Will the COVID-19 pandemic end with the Delta and Omicron variants?

Effect of polyphenols against complications of COVID-19: current evidence and potential efficacy

The COVID-19 pandemic that started in 2019 and resulted in significant morbidity and mortality continues to be a significant global health challenge, characterized by inflammation, oxidative stress, and immune system dysfunction.. Developing therapies for preventing or treating COVID-19 remains an important goal for pharmacology and drug development research. Polyphenols are effective against various viral infections and can be extracted and isolated from plants without losing their therapeutic potential. Researchers have developed methods for separating and isolating polyphenols from complex matrices. Polyphenols are effective in treating common viral infections, including COVID-19, and can also boost immunity. Polyphenolic-based antiviral medications can mitigate SARS-CoV-2 enzymes vital to virus replication and infection. Individual polyphenolic triterpenoids, flavonoids, anthraquinonoids, and tannins may also inhibit the SARS-CoV-2 protease. Polyphenol pharmacophore structures identified to date can explain their action and lead to the design of novel anti-COVID-19 compounds. Polyphenol-containing mixtures offer the advantages of a well-recognized safety profile with few known severe side effects. However, studies to date are limited, and further animal studies and randomized controlled trials are needed in future studies. The purpose of this study was to review and present the latest findings on the therapeutic impact of plant-derived polyphenols on COVID-19 infection and its complications. Exploring alternative approaches to traditional therapies could aid in developing novel drugs and remedies against coronavirus infection.

Investigating the spatiotemporal characteristics and medical response during the initial COVID-19 epidemic in six Chinese cities

In the future, novel and highly pathogenic viruses may re-emerge, leading to a surge in healthcare demand. It is essential for urban epidemic control to investigate different cities' spatiotemporal spread characteristics and medical carrying capacity during the early stages of COVID-19. This study employed textual analysis, mathematical statistics, and spatial analysis methods to examine the situation in six highly affected Chinese cities. The findings reveal that these cities experienced three phases during the initial outbreak of COVID-19: "unknown-origin incubation", "Wuhan-related outbreak", and "local exposure outbreak". Cities with a high number of confirmed cases exhibited a multicore pattern, while those with fewer cases displayed a single-core pattern. The cores were distributed hierarchically in the central built-up areas of cities' economic, political, or transportation centers. The radii of these cores shrank as the central built-up area's level decreased, indicating a hierarchical decay and a core-edge structure. It suggests that decentralized built environments (non-clustered economies and populations) are less likely to facilitate large-scale epidemic clusters. Additionally, the deployment of designated hospitals in these cities was consistent with the spatial distribution of the epidemic; however, their carrying capacity requires urgent improvement. Ultimately, the essence of prevention and control is the governance of human activities and the efficient management of limited resources about individuals, places, and materials through leveraging IT and GIS technologies to address supply-demand contradictions.

COVID-19 Linked Social Stigma Among Arab Survivors: A Cross-Sectional Experiences from the Active Phase of the Pandemic

Objective

This study aimed to explore the magnitude and variability of the disease-linked stigma among COVID-19 survivors and their experiences of social stigma, coping strategies, contextual challenges, and preferences for support.

Methods

An Arabic version of the social stigma survey questionnaire was designed and validated to obtain socio-demographic characteristics and quantitative measures of stigma encountered by the survivors. 482 COVID-19 survivors completed the survey, and the data were analyzed using descriptive statistics and thematic analysis.

Results

The results of this study revealed the prevalence of high levels of both perceived external stigma and enacted stigma among participants. Enacted and Internalized stigma were associated with survivors' educational background/ status. The participants suggested three levels of support: organizational, social, and personal. Establishing an online stigma reduction program and national psychological crisis interventions at the organizational level. It is crucial to assist coping mechanisms and societal reintegration techniques at the social level.

Conclusion

These results provide valuable insights for holistic health policy formation and preparedness strategies for future pandemics, helping survivors promote health and reintegrate into society, where stigma reduction and psychological crisis interventions are underdeveloped.

Impact of COVID-19 on Academic Burnout among Medical College Students in China: Findings from a Web-Based Survey

BACKGROUND Academic burnout can affect students' academic behavior and performance and especially damages the careers of medical college students. Medical education systems during the COVID-19 pandemic have met unprecedented challenges that have influenced medical students. This study aimed to explore the effects of psychological resilience, stress, and smartphone addiction on academic burnout among Chinese medical students. MATERIAL AND METHODS This study utilized a cross-sectional design, from March 13, 2022 to March 31, 2022, within the Wannan Medical College, where students completed a web-based survey. The Chinese version of the Academic Burnout Scale (ABS), the 10-item Smartphone Addiction Scale-Short Version (SAS-SV), the Connor-Davidson Resilience Scale (CD-RISC 10) and the Perceived Stress Scale (PSS-4) were used in this survey. Data entry and analysis were conducted using IBM SPSS ver. 22.0. Pearson's correlation coefficient (r) was used to examine the correlations between medical college students' academic burnout and smartphone addiction and mental health. Binary logistic regression analysis was carried out to evaluate the factors influencing academic burnout. RESULTS Of 3190 medical college students who completed the survey, 1521 (47.7%) had some degree of academic burnout. Gender, being a student leader, grades, perceived stress, and smartphone addiction were associated with the total score of academic burnout. Psychological resilience and adapting to online classes were protective factors against academic burnout. CONCLUSIONS Academic burnout is common among medical college students in China after the COVID-19 pandemic, and it is urgent to address this situation to improve the quality of medical education.

A systematic review on post-discharge venous thromboembolism prophylaxis in patients with COVID-19

BACKGROUND

Coronavirus disease of 2019 (COVID-19) is associated with venous thromboembolism (VTE), not only during hospitalization but also after discharge, raising concerns about anticoagulant (AC) use for post-discharge COVID-19 patients. We aimed to systematically review the current literature on the possible benefits or risks regarding extended thromboprophylaxis.

MAIN BODY

We searched related databases from December 1, 2019, to October 6, 2022, including studies on the necessity, duration, and selection of the ideal AC regarding extended thromboprophylaxis for post-discharge COVID-19 patients. The screening of the selected databases led to 18 studies and 19 reviews and guidelines. Studies included 52,927 hospitalized COVID-19 patients, with 19.25% receiving extended thromboprophylaxis. VTE events ranging from 0 to 8.19% (median of 0.7%) occurred in a median follow-up of 49.5 days. All included studies and guidelines, except four studies, recommended post-discharge prophylaxis after an individual risk assessment indicating high thrombotic and low bleeding risk. Studies used risk assessment models (RAMs), clinical evaluation, and laboratory data to identify COVID-19 patients with a high risk of VTE. IMPROVE-DD was the most recommended RAM. Direct oral anticoagulants (DOACs) and low molecular weight heparins (LMWHs) were the most used AC classes.

CONCLUSIONS

Post-discharge prophylaxis for COVID-19 patients is recommended after an individual assessment. The IMPROVE-DD model can help predict VTE risk. After distinguishing patients who need post-discharge AC therapy, DOACs for 30-35 days and LMWHs for 40-45 days can be the drug of choice. Further studies, particularly the results of the ongoing randomized controlled trials (RCTs), are required. Also, to properly handle such patients, every physician should consider lifestyle modification in addition to pharmacological treatment for post-discharge VTE prophylaxis.

Spatiotemporal dynamics of confirmed case distribution during the COVID-19 pandemic in China: data comparison between 2020/04-2020/08 and 2021/04-2021/08

The COVID-19 pandemic across Chinese mainland was gradually stabilized at a low level with sporadic outbreaks, before the emergence of Omicron variant. Apart from non-pharmacological interventions (NPIs), COVID-19 vaccine has also been implemented to prevent and control the pandemic since early 2021. Although many aspects have been focused, the change of the spatiotemporal distribution of COVID-19 epidemic across Chinese mainland responding to the change of prevention and control measures were less concerned. Here, we collected the confirmed case data (including domestic cases and overseas imported cases) across Chinese mainland during both 2020/04-2020/08 and 2021/04-2021/08, and then conducted a preliminary data comparison on the spatiotemporal distribution of confirmed cases during the identical period between the two years. Distribution patterns were evaluated both qualitatively by classification method and quantitatively through employing coefficient of variation. Results revealed significant differences in the homogeneity of spatiotemporal distributions of imported or domestic cases between the two years, indicating that the important effect of the adjustment of prevention and control measures on the epidemic evolution. The findings here enriched our practical experience of COVID-19 prevention and control. And, the collected data here might be helpful for improving or verifying spatiotemporally dynamic models of infectious diseases.

Mechanisms controlling the transport and evaporation of human exhaled respiratory droplets containing the severe acute respiratory syndrome coronavirus: a review

Transmission of the coronavirus disease 2019 is still ongoing despite mass vaccination, lockdowns, and other drastic measures to control the pandemic. This is due partly to our lack of understanding on the multiphase flow mechanics that control droplet transport and viral transmission dynamics. Various models of droplet evaporation have been reported, yet there is still limited knowledge about the influence of physicochemical parameters on the transport of respiratory droplets carrying the severe acute respiratory syndrome coronavirus 2. Here we review the effects of initial droplet size, environmental conditions, virus mutation, and non-volatile components on droplet evaporation and dispersion, and on virus stability. We present experimental and computational methods to analyze droplet transport, and factors controlling transport and evaporation. Methods include thermal manikins, flow techniques, aerosol-generating techniques, nucleic acid-based assays, antibody-based assays, polymerase chain reaction, loop-mediated isothermal amplification, field-effect transistor-based assay, and discrete and gas-phase modeling. Controlling factors include environmental conditions, turbulence, ventilation, ambient temperature, relative humidity, droplet size distribution, non-volatile components, evaporation and mutation. Current results show that medium-sized droplets, e.g., 50 µm, are sensitive to relative humidity. Medium-sized droplets experience delayed evaporation at high relative humidity, and increase airborne lifetime and travel distance. By contrast, at low relative humidity, medium-sized droplets quickly shrink to droplet nuclei and follow the cough jet. Virus inactivation within a few hours generally occurs at temperatures above 40 °C, and the presence of viral particles in aerosols impedes droplet evaporation.

The ecosyndemic framework of the global environmental change and the COVID-19 pandemic

The ecosyndemic theory combines the concept of 'synergy' with 'epidemic' and the term "eco" implies the role of the environmental changes. Each of the conditions enhances the negative impacts of the other in an additive way making our society more vulnerable and heightening individual risk factors. In this study, we analyze the mutually reinforcing links between the environment and health from the complexity angle of the ecosyndemic theory and propose the characterization of the COVID-19 pandemic as ecosyndemic. We use the term 'ecosyndemic' because the global environmental change contributes to local-scale, regional-scale and global-scale alterations of the Earth's systems. These changes have their root causes in the way that people interact with the physical, chemical, and biotic factors of the environment. These interactions disturb nature and the consequences have feedbacks in every living organism.

Unanswered questions on the airborne transmission of COVID-19

Policies and measures to control pandemics are often failing. While biological factors controlling transmission are usually well explored, little is known about the environmental drivers of transmission and infection. For instance, respiratory droplets and aerosol particles are crucial vectors for the airborne transmission of the severe acute respiratory syndrome coronavirus 2, the causation agent of the coronavirus 2019 pandemic (COVID-19). Once expectorated, respiratory droplets interact with atmospheric particulates that influence the viability and transmission of the novel coronavirus, yet there is little knowledge on this process or its consequences on virus transmission and infection. Here we review the effects of atmospheric particulate properties, vortex zones, and air pollution on virus survivability and transmission. We found that particle size, chemical constituents, electrostatic charges, and the moisture content of airborne particles can have notable effects on virus transmission, with higher survival generally associated with larger particles, yet some viruses are better preserved on small particles. Some chemical constituents and surface-adsorbed chemical species may damage peptide bonds in viral proteins and impair virus stability. Electrostatic charges and water content of atmospheric particulates may affect the adherence of virion particles and possibly their viability. In addition, vortex zones and human thermal plumes are major environmental factors altering the aerodynamics of buoyant particles in air, which can strongly influence the transport of airborne particles and the transmission of associated viruses. Insights into these factors may provide explanations for the widely observed positive correlations between COVID-19 infection and mortality with air pollution, of which particulate matter is a common constituent that may have a central role in the airborne transmission of the novel coronavirus.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10311-022-01557-z.

Five waves of the COVID-19 pandemic and green-blue spaces in urban and rural areas in Poland

Several waves of COVID-19 caused by different SARS-CoV-2 variants have been recorded worldwide. During this period, many publications were released describing the influence of various factors, such as environmental, social and economic factors, on the spread of COVID-19. This paper presents the results of a detailed spatiotemporal analysis of the course of COVID-19 cases and deaths in five waves in Poland in relation to green‒blue spaces. The results, based on 380 counties, reveal that the negative correlation between the indicator of green‒blue space per inhabitant and the average daily number of COVID-19 cases and deaths was clearly visible during all waves. These relationships were described by a power equation (coefficient of determination ranging from 0.83 to 0.88) with a high level of significance. The second important discovery was the fact that the rates of COVID-19 cases and deaths were significantly higher in urban counties (low values of the green-blue space indicator in m²/people) than in rural areas. The developed models can be used in decision-making by local government authorities to organize anti-COVID-19 prevention measures, including local lockdowns, especially in urban areas.

COVID-DSNet: A novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and Chest X-Ray images

COVID-19 (SARS-CoV-2), which causes acute respiratory syndrome, is a contagious and deadly disease that has devastating effects on society and human life. COVID-19 can cause serious complications, especially in patients with pre-existing chronic health problems such as diabetes, hypertension, lung cancer, weakened immune systems, and the elderly. The most critical step in the fight against COVID-19 is the rapid diagnosis of infected patients. Computed Tomography (CT), chest X-ray (CXR), and RT-PCR diagnostic kits are frequently used to diagnose the disease. However, due to difficulties such as the inadequacy of RT-PCR test kits and false negative (FN) results in the early stages of the disease, the time-consuming examination of medical images obtained from CT and CXR imaging techniques by specialists/doctors, and the increasing workload on specialists, it is challenging to detect COVID-19. Therefore, researchers have suggested searching for new methods in COVID- 19 detection. In analysis studies with CT and CXR radiography images, it was determined that COVID-19-infected patients experienced abnormalities related to COVID-19. The anomalies observed here are the primary motivation for artificial intelligence researchers to develop COVID-19 detection applications with deep convolutional neural networks. Here, convolutional neural network-based deep learning algorithms from artificial intelligence technologies with high discrimination capabilities can be considered as an alternative approach in the disease detection process. This study proposes a deep convolutional neural network, COVID-DSNet, to diagnose typical pneumonia (bacterial, viral) and COVID-19 diseases from CT, CXR, hybrid CT + CXR images. In the multi-classification study with the CT dataset, 97.60 % accuracy and 97.60 % sensitivity values were obtained from the COVID-DSNet model, and 100 %, 96.30 %, and 96.58 % sensitivity values were obtained in the detection of typical, common pneumonia and COVID-19, respectively. The proposed model is an economical, practical deep learning network that data scientists can benefit from and develop. Although it is not a definitive solution in disease diagnosis, it may help experts as it produces successful results in detecting pneumonia and COVID-19.

An overview of viral mutagenesis and the impact on pathogenesis of SARS-CoV-2 variants

Viruses are submicroscopic, obligate intracellular parasites that carry either DNA or RNA as their genome, protected by a capsid. Viruses are genetic entities that propagate by using the metabolic and biosynthetic machinery of their hosts and many of them cause sickness in the host. The ability of viruses to adapt to different hosts and settings mainly relies on their ability to create de novo variety in a short interval of time. The size and chemical composition of the viral genome have been recognized as important factors affecting the rate of mutations. Coronavirus disease 2019 (Covid-19) is a novel viral disease that has quickly become one of the world's leading causes of mortality, making it one of the most serious public health problems in recent decades. The discovery of new medications to cope with Covid-19 is a difficult and time-consuming procedure, as new mutations represent a serious threat to the efficacy of recently developed vaccines. The current article discusses viral mutations and their impact on the pathogenicity of newly developed variants with a special emphasis on Covid-19. The biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), its mutations, pathogenesis, and treatment strategies are discussed in detail along with the statistical data.

RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern

There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.

Assessing the Impact of Contact Tracing, Quarantine and Red Zone on the Dynamical Evolution of the Covid-19 Pandemic using the Cellular Automata Approach and the Resulting Mean Field System: A Case study in Mauritius

A cellular automaton (CA) depicting the dynamics of the Covid-19 pandemic, is set up. Unlike the classic CA models, the present CA is an enhanced version, embodied with contact tracing, quarantine and red zones to model the spread of the Covid-19 pandemic. The incubation and illness periods are assimilated in the CA system. An algorithm is provided to showcase the rules governing the CA, with and without the enactment of red zones. By means of mean field approximation, a nonlinear system of delay differential equations (DDE) illustrating the dynamics of the CA is emanated. The concept of red zones is incorporated in the resulting DDE system, forming a DDE model with red zone. The stability analysis of both systems are performed and their respective reproduction numbers are derived. The effect of contact tracing and vaccination on both reproduction numbers is also investigated. Numerical simulations of both systems are conducted and real time Covid-19 data in Mauritius for the period ranged from 5 March 2021 to 2 September 2021, is employed to validate the model. Our findings reveal that a combination of both contact tracing and vaccination is indispensable to attenuate the reproductive ratio to less than 1. Effective contact tracing, quarantine and red zones have been the key strategies to contain the Covid-19 virus in Mauritius. The present study furnishes valuable perspectives to assist the health authorities in addressing the unprecedented rise of Covid-19 cases.

Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities

Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities.

Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities

Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities.

Comparison of the reactogenicity and immunogenicity of a reduced and standard booster dose of the mRNA COVID-19 vaccine in healthy adults after two doses of inactivated vaccine

The coronavirus disease 2019 (COVID-19) pandemic has been a serious healthcare problem worldwide since December 2019. The third dose of heterologous vaccine was recently approved by World Health Organization. The present study compared the reactogenicity and immunogenicity of the reduced and standard third booster dose of the BNT162b2 and mRNA-1273 vaccine in adults who previously received the two-dose CoronaVac vaccine. Results showed that headache, joint pain, and diarrhea were more frequent in the 15 μg- than the 30 μg-BNT162b2 groups, whereas joint pain and chilling were more frequent in the 100 μg- than the 50 μg-mRNA-1273 groups. No significant differences in immunogenicity were detected. These findings demonstrate that the reduced dose of the mRNA vaccines elicited antibody responses against the SARS-CoV-2 delta and omicron variants that were comparable to the standard dose. The reduced dose could be used to increase vaccine coverage in situations of limited global vaccine supply.

Municipal solid waste, an overlooked route of transmission for the severe acute respiratory syndrome coronavirus 2: a review

Municipal solid waste could potentially transmit human pathogens during the collection, transport, handling, and disposal of waste. Workers and residents living in the vicinity of municipal solid waste collection or disposal sites are particularly susceptible, especially unprotected workers and waste pickers. Recent evidence suggests that municipal solid waste-mediated transmission can spread the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to humans. Such risks, however, have received little attention from public health authorities so far and may present an under-investigated transmission route for SARS-CoV-2 and other infectious agents during pandemics. In this review, we provide a retrospective analysis of the challenges, practices, and policies on municipal solid waste management during the current pandemic, and scrutinize the recent case reports on the municipal solid waste-mediated transmission of the coronavirus disease 2019 (COVID-19). We found abrupt changes in quantity and composition of municipal solid wastes during the COVID-19. We detail pathways of exposure to SARS-CoV-2 and other pathogens carried on municipal solid wastes. We disclose evidence of pathogenic transmission by municipal solid waste to humans and animals. Assessments of current policies, gaps, and voluntary actions taken on municipal solid waste handling and disposal in the current pandemic are presented. We propose risk mitigation strategies and research priorities to alleviate the risk for humans and vectors exposed to municipal solid wastes.

Network analysis of the relationships between conspiracy beliefs towards COVID-19 vaccine and symptoms of fear of COVID-19 in a sample of latin american countries

The present study examined how conspiracy beliefs about COVID-19 vaccines specifically relate to symptoms of fear of COVID-19 in a sample of four South American countries. A total of 1785 people from Bolivia, Colombia, Ecuador, and Peru participated, responding to a sociodemographic survey, the Fear of COVID-19 scale (FCV-19 S) and the Vaccine Conspiracy Beliefs Scale-COVID-19 (VCBS-COVID-19). Network analysis identified the most important symptoms of fear and conspiracy beliefs about COVID-19 vaccines (nodes) and the associations between them (edges). In addition, the robustness of the network of these indicators of centrality and the possible differences in the structure and connectivity of the networks between the four countries were evaluated. The results suggest that the nodes with the highest centrality were items 2 and 5 of the FCV-19 S and item 2 of the VCBS-COVID-19. Likewise, item 6 is the belief that most predicts conspiracy beliefs about vaccines against COVID-19; while item 6 was the symptom that most predicts fear of COVID-19. The findings strongly support cross-cultural similarities in the networks across the four countries rather than differences. Although it was expected that a higher presence of symptoms of fear of COVID-19 may lead people to compensate for their fear by believing in conspiratorial ideas about vaccines and, consequently, rejecting the COVID-19 vaccine, the results do not clearly show this relationship. This could lead other researchers to generate evidence to explain the differences between Latin American countries and countries in other contexts in terms of vaccination rates. This evidence could be useful to develop policies favoring vaccination against COVID-19 that are more contextualized to the Latin American region, characterized by social instability and economic recession during the pandemic.

Low-dose radiotherapy to the lungs using an interventional radiology C-arm fluoroscope: Monte Carlo treatment planning and dose measurements in a postmortem subject

OBJECTIVE

The goal of this study was to use Monte Carlo (MC) simulations and measurements to investigate the dosimetric suitability of an interventional radiology (IR) c-arm fluoroscope to deliver low-dose radiotherapy to the lungs.

APPROACH

A previously-validated MC model of an IR fluoroscope was used to calculate the dose distributions in a COVID-19-infected patient, 20 non-infected patients of varying sizes, and a postmortem subject. Dose distributions for PA, AP/PA, 3-field and 4-field treatments irradiating 95% of the lungs to a 0.5 Gy dose were calculated. An algorithm was created to calculate skin entrance dose as a function of patient thickness for treatment planning purposes. Treatments were experimentally validated in a postmortem subject by using implanted dosimeters to capture organ doses.

MAIN RESULTS

Mean doses to the left/right lungs for the COVID-19 CT data were 1.2/1.3 Gy, 0.8/0.9 Gy, 0.8/0.8 Gy and 0.6/0.6 Gy for the PA, AP/PA, 3-field, and 4-field configurations, respectively. Skin dose toxicity was the highest probability for the PA and lowest for the 4-field configuration. Dose to the heart slightly exceeded the ICRP tolerance; all other organ doses were below published tolerances. The AP/PA configuration provided the best fit for entrance skin dose as a function of patient thickness (R2 = 0.8). The average dose difference between simulation and measurement in the postmortem subject was 0.7%.

SIGNIFICANCE

An IR fluoroscope should be capable of delivering low-dose radiotherapy to the lungs with tolerable collateral dose to nearby organs.

Nature's contributions in coping with a pandemic in the 21st century: A narrative review of evidence during COVID-19

While COVID-19 lockdowns have slowed coronavirus transmission, such structural measures also have unintended consequences on mental and physical health. Growing evidence shows that exposure to the natural environment (e.g., blue-green spaces) can improve human health and wellbeing. In this narrative review, we synthesized the evidence about nature's contributions to health and wellbeing during the first two years of the COVID-19 pandemic. We found that during the pandemic, people experienced multiple types of nature, including both outdoors and indoors. Frequency of visits to outdoor natural areas (i.e., public parks) depended on lockdown severity and socio-cultural contexts. Other forms of nature exposure, such as spending time in private gardens and viewing outdoor greenery from windows, may have increased. The majority of the evidence suggests nature exposure during COVID-19 pandemic was associated with less depression, anxiety, stress, and more happiness and life satisfaction. Additionally, nature exposure was correlated with less physical inactivity and fewer sleep disturbances. Evidence was mixed regarding associations between nature exposure and COVID-related health outcomes, while nature visits might be associated with greater rates of COVID-19 transmission and mortality when proper social distancing measures were not maintained. Findings on whether nature exposure during lockdowns helped ameliorate health inequities by impacting the health of lower-socioeconomic populations more than their higher-socioeconomic counterparts for example were mixed. Based on these findings, we argue that nature exposure may have buffered the negative mental and behavioral impacts of lockdowns during the COVID-19 pandemic. Recovery and resilience during the current crises and future public health crises might be improved with nature-based infrastructure, interventions, designs, and governance.

Nature's contributions in coping with a pandemic in the 21st century: A narrative review of evidence during COVID-19

While COVID-19 lockdowns have slowed coronavirus transmission, such structural measures also have unintended consequences on mental and physical health. Growing evidence shows that exposure to the natural environment (e.g., blue-green spaces) can improve human health and wellbeing. In this narrative review, we synthesized the evidence about nature's contributions to health and wellbeing during the first two years of the COVID-19 pandemic. We found that during the pandemic, people experienced multiple types of nature, including both outdoors and indoors. Frequency of visits to outdoor natural areas (i.e., public parks) depended on lockdown severity and socio-cultural contexts. Other forms of nature exposure, such as spending time in private gardens and viewing outdoor greenery from windows, may have increased. The majority of the evidence suggests nature exposure during COVID-19 pandemic was associated with less depression, anxiety, stress, and more happiness and life satisfaction. Additionally, nature exposure was correlated with less physical inactivity and fewer sleep disturbances. Evidence was mixed regarding associations between nature exposure and COVID-related health outcomes, while nature visits might be associated with greater rates of COVID-19 transmission and mortality when proper social distancing measures were not maintained. Findings on whether nature exposure during lockdowns helped ameliorate health inequities by impacting the health of lower-socioeconomic populations more than their higher-socioeconomic counterparts for example were mixed. Based on these findings, we argue that nature exposure may have buffered the negative mental and behavioral impacts of lockdowns during the COVID-19 pandemic. Recovery and resilience during the current crises and future public health crises might be improved with nature-based infrastructure, interventions, designs, and governance.

Is Omicron the end of pandemic or start of a new innings?

In the middle of November 2021, Omicron (B.1.1.529), a novel variant of SARS-CoV-2 was identified in South Africa. Owing to continuous increasing cases with rapid transmissibility and immune evasion, the World Health Organization (WHO) has categorized this strain as a variant of concern (VOC). In total, over 60 mutations have been identified in Omicron (BA.1) and latterly, its three sub-lineages (BA.1.1, BA.2, and BA.3) have also been found with additional mutations and pathogenicity. The highly contagious Omicron causes less severe sickness than Delta, but it is still dangerous for those who have not been vaccinated. Following the unique identification of the Omicron variant, a fresh debate has erupted regarding the natural vaccines. A number of experts believe that Omicron can work as a natural vaccine, because it is similar to live attenuated vaccines in certain ways. Additionally, it was highlighted that the high rate of antibody generation in individuals cured of Omicron provide suggestive evidence in favor of those researchers who claimed Omicron acts as natural vaccine. Some disagreements also noted, as it also has tremendous health effects and high infection rate, as similar to the prior variants. This review summarizes the contradictory scenario among the scientists about Omicron variant.

The changing economic relationship between some of the major COVID-19 impacted countries with prominent wealth: a comparative study from the view point of stock markets

In the present work, a study has been made over the prime stock indices of some fiscally prominent countries impacted by COVID-19. The countries are separated in two ways: (1) considering gross total number of infected cases-here seven mostly impacted countries with certain global economic influence are selected; (2) considering the concentration of the infected cases-here six major impacted countries with considerable influence are selected. This sort of categorization is itself a novel strategy which is capable of including some less populated, but severely impacted countries of economic importance. The objective of the present analysis is to comprehend the impact of COVID-19 on these markets and to recognize the effect of COVID-19 on mutual association and dependence between these markets. To add more flavour of reliability, we have taken a new and fresh strategy of fixing the time frames under consideration before and during COVID-19 pandemic as uniform. We have used both linear and nonlinear Granger causality analysis and employed generalized forecast error variance decomposition analysis to review the exogeneity and endogeneity of the individual markets. The present study shows that this pandemic has changed the underlying relationship: some exogenous stock markets have become endogenous and vice versa in the pandemic. Linear relationship has been reduced radically, whereas nonlinear relationship has been improved during the COVID-affected period. TASE, the highest returned and significantly uncorrelated index, emerged as the most exogenous market in the pre-COVID period, though it is nonlinearly endogenous in the long term, in the COVD-affected period. CAC 40 is the most endogenous market for the short term in both pre-COVID and COVID-affected period. B3 and NYSE, exogenous in the pre-COVID period, turned out to be linearly endogenous in the COVID-affected duration, whereas BIST 100 and BSE SENSEX are found to be exogenous markets in the COVID-affected period according to both linear and nonlinear causal analysis. They were also exogenous in the pre-COVID era for the short-term period, with BSE SENSEX exhibiting exogeneity anti-persistently for the COVID-affected period too. Association among the markets is more in long term rather than short term. A possible conclusion is also that the markets may regain long-term association once the effect of COVID would fade away.

Comparative Analysis of Age, Sex, and Viral Load in Outpatients during the Four Waves of SARS-CoV-2 in A Mexican Medium-Sized City

Governments have implemented measures to minimize SARS-CoV-2 spread. However, these measures were relaxed, and the appearance of new variants has prompted periods of high contagion known as waves. In Mexico, four waves distributed between July and August 2020, January and February 2021, August and September 2021, and January and February 2022 have appeared. Current health policies discourage mass sampling, preferring to focus on the corrective treatment of severe cases. Outpatients are only advised to undergo brief voluntary confinement and symptomatic treatment, with no follow-up. Therefore, the present study aimed to analyze sex, age, and viral load in outpatients during the four waves in a medium-sized city in Mexico. For each wave, the date of peak contagion was identified, and data were collected within ±15 days. In this regard, data from 916 patients (434 men and 482 women) were analyzed. The age range of positive patients (37-45 years) presented a higher frequency during the first and third waves, while 28-36 years was the most frequent age range during the second and fourth waves, while the viral load values were significantly higher, for both sexes, during the fourth wave. Obtained data of COVID-19 prevalence in population segments can be used for decision-making in the design of effective public health policies.

Associations Between Online Learning, Smartphone Addiction Problems, and Psychological Symptoms in Chinese College Students After the COVID-19 Pandemic

Background

Smartphone-based online education gained popularity during and after the COVID-19 pandemic. Although recent studies have highlighted the association between problematic smartphone use (PSU) and mental health symptoms, the potential role of online learning in this relationship remains unclear. This study aimed to analyze the relationships between higher education modes, PSU, and related psychological symptoms in university students.

Methods

A total of 1,629 Chinese university students from five provinces completed a web-based questionnaire survey between March 2020 and October 2021. Demographic characteristics and learning conditions were recorded. All participants completed the Smartphone Addiction Scale-Short Version, Patient Health Questionnaire, Generalized Anxiety Disorder Scale, and Athens Insomnia Scale. Multiple regressions models and stratified analyses were used to examine the association between online education mode, PSU, and symptoms of depression, anxiety, and insomnia.

Results

The prevalence of PSU was 58.5%. Students who relied primarily on online learning had a higher prevalence of depressive symptoms (29.95% vs. 22.24%), anxiety symptoms (25.13% vs. 18.91%), and insomnia symptoms (75.89% vs. 70.27%) than those who relied on traditional face-to-face learning (Ps < 0.05). After adjusting for covariates, subjects with PSU were more likely to report depressive symptoms (AdjOR = 3.14, 95% CI = 2.26–4.37), anxiety symptoms (AdjOR = 3.73, 95% CI = 2.13–4.59), and insomnia symptoms (AdjOR = 2.96, 95% CI = 2.23–3.92) than those without PSU. Furthermore, the associations of PSU with depressive symptoms (OR = 4.66 vs. 2.33, P for interaction = 0.015) and anxiety symptoms (OR = 6.05 vs. 2.94, P for interaction = 0.021) were more pronounced in the online learning group.

Conclusion

Our study provides preliminary evidence that Chinese university students have serious smartphone addiction problems, which are associated with depressive, anxiety, and insomnia symptoms. Online learning is found to exacerbate PSU and mental health problems. Our findings provide valuable information for targeted psychological interventions in the post-COVID-19 era.

Canadian Consumers’ Dining Behaviors during the COVID-19 Pandemic: Implications for Channel Decisions in the Foodservice Industry

The past two years have been challenging for the restaurant industry in Canada and countries worldwide. This has led many casual and fine dining restaurants to adapt their business models to overcome the immediate and long-term impacts of the COVID-19 pandemic. This paper aims to understand how COVID-19 has impacted Canadian consumers’ on- and off-premise dining behaviors and how such behaviors vary among various sociodemographic groups, general knowledge of COVID-19, and telecommuting. Data were collected from a nationally representative consumer panel (n = 1091), from a survey administered online by Angus Reid. The results show that Canadian consumers increased their off-premise dining experiences during the COVID-19 pandemic, which also varied across various sociodemographic groups. There was also an increased level of telecommuting during the pandemic, of which 68% started following the pandemic. However, telecommuting was negatively correlated with off-premise dining experiences during the pandemic. Canadian consumers perceived off-premise dining during the pandemic as reasonably expensive, lesser quality, and more convenient. The findings may have important implications for casual and dining restaurants in Canada to improve channel decisions and messaging as operators prepare for a full-service post-COVID-19. They can build on the infrastructure and capability that has been established during the COVID-19 pandemic to offer sustainable services beyond the pandemic.

COVID-19 at a Glance: An Up-to-Date Overview on Variants, Drug Design and Therapies

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a member of the Coronavirus family which caused the worldwide pandemic of human respiratory illness coronavirus disease 2019 (COVID-19). Presumably emerging at the end of 2019, it poses a severe threat to public health and safety, with a high incidence of transmission, predominately through aerosols and/or direct contact with infected surfaces. In 2020, the search for vaccines began, leading to the obtaining of, to date, about twenty COVID-19 vaccines approved for use in at least one country. However, COVID-19 continues to spread and new genetic mutations and variants have been discovered, requiring pharmacological treatments. The most common therapies for COVID-19 are represented by antiviral and antimalarial agents, antibiotics, immunomodulators, angiotensin II receptor blockers, bradykinin B2 receptor antagonists and corticosteroids. In addition, nutraceuticals, vitamins D and C, omega-3 fatty acids and probiotics are under study. Finally, drug repositioning, which concerns the investigation of existing drugs for new therapeutic target indications, has been widely proposed in the literature for COVID-19 therapies. Considering the importance of this ongoing global public health emergency, this review aims to offer a synthetic up-to-date overview regarding diagnoses, variants and vaccines for COVID-19, with particular attention paid to the adopted treatments.

Escaping from COVID-19 emergency accounting on previously infected subjects?

The efficacy of vaccination to prevent a huge widespread SARS-CoV2 infection is quite undoubtedly assessed by recent data and reports, yet the co-existence of naturally immunized (serum positive, SP) non-vaccinated people, SP vaccinated people and naïve (serum negative) people, should thoroughly revise our epidemiological overview and data interpretation about social contacts and even restriction measures. We are not merely talking about a blank immune population needing urgent vaccination but of a complex milieu of immunized subjects, whose thorough and expert knowledge may provide fundamental insights to improve the management of COVID-19 pandemic emergency. For example, upon vaccination, a good recommended practice is to evaluate both mucosal and serum immunity, by a quantitative salivary sIgAs and serum IgGs search, better if along a swab test, in order to group individuals called for vaccination in cohorts of susceptibility, which should enable physicians to take a decision about how many doses of vaccine and when, they should take into consideration, based on the previous immunity assessed from the subject. Actually, it seems that vaccines act quite exclusively as boosters This article is protected by copyright. All rights reserved.

Barcoding drug information to recycle unwanted household pharmaceuticals: a review

Huge quantities of unwanted pharmaceuticals are left in households, notably as a consequence of the rising drug demand caused by improved healthcare and the aging population. Unwanted pharmaceuticals may thus easily end up polluting ecosystems upon disposal. This pharmaceutical waste issue has been aggravated during the coronavirus disease pandemic (COVID-19) by excess prescription and panic buying. Unwanted household pharmaceuticals are normally collected by owners and volunteers, then incinerated in centralized facilities, yet with low efficiency during the COVID-19 lockdowns. Most pharmaceuticals could be recycled because they are rather stable, however there is actually no sustainable strategy to manage unwanted pharmaceuticals in a pandemic. Here I review the management of unwanted pharmaceuticals in households during the pandemic, with emphasis on drug take-back programs, waste minimization and recycling efforts. Reducing pharamaceutical waste could be done by informing people on what to do with unwanted pharmaceutical products; using machine-readable codes for automatic sorting; and applying existing techniques for recovery of active pharmaceutical ingredients for reuse. I propose a new strategy where owners sort their unwanted pharmaceuticals and submit information online. This will generate coded mailing labels that allow the owner to separate pharmaceuticals into categories such as opened, unused, expired, and non-expired. Once collected by recycling facilities and manufacturers, active ingredients will be extracted to create new pharmaceuticals which will be recycled to other patients.

Environmental factors influencing the transmission of the coronavirus 2019: a review

The coronavirus 2019 pandemic, induced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has strongly altered healthcare systems and the economy worldwide. The lack of knowledge on this virus has led to the implementation of uncertain strategies and measures to fight the pandemic. Here, we review environmental factors that control viral transmission, such as air, temperature, humidity, food, water and sewage, insects, inanimate surfaces, hand hygiene, and social distancing. The main route of viral transmission is the respiratory tract through aerosols. Masks and social distancing are effective in ceasing air transmission. Proper cleaning of surfaces and hand disinfection are required, especially in healthcare units. Food should be handled properly, and food handlers should work based on hygienic protocols. Water and sewage transmission, and transmission through insects appear less important than other environmental factors.