COVID-19: Epidemiology, Evolution, and Cross-Disciplinary Perspectives

Spatial analysis of dengue fever incidence and serotype distribution in Vientiane Capital, Laos: A multi-year study

Laos is a hyperendemic country of all 4 dengue serotypes. Various factors contribute to the spread of the disease including viral itself, vectors, and environment. This study aims to analyze dengue data and its incidence in nine districts of Vientiane Capital, Laos spanning from 2019 to 2021 by data collected from Mittaphab Hospital. The Maximum Entropy algorithm (MaxEnt) was applied to assess spatial distribution and identify high-probability locations for dengue occurrence by analyzing crucial environmental and climatic conditions. Dengue cases were more prominent in female (54.88 %) and highest case number was found in worker group (29.02 %) followed by student (28.47 %) and officer (16.92 %). In this study, the age group 21-30 years old had the highest infection rate (42.23 %), followed by 10-20 years old (24.21 %). Most of dengue cases was primary infection (91.61 %). Dengue serotype 2 predominated in 2019 and 2020 and substitute by serotype 1 in 2021. Across the nine districts of Vientiane Capital, the highest incidence of dengue was found in Xaythany district population in 2019, shifting to Chanthabouly district in 2020 and 2021. The MaxEnt revealed potentially most suitable areas for dengue were widely distributed central south part of Vientiane, Laos. Additionally, the best predictive variable for dengue occurrence was normalized difference vegetation index. Understanding of case characteristics and spatial distribution features of dengue will be helpful in effective surveillance and disease control in the future.

Relationship between blood group (ABO) and risk of COVID-19 infection in a patient cohort in Tehran, Iran

Background and purpose. Coronavirus (COVID-19) is a contagious disease causing severe acute respiratory syndrome which had a catastrophic effect on the world population and resulted in more than 2.9 million deaths worldwide. Epidemiological investigations have recently announced blood type has an association with the incidence of COVID-19 infection. Consequently, research in this regard can be effective in determining a person's susceptibility to a viral infection. Therefore, we investigated the relationship between blood types and the risk of COVID-19 in patients admitted to Khorshid laboratory, Tehran, Iran. Materials and methods. From January to March 2020, 50 nasal and throat swapb samples of patients' secretions were obtained from patients who were admitted to Khorshid laboratory. They were confirmed to have COVID-19 virus RNA and real-time polymerase chain reaction (PCR)-ABI, and their blood type was determined simultaneously. After collecting data to determine the relationship between COVID-19 infection and blood type, a confidence interval of 90 % was considered using SPSS 16. Results. The mean age of the patients was measured at 38.4±6.3 years. According to PCR results, 100 % of the subjects with COVID-19 showed blood type A. In addition, the ratio of blood type A to the percentage of reference type O was higher (P=0.009). Conclusion. There was a significant relationship between ABO blood type and susceptibility to COVID-19. As the current study suggests, those with blood type A are at a higher COVID-19 infection risk than those with blood type O.

VLP-based model for the study of airborne viral pathogens

The recent COVID-19 pandemic has underscored the danger of airborne viral pathogens. The lack of model systems to study airborne pathogens limits the understanding of airborne pathogen distribution as well as potential surveillance and mitigation strategies. In this work, we develop a novel model system to study airborne pathogens using virus-like particles (VLPs). Specifically, we demonstrate the ability to aerosolize VLP and detect and quantify aerosolized VLP RNA by reverse transcription-loop-mediated isothermal amplification in real-time fluorescent and colorimetric assays. Importantly, the VLP model presents many advantages for the study of airborne viral pathogens: (i) similarity in size and surface components; (ii) ease of generation and noninfectious nature enabling the study of biosafety level 3 and biosafety level 4 viruses; (iii) facile characterization of aerosolization parameters; (iv) ability to adapt the system to other viral envelope proteins, including those of newly discovered pathogens and mutant variants; and (v) the ability to introduce viral sequences to develop nucleic acid amplification assays.

IMPORTANCE

The study and detection of airborne pathogens are hampered by the lack of appropriate model systems. In this work, we demonstrate that noninfectious virus-like particles (VLPs) represent attractive models to study airborne viral pathogens. Specifically, VLPs are readily prepared, are similar in size and composition to infectious viruses, and are amenable to highly sensitive nucleic acid amplification techniques.

Consumption of Food Offered by Delivery Applications (Apps)

This study aimed to investigate whether the use of food delivery applications is related to food consumption practices.

METHODS

Data collection was carried out between 5 and 20 June 2020 in a Brazilian capital with a final sample of 2113 individuals. The instrument included questions about socioeconomic characteristics, anthropometric data, and information about eating practices and the use of delivery apps. Logistic regression models were developed with the consumption of each food group as the outcome variable and the use of the application as the exposure variable.

RESULTS

Of those interviewed, 78.1% used delivery apps to purchase food. The frequencies of the consumption of foods considered markers of healthy eating were higher for individuals who did not use the applications (59.7% vs. 38.7% for the daily consumption of fresh fruit, respectively, p < 0.0001). The frequencies of the consumption of items considered markers of unhealthy eating were higher for individuals who used apps to purchase food prepared outside the home compared to those who did not (53.7 vs. 38.1 for weekly consumption of hamburgers, respectively, p < 0.0001).

CONCLUSION

The use of delivery applications influenced the users' eating practices through the acquisition of food within the digital scope and is related to a greater frequency of the consumption of unhealthy items by users.

Mesenchymal stem cells and their derived exosomes for the treatment of COVID-19

Coronavirus disease 2019 (COVID-19) is an acute respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 infection typically presents with fever and respiratory symptoms, which can progress to severe respiratory distress syndrome and multiple organ failure. In severe cases, these complications may even lead to death. One of the causes of COVID-19 deaths is the cytokine storm caused by an overactive immune response. Therefore, suppressing the overactive immune response may be an effective strategy for treating COVID-19. Mesenchymal stem cells (MSCs) and their derived exosomes (MSCs-Exo) have potent homing abilities, immunomodulatory functions, regenerative repair, and antifibrotic effects, promising an effective tool in treating COVID-19. In this paper, we review the main mechanisms and potential roles of MSCs and MSCs-Exo in treating COVID-19. We also summarize relevant recent clinical trials, including the source of cells, the dosage and the efficacy, and the clinical value and problems in this field, providing more theoretical references for the clinical use of MSCs and MSCs-Exo in the treatment of COVID-19.

A randomized clinical trial investigating the impact of magnesium supplementation on clinical and biochemical measures in COVID-19 patients

BACKGROUND

This study sought to examine the impact of magnesium supplementation on clinical outcomes and biochemical factors among hospitalized patients with COVID-19.

METHODS

This double-blind, randomized clinical trial was conducted at Razi Hospital, Ahvaz, Iran, between September 2021 and March 2022. Participants aged 18-70 years with moderate disease severity were enrolled. Magnesium supplementation (300 mg daily) was administered to the intervention group, while the control group received a placebo. Clinical outcomes, including the need for oxygen therapy, oxygen saturation, respiratory rate, fever, hs-CRP and TNF-α levels, as well as quality of life and mental health, were assessed. Blood samples were collected to measure biochemical variables.

RESULTS

The main result was the count of individuals requiring oxygen therapy. Additional outcomes comprised of oxygen saturation, respiratory rate, fever, hs-CRP and TNF-α levels, as well as quality of life and mental health. Out of 64 participants, 60 completed the study. The results showed that magnesium supplementation significantly reduced the number of patients requiring oxygen therapy (9 vs. 14; P < 0.001). Moreover, the magnesium group demonstrated improved oxygen saturation compared to the control group (4.55 ± 2.35 vs. 1.8 ± 1.67; P < 0.001). Furthermore, we observed a noteworthy enhancement in the quality of life and depression score in the magnesium group. No significant differences were observed in respiratory rate, fever, hs-CRP, and TNF-α levels (P > 0.05).

CONCLUSION

The findings suggest that magnesium supplementation may have beneficial effects on clinical outcomes and arterial oxygen saturation in COVID-19 patients. More investigation is necessary to delve into its potential mechanisms and long-term effects on patient outcomes.

TRIAL REGISTRATION

This study is registered on Iranian Registry of Clinical Trials (IRCT) under identifier IRCT20210413050957N1. (The registration date: May 1, 2021).

On-site detection of infectious disease based on CaCO3-based magnetic micromotor integrated with graphene field effect transistor

A new detection platform based on CaCO3-based magnetic micromotor (CaCO3@Fe3O4) integrated with graphene field effect transistor (GFET) was construct and used for on-site SARS-CoV-2 coronavirus pathogen detection. The CaCO3@Fe3O4 micromotor, which was modified with anti-SARS-CoV-2 (labelled antibody, AntiE1), can self-moved in the solution containing hydrochloric acid (HCl) and effective to capture the SARS-CoV-2 coronavirus pathogens. After magnetic field separation, the capture micromotor was detected by GFET, exhibiting a good linear relationship within the range of 1 ag/mL to 100 ng/mL and low detection limit (0.39 ag/mL). Furthermore, the detection platform was also successfully applied to detection of SARS-CoV-2 coronavirus pathogens in soil solution, indicating the potential use in on-site application.

Global Mapping and Visualization Analysis of One Health Knowledge in the COVID-19 Context

Globally, the COVID-19 pandemic had a significant impact on the health, social, and economic systems, triggering lasting damage and exposing the complexity of the problem beyond just being a health emergency. This crisis has highlighted the need for a comprehensive and collaborative strategy to successfully counter infectious diseases and other global challenges. With the COVID-19 pandemic pushing One Health to the forefront of global health and sustainable development agendas, this concept has emerged as a potential approach for addressing these challenges. In the context of COVID-19, this study investigates global knowledge about One Health by examining its state, significant contributions, and future directions. It seeks to offer an integrated framework of insights guiding the development of well-informed decisions. A comprehensive search using the Scopus database was conducted, employing specific terms related to One Health and COVID-19. VOSviewer 1.6.19 software was used to generate network visualization maps. Countries' research output was adjusted based on their gross domestic product (GDP) and population size. The study identified a total of 527 publications. The United States led with 134 documents (25.4%), but India topped the adjusted ranking. One Health journal stood as the most common outlet for disseminating knowledge (49 documents; 9.3%), while Centers for Disease Control and Prevention (CDC), the United States emerged as the most prolific institution (13 documents; 2.5%). Key topics were related to the virus transmission mechanisms, climate change impacts, antimicrobial resistance, ecosystem health, preparedness, collaboration, community engagement, and developing of efficient surveillance systems. The study emphasizes how critical it is to capitalize on the present momentum of COVID-19 to advance One Health concepts. Integrating social and environmental sciences, and a variety of professions for better interaction and collaboration is crucial. Additionally, increased funding for developing countries, and legislative empowerment are vital to advance One Health and boost disease prevention.

Understanding clinical complexity in organ and organizational systems: Challenges local and global

INTRODUCTION

Complexity in healthcare systems has been arbitrarily defined as tasks or systems ranging from complicated to intractable, with a general view of these not being 'simple'. Complexity in healthcare systems in first-world countries has been well elucidated, however, data from third-world countries is still scant. MATERIALS AND METHODS: We present four cases each from three different organ systems-chronic kidney disease, alcohol use disorder, and heart failure-in the backdrop of our healthcare organization. We present our analysis of the complexities faced clinically and, in our local healthcare system which led to these events.

RESULTS

Analysis of these cases showed that patients with chronic kidney disease had vertebral-spinal pathologies due to poor infection control measures during haemodialysis. All these patients were young with a long history of secondary hypertension. In patients with alcohol use disorder, a common theme of how government regulations and peer pressure promote alcohol use is analysed. In the four patients with unexplained heart failure, vascular health is viewed as a fractal dimension and the various factors affecting vascular health are elaborated.

CONCLUSION

Complexities exist clinically in making a diagnosis, and organizationally, in the variables and nodes dictating patient outcomes. Clinical complexities cannot be simplified but have to be navigated in an optimized way to improve clinical outcomes.

Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review

BACKGROUND

In the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of mobile apps and technology for the detection and diagnosis of COVID-19 has been the subject of numerous investigations, although no thorough analysis of COVID-19 pandemic prevention has been conducted using mobile apps, creating a gap.

OBJECTIVE

With the intention of helping software companies and clinical researchers, this study provides comprehensive information regarding the different fields in which mobile apps were used to diagnose COVID-19 during the pandemic.

METHODS

In this systematic review, 535 studies were found after searching 5 major research databases (ScienceDirect, Scopus, PubMed, Web of Science, and IEEE). Of these, only 42 (7.9%) studies concerned with diagnosing and detecting COVID-19 were chosen after applying inclusion and exclusion criteria using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) protocol.

RESULTS

Mobile apps were categorized into 6 areas based on the content of these 42 studies: contact tracing, data gathering, data visualization, artificial intelligence (AI)-based diagnosis, rule- and guideline-based diagnosis, and data transformation. Patients with COVID-19 were identified via mobile apps using a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. Most studies concentrated on using AI methods to identify people who might have COVID-19. Additionally, symptoms, cough sounds, and radiological images were used more frequently compared to other data types. Deep learning techniques, such as convolutional neural networks, performed comparatively better in the processing of health care data than other types of AI techniques, which improved the diagnosis of COVID-19.

CONCLUSIONS

Mobile apps could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and the early identification of suspected cases. These technologies can work with the internet of things, cloud storage, 5th-generation technology, and cloud computing. Processing pipelines can be moved to mobile device processing cores using new deep learning methods, such as lightweight neural networks. In the event of future pandemics, mobile apps will play a critical role in rapid diagnosis using various image data and clinical symptoms. Consequently, the rapid diagnosis of these diseases can improve the management of their effects and obtain excellent results in treating patients.

The relationship of smartphone addiction with depression, anxiety, and stress among medical students

Introduction

An increasing amount of research has shown a link between psychopathological behaviors such as smartphone addiction, depression, anxiety, and stress. The aim of this study was to assess the association of smartphone addiction with depression, anxiety, and stress.

Methods

A cross-sectional study was conducted between 26th January and 3rd March 2021. The sample was chosen using a convenient sampling technique and Raosoft tool. The survey assessed smartphone addiction using abbreviated versions of the Addiction Scale Short Version, a self-administered questionnaire that has been validated in the English and Arabic languages. Also, Depression and Anxiety Stress Scale was used to measure the level of depression, anxiety, and stress among the university students.

Results

A total of 367 university students from the Medical and Health Sciences College participated. Our findings showed that smartphone addiction exhibited positive correlations with depression (r = 0.375, p < 0.01), anxiety (r = 0.253, p < 0.01), and stress (r = 0.328, p < 0.05). In addition, there was a strong positive correlation between depression and both anxiety and stress (r = 0.731, p < 0.01) (r = 0.778, p < 0.01), respectively. Finally, stress and anxiety showed a positive correlation (r = 0.708, p < 0.01).

Conclusion

When combined, our data offer strong support for a bidirectional hybrid theory that takes into account the link between smartphone addiction and depression, anxiety, and stress. The current study's findings might assist national health authorities in strengthening their efforts to prevent depression, anxiety, and stress associated with the use of modern technology.

Porcine Epidemic Diarrhea Virus: Etiology, Epidemiology, Antigenicity, and Control Strategies in China

Porcine epidemic diarrhea virus (PEDV) is a porcine enteric coronavirus, which is one of the main causative agents of porcine epidemic diarrhea (PED), with 100% morbidity and 80-100% mortality in neonatal piglets. Since 2010, large-scale PED caused by highly pathogenic variants of PEDV has occurred successively in China and other countries in the world, posing a great threat to the global pig industry. It has been demonstrated in many investigations that the classic attenuated vaccine strain, PEDV CV777, is insufficient to fully protect against the PEDV variants. Moreover, the maternally derived antibodies elicited by inactivated vaccines also cannot completely protect piglets from infection. In addition, feedback feeding poses a risk of periodic PEDV recurrence in pig farms, making it challenging to successfully limit the spread of PEDV in China. This review focuses on the etiology, epidemiology, antigenicity, and control strategies of PEDV in China and provides information for the formulation of effective control measures.

Estimating the heritability of SARS-CoV-2 susceptibility and COVID-19 severity

SARS-CoV-2 has infected over 340 million people, prompting therapeutic research. While genetic studies can highlight potential drug targets, understanding the heritability of SARS-CoV-2 susceptibility and COVID-19 severity can contextualize their results. To date, loci from meta-analyses explain 1.2% and 5.8% of variation in susceptibility and severity respectively. Here we estimate the importance of shared environment and additive genetic variation to SARS-CoV-2 susceptibility and COVID-19 severity using pedigree data, PCR results, and hospitalization information. The relative importance of genetics and shared environment for susceptibility shifted during the study, with heritability ranging from 33% (95% CI: 20%-46%) to 70% (95% CI: 63%-74%). Heritability was greater for days hospitalized with COVID-19 (41%, 95% CI: 33%-57%) compared to shared environment (33%, 95% CI: 24%-38%). While our estimates suggest these genetic architectures are not fully understood, the shift in susceptibility estimates highlights the challenge of estimation during a pandemic, given environmental fluctuations and vaccine introduction.

VLP-Based Model for Study of Airborne Viral Pathogens

The recent COVID-19 pandemic has underscored the danger of airborne viral pathogens. The lack of model systems to study airborne pathogens limits the understanding of airborne pathogen distribution, as well as potential surveillance and mitigation strategies. In this work, we develop a novel model system to study airborne pathogens using virus like particles (VLP). Specifically, we demonstrate the ability to aerosolize VLP and detect and quantify aerosolized VLP RNA by Reverse Transcription-Loop-Mediated Isothermal Amplification (RT-LAMP) in real-time fluorescent and colorimetric assays. Importantly, the VLP model presents many advantages for the study of airborne viral pathogens: (i) similarity in size and surface components; (ii) ease of generation and noninfectious nature enabling study of BSL3 and BSL4 viruses; (iii) facile characterization of aerosolization parameters; (iv) ability to adapt the system to other viral envelope proteins including those of newly discovered pathogens and mutant variants; (v) the ability to introduce viral sequences to develop nucleic acid amplification assays.

The risk of pet animals in spreading severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and public health importance: An updated review

Since the outbreak of SARS-CoV-2 was first identified in 2019, it has been reported that the virus could infect a variety of animals either naturally or experimentally. This review discusses the occurrence SARS-CoV-2 in dogs and cats and the role of these animals in transmitting coronavirus disease 2019 (COVID-19) to their owners. The data were collected from epidemiological studies and case reports that focused on studying the occurrence of SARS-CoV-2 in pet animals and their owners. Epidemiological studies and case reports indicate that dogs and cats are infected with SARS-CoV-2 either naturally or experimentally; however, the global number of naturally infected animals is far lower than the number of people who have COVID-19. These studies demonstrate that pet animals acquire the infection from direct contact with COVID-19-infected owners. Currently, there are no studies reporting that dogs and cats can transmit SARS-CoV-2 to other animals and humans, under natural conditions. The emergence of SARS-CoV-2 infection in companion animals (dogs and cats) in different countries worldwide raises concerns that pets are at higher risk for spreading and transmitting SARS-CoV-2 to humans and other animals, which poses a hazard to the public health. Therefore, investigating the role of dogs and cats in the transmission and epidemiology of SARS-CoV-2 will help us to design and implement appropriate preventive measures against the further transmission of SARS-CoV-2.

Development of a quantum dot-based lateral flow immunoassay strip for rapid and sensitive detection of SARS-CoV-2 neutralizing antibodies

To a certain extent, the development and vaccination of COVID-19 vaccine have reduced the alarming rate of transmission speed and mortality rate. At present, vaccine coverage is quite high in countries around the world. Since individual differences are unavoidable, it is necessary to assess the efficacy of the vaccine in each vaccinated person in order to reflect the protective effect of the vaccine in different populations. In this study, we developed a novel COVID-19 neutralizing antibody detection kit combining lateral flow immunochromatography and novel quantum dot technology with 85.23% sensitivity, 92.50% specificity. The novel QD-ICA could achieve an accurate detection of SARS-CoV-2 neutralizing antibodies with 10 minutes, two steps, small equipment size, and broad testing application, suggesting its capability to assess vaccine effectiveness on a large scale in areas of world that currently affected by the pandemic.

Posttranslational modifications of ACE2 protein: Implications for SARS-CoV-2 infection and beyond

The present worldwide pandemic of coronavirus disease 2019 (COVID-19) has highlighted the important function of angiotensin-converting enzyme 2 (ACE2) as a receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry. A deeper understanding of ACE2 could offer insights into the mechanisms of SARS-CoV-2 infection. While ACE2 is subject to regulation by various factors in vivo, current research in this area is insufficient to fully elucidate the corresponding pathways of control. Posttranslational modification (PTM) is a powerful tool for broadening the variety of proteins. The PTM study of ACE2 will help us to make up for the deficiency in the regulation of protein synthesis and translation. However, research on PTM-related aspects of ACE2 remains limited, mostly focused on glycosylation. Accordingly, a comprehensive review of ACE2 PTMs could help us better understand the infection process and provide a basis for the treatment of COVID-19 and beyond.

Heavy-tailed distributions of confirmed COVID-19 cases and deaths in spatiotemporal space

This paper conducts a systematic statistical analysis of the characteristics of the geographical empirical distributions for the numbers of both cumulative and daily confirmed COVID-19 cases and deaths at county, city, and state levels over a time span from January 2020 to June 2022. The mathematical heavy-tailed distributions can be used for fitting the empirical distributions observed in different temporal stages and geographical scales. The estimations of the shape parameter of the tail distributions using the Generalized Pareto Distribution also support the observations of the heavy-tailed distributions. According to the characteristics of the heavy-tailed distributions, the evolution course of the geographical empirical distributions can be divided into three distinct phases, namely the power-law phase, the lognormal phase I, and the lognormal phase II. These three phases could serve as an indicator of the severity degree of the COVID-19 pandemic within an area. The empirical results suggest important intrinsic dynamics of a human infectious virus spread in the human interconnected physical complex network. The findings extend previous empirical studies and could provide more strict constraints for current mathematical and physical modeling studies, such as the SIR model and its variants based on the theory of complex networks.

Exploring disparities and novel insights into metabolic and cardiovascular comorbidities among COVID-19 patients in Mexico

Introduction

The COVID-19 pandemic, especially its early stages, sparked extensive discussions regarding the potential impact of metabolic and cardiovascular comorbidities on the severity and fatality of SARS-CoV-2 infection, yielding inconclusive outcomes. In this study, we delve into the prevalence of metabolic and cardiovascular comorbidities within COVID-19 patients in Mexico.

Methods

Employing a retrospective observational study design, we collected data from official databases encompassing COVID-19 patients admitted to both public and private hospitals in Mexico City.

Results

Our investigation unveiled a noteworthy incongruity in the prevalence of metabolic and cardiovascular comorbidities among COVID-19 patients, with a particular emphasis on obesity, hypertension, and diabetes. This incongruity manifests as location-dependent phenomena, where the prevalence of these comorbidities among COVID-19 patients significantly deviates from the reported values for the general population in each specific location.

Discussion

These findings underscore the critical importance of screening for metabolic and cardiovascular comorbidities in COVID-19 patients and advocate for the necessity of tailored interventions for this specific population. Furthermore, our study offers insights into the intricate interplay between COVID-19 and metabolic and cardiovascular comorbidities, serving as a valuable foundation for future research endeavors and informing clinical practice.

Adverse Effects Reported and Insights Following Sinopharm COVID-19 Vaccination

Vaccines are promising strategies for controlling COVID-19; however, COVID-19 vaccine side effects play a central role in public confidence in the vaccine and its uptake process. This study aimed to provide evidence on the post-vaccination early side effects of the BBIBP-CorV (Sinopharm) vaccine. This cross-sectional survey-based study was conducted between November 2021 and January 2022 among recipients of the BBIBP-CorV vaccine, using a questionnaire-based survey. Our final sample consisted of 657 participants, including 392 women. Among the study cases, only 103 (15.7%) participants received one dose of vaccine, and the rest received both doses (N = 554, 84.3%). Systemic symptoms (first dose: N = 187, both doses: N = 128) were the most commonly reported events after vaccination, and among them, injection site pain (first dose: 19.3%, both doses: 12.9%) was the most prevalent adverse effect. All reporting events were mild and resolved in less than 3 days without hospitalization. Among the participants, females and young people aged 35-65 were more prone to manifest side effects (N = 169, 53.3%) after the vaccine injection. Furthermore, our results revealed that the recipients who were suffering from underlying diseases, including diabetes, renal disorder, and respiratory illness, reported fewer adverse responses after vaccination in comparison with healthy individuals. Vaccination against SARS-CoV-2 may lead to some adverse reactions in recipients. However, the frequency of post-vaccination early side effects differed in people, but all responses were slight and temporary.

Assessment of the impact of reopening strategies on the spatial transmission risk of COVID-19 based on a data-driven transmission model

COVID-19 has dramatically changed people's mobility geste patterns and affected the operations of different functional spots. In the environment of the successful reopening of countries around the world since 2022, it's pivotal to understand whether the reopening of different types of locales poses a threat of wide epidemic transmission. In this paper, by establishing an epidemiological model based on mobile network data, combining the data handed by the Safegraph website, and taking into account the crowd inflow characteristics and the changes of susceptible and latent populations, the trends of the number of crowd visits and the number of epidemic infections at different functional points of interest after the perpetration of continuing strategies were simulated. The model was also validated with daily new cases in ten metropolitan areas in the United States from March to May 2020, and the results showed that the model fitted the evolutionary trend of realistic data more accurately. Further, the points of interest were classified into risk levels, and the corresponding reopening minimum standard prevention and control measures were proposed to be implemented according to different risk levels. The results showed that restaurants and gyms became high-risk points of interest after the perpetration of the continuing strategy, especially the general dine-in restaurants were at higher risk levels. Religious exertion centers were the points of interest with the loftiest average infection rates after the perpetration of the continuing strategy. Points of interest such as convenience stores, large shopping malls, and pharmacies were at a lower risk for outbreak impact after the continuing strategy was enforced. Based on this, continuing forestallment and control strategies for different functional points of interest are proposed to provide decision support for the development of precise forestallment and control measures for different spots.

Facilitating COVID recognition from X-rays with computer vision models and transfer learning

Multimedia data plays an important role in medicine and healthcare since EHR (Electronic Health Records) entail complex images and videos for analyzing patient data. In this article, we hypothesize that transfer learning with computer vision can be adequately harnessed on such data, more specifically chest X-rays, to learn from a few images for assisting accurate, efficient recognition of COVID. While researchers have analyzed medical data (including COVID data) using computer vision models, the main contributions of our study entail the following. Firstly, we conduct transfer learning using a few images from publicly available big data on chest X-rays, suitably adapting computer vision models with data augmentation. Secondly, we aim to find the best fit models to solve this problem, adjusting the number of samples for training and validation to obtain the minimum number of samples with maximum accuracy. Thirdly, our results indicate that combining chest radiography with transfer learning has the potential to improve the accuracy and timeliness of radiological interpretations of COVID in a cost-effective manner. Finally, we outline applications of this work during COVID and its recovery phases with future issues for research and development. This research exemplifies the use of multimedia technology and machine learning in healthcare.

Comparison study of Beninese and Chinese herbal medicines in treating COVID-19

ETHNOPHARMACOLOGICAL RELEVANCE

The worldwide use of natural remedies is an alternative therapeutic solution to strengthen immunity, fight, and prevent this disease. The rapid spread of the coronavirus disease worldwide has promoted the search for therapeutic solutions following different approaches. China and Benin have seen the use of natural remedies such as Chinese herbal medicine and local endemic plants as alternative solutions in treating COVID-19.

AIM OF THE STUDY

The present study was designed to identify the prevalence of medicinal plant use in four municipalities of Benin most affected by COVID-19 and compare them with traditional Chinese medicine and finally verify the efficacy of the main components of the six plants most frequently used, via in vitro experiments.

MATERIALS AND METHODS

This study targeting market herbalists and traditional healers was conducted in the form of an ethnomedicinal survey in four representative communities (Cotonou, Abomey-Calavi, Zè, and Ouidah) of southern Benin. The chemical compositions of the six most commonly used herbs were investigated using network pharmacology. Network-based global prediction of disease genes and drug, target, function, and pathway enrichment analysis of the top six herbs was conducted using databases including IPA and visualised using Cytoscape software. The natural botanical drugs involved three medicines and three formulas used in the treatment of COVID-19 in China from the published literature were compared with the top six botanical drugs used in Benin to identify similarities between them and guide the clinical medication in both countries. Finally, the efficacy of the common ingredients in six plants was verified by measuring the viability of BEAS-2B cells and the release of inflammatory factors after administration of different ingredients. Binding abilities of six components to COVID-19 related targets were verified by molecular docking.

RESULTS

According to the medication survey investigation, the six most used herbs were Citrus aurantiifolia (13.18%), Momordica charantia (7.75%), Ocimum gratissimum (7.36%), Crateva adansonii (6.59%), Azadirachta indica (5.81%), and Zanthoxylum zanthoxyloides (5.42%). The most represented botanical families were Rutaceae, Lamiaceae, Cucurbitaceae, Meliaceae, and Capparaceae. The network pharmacology of these six herbal plants showed that the flavonoids quercetin, kaempferol, and β-sitosterol were the main active ingredients of the Benin herbal medicine. Chinese and Beninese herbal medicine are similar in that they have the same targets and pathways in inflammation and oxidative stress relief. Mild COVID-19-related targets come from C. aurantiifolia and M. charantia, and severe COVID-19-related targets come from A. indica A. Juss. Cell viability and enzyme-linked immunosorbent assay results confirmed that six major compounds could protect BEAS-2B cells against injury by inhibiting the expression of inflammatory factors, among which quercetin and isoimperatorin were more effective. Docking verified that the six compounds have good binding potential with COVID-19 related targets.

CONCLUSIONS

These results suggest that Benin herbal medicine and Chinese herbal medicine overlap in compounds, targets, and pathways to a certain extent. Among the commonly used plants in Benin, C. aurantiifolia and M. charantia may have a good curative effect on the treatment of mild COVID-19, while for severe COVID-19, A. indica can be added on this basis.

Efficacy and safety of human umbilical cord-derived mesenchymal stem cells for COVID-19 pneumonia: a meta-analysis of randomized controlled trials

BACKGROUND

Elevated levels of inflammatory factors are associated with poor prognosis in coronavirus disease-19 (COVID-19). However, mesenchymal stem cells (MSCs) have immunomodulatory functions. Accordingly, this meta-analysis aimed to determine the efficacy and safety of MSC-based therapy in patients with COVID-19 pneumonia.

METHODS

Online global databases were used to find relevant studies. Two independent researchers then selected and evaluated the studies for suitability while the Cochrane risk of bias tool determined the quality of all articles and Cochran's Q test and I² index assessed the degree of heterogeneity in the principal studies. Statistical analysis was performed using Review Manager software, and the effect of each study on the overall estimate was evaluated by sensitivity analysis.

RESULTS

Seven studies were included in the meta-analysis, and all MSCs used in the trials were acquired from the umbilical cord. The results of these studies (n = 328) indicated that patients with COVID-19 pneumonia who received MSCs had a 0.58 risk of death compared with controls (95% CI = 0.38, 0.87; P = 0.53; I² = 0%). In terms of inflammatory biomarkers, MSCs reduced the levels of C-reactive protein (n = 88; MD =  - 32.49; 95% CI =  - 48.43, - 16.56; P = 0.46; I² = 0%) and interferon-gamma (n = 44; SMD =  - 1.23; 95% CI =  - 1.89, - 0.57; P = 0.37; I² = 0%) in severe COVID-19 patients but had no significant effect on interleukin-6 (n = 185; MD =  - 0.75; 95% CI =  - 7.76, 6.27; P = 0.57; I² = 0%). A summary of the data revealed no significant differences in adverse events (n = 287) or serious adverse events (n = 229) between the MSC and control groups.

CONCLUSIONS

Infusion of umbilical cord-derived MSCs is an effective strategy for treating patients with COVID-19 pneumonia, with no noticeable adverse effects.

Two Resveratrol Oligomers Inhibit Cathepsin L Activity to Suppress SARS-CoV-2 Entry

Cell entry of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) depends on specific host cell proteases, which are the key targets for preventing and treating viral infections. Herein, we describe miyabenol C and trans-ε-viniferin, two resveratrol oligomers that specifically inhibit SARS-CoV-2 entry by targeting host protease cathepsin L. Several cell-based assays were used to demonstrate the effect of resveratrol oligomers, and their target was identified via screening of antiviral targets. Molecular docking analysis suggested that the oligomers could occupy the active cavity of cathepsin L. The surface plasmon resonance assay showed that the equilibrium dissociation constant (KD) values of miyabenol C-cathepsin L and trans-ε-viniferin-cathepsin L were 5.54 and 8.54 μM, respectively, indicating their excellent binding ability for cathepsin L. Our study demonstrated the potential application of resveratrol oligomers as lead compounds in controlling SARS-CoV-2 infection by targeting cathepsin L.

A Review of the Mental Health Sequelae of the SARS-CoV-2 (COVID-19): Preparedness Perspective

Despite the three significant epidemics that have rattled the world in the last two decades, many questions remain unanswered! The concept of unwanted psychological distress remains looming after any epidemic or pandemic. The public health burden of the COVID-19 pandemic still resonates with different aspects of life with predicted mental health sequelae. This review will focus on the role of natural disasters and past infectious epidemic-related mental health complications. Additionally, the study provides recommendations and policy suggestions for mitigating COVID-19-related mental health prevalence.

Consequences of COVID-19 Among Adult HIV Patients Versus Non-HIV Patients: Two-Year Data From the Primary Isolation Centre in Sudan

Background The COVID-19 pandemic remains to have a global impact despite the great efforts in prevention. Controversy persists regarding the outcomes of SARS-CoV-2 among HIV patients versus non-HIV individuals. Objective This study aimed to assess the impact of COVID-19 among adult patients with HIV versus non-HIV in the chief isolation centre in Khartoum state, Sudan. Methods This is an analytical cross-sectional, comparative single-centre study conducted at the Chief Sudanese Coronavirus Isolation Centre in Khartoum from March 2020 to July 2022. Data were analysed using SPSS V.26 (IBM Corp., Armonk, USA). Results This study included 99 participants. The overall age mean was 50±1 years old, with a male predominance of 66.7% (n=66). 9.1% (n=9) of the participants were HIV cases, 33.3% of whom were newly diagnosed. The majority, 77.8%, reported poor adherence to anti-retroviral therapy. The most common complications included acute respiratory failure (ARF) and multiple organ failure, 20.2% and 17.2%, respectively. The overall complications were higher among HIV cases than non-HIV cases; however, statistically insignificant (p>0.05 ), except for acute respiratory failure (p<0.05). 48.5% of participants were admitted to the intensive care unit (ICU), with slightly higher rates among HIV cases; however, this was statistically insignificant (p=0.656). Regarding the outcome, 36.4% (n=36) recovered and were discharged. Although a higher mortality rate was reported among HIV cases compared to non-HIV cases (55% vs 40%), it was statistically insignificant (p=0.238). Conclusion The mortality and morbidity percent proportion among HIV patients with superimposed COVID-19 infection was higher than in non-HIV patients but statistically insignificant aside from ARF. Consequently, this category of patients, to a large extent, should not be considered highly susceptible to adverse outcomes when infected with COVID-19; however, ARF should be closely monitored for.

On the contact tracing for COVID-19: A simulation study☆

Background:

Contact tracing is one of the most effective non-pharmaceutical interventions in the COVID-19 pandemic. This study uses a multi-agent model to investigate the impact of four types of contact tracing strategies to prevent the spread of COVID-19.

Methods:

In order to analyse individual contact tracing in a reasonably realistic setup, we construct an agent-based model of a small municipality with about 60.000 inhabitants (nodes) and about 2.8 million social contacts (edges) in 30 different layers. Those layers reflect demographic, geographic, sociological and other patterns of the TTWA (Travel-to-work-area) Hodonín in Czechia. Various data sources such as census, land register, transport data or data reflecting the shopping behaviour, were employed to meet this purpose. On this multi-graph structure we run a modified SEIR model of the COVID-19 dynamics. The parameters of the model are calibrated on data from the outbreak in the Czech Republic in the period March to June 2020. The simplest type of contact tracing follows just the family, the second tracing version tracks the family and all the work contacts, the third type finds all contacts with the family, work contacts and friends (leisure activities). The last one is a complete (digital) tracing capable of recalling any and all contacts.

We evaluate the performance of these contact tracing strategies in four different environments. First, we consider an environment without any contact restrictions (benchmark); second with strict contact restriction (replicating the stringent non-pharmaceutical interventions employed in Czechia in the spring 2020); third environment, where the measures were substantially relaxed, and, finally an environment with weak contact restrictions and superspreader events (replicating the situation in Czechia in the summer 2020).

Findings:

There are four main findings in our paper. 1. In general, local closures are more effective than any type of tracing. 2. In an environment with strict contact restrictions there are only small differences among the four contact tracing strategies. 3. In an environment with relaxed contact restrictions the effectiveness of the tracing strategies differs substantially. 4. In the presence of superspreader events only complete contact tracing can stop the epidemic.

Interpretation:

In situations, where many other non-pharmaceutical interventions are in place, the specific extent of contact tracing may not have a large influence on their effectiveness. In a more relaxed setting with few contact restrictions and larger events the effectiveness of contact tracing depends heavily on their extent.

Development of a multiplex qRT-PCR assay for the detection of porcine epidemic diarrhea virus, porcine transmissible gastroenteritis virus and porcine Deltacoronavirus

Currently, porcine coronaviruses are prevalent in pigs, and due to the outbreak of COVID-19, porcine coronaviruses have become a research hotspot. porcine epidemic diarrhea virus (PEDV), Transmissible Gastroenteritis Virus (TGEV), and Porcine Deltacoronavirus (PDCoV) mentioned in this study mainly cause diarrhea in pigs. These viruses cause significant economic losses and pose a potential public health threat. In this study, specific primers and probes were designed according to the M gene of PEDV, the S gene of TGEV, and the M gene of PDCoV, respectively, and TaqMan probe-based multiplex real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was developed for the simultaneous detection of PEDV, TGEV, and PDCoV. This method has high sensitivity and specificity, and the detection limit of each virus can reach 2.95 × 100 copies/μl. An assay of 160 clinical samples from pigs with diarrhea showed that the positive rates of PEDV, TGEV, and PDCoV were 38.13, 1.88, and 5.00%; the coinfection rates of PEDV+TGEV, PEDV+PDCoV, TGEV+PDCoV, PEDV+TGEV+PDCoV were 1.25, 1.25, 0, 0.63%, respectively. The positive coincidence rates of the multiplex qRT-PCR and single-reaction qRT-PCR were 100%. This method is of great significance for clinical monitoring of the porcine enteric diarrhea virus and helps reduce the loss of the breeding industry and control the spread of the disease.

Risk factors and digital interventions for anxiety disorders in college students: Stakeholder perspectives

The worldwide prevalence of anxiety disorders among college students is high, which negatively affects countries, schools, families, and individual students to varying degrees. This paper reviews the relevant literature regarding risk factors and digital interventions for anxiety disorders among college students from the perspectives of different stakeholders. Risk factors at the national and societal levels include class differences and the coronavirus disease 2019 pandemic. College-level risk factors include the indoor environment design of the college environment, peer relationships, student satisfaction with college culture, and school functional levels. Family-level risk factors include parenting style, family relationship, and parental level of education. Individual-level risk factors include biological factors, lifestyle, and personality. Among the intervention options for college students' anxiety disorders, in addition to traditional cognitive behavioral therapy, mindfulness-based interventions, psychological counseling, and group counseling, digital mental health interventions are increasingly popular due to their low cost, positive effect, and convenient diagnostics and treatment. To better apply digital intervention to the prevention and treatment of college students' anxiety, this paper suggests that the different stakeholders form a synergy among themselves. The nation and society should provide necessary policy guarantees, financial support, and moral and ethical supervision for the prevention and treatment of college students' anxiety disorders. Colleges should actively participate in the screening and intervention of college students' anxiety disorders. Families should increase their awareness of college students' anxiety disorders and take the initiative to study and understand various digital intervention methods. College students with anxiety disorders should actively seek psychological assistance and actively accept and participate in digital intervention projects and services. We believe that in the future, the application of methods such as big data and artificial intelligence to improve digital interventions and provide individualized treatment plans will become the primary means of preventing and treating anxiety disorders among college students.

Using space-time scan statistic for studying the effects of COVID-19 in Punjab, Pakistan: a guideline for policy measures in regional agriculture

Pakistan is included in top 50 countries which are estimated to face serious agriculture and food deficiency related challenges due to the worldwide pandemic coronavirus 2019 (COVID-19). The aim of this study was to evaluate the effects of COVID-19 on food supply chain and agriculture in Punjab, Pakistan, by using space-time scan statistic (STSS). A survey was conducted at 720 points in different districts of the province. The STSS detected "active" and emerging clusters that are current at the end of our study area-particularly, 17 clusters were formed while adding the updated case data. Software ArcGIS 10.3 was used to find relative risk (RR) values; the maximum RR value was found to be 42.19 and maximum observed cases 53,265 during June 15-July 1, 2020. It was not always necessary that if the number of active cases in Punjab increased, there should be higher relative risk for more number of districts and vice versa. Due to the highest number of cases of COVID-19 and RR values during July, mostly farmers faced many difficulties during the cultivation of cotton and rice. Mostly farmers (72%) observed increase in prices of inputs (fertilizers and pesticides) during lockdown. If the supply chain of agriculture related inputs is disturbed, farmers may find it quite difficult to access markets, which could result in a decline in production and sales of crops and livestock in study area. It is suggested that to protect the food security and to decrease the effect of the lockdown, Punjab government needs to review food policy and analyse how market forces will respond to the imbalanced storage facilities and capacity, supply and demand and price control of products. The findings of this study can also help policy-makers to formulate an effective food security and agriculture adaptation strategy.

Interactions between Humans and Dogs during the COVID-19 Pandemic: Recent Updates and Future Perspectives

COVID-19 is one of the deadliest epidemics. This pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the role of dogs in spreading the disease in human society is poorly understood. This review sheds light on the limited susceptibility of dogs to COVID-19 infections which is likely attributed to the relatively low levels of angiotensin-converting enzyme 2 (ACE2) in the respiratory tract and the phylogenetic distance of ACE2 in dogs from the human ACE2 receptor. The low levels of ACE2 affect the binding affinity between spike and ACE2 proteins resulting in it being uncommon for dogs to spread the disease. To demonstrate the role of dogs in spreading COVID-19, we reviewed the epidemiological studies and prevalence of SARS-CoV-2 in dogs. Additionally, we discussed the use of detection dogs as a rapid and reliable method for effectively discriminating between SARS-CoV-2 infected and non-infected individuals using different types of samples (secretions, saliva, and sweat). We considered the available information on COVID-19 in the human-dog interfaces involving the possibility of transmission of COVID-19 to dogs by infected individuals and vice versa, the human-dog behavior changes, and the importance of preventive measures because the risk of transmission by domestic dogs remains a concern.

Does COVID-19 infection increase the risk of pulmonary embolism in ambulatory patients with deep vein thrombosis

OBJECTIVES

Coronavirus disease 2019 (COVID-19) can lead to systemic coagulation activation and thrombotic complications including venous thromboembolism. This study compares the development of pulmonary embolism, post-thrombotic syndrome, and clinical outcomes of COVID-19 and non-COVID-19 patients with deep vein thrombosis (DVT).

METHODS

One hundred and eight patients diagnosed with acute deep vein thrombosis (DVT) between June 2020 and February 2021 in our institution were included in this retrospective study. Thirty-nine patients had been previously diagnosed with COVID-19 and specified as the COVID-19 group. Sixty-nine patients did not have COVID-19 and specified as the non-COVID-19 group. Mean ages of both groups were 64.3 ± 15.8 and 60.1 ± 19.7 years, respectively (p = .37).

RESULTS

The median duration from the onset of the COVID-19 to diagnosis of DVT was 22 (2-120) days in the COVID-19 group. The patients of two groups were mostly treated outpatient at rates of 94.9% vs 94.2%, respectively (p = .88). Pulmonary embolism was seen in six patients (15.4%) in the COVID-19 group and in three patients (4.3%) in the non-COVID-19 group (p = .04). Kaplan-Meir curves showed that patients with COVİD-19 had significantly higher pulmonary embolism than those without COVID-19 (p = .015). The recurrence rate of DVT was 2.6% in the COVID-19 group (n = 1), and 4.3% in the non-COVID-19 group (n = 3), indicating no statistically significant difference (p = .63). Mortality was seen in six patients (15.4%) in the COVİD-19 group, and in seven patients (10.1%) in the non-COVID-19 group. According to the Kaplan-Meir method, 10 months survival rates were 73.9 ± 10% in the COVID-19 group, and 66.3 ± 12.8% in the non-COVID-19 group with no statistical significance (p = .218).

CONCLUSIONS

Our data draw attention to the fact that deep vein thrombosis should not be considered a safe and self-limited condition. Efficient preventive measures such as mobilization and prophylactic drug use should be considered to prevent DVT during the management of COVID-19.

Early Genomic Surveillance and Phylogeographic Analysis of Getah Virus, a Reemerging Arbovirus, in Livestock in China

Getah virus (GETV) mainly causes disease in livestock and may pose an epidemic risk due to its expanding host range and the potential of long-distance dispersal through animal trade. Here, we used metagenomic next-generation sequencing (mNGS) to identify GETV as the pathogen responsible for reemerging swine disease in China and subsequently estimated key epidemiological parameters using phylodynamic and spatially-explicit phylogeographic approaches. The GETV isolates were able to replicate in a variety of cell lines, including human cells, and showed high pathogenicity in a mouse model, suggesting the potential for more mammal hosts. We obtained 16 complete genomes and 79 E2 gene sequences from viral strains collected in China from 2016 to 2021 through large-scale surveillance among livestock, pets, and mosquitoes. Our phylogenetic analysis revealed that three major GETV lineages are responsible for the current epidemic in livestock in China. We identified three potential positively selected sites and mutations of interest in E2, which may impact the transmissibility and pathogenicity of the virus. Phylodynamic inference of the GETV demographic dynamics identified an association between livestock meat consumption and the evolution of viral genetic diversity. Finally, phylogeographic reconstruction of GETV dispersal indicated that the sampled lineages have preferentially circulated within areas associated with relatively higher mean annual temperature and pig population density. Our results highlight the importance of continuous surveillance of GETV among livestock in southern Chinese regions associated with relatively high temperatures. IMPORTANCE Although livestock is known to be the primary reservoir of Getah virus (GETV) in Asian countries, where identification is largely based on serology, the evolutionary history and spatial epidemiology of GETV in these regions remain largely unknown. Through our sequencing efforts, we provided robust support for lineage delineation of GETV and identified three major lineages that are responsible for the current epidemic in livestock in China. We further analyzed genomic and epidemiological data to reconstruct the recent demographic and dispersal history of GETV in domestic animals in China and to explore the impact of environmental factors on its genetic diversity and its diffusion. Notably, except for livestock meat consumption, other pig-related factors such as the evolution of live pig transport and pork production do not show a significant association with the evolution of viral genetic diversity, pointing out that further studies should investigate the potential contribution of other host species to the GETV outbreak. Our analysis of GETV demonstrates the need for wider animal species surveillance and provides a baseline for future studies of the molecular epidemiology and early warning of emerging arboviruses in China.

Aspects of Nanotechnology for COVID-19 Vaccine Development and Its Delivery Applications

Coronavirus, a causative agent of the common cold to a much more complicated disease such as "severe acute respiratory syndrome (SARS-CoV-2), Middle East Respiratory Syndrome (MERS-CoV-2), and Coronavirus Disease 2019 (COVID-19)", is a member of the coronaviridae family and contains a positive-sense single-stranded RNA of 26-32 kilobase pairs. COVID-19 has shown very high mortality and morbidity and imparted a significantly impacted socioeconomic status. There are many variants of SARS-CoV-2 that have originated from the mutation of the genetic material of the original coronavirus. This has raised the demand for efficient treatment/therapy to manage newly emerged SARS-CoV-2 infections successfully. However, different types of vaccines have been developed and administered to patients but need more attention because COVID-19 is not under complete control. In this article, currently developed nanotechnology-based vaccines are explored, such as inactivated virus vaccines, mRNA-based vaccines, DNA-based vaccines, S-protein-based vaccines, virus-vectored vaccines, etc. One of the important aspects of vaccines is their administration inside the host body wherein nanotechnology can play a very crucial role. Currently, more than 26 nanotechnology-based COVID-19 vaccine candidates are in various phases of clinical trials. Nanotechnology is one of the growing fields in drug discovery and drug delivery that can also be used for the tackling of coronavirus. Nanotechnology can be used in various ways to design and develop tools and strategies for detection, diagnosis, and therapeutic and vaccine development to protect against COVID-19. The design of instruments for speedy, precise, and sensitive diagnosis, the fabrication of potent sanitizers, the delivery of extracellular antigenic components or mRNA-based vaccines into human tissues, and the administration of antiretroviral medicines into the organism are nanotechnology-based strategies for COVID-19 management. Herein, we discuss the application of nanotechnology in COVID-19 vaccine development and the challenges and opportunities in this approach.

The emotional well-being of Long COVID patients in relation to their symptoms, social support and stigmatization in social and health services: a qualitative study

BACKGROUND

Long COVID patients have experienced a decline in their quality of life due to, in part but not wholly, its negative emotional impact. Some of the most prevalent mental health symptoms presented by long COVID patients are anxiety, depression, and sleep disorders. As such, the need has arisen to analyze the personal experiences of these patients to understand how they are managing their daily lives while dealing with the condition. The objective of this study is to increase understanding about the emotional well-being of people diagnosed with long COVID.

METHODS

A qualitative design was created and carried out using 35 patients, with 17 participants being interviewed individually and 18 of them taking part in two focus groups. The participating patients were recruited in November and December 2021 from Primary Health Care (PHC) centers in the city of Zaragoza (Northern Spain) and from the Association of Long COVID Patients in Aragon. The study topics were emotional well-being, social support networks, and experience of discrimination. All an inductive thematic content analyses were performed iteratively using NVivo software.

RESULTS

The Long COVID patients identified low levels of self-perceived well-being due to their persistent symptoms, as well as limitations in their daily lives that had been persistent for many months. Suicidal thoughts were also mentioned by several patients. They referred to anguish and anxiety about the future as well as a fear of reinfection or relapse and returning to work. Many of the participants reported that they have sought the help of a mental health professional. Most participants identified discriminatory situations in health care.

CONCLUSIONS

It is necessary to continue researching the impact that Long COVID has had on mental health, as well as to provide Primary Health Care professionals with evidence that can guide the emotional treatment of these patients.

Recombinant Protein Vaccines against Human Betacoronaviruses: Strategies, Approaches and Progress

Betacoronaviruses have already troubled humanity more than once. In 2002-2003 and 2012, the SARS-CoV and MERS-CoV, respectively, caused outbreaks of respiratory syndromes with a fatal outcome. The spread of the SARS-CoV-2 coronavirus has become a pandemic. These three coronaviruses belong to the genus Betacoronavirus and have a zoonotic origin. The emergence of new coronavirus infections in the future cannot be ruled out, and vaccination is the main way to prevent the spread of the infection. Previous experience in the development of vaccines against SARS and MERS has helped to develop a number of vaccines against SARS-CoV-2 in a fairly short time. Among them, there are quite a few recombinant protein vaccines, which seem to be very promising in terms of safety, minimization of side effects, storage and transportation conditions. The problem of developing a universal betacoronavirus vaccine is also still relevant. Here, we summarize the information on the designing of vaccines based on recombinant proteins against highly pathogenic human betacoronaviruses SARS-CoV, MERS-CoV and SARS-CoV-2.

Taste loss as a distinct symptom of COVID-19: a systematic review and meta-analysis

Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19 taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020-2021, with 235 meeting all inclusion criteria. Drawing on previous studies and guided by early meta-analyses, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct measures of taste are at least as sensitive as those obtained by self-report and that the preponderance of evidence confirms taste loss is a symptom of COVID-19. The meta-analysis showed that, among 138,015 COVID-19-positive patients, 36.62% reported taste dysfunction (95% confidence interval: 33.02%-40.39%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 15) versus self-report (n = 220) methodologies (Q = 1.73, df = 1, P = 0.1889). Generally, males reported lower rates of taste loss than did females, and taste loss was highest among middle-aged adults. Thus, taste loss is likely a bona fide symptom of COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms.

Recent advances of nanotechnology in COVID 19: A critical review and future perspective

The global anxiety and economic crisis causes the deadly pandemic coronavirus disease of 2019 (COVID 19) affect millions of people right now. Subsequently, this life threatened viral disease is caused due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, morbidity and mortality of infected patients are due to cytokines storm syndrome associated with lung injury and multiorgan failure caused by COVID 19. Thereafter, several methodological advances have been approved by WHO and US-FDA for the detection, diagnosis and control of this wide spreadable communicable disease but still facing multi-challenges to control. Herein, we majorly emphasize the current trends and future perspectives of nano-medicinal based approaches for the delivery of anti-COVID 19 therapeutic moieties. Interestingly, Nanoparticles (NPs) loaded with drug molecules or vaccines resemble morphological features of SARS-CoV-2 in their size (60–140 nm) and shape (circular or spherical) that particularly mimics the virus facilitating strong interaction between them. Indeed, the delivery of anti-COVID 19 cargos via a nanoparticle such as Lipidic nanoparticles, Polymeric nanoparticles, Metallic nanoparticles, and Multi-functionalized nanoparticles to overcome the drawbacks of conventional approaches, specifying the site-specific targeting with reduced drug loading and toxicities, exhibit their immense potential. Additionally, nano-technological based drug delivery with their peculiar characteristics of having low immunogenicity, tunable drug release, multidrug delivery, higher selectivity and specificity, higher efficacy and tolerability switch on the novel pathway for the prevention and treatment of COVID 19.

A clinical case of coinfection of COVID-19 and tropical malaria

   The global outbreak of the new coronavirus infection COVID-19 is still ongoing, leading to coinfections such as malaria and COVID-19 and others. As evidenced by the increase in various reports of coinfections. In recent years, Uzbekistan has achieved epidemiological stability for malaria and in 2018 received an official World Health Organization certificate confirming the country’s “malaria-free” status. At the present stage during the COVID-19 pandemic, imported malaria from abroad is relevant for our republic and, therefore, there is a constant danger of renewed transmission from imported cases. In this article presented the clinical case of coinfection of COVID-19 and malaria in a patient. From the epidemiological data, the patient was a citizen of Cameroon. During treatment of coronavirus infection, the patient noted intermittent chills all over the body and sweating, clinical symptoms of tropical malaria began to appear. Microscopy of a thick drop and a thin blood smear confirmed the presence of Pl. falciparum. The patient was prescribed antimalarial therapy with mefloquine, resulting in clinical recovery.

[Seroprevalence of anti-SARS-CoV-2 IgG antibodies in resident physicians]

Background

COVID-19 pandemic spread around the world swiftly; there are several diagnostic strategies available. Health workers, especially medical residents (MR), are a high-risk population for acquiring this infection.

Objective

To estimate the seroprevalence of antibodies against SARS-CoV-2 and the associated factors in MR of a third level hospital.

Material and methods

330 MR from different specialties were evaluated with a questionnaire and collection of blood samples for analysis by microparticle chemiluminescent immunoassay. The prevalence of previous infection was defined by seropositivity of these antibodies. Descriptive statistics and concordance between the RT-PCR tests and the presence of anti-SARS-CoV-2 IgG were used.

Results

Of 330 MR, 84.5% actively participated in COVID patient care. One out of 3 reported symptoms of COVID-19; in 67.6% the possible site of infection was a hospital setting not associated with the COVID area. Out of 71 symptomatic subjects, 61.9% underwent RT-PCR against SARS-CoV-2; 20 were positive. In 15.8% of the total, the presence of anti-SARS-CoV-2 IgG antibodies was determined. Only 1 out of 3 subjects with a positive PCR had antibodies, and 11.3% of the cases, even with a positive RT-PCR test, did not develop humoral immunity.

Conclusions

The seroprevalence was lower than that reported at the national level, potentially due to protection measures. The main risk factor was contact with the virus in areas of the hospital not related to COVID, making it imperative to reinforce security protocols in those spaces.

[PCR for COVID in the transplant protocol]

Background

Since the beginning of the SARS-CoV-2 pandemic, identifying the COVID-19 pathophysiology not only has been addressed to applying diagnostic tests or preventing through vaccines, but also to the timely detection, especially of patients in risk groups such as those in transplants areas (renal, hematology, etcetera). In the case of these patients, using RT-PCR tests avoids putting them at risk by subjecting them to states of immunosuppression that could aggravate their situation if they were faced with an onset of a COVID-19 infection.

Objective

To present the results of patients of a transplant unit tested for SARS-CoV-2.

Material and methods

Descriptive, observational, cross-sectional, and retrolective study. Data of results of RT-PCR tests of patients who underwent transplantation from June 2021 to April 2022 in a third level hospital were collected.

Results

755 tests were done to patients who underwent transplantation. 384 (50.8%) were women. Out of all patients, only 73 (9.7%) were positive to SARS-CoV-2.

Conclusions

Implementing RT-PCR tests as a transplant protocol to detect SARS-CoV-2 prevents fatal complications due to COVID infection to donors and receptors.

Numerical simulations on scale-free and random networks for the spread of COVID-19 in Pakistan☆

Epidemiology is the study of how and why an infectious disease occurs in a group of people. Several epidemiological models have been developed to get information on the spread of a disease in society. That information is used to plan strategies to prevent illness and manage patients. But, most of these models consider only random diffusion of the disease and hence ignore the number of interactions among people. To take into account the interactions among individuals, the network approach is becoming increasingly popular. It is novel to consider the dynamics of infectious disease using various networks rather than classical differential equation models. In this paper, we numerically simulate the Susceptible-Infected-Recoverd (SIR) model on Barabási-Albert network and Erdös-Rényi network to analyze the spread of COVID-19 in Pakistan so that we know the severity of the disease. We also show how a situation becomes alarming if hubs in a network get infected.

Clinical characterization and factors associated with quality of life in Long COVID patients: Secondary data analysis from a randomized clinical trial

BACKGROUND

Long COVID patients suffer a negative impact on their quality of life, as well as their functioning, productivity or socialization. There is a need to better understand the individual experience and circumstances surrounding these patients.

OBJECTIVE

To characterize clinical picture of Long COVID patients and to identify factors associated with quality of life.

METHODS

A secondary data analysis from a randomized clinical trial (RCT) was carried out with 100 Long COVID patients treated by Primary Health Care and residents in the territory of Aragon (northeast of Spain). The main variable of the study was quality of life, evaluated using the SF-36 Questionnaire, in relation to socio-demographic and clinical variables. In addition, ten validated scales were used that contemplated their cognitive, affective, functional and social status, as well as personal constructs. Correlation statistics and linear regression model were calculated.

RESULTS

Long COVID patients suffer a decrease in their levels of physical and mental health. On the one hand, the higher number of persistent symptoms (b = -0.900, p = 0.008), worse physical functioning (b = 1.587, p = 0.002) and sleep quality (b = -0.538, p = 0.035) are predictors of worse quality of life, physical subscale. On the other hand, higher educational level (b = 13.167, p = 0.017), lower number of persistent symptoms (b = -0.621, p = 0.057) and higher affective affectation (b = -1.402, p<0.001) are predictors of worse quality of life, mental subscale.

CONCLUSION

It is necessary to design rehabilitation programs that consider both the physical and mental health of these patients, thus obtaining an improvement in their quality of life.

Quantitative evaluation of the role of Fangcang shelter hospitals in the control of Omicron transmission: A case study of the outbreak in Shanghai, China in 2022

Since Omicron began to spread in China, Shanghai has become one of the cities with more severe outbreaks. Under the comprehensive consideration of the vaccine coverage rate, the number of Fangcang shelter hospital beds and the number of designated hospital beds in Shanghai, this paper established a deterministic compartmental model and used the Nelder-Mead Simplex Direct Search Algorithm and chi-square values to estimate the model parameters. we calculate ℛ₀ = 3.6429 when the number of beds in the Fangcang shelter hospital is relatively tight in the second stage and ℛ₀ = 0.4974 in the fifth stage when there are enough beds in both Fangcang shelter hospital and designated hospital. Then we perform a sensitivity analysis on ℛ₀ by using perturbation of fixed point estimation of model parameters in the fifth stage, and obtain three parameters that are more sensitive to ℛ₀, which are transmission rate (β _1d ), proportion of the infectious (η) and the hospitalization rate of asymptomatic infected cases (δ ₁). Through simulation, we obtain that if the hospitalization rate of asymptomatic infections δ ₂ > 0.9373 or the transmission rate β _1b  < 0.0467, the second stage of Omicron transmission in Shanghai can be well controlled. Finally, we find the measure that converting the National Convention and Exhibition Center (NECC) into a Fangcang shelter hospital has played an important role in curbing the epidemic. Whether this temporary Fangcang shelter hospital is not built or delayed, the cumulative number of confirmed cases will both exceed 100,000, and the cumulative asymptomatic infections will both exceed 1 million. In addition, for a city of 10 million people, we obtain that if a permanent Fangcang shelter hospital with 17,784 beds is built ahead of epidemic, there will be no shortage of beds during the outbreak of Omicron. Our findings enrich the content of the impact of Fangcang shelter hospital beds on the spread of Omicron and confirm the correct policy adopted by the Chinese government.

Understanding travel behavior adjustment under COVID-19

The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system. By analyzing the impact of the pandemic on the transportation system, the impact of the pandemic on the social economy can be reflected to a certain extent, and the effect of anti-pandemic policy implementation can also be evaluated. In addition, the analysis results are expected to provide support for policy optimization. Currently, most of the relevant studies analyze the impact of the pandemic on the overall transportation system from the macro perspective, while few studies quantitatively analyze the impact of the pandemic on individual spatiotemporal travel behavior. Based on the license plate recognition (LPR) data, this paper analyzes the spatiotemporal travel patterns of travelers in each stage of the pandemic progress, quantifies the change of travelers' spatiotemporal behaviors, and analyzes the adjustment of travelers' behaviors under the influence of the pandemic. There are three different behavior adjustment strategies under the influence of the pandemic, and the behavior adjustment is related to the individual's past travel habits. The paper quantitatively assesses the impact of the COVID-19 pandemic on individual travel behavior. And the method proposed in this paper can be used to quantitatively assess the impact of any long-term emergency on individual micro travel behavior.

Nanomedicine approaches to reduce cytokine storms in severe infections

During a cytokine storm, dysregulated proinflammatory cytokines are produced in excess. Cytokine storms occur in multiple infectious diseases, including Coronavirus 2019 (COVID-19). Thus, eliminating cytokine storms to enhance patient outcomes is crucial. Given the numerous cytokines involved, individual therapies might have little effect. Traditional cytokines might be less effective than medicines that target malfunctioning macrophages. Nanomedicine-based therapeutics reduce cytokine production in animal models of proinflammatory illnesses. The unique physicochemical features and controlled nano-bio interactions of nanotechnology show promise in healthcare and could be used to treat several stages of this virus-induced sickness, including cytokine storm mortality. Macrophage-oriented nanomedicines can minimize cytokine storms and associated harmful effects, enhancing patient outcomes. Here, we also discuss engineering possibilities for enhancing macrophage efficacy with nanodrug carriers.

Effects of climate variables on the COVID-19 mortality in Bangladesh

Infectious diseases such as severe acute respiratory syndrome (SARS) and influenza are influenced by weather conditions. Climate variables, for example, temperature and humidity, are two important factors in the severity of COVID-19's impact on the human respiratory system. This study aims to examine the effects of these climate variables on COVID-19 mortality. The data are collected from March 08, 2020, to April 30, 2022. The parametric regression under GAM and semiparametric regression under GAMLSS frameworks are used to analyze the daily number of death due to COVID-19. Our findings revealed that temperature and relative humidity are commencing to daily deaths due to COVID-19. A positive association with COVID-19 daily death counts was observed for temperature range and a positive association for humidity. In addition, one-unit increase in daily temperature range was only associated with a 1.08% (95% CI: 1.06%, 1.10%), and humidity range was only associated with a 1.03% (95% CI: 1.02%, 1.03%) decrease in COVID-19 deaths. A flexible regression model within the framework of Generalized Additive Models for Location Scale and Shape is used to analyze the data by adjusting the time effect. We used two adaptable predictor models, such as (i) the Fractional polynomial model and (ii) the B-spline smoothing model, to estimate the systematic component of the GAMLSS model. According to both models, high humidity and temperature significantly (and drastically) lessened the severity of COVID-19 death. The findings on the epidemiological trends of the COVID-19 pandemic and weather changes may interest policymakers and health officials.

Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic

This work systematically conducts a data analysis based on the numbers of both cumulative and daily confirmed COVID-19 cases and deaths in a time span through April 2020 to June 2022 for over 200 countries around the world. Such research feature aims to reveal the temporal and spatial evolution of the country-level distribution observed in COVID-19 pandemic, and obtains some interesting results as follows. (1) The distributions of the numbers for cumulative confirmed cases and deaths obey power-law in early stages of COVID-19 and stretched exponential function in subsequent course. (2) The distributions of the numbers for daily confirmed cases and deaths obey power-law in early and late stages of COVID-19 and stretched exponential function in middle stages. The crossover region between power-law and stretched exponential behavior seems to depend on the evolution of "infection" event and "death" event. Such observation implies a kind of important symmetry related to the dynamics process of COVID-19 spreading. (3) The distributions of the normalized numbers for each metric show a temporal scaling behavior in 2-year period, and are well described by stretched exponential function. The observation of power-law and stretched exponential behavior in such country-level distributions suggests underlying intrinsic dynamics of a virus spreading process in human interconnected society. And thus it is important for understanding and mathematically modeling the COVID-19 pandemic.