVID-19 patients with overall secondary attack rate of 0.31%, and 4 201 secondary contacts were tracked, in whom no subsequent infections occurred. Conclusion: Close contacts of COVID-19 patients entered in centralized isolation for medical observation with negative nucleic acid tese results,the secondary close contacts of COVID-19 patients have no risk of infection.
Subject(s)
COVID-19 , Nucleic Acids , COVID-19/epidemiology , Contact Tracing , Humans , Incidence , Prospective Studies , SARS-CoV-2ABSTRACT
Purpose During the COVID-19 pandemic, in order to prevent the spread of disease, the National Library of Indonesia Cataloging Department adopted remote working. There is a need to examine the productivity of remote cataloging as this form of cataloging becomes more prevalent. Design/methodology/approach The study was conducted using a mixed methods approach. The authors analyzed data to assess cataloging librarians' productivity based on system logs. Then, the authors interviewed librarians to understand librarians' perspectives concerning productivity and remote cataloging, and also to seek insights into factors that may affect productivity while working remotely. Findings The analysis found higher productivity in terms of quantity of cataloging. Librarians' productivity during remote cataloging is not statistically related to individual factors of age, years of experience, or gender. The in-depth interviews found that other factors may hinder the quality and quantity of the remote cataloging, including the working environment, infrastructure, and lack of policies on remote working. Research limitations/implications The findings were based on a study conducted in the National Library of Indonesia, which may not apply to libraries with different infrastructures or existing policies in remote cataloging. However, the authors identified numerous factors that could be related to remote cataloging productivity. More work needs to be done to identify these factors that impact productivity by conducting further surveys. Practical implications The research provides evidence showing the productivity of cataloging can be higher in remote working mode. The study provides insights for library managers to decide whether to implement remote cataloging and what additional perspectives could be considered for the better implementation of remote cataloging. Originality/value The gap in the literature about remote cataloging and productivity has been bridged.
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Accurate facial recognition can effectively help the population combat the disease by offering risk-free phone usage, access controls, etc. In the era of COVID-19, a mask has become a necessity. However, masks may reduce the accuracy of face recognition to some degree. Thus, it is necessary to use deep learning to increase face recognition accuracy by recovering the face with a mask. For this purpose, this study proposed an AI-based model based on Pix2pix and U-net generator for restoring face mask images using the paired image database. In the training step, we used two adversarial models, including one generator and one discriminator. Then they are extended to a conditional model, which will be piped to the Pix2pix algorithm once again. U-Net was built in the training of the generator. The loss curves of generator and discriminators show that as iteration time increases, the loss of fake discriminator becomes lower stably. In contrast, the loss of real discriminator has the same tendency. In the meantime, the loss of generator shows an increased tendency. The result indicates that our model can help build reliable face mask restoration for daily use, which helps to improve the recognition accuracy of the face with a mask.
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Serological surveillance studies of infectious diseases provide population-level estimates of infection and antibody prevalence, generating crucial insight into population-level immunity, risk factors leading to infection, and effectiveness of public health measures. These studies traditionally rely on detection of pathogen-specific antibodies in samples derived from venipuncture, an expensive and logistically challenging aspect of serological surveillance. During the COVID-19 pandemic, guidelines implemented to prevent the spread of SARS-CoV-2 infection made collection of venous blood logistically difficult at a time when SARS-CoV-2 serosurveillance was urgently needed. Dried blood spots (DBS) have generated interest as an alternative to venous blood for SARS-CoV-2 serological applications due to their stability, low cost, and ease of collection; DBS samples can be self-generated via fingerprick by community members and mailed at ambient temperatures. Here, we detail the development of four DBS-based SARS-CoV-2 serological methods and demonstrate their implementation in a large serological survey of community members from 12 cities in the East Bay region of the San Francisco metropolitan area using at-home DBS collection. We find that DBS perform similarly to plasma/serum in enzyme-linked immunosorbent assays and commercial SARS-CoV-2 serological assays. In addition, we show that DBS samples can reliably detect antibody responses months postinfection and track antibody kinetics after vaccination. Implementation of DBS enabled collection of valuable serological data from our study population to investigate changes in seroprevalence over an 8-month period. Our work makes a strong argument for the implementation of DBS in serological studies, not just for SARS-CoV-2, but any situation where phlebotomy is inaccessible. IMPORTANCE Estimation of community-level antibody responses to SARS-CoV-2 from infection or vaccination is critical to inform public health responses. Traditional studies of antibodies rely on collection of blood via venipuncture, an invasive procedure not amenable to pandemic-related social-distancing measures. Dried blood spots (DBS) are an alternative to venipuncture, since they can be self-collected by study participants at home and do not require refrigeration for shipment or storage. However, DBS-based assays to measure antibody levels to SARS-CoV-2 have not been widely utilized. Here, we show that DBS are comparable to blood as a sampling method for antibody responses to SARS-CoV-2 infection and vaccination over time measured using four distinct serological assays. The DBS format enabled antibody surveillance in a longitudinal cohort where study participants self-collected samples, ensuring the participants' safety during an ongoing pandemic. Our work demonstrates that DBS are an excellent sampling method for measuring antibody responses whenever venipuncture is impractical.
Subject(s)
COVID-19 , Antibodies, Viral , COVID-19/diagnosis , COVID-19/epidemiology , Epidemiologic Studies , Humans , Pandemics , SARS-CoV-2 , Seroepidemiologic StudiesABSTRACT
Capacity planning is a very important global challenge in the face of Covid-19 pandemic. In order to hedge against the fluctuations in the random demand and to take advantage of risk pooling effect, one needs to have a good understanding of the variabilities in the demand of resources. However, Covid-19 predictive models that are widely used in capacity planning typically often predict the mean values of the demands (often through the predictions of the mean values of the confirmed cases and deaths) in both the temporal and spatial dimensions. They seldom provide trustworthy prediction or estimation of demand variabilities, and therefore, are insufficient for proper capacity planning. Motivated by the literature on variability scaling in the areas of physics and biology, we discovered that in the Covid-19 pandemic, both the confirmed cases and deaths exhibit a common variability scaling law between the average of the demand μ and its standard deviation σ, that is, σ∝μβ, where the scaling parameter β is typically in the range of 0.65 to 1, and the scaling law exists in both the temporal and spatial dimensions. Based on the mechanism of contagious diseases, we further build a stylized network model to explain the variability scaling phenomena. We finally provide simple models that may be used for capacity planning in both temporal and spatial dimensions, with only the predicted mean demand values from typical Covid-19 predictive models and the standard deviations of the demands derived from the variability scaling law.
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Automatic medical report generation is an emerging field that aims to generate medical reports based on medical images. The report writing process can be tedious for senior radiologists and challenging for junior ones. Thus it is of great importance to expedite the process. In this work, we propose an EnricheD DIsease Embedding based Transformer (Eddie-Transformer) model, which jointly performs disease detection and medical report generation. This is done by decoupling the latent visual features into semantic disease embeddings and disease states via our state-aware mechanism. Then, our model entangles the learned diseases and their states, enabling explicit and precise disease representations. Finally, the Transformer model receives the enriched disease representations to generate high-quality medical reports. Our approach shows promising results on the widely-used Open-I benchmark and COVID-19 dataset. © 2022 IEEE.
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Social media data are used to enhance crisis management, as people widely adopt social media to share and acquire information to cope with uncertainties in crises. Identification and extraction of informative communications out of large volumes of data is critical for accurate situational awareness and timely response. Existing studies use conditions of geolocations, keywords, and topics separately or jointly to retrieve data that can be crisis related, but are not enough to filter subsets of data for different crisis management tasks. We propose that the crisis communication purposes of users can be detected to enhance data selection and prioritization for different crisis management tasks. A classification framework was built to identify three facets of a message: content type, audience type, and information source. The definitions of these categories are not dependent on a specific type of crises. So the classification framework can be potentially applied to different crisis scenarios. Machine learning models were created for the automatic classification of messages. Results showed the CNN-based model achieved the best accuracy (88.5%) for the classification of content type. The proposed Naive Bayes and logistic repression with predetermined features can best differentiate audience types and information source with an accuracy of 72.7% and 72.2%, respectively. © 2021 IEEE.
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OBJECTIVE: Re-positivity of SARS-CoV-2 in discharged COVID-19 patients have been reported;however, early risk factors for SARS-CoV-2 re-positivity evaluation are limited. METHODS: This is a prospective study, a total of 145 COVID-19 patients were treated and all discharged according to the guideline criteria by Mar 11th 2020. After discharge, clinical visits and viral RT-PCR tests by the second and fourth week follow-up were carried-out. Patient demographic and clinical characteristics and laboratory data on admission and discharge were retrieved, and predictive factors for SARS-CoV-2 re-positivity were analyzed. RESULTS: 13 out of 145 (9.0%) COVID-19 patients were confirmed re-positivity of SARS-CoV-2 by RT-PCR test. The median interval between disease onset to recurrence was 38 days. SARS-CoV-2 re-positive cases were of significantly longer virus shedding duration, notably higher body temperature, heart rate and lower TNF-alpha and IgG levels on admission. Covariate logistic regression analysis revealed virus shedding duration and IgG levels are independent risk factors for SARS-CoV-2 return positive after discharge. CONCLUSION: Longer viral shedding duration and lower IgG levels are risk factors for re-positivity of SARS-CoV-2 for discharged COVID-19 patients.
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The ongoing coronavirus disease (COVID-19) pandemic is caused by a new coronavirus (severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)) first reported in Wuhan City, China. From there, it has been rapidly spreading to many cities inside and outside China. Nowadays, more than 110 million cases with deaths surpassing 2 million have been recorded worldwide, thus representing a major health and economic issues. Rapid development of a protective vaccine against COVID-19 is therefore of paramount importance. Here, we demonstrated that the recombinantly expressed receptor-binding domain (RBD) of the spike protein can be coupled to immunologically optimized virus-like particles derived from cucumber mosaic virus (CuMV<sub>TT</sub>). The RBD displayed CuMV<sub>TT</sub> bound to ACE2, the viral receptor, demonstrating proper folding of RBD. Furthermore, a highly repetitive display of the RBD on CuMV<sub>TT</sub> resulted in a vaccine candidate that induced high levels of specific antibodies in mice, which were able to block binding of the spike protein to ACE2 and potently neutralize SARS-CoV-2 virus in vitro.
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OBJECTIVES: To investigate the clinical and epidemiological characteristics of paediatric patients with coronavirus disease-19 (COVID-19). METHODS: Paediatric patients diagnosed with COVID-19 between January 15 and March 15, 2020, from seven hospitals in Zhejiang Province, China, were collected retrospectively and analysed. RESULTS: Thirty-two children with COVID-19, ranging in age from 3 months to 18 years, were enrolled. Family aggregation occurred in 87.5% of infant and preschool-aged children (7/8), and also school-aged children (14/16), but in only 12.5% (1/8) of adolescents (p < 0.05, p < 0.001). Most of these patients had mild symptoms: mainly fever (20/32) followed by cough (10/32) and fatigue (4/32). The average durations of viral RNA in respiratory samples and gastrointestinal samples were 15.8 d and 28.9 d, respectively. Detox duration in faeces decreased with age: 39.8 d, 27.5 d and 20.4 d in infants and preschool children, school children, and adolescents respectively (p0-6, -18 <0.01, p0-6, -14 <0.05). Pneumonia was found in 14 children, but there was no statistical significance in the incidence of pneumonia between different age groups. Thirty patients were treated with antiviral drugs, and all patients were stable and gradually improved after admission. CONCLUSIONS: Most children with COVID-19 had a mild process and a good prognosis. More attention should be paid to investigation of household contact history in the diagnosis of COVID-19 in young children. Viral RNA lasts longer in the gastrointestinal system than in the respiratory tract, especially in younger children.
Subject(s)
COVID-19/epidemiology , Adolescent , Antiviral Agents/therapeutic use , COVID-19/diagnosis , COVID-19/therapy , Child , Child, Preschool , China , Female , Humans , Infant , Male , RNA, Viral/analysis , Retrospective StudiesABSTRACT
OBJECTIVE: Lopinavir/ritonavir has modest antiviral activity against severe acute respiratory syndrome coronavirus 2. The aim was to investigate the viral kinetics and factors associated with viral clearance during lopinavir/ritonavir-based combination treatment in non-severe patients. PATIENTS AND METHODS: Sixty-four patients were retrospectively enrolled. Viral RNA was detected by real-time RT-PCR assay from sputum or throat swab samples at different time points. The patterns of viral kinetics were characterized, and factors associated with rapid viral clearance, which was defined as viral RNA undetectable within two weeks, were analyzed using multivariate logistic regression analyses. RESULTS: All patients achieved viral RNA negativity and were discharged from the hospital. Furthermore, 48 (75%) and 16 (25%) patients achieved rapid and delayed viral clearance, respectively. The lymphocyte counts of rapid viral clearance patients (1.40 [1.20-1.80] × 109/L) were higher, when compared to delayed viral clearance patients (1.00 [0.70-1.47] × 109/L) (p=0.024). The multivariate logistic analysis revealed that high lymphocyte count (≥1.3×109/L) is an independent factor associated with rapid viral clearance (OR=7.62, 95% CI=1.15-50.34, p=0.035). CONCLUSIONS: The viral shedding exhibited different patterns during treatment. Immune insufficiency is responsible for the delayed viral clearance, suggesting that an immunomodulator should be considered to promote viral clearance in patients with low lymphocyte counts.