An Efficient Face Mask Wearing Detection Algorithm Based on Improved YOLOv3

In recent years, the Corona Virus Disease 2019 (Covid-19) epidemic has raged around the world, with more than 500 million people diagnosed. Relevant medical research and analysis results on Covid-19 indicate that wearing masks is an effective method to prevent and restrain virus transmission. Mask detection stations have been set up in hospitals, railway stations, schools, where there is large crowd flow, but results are not as good as expected. In order to ameliorate pandemic preventing and control measures, a mask wearing detection algorithm YOLOv3-M3 was designed and proposed in this paper. The algorithm can effectively detect people without mask, while consequently reminding them. Firstly, we substituted the feature extraction network of YOLOv3 with MobileNetv3, a lightweight convolutional neural network. Secondly, we utilized K-Means++ to substitute the original ground truth clustering algorithm to improve prediction precision. In addition, the bounding box regression loss function was revised as CIoU loss function. This loss function solves the issues of overlapping between the ground truth and the anchor box, which has increased the training speed. After experiments, the precision of YOLOv3 algorithm on mAP 0.5 and mAP 0.75 is 93.5% and 71.9%, respectively. Elevating 3.1% and 2.6%, respectively, higher than that of YOLOv3 algorithm, and it was superior to SSD, SSD Lite, YOLOv3-Tiny and other one-stage object detection algorithms. The detection speed can reach 13.6 frame/s, which has met the requirements of pandemic prevention and control in most places and can be deployed on terminal devices for object detection. [ FROM AUTHOR]

How culture orientation influences the COVID-19 pandemic: An empirical analysis

Purpose This study aims to investigate the mediational path of the influence of cultural orientation on the COVID-19 pandemic outcome at the national level and find out whether some culture-related factors can have a moderating effect on the influence of culture. Methodology Cultural dimension theory of Hofstede is used to quantify the degree of each dimension of culture orientation. The cross-section regression model is adopted to test if culture orientations affect the pandemic outcome, controlling for democracy, economy, education, population, age, and time. Then, a mediational analysis is conducted to examine if policy response is the mediator that culture makes an impact on the pandemic outcome. Finally, a moderation analysis is carried out to determine how each control variable has moderated the influence. Findings The cross-section regression results showed that culture orientation influences the outcome of the COVID-19 pandemic at the 99% confidence level and that among the six cultural dimensions, collectivism-individualism has the most significant impact. It has also been found that policy response is the mediator of cultural influence, and culture-related factors can moderate the influence. Contribution The contribution of this research lies in developing the assertion that culture influences pandemic outcomes. Our findings indicate that collectivism-individualism culture orientation affects the effectiveness of epidemic controls the most among the six culture dimensions. Additionally, our research is the first to study the mediating effect of policy responses and the moderating effect of culture-related factors on the influence of cultural orientation on the pandemic outcome.

Evaluating Effects of Dynamic Interventions to Control COVID-19 Pandemic: A Case Study of Guangdong, China.

The emergence of different virus variants, the rapidly changing epidemic, and demands for economic recovery all require continual adjustment and optimization of COVID-19 intervention policies. For the purpose, it is both important and necessary to evaluate the effectiveness of different policies already in-place, which is the basis for optimization. Although some scholars have used epidemiological models, such as susceptible-exposed-infected-removed (SEIR), to perform evaluation, they might be inaccurate because those models often ignore the time-varying nature of transmission rate. This study proposes a new scheme to evaluate the efficiency of dynamic COVID-19 interventions using a new model named as iLSEIR-DRAM. First, we improved the traditional LSEIR model by adopting a five-parameter logistic function ß(t) to depict the key parameter of transmission rate. Then, we estimated the parameters by using an adaptive Markov Chain Monte Carlo (MCMC) algorithm, which combines delayed rejection and adaptive metropolis samplers (DRAM). Finally, we developed a new quantitative indicator to evaluate the efficiency of COVID-19 interventions, which is based on parameters in ß(t) and considers both the decreasing degree of the transmission rate and the emerging time of the epidemic inflection point. This scheme was applied to seven cities in Guangdong Province. We found that the iLSEIR-DRAM model can retrace the COVID-19 transmission quite well, with the simulation accuracy being over 95% in all cities. The proposed indicator succeeds in evaluating the historical intervention efficiency and makes the efficiency comparable among different cities. The comparison results showed that the intervention policies implemented in Guangzhou is the most efficient, which is consistent with public awareness. The proposed scheme for efficiency evaluation in this study is easy to implement and may promote precise prevention and control of the COVID-19 epidemic.

Efficacy of Parainfluenza Virus 5 (PIV5)-vectored Intranasal COVID-19 Vaccine as a Single Dose Vaccine and as a Booster against SARS-CoV-2 Variants (preprint)

Immunization with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines has greatly reduced coronavirus disease 2019 (COVID-19)-related deaths and hospitalizations, but waning immunity and the emergence of variants capable of immune escape indicate the need for novel SARS-CoV-2 vaccines. An intranasal parainfluenza virus 5 (PIV5)-vectored COVID-19 vaccine CVXGA1 has been proven efficacious in animal models and blocks contact transmission of SARS-CoV-2 in ferrets. CVXGA1 vaccine is currently in human clinical trials in the United States. This work investigates the immunogenicity and efficacy of CVXGA1 and other PIV5-vectored vaccines expressing additional antigen SARS-CoV-2 nucleoprotein (N) or SARS-CoV-2 variant spike (S) proteins of beta, delta, gamma, and omicron variants against homologous and heterologous challenges in hamsters. A single intranasal dose of CVXGA1 induces neutralizing antibodies against SARS-CoV-2 WA1 (ancestral), delta variant, and omicron variant and protects against both homologous and heterologous virus challenges. Compared to mRNA COVID-19 vaccine, neutralizing antibody titers induced by CVXGA1 were well-maintained over time. When administered as a boost following two doses of a mRNA COVID-19 vaccine, PIV5-vectored vaccines expressing the S protein from WA1 (CVXGA1), delta, or omicron variants generate higher levels of cross-reactive neutralizing antibodies compared to three doses of a mRNA vaccine. In addition to the S protein, the N protein provides added protection as assessed by the highest body weight gain post-challenge infection. Our data indicates that PIV5-vectored COVID-19 vaccines, such as CVXGA1, can serve as booster vaccines against emerging variants.

Can infectious disease pandemic impact the long-term volatility and correlation of gold and crude oil markets?

Infectious disease pandemic has been proved to have deep effects on financial and commodity markets. Gold and crude oil as two commonly used commodities to diversify a wide variety of uncertainties are both very susceptible to public health emergencies. The aim of this paper is to quantify the impacts of infectious disease pandemic on the long-term volatility and correlation of gold and crude oil markets by using the DCC-MIDAS approach. The empirical results show that infectious disease pandemic does has prominent positive impacts on the long-run volatilities of both gold and crude oil markets, and these impacts are strengthened with the time lags of infectious disease pandemic. Furthermore, crude oil market is more vulnerable to public health emergencies than gold market. Finally, infectious disease pandemic also has significantly positive effects on the long-term correlation between gold and crude oil markets. These findings have profound implications for gold and crude oil traders in terms of risk management and portfolio allocation.

Effects of Smoking on ACE2 Expression Pattern: Risk and Severity of SARS-CoV-2 Infection.

BACKGROUND: Respiratory epithelium expressing angiotensin-converting enzyme 2 (ACE2) is the entry for novel coronavirus (SARS-CoV-2), pathogen of the COVID-19 pneumonia outbreak, although a few recent studies have found different ACE2 expression in lung tissue of smokers. The effect of smoking on ACE2 expression and COVID-19 is still not clear. So, we did this research to determine the effect of smoking on ACE2 expression pattern and its relationship with the risk and severity of COVID-19. METHODS: The clinical data of COVID-19 patients with smoking and non-smoking were analyzed, and ACE2 expression of respiratory and digestive mucosa epithelia from smoker and non-smoker patients or healthy subjects were detected by immunohistochemical (IHC) staining. RESULTS: Of all 295 laboratory-confirmed COVID-19 patients, only 24 (8.1%) were current smokers with moderate smoking or above, which accounted for 54.2% of severe cases with higher mortality than non-smokers (8.3% vs. 0.4%, p = 0.018). Data analysis showed the proportion of smokers in COVID-19 patients was lower than that in general population of China (Z = 11.65, P < 0.001). IHC staining showed ACE2 expression in respiratory and digestive epithelia of smokers were generally downregulated. CONCLUSIONS: The proportion of smokers in COVID-19 patients was lower, which may be explained by ACE2 downregulation in respiratory mucosa epithelia. However, smoking COVID-19 patients accounted for a higher proportion in severe cases and higher mortality than for non-smoking COVID-19 patients, which needs to be noted.

Dual roles of a novel oncolytic viral vector-based SARS-CoV-2 vaccine: preventing COVID-19 and treating tumor progression (preprint)

The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Cancer patients are usually immunocompromised and thus are particularly susceptible to SARS-CoV-2 infection resulting in COVID-19. Although many vaccines against COVID-19 are being preclinically or clinically tested or approved, none have yet been specifically developed for cancer patients or reported as having potential dual functions to prevent COVID-19 and treat cancer. Here, we confirmed that COVID-19 patients with cancer have low levels of antibodies against the spike (S) protein, a viral surface protein mediating the entry of SARS-CoV-2 into host cells, compared with COVID-19 patients without cancer. We developed an oncolytic herpes simplex virus-1 vector-based vaccine named oncolytic virus (OV)-spike. OV-spike induced abundant anti-S protein neutralization antibodies in both tumor-free and tumor-bearing mice, which inhibit infection of VSV-SARS-CoV-2 and wild-type (WT) live SARS-CoV-2 as well as the B.1.1.7 variant in vitro. In the tumor-bearing mice, OV-spike also inhibited tumor growth, leading to better survival in multiple preclinical tumor models than the untreated control. Furthermore, OV-spike induced anti-tumor immune response and SARS-CoV-2-specific T cell response without causing serious adverse events. Thus, OV-spike is a promising vaccine candidate for both preventing COVID-19 and enhancing the anti-tumor response. One Sentence Summary A herpes oncolytic viral vector-based vaccine is a promising vaccine with dual roles in preventing COVID-19 and treating tumor progression

High resolution computed tomography for the diagnosis of 2019 novel coronavirus (2019-nCoV) pneumonia: a study from multiple medical centers in western China.

BACKGROUND: To evaluate the role of high-resolution computed tomography (HRCT) in the diagnosis of 2019 novel coronavirus (2019-nCoV) pneumonia and to provide experience in the early detection and diagnosis of 2019-nCoV pneumonia. METHODS: Seventy-two patients confirmed to be infected with 2019-nCoV from multiple medical centers in western China were retrospectively analyzed, including epidemiologic characteristics, clinical manifestations, laboratory findings and HRCT chest features. RESULTS: All patients had lung parenchymal abnormalities on HRCT scans, which were mostly multifocal in both lungs and asymmetric in all patients, and were mostly in the peripheral or subpleural lung regions in 52 patients (72.22%), in the central lung regions in 16 patients (22.22%), and in both lungs with "white lung" manifestations in 4 patients (5.56%). Subpleural multifocal consolidation was a predominant abnormality in 38 patients (52.78%). Ground-glass opacity was seen in 34 patients (47.22%). Interlobular septal thickening was found in 18 patients, 8 of whom had only generally mild thickening with no zonal predominance. Reticulation was seen in 8 patients (11.11%), and was mild and randomly distributed. In addition, both lungs of 28 patients had 2 or 3 CT imaging features. Out of these 72 patients, 36 were diagnosed as early stage, 32 patients as progressive stage, and 4 patient as severe stage pneumonia. Moreover, the diagnostic accuracy of HRCT features combined with epidemiological history was not significantly different from the detection of viral nucleic acid (all P >0.05). CONCLUSIONS: The HRCT features of 2019-nCoV pneumonia are characteristic to a certain degree, which when combined with epidemiological history yield high clinical value in the early detection and diagnosis of 2019-nCoV pneumonia.

Comparison of acute pneumonia caused by SARS-COV-2 and other respiratory viruses in children: a retrospective multi-center cohort study during COVID-19 outbreak (preprint)

Background: Until July 14, 2020, coronavirus disease-2019 (COVID-19) has infected more than 130 million individuals and has caused a certain degree of panic. Viral pneumonia caused by common viruses such as respiratory syncytial virus, rhinovirus, human metapneumovirus, human bocavirus, and parainfluenza viruses have been more common in children. However, the incidence of COVID-19 in children was significantly lower than that in adults. The purpose of this study was to describe the clinical manifestations, treatment and outcomes of COVID-19 in children compared to those of other sources of viral pneumonia diagnosed during the COVID-19 outbreak. Methods: Children with COVID-19 and viral pneumonia admitted to 20 hospitals were enrolled in this retrospective multi-center cohort study. A total of 64 children with COVID-19 were defined as the COVID-19 cohort, of which 40 children who developed pneumonia were defined as the COVID-19 pneumonia cohort. Another 284 children with pneumonia caused by other viruses were defined as the viral pneumonia cohort. Results: Compared to the viral pneumonia cohort, children in the COVID-19 cohort were mostly exposed to family members confirmed to have COVID-19 (53/64 vs. 23/284), were of older median age (6.3 vs. 3.2 years), and had a higher proportion of ground-glass opacity (GGO) on computed tomography (18/40 vs. 0/38) (all P ＜0.001). Children in the COVID-19 pneumonia cohort had a lower proportion of severe cases (1/40 vs. 38/284, P =0.048), and lower cases with high fever (3/40 vs 167/284, P ＜0.001), requiring intensive care (1/40 vs 32/284, P ＜0.047) and with shorter symptomatic duration (median 5 vs 8 days, P ＜0.001). The proportion of cases with evaluated inflammatory indicators, biochemical indicators related to organ or tissue damage, D-dimer and secondary bacterial infection were lower in the COVID-19 pneumonia cohort than in the viral pneumonia cohort (all P ＜0.05). No statistical differences were found in the duration of positive PCR results from pharyngeal swabs in 25 children with COVID-19 who received antiviral drugs (lopinavir-ritonavir, ribavirin, and arbidol) as compared to duration in 39 children without antiviral therapy [median 10 vs. 9 days, P =0.885]. Conclusion: The symptoms and severity of COVID-19 pneumonia in children were no more severe than those in children with other viral pneumonias. Lopinavir-ritonavir, ribavirin and arbidol do not shorten the duration of positive PCR results from pharyngeal swabs in children with COVID-19. During the COVID-19 outbreak, attention also must be given to children with infection by other pathogens infection.

Peripheral blood CD4+ cell counts but not CD3+ and CD8+ cell counts are reduced in SARS-CoV-2 infection.

BACKGROUND: The world is facing the global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). T cell-induced immune responses during acute SARS-CoV-2 infection have rarely been reported. METHODS: We use cell counting chips and PCR arrays to offer the first insights into the T cell involved in the course of acute SARS-CoV-2 infection. All consecutive patients with suspected SARS-CoV-2 infection treated at the designated hospital between January 2020 and February 2020 were recruited for the study, and cases were confirmed by real-time RT-PCR. Baseline characteristics for inpatients were prospectively collected and analyzed. RESULTS: 96 patients with suspected SARS-CoV-2 infection in our center were screened for inclusion in the study. The median age of the patients was 39.0 years, and 47 (49.0%) were female. Multivariate logistic regression analysis showed that only the CD4+ cell counts were significantly lower in the infection group and slightly higher in the control group. Receiver operating characteristic curve analysis showed good discrimination power between subjects with and subjects without infection. LIMITATIONS: This is a single-center study of patients with a specific ethnic background and lacks a mechanism. CONCLUSIONS: These findings imply the importance of CD4+ T cells (but not CD8+ and CD3+ T cells) in SARS-CoV-2 infection associated pneumonia and indicate that CD4+ T cells might be important for the control of SARS-CoV-2.

Theoretical Study of the Optical Spectra of SARS-CoV-2 Proteins (preprint)

Treatment for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes Covid-19, may well be predicated on knowledge of the structures of protein of this virus. However, often these cannot be determined easily or quickly. Herein, we provide calculated circular dichroism (CD) spectra in the far- and near-UV, and infra-red (IR) spectra in the amide I region for experimental structures and computational models of SARS-CoV-2 proteins. The near-UV CD spectra offer greatest sensitivity in assessing the accuracy of models.

Association between ABO blood groups and clinical outcome of coronavirus disease 2019: Evidence from two cohorts (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become the third most common coronavirus that causes large-scale infections worldwide. The correlations between pathogen susceptibility and blood type distribution have attracted attention decades ago. The current retrospective study aimed to examine the correlation between blood type distribution and SARS-CoV-2 infection, progression, and prognosis in patients with coronavirus disease 2019 (COVID-19). With 265 patients from multiple medical centers and two established cohorts, we found that the blood type A population was more sensitive to SARS-CoV-2. Moreover, the blood type distribution was not relevant to acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), and mortality in COVID-19 patients. These findings are indicative of coping with the great threat since it probed the relationship between blood types and ARDS, AKI, and mortality, in addition to susceptibility in COVID-19 patients.

Prognostic Value of Charlton’s Weighted Index of Capabilities Combined with Chronic Health Evaluation II Score in COVID-19：a retrospective cohort study (preprint)

Background: Since December 2019, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread across the world. Age and underlying diseases have been reported as predictors of mortality in 2019-nCoV infection. Charlson's weighted index of comorbidities (WIC) and acute physiology and chronic health evaluation (APACHE) II are two frequently-used measures of comorbidity. In this study, we have assessed the performance of WIC and APACHE II in predicting the mortality of COVID-19 patients.Methods: A total of 76 adult patients with COVID-19 were admitted to a designated hospital in Huangshi province from 1 January 2020 to 29 February 2020. Clinical data including age, gender, underlying diseases, and hospital mortality were collected. The APACHE II and WIC scores were assessed within the first 24 hours of admission. Univariate and multiple logistic regression analyses were used to compare the performance of WIC, APACHE II, and joint detection. The area under the receiver operating characteristic curve (AUC) was used to predict the hospital mortality. Results: Of the 76 enrolled patients, 57 patients survived, and 19 died. The surviving patients had significantly lower WIC and APACHE II than the non-surviving patients (p-value < 0.05). The AUC for the hospital mortality was 0.814 (95% confidence interval (CI) 0.705-0.923) of WIC, 0.854 (95% CI 0.705-0.956) of APACHE II and 0.891(95% CI 0.830-0.966) for the joint detection. The diagnostic value of the joint detection was found to be better than that of WIC (p-value= 0.002) or APACHE II (p-value = 0.042). Conclusions: The WIC and APACHE II scores might serve as independent determinants for the hospital mortality associated with COVID-19 patients. The combined use of WIC and APACHE II is more predictive than individuals．