Epidemiological and clinical features of the 2019 novel coronavirus outbreak in China.. [PMID: 0 DOI: 10.1101/2020.02.10.20021675]

COVID-19: Recent Insight in Genomic Feature, Pathogenesis, Immunological Biomarkers, Treatment Options and Clinical Updates on SARS-CoV-2

SARS-CoV-2 is a highly contagious and transmissible viral infection that first emerged in 2019 and since then has sparked an epidemic of severe respiratory problems identified as "coronavirus disease 2019" (COVID-19) that causes a hazard to human life and safety. The virus developed mainly from bats. The current epidemic has presented a significant warning to life across the world by showing mutation. There are different tests available for testing Coronavirus, and RT-PCR is the best, giving more accurate results, but it is also time-consuming. There are different options available for treating n-CoV-19, which include medications such as Remdesivir, corticosteroids, plasma therapy, Dexamethasone therapy, etc. The development of vaccines such as BNT126b2, ChAdOX1, mRNA-1273 and BBIBP-CorV has provided great relief in dealing with the virus as they decreased the mortality rate. BNT126b2 and ChAdOX1 are two n-CoV vaccines found to be most effective in controlling the spread of infection. In the future, nanotechnology-based vaccines and immune engineering techniques can be helpful for further research on Coronavirus and treatment of this deadly virus. The existing knowledge about the existence of SARS-CoV-2, along with its variants, is summarized in this review. This review, based on recently published findings, presents the core genetics of COVID-19, including heritable characteristics, pathogenesis, immunological biomarkers, treatment options and clinical updates on the virus, along with patents.

Quantitative Computed Tomography Lung COVID Scores with Laboratory Markers: Utilization to Predict Rapid Progression and Monitor Longitudinal Changes in Patients with Coronavirus 2019 (COVID-19) Pneumonia

Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.

COVID-19 induced ischemic stroke and mechanisms of viral entry in brain and clot formation: a systematic review and current update

Background: Coronavirus disease 2019, caused by SARS-CoV-2 (SCV-2) was stated as a pandemic on March 11 2020 by World Health Organization (WHO), and since then, it has become a major health issue worldwide. It mainly attacks the respiratory system with various accompanying complications, including cardiac injury, renal failure, encephalitis and Stroke.Materials and Methods: The current systematic review has been compiled to summarize the available literature on SCV-2 induced ischemic Stroke and its subtypes. Further, the mechanisms by which the virus crosses the blood-brain barrier (BBB) to enter the brain have also been explored. The role of CRP and D-dimer as potent prognostic markers was also explored. The literature search was carried out comprehensively on Google scholar, PubMed, SCOP US, Embase and Cochrane databases by following guidelines.Results: All the studies were reviewed thoroughly by authors and disagreements were resolved by consensus and help of the senior authors. The most common subtype of the IS was found to be large artery atherosclerosis in SCV-2 induced IS. Hypertension emerged as the most significant risk factor. The mechanism resulting in elevated levels of CRP and D-dimer have also been discussed. However, there is a scarcity of definitive evidence on how SCV-2 enters the human brain. The available literature based on various studies demonstrated that SCV-2 enters through the nasopharyngeal tract via olfactory cells to olfactory neurons, astrocytes and via choroid plexus through endothelial cells. Further, disruption of gut-brain axis has been also discussed.Conclusion: Data available in the literature is not adequate to come to a conclusion. Therefore, there is a need to carry out further studies to delineate the possible association between SCV-2 induced IS.

Self-isolation of an Italian long-term care facility during COVID-19 pandemic: A comparison study on care-related infectious episodes

The aim of this retrospective cohort study is to understand if and how much the preventive self-isolation approach might have been a valid model to avoid care-related infection, not only from COVID-19 but also from other non-viral infectious diseases. From March to May 2020, the healthcare and management staff of the Villa Santa Maria long-term care facilities, located in the village of Montenero di Bisaccia (Campobasso, Molise, Italy), decided to carry out a preventive self-isolation plan to safeguard the residents from SARS-CoV-2. The impact on other infectious diseases was evaluated by analyzing the antibiotic therapies prescription trend among the inpatients. Our data showed that although self-isolation protected residents and caregivers from SARS-CoV-2, it can also be associated with mobility reduction, leading to an increase in bedridden pathologies, namely, pressure ulcers and pressure sores. The simultaneous isolation of residents and caregivers in the same location significantly reduced any outside influence as a cause of possible infections.

Targeting the vital non-structural proteins (NSP12, NSP7, NSP8 and NSP3) from SARS-CoV-2 and inhibition of RNA polymerase by natural bioactive compound naringenin as a promising drug candidate against COVID-19

The prevalence of SARS-CoV-2-induced respiratory infections is now a major challenge worldwide. There is currently no specific antiviral drug to prevent or treat this disease. Infection with COVID-19 seriously needs to find effective therapeutic agents. In the present study, naringenin, as a potential inhibitor candidate for RNA Polymerase SARS-CoV-2 was compared with remdesivir (FDA-approved drug) and GS-441,524 (Derivative of the drug remdesivir) by screening with wild-type and mutant SARS-CoV-2 NSP12 (NSP7-NSP8) and NSP3 interfaces, then complexes were simulated by molecular dynamics (MD) simulations to gain their stabilities. The docking results displayed ​scores of -3.45 kcal/mol and -4.32 kcal/mol against NSP12 and NSP3, respectively. Our results showed that naringenin had ΔG values more negative than the ΔG values of Remdesivir (RDV) and GS-441,524. Hence, naringenin was considered to be a potential inhibitor. Also, the number of hydrogen bonds of naringenin with NSP3 and later NSP12 are more than Remdesivir and its derivative. In this research, Mean root mean square deviation (RMSD) values of NSP3 and NSP12with naringenin ligand (5.55±1.58 nm to 3.45±0.56 nm and 0.238±0.01 to 0.242±0.021 nm, respectively showed stability in the presence of ligand. The root mean square fluctuations (RMSF) values of NSP3 and NSP12 amino acid units in the presence of naringenin in were 1.5 ± 0.31 nm and 0.118±0.058, respectively. Pharmacokinetic properties and prediction of absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of naringenin and RDV showed that ​these two compounds had no potential cytotoxicity.

Complement and complement regulatory proteins are upregulated in lungs of COVID-19 patients

We explored the pathological changes and the activation of local complement system in COVID-19 pneumonia. Lung paraffin sections of COVID-19 infected patients were analyzed by HE (hematoxylin-eosin) staining. The deposition of complement C3, the deposition of C3b/iC3b/C3d and C5b-9, and the expression of complement regulatory proteins, CD59, CD46 and CD55 were detected by immunohistochemistry. In COVID-19 patients' lung tissues, fibrin exudation, mixed with erythrocyte, alveolar macrophage and shed pneumocyte are usually observed in the alveoli. The formation of an "alveolar emboli" structure may contribute to thrombosis and consolidation in lung tissue. In addition, we also found that compared to normal tissue, the lung tissues of COVID-19 patients displayed the hyper-activation of complement that is represented by extensive deposition of C3, C3b/iC3b/C3d and C5b-9, and the increased expression level of complement regulatory proteins CD55, and especially CD59 but not CD46. The thrombosis and consolidation in lung tissues may contribute to the pathogenesis of COVID-19. The increased expression of CD55 and CD59 may reflect a feedback of self-protection on the complement hyper-activation. Further, the increased C3 deposition and the strongly activated complement system in lung tissues may suggest the rationale of complement-targeted therapeutics in conquering COVID-19.

The 21st century disaster: The COVID-19 epidemiology, risk factors and control

The 21st century will be indelible in the world as ruin of the outbreak of COVID-19 was arose in Wuhan, China has now spread all over the world, up to August 2020. This study was based on the factors affecting the epidemiology of this virus in human societies of global concern. We studied the articles published in journals on various aspects of nCoVID19. The Wikipedia and WHO situation reports have also been searched out for related information. Outcomes were followed up until 2020. The COVID-19 is a virus with pandemic potential which may continue to cause regular infection in human. The pandemic outbreak of COVID-19 threatened public health across the globe in form of system as reflected in the shape of emergency. Approximately 21 million humans are infected and 759,400 have lost their lives till 2020 in all over the world. We have described epidemiological features, reservoirs, transmission, incubation period, rate of fatality, management including recent clinical chemotherapeutic approach and preventive measurements and masses which are at risk of COVID19. This virus causes viral pneumonia when it attacks on respiratory system and multiple failure which can leads to life threatening complications. It is believed to be zoonotic importance although it is not clear from which animal and how it is transmitted. Zoonotic transmission of COVID-19 has not yet known by science. The current study will help to establish a baseline for early effective control of this rapidly spreading severe viral illness. The available data on COVID-19 indicates that older males with comorbidities would have been more infected, which can result in severe respiratory complications. Implementation of preventive measurements, investigation of proper chemotherapeutics and detection of cross species transmission agents must be ensured.

DYNAMICS OF CLINICAL SYMPTOMS AND SECRETORY IMMUNOGLOBULIN A IN COVID-19 CONVALESCENT PATIENTS

The post-COVID-19 recovery period is characterized by persistence of some symptoms, with immunological alterations being of great importance. Development of preventive measures to normalize mucosal immunity after a coronavirus infection determines the relevance of the current study. The aim. To study dynamics of clinical symptoms and level of secretory immunoglobulin A in individuals after a novel coronavirus infection as well as evaluate effectiveness of using interferon alpha-2b. Materials and methods. A study was conducted with patients aged 18 to 60 years old (n=130), surveyed 1 to 9 months after post-infection, as well as in apparently healthy individuals lacking COVID-19 (n=15). Previous novel coronavirus infection and post-COVID manifestations were verified based on medical documentation, complaints, anamnesis data, physical examination and questionnaires. The concentration of salivatory and nasopharyngeal mucosal sIgA was measured dynamically prior to and after administration of local therapy with interferon alpha-2b (gel applied intranasally twice a day for 30 days). Results. The acute period of COVID-19 was characterized by fever, anosmia, fatigue and weakness, muscle and joint pain. Among the post-COVID manifestations at early period (1-3 months), pain in the joints and muscles (75,0%) as well as elevated body temperature (21,2%) were reliably detected, whereas in the long period (6-9 months) there were revealed dominance with the same frequency of shortness of breath, muscle and joint pain (75,8%, respectively). Based on examination data in healthy subjects, there was determined an arbitrary normal range of secretory IgA in saliva 6.451.81 mg/ml and nasal swabs 13.433.24 mg/ml. In the group of patients 1-3 months post-infection, therapy with interferon alfa-2b one month later resulted in significantly increased level of secretory IgA in saliva (from 1.840.28 to 5.781.96 mg/ml) and in nasal swabs (from 28.613.0 to 39.833.85 mg/ml) by more than 3- and 1.5-fold, respectively. In the group of patients without therapy was featured with stably sustained decline in sIgA level up to 9 months after COVID-19. In particular, the level of saliva sIgA ranged from 2.360.56 down to 2.160.66 mg/ml, and in nasal smears from 15.661.32 to 10.231.07 mg/ml that differed insignificantly compared to baseline level. The rate of respiratory diseases prevailed in this group (27.6% of cases), which fully lacked in the group of topically administered interferon alpha-2b. Conclusion. In the post-COVID period, multiple organ disorders persist and reduced sIgA level is registered. Intranasally applied interferon alfa-2b made possible to normalize sIgA level and prevent accumulation of respiratory infectious pathologies.

The sources of the Kuznets relationship between the COVID-19 mortality rate and economic performance

This paper discusses the findings of an empirical analysis of the Kuznets, or reverse U-shaped relationship, between the COVID-19 mortality rate and economic performance. In the early stages of economic development, the COVID-19 mortality rate is anticipated to rise with rising economic activity and urbanization. Eventually, the mortality rate decreases at higher economic development levels as people and the government are more capable of investing in disease abatement measures. The quality of political institutions, wealth distribution, urbanization, vaccination rate, and improvements in healthcare systems are hypothesized to affect the COVID-19 mortality rate. Examining this relationship can be effective in understanding the change in the COVID-19 mortality rate at different economic performance stages and in identifying appropriate preventive measures. This study employed the negative binomial regression to model a cross-sectional dataset of 137 countries. Results indicated that the relationship between the per-head gross domestic product (GDP) level and the COVID-19 mortality rate appeared to follow a pattern like the Kuznets curve, implying that changes in institutional quality, healthcare advancements, wealth distribution, urbanization, vaccination rate, and the percentage of the elderly population were significant in explaining the relationship. Improvement of the healthcare system has a notable effect on lowering the COVID-19 mortality rate under more effective government conditions. Additionally, the results suggested that a higher per-head GDP is required to reverse the rising trend of the mortality rate under higher income inequality. Based on these results, preventive measures, and policies to reduce COVID-19 mortalities were recommended in the conclusion section.

Correlation of Biomarkers in Severe COVID-19 Patients Cross-sectional Study

BACKGROUND: In patients with coronavirus disease-19 (COVID-19), serious biomarkers (liver function tests and renal functions tests) (urea, creatinine, GOT, GPT, and LDH) are determined immediate to assess in prognosis of the severity of disease. AIM: The aim of the study was to determine correlation between biomarkers (liver function tests and renal functions tests) (urea, creatinine, GOT, GPT, and LDH) among COVID-19 patients. METHODS: A cross-sectional study, a total of 90 COVID-19 patients who attending in the Al-Hussein Medical City in Karbala, Iraq, participated in the present study within a month’s time in late December 2021 to early January of 2022. All COVID-19 patients with positive SARS-COV-2 real-time RT-PCR results were reviewed. The patients were classifying according SPO2 into three groups (mild, moderate, and severe groups). The demographic data (sex, age, and SPO2) were collected while the biomarkers (liver function tests and renal functions tests) for all patients were done by bio-base instrument (ACCENT-200 ALAT KIT). RESULTS: The white blood cell “WBC” and neutrophil in moderate and severe groups had substantially greater counts (p = 0.005) when compared with mild group while lymphocytes were considerably decreased in the severe and moderate groups (p = 0.005). In the moderate group, there was positive significant correlation among neutrophils and serum LDH (r = 0.451*, p = 0.014). There was no significant correlation between neutrophils and liver function tests. Furthermore, in the moderate patient group, a strong positively correlating notably among lymphocytes and serum LDH. Moreover, the concentration of serum GOT, GPT, and LDH (p = 0.05, p = 0.08, and p = 0.5) was higher levels in severe group when compared to moderate and mild groups, on the other hand, the renal function tests (urea and creatinine) were high serum levels in severe group than mild and moderate groups. CONCLUSION: The serum concentration of urea, creatinine, GOPT, GPT, and LDH was high in severe COVID-19 patients group, although there was no statistically significant in ALP, GPT, and urea among COVID-19 patient’s groups (mild, moderate, and severe group). The present study found no significant correlation between biomarkers (liver function tests and renal function test).

Estimation of the Reproductive Number Trend of the Novel Coronavirus "COVID-19" in Southern Iran from July to November 2020

Background

Effective measures to control COVID-19 should be based on an understanding of its epidemiological pattern and the evaluation of its prevalence in the community. This study aimed to examine the reproductive number (R) of COVID-19 and its trend in Fars Province in southern Iran.

Methods

In this ecological study, the R trend was examined from July to November 2020. Data were collected from the daily reports of Shiraz University of Medical Sciences. R is the product of three components, namely the number of infection-producing contacts per unit time, the probability of transmission per contact, and the contagiousness period. Incidence and prevalence rates were used to calculate R. The R value was calculated in Microsoft Excel 2016.

Results

The first and second peaks of COVID-19 were observed on July 6^th and November 22^nd, respectively. The median and mean of R were 1.42 and 1.41, respectively. The highest and lowest values of R were observed on October 20^th (2.60) and September 1^st (0.46), respectively. The values of R had a slightly decreasing trend in the second half of July and November than the first half. In the second half of August and September, an increasing trend was observed than the first half. There was not much change in the second half of October.

Conclusion

The highest value of R was related to the dates when there was a higher probability of exposure to the virus, including public holidays and different occasions on which the probability of people's participation in ceremonies, communities, and gatherings was higher.

Artificial intelligence effectively predicts the COVID-19 death rate in different UK cities

The emergence of a new variant of SARS-CoV-2 in the UK that is spreading more rapidly has raised great concerns not only in the UK but also whole Europe and other parts of the globe. The newly identified variant of SARS-CoV-2 that is reported to be more contagious has prompted many countries to ban travel to and from the UK. As of April 2, 2021, nearly 4.35 million confirmed cases of coronavirus (COVID-19) have been reported in the UK out of which more than 127,000 people have died. These numbers reveal a need for predictor models to assist with management, prevention, and treatment decisions. Here, we presented an Artificial Intelligence (AI) model to predict the death rate in various cities of the United Kingdom. Training and testing the model using the data available on the European data portal showed promising results with predicted R2 = 0.88.

Association Between Symptoms and Severity of Disease in Hospitalised Novel Coronavirus (COVID-19) Patients: A Systematic Review and Meta-Analysis

Background

Symptoms of the novel coronavirus disease (COVD-19) are well known, although asymptomatic cases were also reported due to this rapidly evolving viral disease. However, there has been limited research with inconsistent findings on symptoms of COVID-19 and disease severity. We aimed to evaluate the association between symptoms and severity of disease in adult patients with confirmed COVID-19 by performing a meta-analysis.

Methods

We conducted this study by searching four online databases (Medline, Web of Science, EMBASE and Cochrane library) of published studies that included symptoms of COVID-19 cases and severity of the disease between January 1, 2020, and October 31, 2021. PRISMA and MOOSE guidelines were followed, and only articles published in English were selected. We performed meta-analysis using Mantel-Haenszel random-effects model. Note that we included peer-reviewed studies conducted in Wuhan and published in the English language that reported the clinical characteristics of COVID-19, particularly the symptoms of novel coronavirus patients with their prevalence and distribution of patients based on the severity of the disease.

Results

Out of 255 articles identified, a total of twenty articles, including 5390 participants, met the inclusion criteria and were included. Among the participants, 2997 (55.60%) were males, and 974 (18.07%) reported severe conditions. Fever was the most commonly reported symptom in the reported COVID-19 confirmed cases (88.47%, 95% CI: 80.74-93.35%), which was followed by cough, fatigue, and less proportionally dyspnea and myalgia. Dyspnea was the only symptom, which was associated with severity of COVID-19 (OR 2.43, 95% CI: 1.52-3.89).

Conclusion

Dyspnoea was found to be associated with severity of COVID-19. People with existing respiratory illnesses, such as chronic obstructive pulmonary diseases need to be careful about the onset of such symptom and should seek medical attention.

Prediction Model of Adverse Effects on Liver Functions of COVID-19 ICU Patients

SARS-CoV-2 is a recently discovered virus that poses an urgent threat to global health. The disease caused by this virus is termed COVID-19. Death tolls in different countries remain to rise, leading to continuous social distancing and lockdowns. Patients of different ages are susceptible to severe disease, in particular those who have been admitted to an ICU. Machine learning (ML) predictive models based on medical data patterns are an emerging topic in areas such as the prediction of liver diseases. Prediction models that combine several variables or features to estimate the risk of people being infected or experiencing a poor outcome from infection could assist medical staff in the treatment of patients, especially those that develop organ failure such as that of the liver. In this paper, we propose a model called the detecting model for liver damage (DMLD) that predicts the risk of liver damage in COVID-19 ICU patients. The DMLD model applies machine learning algorithms in order to assess the risk of liver failure based on patient data. To assess the DMLD model, collected data were preprocessed and used as input for several classifiers. SVM, decision tree (DT), Naïve Bayes (NB), KNN, and ANN classifiers were tested for performance. SVM and DT performed the best in terms of predicting illness severity based on laboratory testing.

Clinical features associated with Severe Acute Respiratory Syndrome (SARS-COV2)

The present study was conducted to isolation and identification of Aspergillus fumigatus. Isolated from immunocompromised patients with (Diabetes, Cancer) by different identification methods including direct examination, laboratory culture and electron microscopy. During the period from (July to September 2016), a total of 50 swab were collected from immunocompromised patients with attending to the in AL- Sadder Medical City (the Center for Diabetes and Endocrinology) and (Euphrates middle Center for cancer diseases). In AL-Najaf Governorate, the samples were collected as following: 30 swab from the eyes of cancer patients who were suffering from prostate, leukemia, stomach and intestines cancer, also 20 swabs from the ears of diabetic patients. The percentage of female to male was as following, 29 females (58%) males and 21 (42%). In this study, the results show that the incidence of aspergillosis in women was higher than the male. The results of the present study reveal that the prevalence of aspergillosis from patient with cancer was more than diabetes patients which was 18 (66.66%) and 9 (33.33%), respectively.

Inhibitory effects and mechanisms of the anti-covid-19 traditional Chinese prescription, Keguan-1, on acute lung injury

ETHNOPHARMACOLOGICAL RELEVANCE

Keguan-1, a new traditional Chinese medicine (TCM) prescription contained seven Chinese herbs, is developed to treat coronavirus disease 19 (COVID-19). The first internationally registered COVID-19 randomised clinical trial on integrated therapy demonstrated that Keguan-1 significantly reduced the incidence of ARDS and inhibited the severe progression of COVID-19.

AIM OF THE STUDY

To investigate the protective mechanism of Keguan-1 on ARDS, a lipopolysaccharide (LPS)-induced acute lung injury (ALI) model was used to simulate the pathological state of ARDS in patients with COVID-19, focusing on its effect and mechanism on ALI.

MATERIALS AND METHODS

Mice were challenged with LPS (2 mg/kg) by intratracheal instillation (i.t.) and were orally administered Keguan-1 (low dose, 1.25 g/kg; medium dose, 2.5 g/kg; high dose, 5 g/kg) after 2 h. Bronchoalveolar lavage fluid (BALF) and lung tissue were collected 6 h and 24 h after i.t. administration of LPS. The levels of inflammatory factors tumour necrosis factor alpha (TNF-α), interleukin (IL)-6, IL-1β, keratinocyte-derived chemokine (KC or mCXCL1), macrophage inflammatory protein 2 (MIP2 or mCXCL2), angiotensin II (Ang II), and endothelial cell junction-associated proteins were analysed using ELISA or western blotting.

RESULTS

Keguan-1 improved the survival rate, respiratory condition, and pathological lung injury; decreased the production of proinflammatory factors (TNF-α, IL-6, IL-1β, KC, and MIP2) in BALF and the number of neutrophils in the lung tissues; and ameliorated inflammatory injury in the lung tissues of the mice with LPS-induced ALI. Keguan-1 also reduced the expression of Ang II and the adhesion molecule ICAM-1; increased tight junction proteins (JAM-1 and claudin-5) and VE-cadherin expression; and alleviated pulmonary vascular endothelial injury in LPS-induced ALI.

CONCLUSION

These results demonstrate that Keguan-1 can improve LPS-induced ALI by reducing inflammation and pulmonary vascular endothelial injury, providing scientific support for the clinical treatment of patients with COVID-19. Moreover, it also provides a theoretical basis and technical support for the scientific use of TCMs in emerging infectious diseases.

A review on corona virus disease 2019 (COVID-19): current progress, clinical features and bioanalytical diagnostic methods

A new epidemic of acute respiratory viral pneumonia was discovered in central China at the end of 2019. The disease was given the name coronavirus disease 2019 (COVID-19), and the virus that caused this disease was known as severe acute respiratory syndrome coronavirus (SARS-CoV-2). So far, diagnostic methods have been focused on (a) human antibody detection, (b) viral antigen detection and (c) viral gene detection, the latter using RT-PCR being the most accurate approach. In this paper, we present a summary of the COVID-19 pandemic, clinical features and epidemiology and pathogenesis. Also, we focus on the recent advances in bioanalytical diagnostic methods based on various techniques for SARS-CoV-2 sensing that have recently been published (2020–2021). Furthermore, we present the mechanisms, advantages and disadvantages of the most common biosensors for COVID-19 detection, which include optical, electrochemical and piezoelectric biosensors as well as wearable and smart nanobiosensors, immunosensors, aptasensors and genosensors.

Toll-Like Receptors (TLRs) as Therapeutic Targets for Treating SARS-CoV-2: An Immunobiological Perspective

INTRODUCTION

Coronavirus disease-19 (COVID-19) caused by SARS-CoV-2 is presently the biggest threat to mankind throughout the globe. Increasing reports on deaths, cases of new infection, and socioeconomic losses are continuously coming from all parts of the world. Developing an efficacious drug and/or vaccine is currently the major goal to the scientific communities. In this context, toll-like receptors (TLRs) could be the useful targets in adopting effective therapeutic approaches.

METHODS

This chapter has been written by incorporating the findings on TLR-based therapies against SARS-CoV-2 demonstrated in the recently published research papers/reviews.

RESULTS

TLRs are the essential components of host immunity and play critical roles in deciding the fate of SARS-CoV-2 by influencing the immunoregulatory circuits governing human immune response to this pathogen. Hitherto, a number of multi-subunit peptide-based vaccines and pharmacological agents developed against SARS-CoV-2 have been found to manipulate TLR function. Therefore, circumventing overt immunopathology of COVID-19 applying TLR-antagonists can effectively reduce the morality caused from "cytokine storm"-induced multiorgan failure. Similarly, pre-administration of TLR- agonists may be used as a prophylaxis to sensitize the immune system of the individuals having risk of infection. A lot of collaborative efforts are required for bench-to-bench transformation of these knowledges.

CONCLUSION

This chapter enlightens the potentials and promises of TLR-guided therapeutic strategies against COVID-19 by reviewing the major findings and achievements depicted in the literatures published till date.

Modeling and Evaluation of the Joint Prevention and Control Mechanism for Curbing COVID-19 in Wuhan

The spread of COVID-19 in Wuhan was successfully curbed under the strategy of “Joint Prevention and Control Mechanism.” To understand how this measure stopped the epidemics in Wuhan, we establish a compartmental model with time-varying parameters over different stages. In the early stage of the epidemic, due to resource limitations, the number of daily reported cases may lower than the actual number. We employ a dynamic-based approach to calibrate the accumulated clinically diagnosed data with a sudden jump on February 12 and 13. The model simulation shows reasonably good match with the adjusted data which allows the prediction of the cumulative confirmed cases. Numerical results reveal that the “Joint Prevention and Control Mechanism” played a significant role on the containment of COVID-19. The spread of COVID-19 cannot be inhibited if any of the measures was not effectively implemented. Our analysis also illustrates that the Fangcang Shelter Hospitals are very helpful when the beds in the designated hospitals are insufficient. Comprised with Fangcang Shelter Hospitals, the designated hospitals can contain the transmission of COVID-19 more effectively. Our findings suggest that the combined multiple measures are essential to curb an ongoing epidemic if the prevention and control measures can be fully implemented.

Recognizing COVID-19 from chest X-ray images for people in rural and remote areas based on deep transfer learning model

In this article, we propose Deep Transfer Learning (DTL) Model for recognizing covid-19 from chest x-ray images. The latter is less expensive, easily accessible to populations in rural and remote areas. In addition, the device for acquiring these images is easy to disinfect, clean and maintain. The main challenge is the lack of labeled training data needed to train convolutional neural networks. To overcome this issue, we propose to leverage Deep Transfer Learning architecture pre-trained on ImageNet dataset and trained Fine-Tuning on a dataset prepared by collecting normal, COVID-19, and other chest pneumonia X-ray images from different available databases. We take the weights of the layers of each network already pre-trained to our model and we only train the last layers of the network on our collected COVID-19 image dataset. In this way, we will ensure a fast and precise convergence of our model despite the small number of COVID-19 images collected. In addition, for improving the accuracy of our global model will only predict at the output the prediction having obtained a maximum score among the predictions of the seven pre-trained CNNs. The proposed model will address a three-class classification problem: COVID-19 class, pneumonia class, and normal class. To show the location of the important regions of the image which strongly participated in the prediction of the considered class, we will use the Gradient Weighted Class Activation Mapping (Grad-CAM) approach. A comparative study was carried out to show the robustness of the prediction of our model compared to the visual prediction of radiologists. The proposed model is more efficient with a test accuracy of 98%, an f1 score of 98.33%, an accuracy of 98.66% and a sensitivity of 98.33% at the time when the prediction by renowned radiologists could not exceed an accuracy of 63.34% with a sensitivity of 70% and an f1 score of 66.67%.

Evaluation of Treatment Outcome for Pneumonia among Pre-Vaccinated COVID-19 Patients with/without Comorbidity in a Public Hospital in Bengkulu, Indonesia

Pneumonia is one of the common complications of SARS-CoV-2 infection where most patients have moderate to severe symptoms that pose a higher risk for death. This study aims to evaluate the treatment outcome of COVID-19-associated Pneumonia among patients with/without comorbidity in a public hospital in Indonesia. This is a retrospective cohort study involving unvaccinated confirmed COVID-19 patients admitted to the hospital between March and December 2020. All confirmed COVID-19 patients with Pneumonia (n = 1522) treated at the hospital were included. The majority of patients (99%) had mild COVID-19 symptoms while the remaining had moderate symptoms. The median age was about 32 years old and the average treatment duration was 6.25 ± 1.83 days. Most patients (88.8%) received a combination of azithromycin and oseltamivir. There was a very significant relationship (p < 0.001) between comorbidities with treatment and duration of treatment of Pneumonia in COVID-19 patients. Although most patients had Pneumonia and comorbidities, they were successfully treated with azithromycin and oseltamivir combination following approximately five days of treatment.

Acceptability of COVID-19 vaccine in the working-age population in Shanghai city: a cross-sectional study

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is still an enormous threat to global health and the economy. Although China has adopted effective measures to control the outbreak, there is still a risk of local transmission from imported cases. Meanwhile, considering the high mortality rate and rapid spread of the disease, a safe and effective vaccine is urgently needed to control the pandemic. With COVID-19 vaccines becoming available to the population, it has become important to know about their acceptance in the population. This is important to enable high vaccination coverage rates and reflects the demand within the general population. An cross-sectional survey was conducted during October 2020 in Shanghai using a well-designed questionnaire, which aimed to evaluate the acceptability of COVID-19 vaccines and to identify the factors affecting its acceptability among working-age adults in Shanghai, China. We found that the acceptability of COVID-19 vaccines was high in work-age adults in Shanghai, China. The factors affecting the acceptability of vaccination identified in this study can provide guides to increase COVID-19 vaccine acceptability in future.

A brief molecular insight of COVID-19: epidemiology, clinical manifestation, molecular mechanism, cellular tropism and immuno-pathogenesis

In December 2019, the emergence and expansion of novel and infectious respiratory virus SARS-CoV-2 originated from Wuhan, China caused an unprecedented threat to the public health and became a global pandemic. SARS-CoV-2 is an enveloped, positive sense and single stranded RNA virus belonging to genera betacoronavirus, of Coronaviridae family. The viral genome sequencing studies revealed 75-80% similarity with SARS-CoV. SARS-CoV-2 mainly affects the lower respiratory system and may progress to pneumonia and Acute Respiratory Distress Syndrome (ARDS). Apart from life-threatening situations and burden on the global healthcare system, the COVID-19 pandemic has imposed several challenges on the worldwide economics and livelihood. The novel pathogen is highly virulent, rapidly mutating and has a tendency to cross the species boundaries such as from bats to humans through the evolution and natural selection from intermediate host. In this review we tried to summarize the overall picture of SARS-CoV-2 including origin/ emergence, epidemiology, pathogenesis, genome organization, comparative analysis with other CoVs, infection and replication mechanism along with cellular tropism and immunopathogenesis which will provide a brief panoramic view about the virus and disease.

Reductions of migrant population reduces the number of COVID-19 epidemic: a case study in China

The novel coronavirus disease (COVID-19) broke out worldwide in 2020. The purpose of this paper was to find out the impact of migrant population on the epidemic, aiming to provide data support and suggestions for control measures in various epidemic areas. Generalized additive model was utilized to model the relationship between migrant population and the cumulative number of confirmed cases of COVID-19. The difference of spatial distribution was analyzed through spatial autocorrelation and hot spot analysis. Generalized additive model demonstrated that the cumulative number of confirmed cases was positively correlated with migration index and population density. The predictive results showed that, if no travel restrictions are imposed on the migrant population as usual, this number of COVID-19 would have reached 27,483 (95% CI 16,074, 48,097; the actual number was 23,177). The increase in one city (Jian) would be 577.23% (95% CI 322.73%, 972.73%) compared with the real confirmed cases of COVID-19. The average increase in 73 cities was 85.53% (95% CI 19.53%, 189.81%). Among the migration destinations, the number of cases in cities of Hubei province, Chongqing, and Beijing was relatively high, and there were large-scale high-prevalence clusters in eastern Hubei province. Without restrictions on migration, the high prevalence areas in Hubei province and its surrounding areas will be further expanded. The reduced population mobility and population density can greatly slow down the spread of the epidemic. All epidemic areas should suspend the transportation between cities, strictly control the population travel, and decrease the population density, so as to reduce the spread of COVID-19.

Inconsistent and incomplete retraction of published research: A cross-sectional study on Covid-19 retractions and recommendations to mitigate risks for research, policy and practice

BACKGROUND

Retraction of published research can reduce the dissemination of incorrect or misleading information, but concerns have been raised about the clarity and rigor of the retraction process. Failure to clearly and consistently retract research has several risks, for example discredited or erroneous research may inform health research studies (e.g. clinical trials), policies and practices, potentially rendering these unreliable.

OBJECTIVE

To investigate consistency and clarity of research retraction, based on a case study of retracted Covid-19 research.

STUDY DESIGN

A cross-sectional study of retracted Covid-19 articles reporting empirical research findings, based on searches of Medline, Embase and Scopus on 10th July and 19th December 2020.

KEY RESULTS

We included 46 retracted Covid-19 articles. The number eligible for inclusion nearly doubled, from 26 to 46, in five months. Most articles (67%) were retracted from scientific journals and the remainder from preprint servers. Key findings: (1) reasons for retraction were not reported in 33% (15/46) of cases; (2) time from publication to retraction could not be determined in 43% (20/46) of cases; (3) More than half (59%) of retracted Covid-19 articles (27/46) remained available as original unmarked electronic documents after retraction (33% as full text and 26% as an abstract only). Sources of articles post-retraction were preprint servers, ResearchGate and, less commonly, websites including PubMed Central and the World Health Organization. A retracted journal article which controversially claimed a link between 5G technology and Covid-19 remains available in its original full text from at least 60 different websites.

CONCLUSIONS

The retraction process is inconsistent and often ambiguous, with more than half of retracted Covid-19 research articles remaining available, unmarked, from a wide range of online sources. There is an urgent need to improve guidance on the retraction process and to extend this to cover preprint servers. We provide structured recommendations to address these concerns and to reduce the risks that arise when retracted research is inappropriately cited.

Vaping and COVID-19: Insights for Public Health and Clinical Care from Twitter

This study describes key topics of discussions on Twitter at the intersection of vaping and COVID-19 and documents public reactions to announcements from authoritative health agencies. Twitter posts containing vaping and COVID-19-related terms were collected from 1 December 2019 to 3 May 2020 (n = 23,103 posts). Text classifiers and unsupervised machine learning were used to identify topics in posts. Predominant topics included COVID-19 Respiratory Health (18.87%), COVID-19 Susceptibility (17.53%), Death (10.07%), Other COVID-19 Health Effects (9.62%), and Severity of COVID-19 (7.72%), among others. Public conversations on topics, such as Severity of COVID-19, Transmission, Susceptibility, Health Effects, Death, and Smoking cessation, were shaped by announcements from U.S. and international health agencies. Armed with the insights from this study, medical providers should be prepared to discuss vaping-related health risks with their patients in the era of COVID-19. Misconceptions around vaping as a protective behavior from, and an effective treatment against, COVID-19 should also be corrected.

Environmental perspectives of COVID-19 outbreaks: A review

The coronavirus disease 2019 (COVID-19) pandemic, caused by the novel virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in December 2019 in China and has led to a global public health emergency. Previously, it was known as 2019-nCoV and caused disease mainly through respiratory pathways. The COVID-19 outbreak is ranked third globally as the most highly pathogenic disease of the twenty-first century, after the outbreak of SARS-CoV and Middle East respiratory syndrome in 2002 and 2012, respectively. Clinical, laboratory, and diagnostic methodology have been demonstrated in some observational studies. No systematic reviews on COVID-19 have been published regarding the integration of COVID-19 outbreaks (monitoring, fate and treatment) with environmental and human health perspectives. Accordingly, this review systematically addresses environmental aspects of COVID-19 outbreak such as the origin of SARS-CoV-2, epidemiological characteristics, diagnostic methodology, treatment options and technological advancement for the prevention of COVID-19 outbreaks. Finally, we integrate COVID-19 outbreaks (monitoring, fate and treatment) with environmental and human health perspectives. We believe that this review will help to understand the SARS-CoV-2 outbreak as a multipurpose document, not only for the scientific community but also for global citizens. Countries should adopt emergency preparedness such as prepare human resources, infrastructure and facilities to treat severe COVID-19 as the virus spreads rapidly globally.

Electrochemical investigations for COVID-19 detection-A comparison with other viral detection methods

Virus-induced infection such as SARS-CoV-2 is a serious threat to human health and the economic setback of the world. Continued advances in the development of technologies are required before the viruses undergo mutation. The low concentration of viruses in environmental samples makes the detection extremely challenging; simple, accurate and rapid detection methods are in urgent need. Of all the analytical techniques, electrochemical methods have the established capabilities to address the issues. Particularly, the integration of nanotechnology would allow miniature devices to be made available at the point-of-care. This review outlines the capabilities of electrochemical methods in conjunction with nanotechnology for the detection of SARS-CoV-2. Future directions and challenges of the electrochemical biosensors for pathogen detection are covered including wearable and conformal biosensors, detection of plant pathogens, multiplexed detection, and reusable biosensors for on-site monitoring, thereby providing low-cost and disposable biosensors.

An Overview of the Pathogenesis, Transmission, Diagnosis, and Management of Endemic Human Coronaviruses: A Reflection on the Past and Present Episodes and Possible Future Outbreaks

The outbreak of the 2019 coronavirus pandemic caught the world by surprise in late 2019 and has held it hostage for months with an increasing number of infections and deaths. Although coronavirus was first discovered in the 1960s and was known to cause respiratory infection in humans, no information was available about the epidemic pattern of the virus until the past two decades. This review addresses the pathogenesis, transmission dynamics, diagnosis, management strategies, the pattern of the past and present events, and the possibility of future outbreaks of the endemic human coronaviruses. Several studies have described bats as presumptive natural reservoirs of coronaviruses. In essence, the identification of a diverse group of similar SARS coronaviruses in bats suggests the possibility of a future epidemic due to severe acute respiratory syndrome (SARS-like) coronaviruses originating from different reservoir hosts. The study also identified a lack of vaccines to prevent human coronavirus infections in humans in the past, however, the recent breakthrough in vaccine discovery and approval for emergency use for the treatment of Severe Acute Respiratory Syndrome Coronavirus 2 is commendable. The high rates of genomic substitution and recombination due to errors in RNA replication and the potential for independent species crossing suggest the chances of an entirely new strain evolving. Therefore, rapid research efforts should be deployed for vaccination to combat the COVID-19 pandemic and prevent a possible future outbreak. More sensitization and enlightenment on the need to adopt good personal hygiene practices, social distancing, and scientific evaluation of existing medications with promising antiviral effects against SARS-CoV-2 is required. In addition, intensive investigations to unravel and validate the possible reservoirs, the intermediate host, as well as insight into the ability of the virus to break the species barrier are needed to prevent future viral spillover and possible outbreaks.

Caring for Cancer Patients during Corona Pandemic-(COVID-19)-A Narrative Review

Background Coronavirus disease 2019, the third pandemic of 21st century which has brought the whole world under panic, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a zoonotic beta coronavirus sharing phylogenetic, genomic similarities with SARS virus and Middle East Respiratory Syndrome virus. Specific Concerns Cancer patients are at double the risk than normal patients since these patients are at immunocompromised state. WHO guidelines advice the patients to plan only emergency hospital visits only till the pandemic persists. Should meet patient/visitors in a well-ventilated room or outdoors and maintain at least 2 m distance between the visitor/patients. It also encourages the patient to refill the prescribed medications in well advance and to stay physically active, if possible. Discussion The World Health Organizations' isolate, trace, test, treat policy needs to be followed to protect these high-risk patients from this global pandemic.].

COVID-19 Associated Coagulopathy in an Indian Scenario: A Correlation with Disease Severity and Survival Status

Covid-19 pandemic reveals that the virus causes Covid-19 associated coagulopathy and it is well known that thrombotic risk is associated with ethnicity. To describe the Covid-19 associated coagulopathy in Indian population and to correlate it with the disease severity and survivor status. A cross sectional descriptive study of 391 confirmed Covid-19 cases was carried out over a period of 1.5 months. Patients were categorised as mild to moderate, severe and very severe and also labelled as survivors and non survivors. Prothrombin time (PT), International normalised ratio (INR), activated partial thromboplastin time, D dimer, Fibrin degradation products (FDP), fibrinogen and thrombin time and platelet counts were investigated among the subgroups. Mean age was higher in patients with severe disease (57.62 ± 13.08) and among the non survivors (56.54 ± 12.78). Statistically significant differences in D dimer, FDP, PT, INR and age were seen among the 3 subgroups and survivors. Strong significant positive correlation was noted between D dimer and FDP (r = 0.838, p < .001), PT and INR (r = 0.986, p < 0.001). D dimer was the best single coagulation parameter as per the area under curve (AUC: 0.762, p < 0.001) and D dimer + FDP was the best combination parameter (AUC: 0.764, p = 0) to differentiate mild moderate from severe disease. Raised levels of D dimer, FDP, PT, PT INR and higher age correlated positively with disease severity and mortality in Indian Population.

The neutrophil to lymphocyte ratio is an independent predictor for severe COVID-19 : Evidence from a multicenter case-control study and meta-analyses

Purpose

The aim of this study was to determine whether the neutrophil to lymphocyte ratio (NLR) can predict severe Coronavirus disease 2019 (COVID-19).

Patients and methods

A multicenter case-control study was conducted to investigate whether the NLR can help predict the severity of COVID-19. Patients confirmed to have COVID-19 between 16 January 2020 and 15 March 2020 were enrolled. Furthermore, meta-analyses were conducted based on both previous studies and our case-control study.

Results

In the case-control study, 213 patients (severe: 81) were included. The results suggested that the NLR was an independent risk factor (odds ratio [OR], 1.155, 95% confidence interval [95% CI]: 1.043–1.279, P = 0.006) and a great predictor (the area under the ROC curve was 0.728, 95% CI: 0.656–0.800) for severe COVID-19. In total, 18 datasets from 16 studies combined with our case-control study (severe: 1211; non-severe: 5838) were included in the meta-analyses and the results showed that the NLR of the severe COVID-19 group was significantly higher than that of the non-severe group (SMD = 1.10, 95% CI: 0.90–1.31, P < 0.001). Based on the 2 × 2 data from 6 studies, the SROC of NLR for predicting severe COVID-19 was 0.802, with a sensitivity of 0.67 (95% CI: 0.61–0.72) and a specificity of 0.75 (95% CI: 0.73–0.78).

Conclusion

Based on a multicenter case-control study and a meta-analysis, we found that the initial NLR was a great predictor of severe COVID-19.

Supplementary Information

The online version of this article (10.1007/s00508-021-01917-9) contains supplementary material, which is available to authorized users.

Nature inspired optimization model for classification and severity prediction in COVID-19 clinical dataset

The spread rate of COVID-19 is expected to be high in the wake of the virus's mutated strain found recently in a few countries. Fast diagnosis of the disease and knowing its severity are the two significant concerns of all physicians. Even though positive or negative diagnosis can be obtained through the RT-PCR test, an automatic model that predicts severity and the diagnosis will help medical practitioners to a great extend for affirming medication. Machine learning is an efficient tool that can process vast volume of data deposited in various formats, including clinical symptoms. In this work, we have developed machine learning models for analysing a clinical data set comprising 65000 records of patients, consisting of 26 features. An optimum set of features was derived from this data set by the proposed variant of artificial bee colony optimization algorithm. By making use of these features, a binary classifier is modelled with support vector machine for the screening of COVID-19 patients. Different models were tested for this purpose and the support vector machine has showcased the highest accuracy of 96%. Successively, severity prediction in COVID positive patients was also performed successfully by the logistic regression model. The model managed to predict three severity status viz mild, moderate, and severe. The confusion matrix and the precision-recall values (0.96 and 0.97) of the binary classifier indicate the classifier's efficiency in predicting positive cases correctly. The receiver operating curve generated for the severity predicting model shows the highest accuracy, 96.0% for class 1 and 85.0% for class 2 patients. Doctors can infer these results to finalize the type of treatment/care/facilities that need to be given to the patients from time to time.

SARS-CoV-2 N Protein Targets TRIM25-Mediated RIG-I Activation to Suppress Innate Immunity

A weak production of INF-β along with an exacerbated release of pro-inflammatory cytokines have been reported during infection by the novel SARS-CoV-2 virus. SARS-CoV-2 encodes several proteins able to counteract the host immune system, which is believed to be one of the most important features contributing to the viral pathogenesis and development of a severe clinical picture. Previous reports have demonstrated that SARS-CoV-2 N protein, along with some non-structural and accessory proteins, efficiently suppresses INF-β production by interacting with RIG-I, an important pattern recognition receptor (PRR) involved in the recognition of pathogen-derived molecules. In the present study, we better characterized the mechanism by which the SARS-CoV-2 N counteracts INF-β secretion and affects RIG-I signaling pathways. In detail, when the N protein was ectopically expressed, we noted a marked decrease in TRIM25-mediated RIG-I activation. The capability of the N protein to bind to, and probably mask, TRIM25 could be the consequence of its antagonistic activity. Furthermore, this interaction occurred at the SPRY domain of TRIM25, harboring the RNA-binding activity necessary for TRIM25 self-activation. Here, we describe new findings regarding the interplay between SARS-CoV-2 and the IFN system, filling some gaps for a better understanding of the molecular mechanisms affecting the innate immune response in COVID-19.

Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates

Since it was first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. Using a transmission model, we estimate a basic reproductive number of 3.11 (95% CI, 2.39-4.13), indicating that 58-76% of transmissions must be prevented to stop increasing. We also estimate a case ascertainment rate in Wuhan of 5.0% (95% CI, 3.6-7.4). The true size of the epidemic may be significantly greater than the published case counts suggest, with our model estimating 21 022 (prediction interval, 11 090-33 490) total infections in Wuhan between 1 and 22 January. We discuss our findings in the light of more recent information. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Urban Hierarchical Open-up Schemes Based on Fine Regional Epidemic Data for the Lockdown in COVID-19☆☆☆

During the COVID-19 outbreaking, China's lock-down measures have played an outstanding role in epidemic prevention; many other countries have followed similar practices. The policy of social alienation and community containment was executed to reduce civic activities, which brings up numerous economic losses. It has become an urgent task for these countries to open-up, while the epidemic has almost under control. However, it still lacks sufficient literature to set appropriate open-up schemes that strike a balance between open-up risk and lock-down cost. Big data collection and analysis, which play an increasingly important role in urban governance, provide a useful tool for solving the problem. This paper explores the influence of open-up granularity on both the open-up risk and the lock-down cost. It proposes an SEIR-CAL model considering the effect of asymptomatic patients based on propagation dynamics, and offered a model to calculate the lock-down cost based on the lock-down population. A simulation experiment is then carried out based on the mass actual data of Wuhan City to explore the influence of open-up granularity. Finally, this paper proposed the evaluation score (ES) to comprehensively measure schemes with different costs and risks. The experiments suggest that when released under the non-epidemic situation, the open-up scheme with the granularity refined to the block has the optimal ES. Results indicated that the fine-grained open-up scheme could significantly reduce the lock-down cost with a relatively low open-up risk increase.

Epidemiological characteristics of children with coronavirus at a joint commission-accredited hospital in the United Arab Emirates

Objectives:

Our aim was to identify the epidemiological characteristics and transmission patterns of coronavirus (COVID-19) among pediatric patients in the multicultural and multiethnic city of Al Ain in the United Arab Emirates (UAE).

Method:

A retrospective study was conducted by abstracting data from the electronic medical records of pediatric patients with COVID-19 from two major public hospitals in Al Ain. The data of patients from birth through 16 years of the cases with COVID-19 confirmed by reverse transcription-polymerase chain reaction were obtained. In addition to the epidemiological characteristics, transmission patterns, comorbidities, index cases, travel history, and coinfection with other viruses were analyzed. Cohen's kappa was used to assess interrater reliability and descriptive data. Chi-square test was used to assess significant differences between the variables and was conducted using Statistical Product and Service Solutions software.

Results:

We identified 298 (150 males, 148 females) laboratory-confirmed cases. The patients’ median age was 7 years. Of these, 50% had parents who also tested positive. Most patients (86.9%) were healthy without any known medical problems. The coinfection rate was ~2%.

Conclusion:

The epidemiological characteristics of children with COVID-19 in Al Ain are similar to those observed internationally. Children of all ages appeared to be susceptible to COVID-19 and no significant sex or ethnicity differences were detected. Furthermore, this study provides strong evidence of human-to-human transmission.

In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2

We propose a computational investigation on the interaction mechanisms between SARS-CoV-2 spike protein and possible human cell receptors. In particular, we make use of our newly developed numerical method able to determine efficiently and effectively the relationship of complementarity between portions of protein surfaces. This innovative and general procedure, based on the representation of the molecular isoelectronic density surface in terms of 2D Zernike polynomials, allows the rapid and quantitative assessment of the geometrical shape complementarity between interacting proteins, which was unfeasible with previous methods. Our results indicate that SARS-CoV-2 uses a dual strategy: in addition to the known interaction with angiotensin-converting enzyme 2, the viral spike protein can also interact with sialic-acid receptors of the cells in the upper airways.

Characteristics and Developments in Mesenchymal Stem Cell Therapy for COVID-19: An Update

The outbreak of coronavirus disease 2019 (COVID-19) has so far resulted in over a hundred million people being infected. COVID-19 poses a threat to human health around the world. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been confirmed as the pathogenic virus of COVID-19. SARS-CoV-2 belongs to the β-coronavirus family of viruses and is mainly transmitted through the respiratory tract. It has been proven that SARS-CoV-2 mainly targets angiotensin-converting enzyme II (ACE2) receptors on the surface of various cells in humans. The main clinical symptoms of COVID-19 include fever, cough, and severe acute respiratory distress syndrome (ARDS). Current evidence suggests that the damage caused by the virus may be closely related to the induction of cytokine storms in COVID-19. No specific drugs or measures have yet to be shown to cure COVID-19 completely. Cell-based approaches, primarily mesenchymal stem cells (MSCs), have been identified to have anti-inflammatory and immune functions in COVID-19. Clinical studies about using MSCs and its derivatives-exosomes for COVID-19 treatment-are under investigation. Here, we review the current progress of the biological characteristics, clinical manifestations, and cell-based treatment development for COVID-19. Providing up-to-date information on COVID-19 and potential MSC therapies will help highlight routes to prevent and treat the disease.

A narrative review of coronavirus disease 2019 (COVID-19): clinical, epidemiological characteristics, and systemic manifestations

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease which has had a rapid surge in cases and deaths since it is first documented in Wuhan, China, in December 2019. COVID-19 is caused by the Betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 uses angiotensin-converting enzyme 2, which is highly expressed in the human lower respiratory tract but also in other tissues, as the cellular entry receptor. Thus, COVID-19 mainly affects the respiratory system but can cause damage to other body systems, including the cardiovascular, gastrointestinal, hepatobiliary, renal, and central nervous systems. We review the pathogenesis and clinical manifestations of the infection, focusing on our current understanding of the disease mechanisms and their translation to clinical outcomes, as well as adverse effects on different body systems. We also discuss the epidemiology pathogenesis, clinical, and multi-organ consequences, and highlight some of the research gaps regarding COVID-19.

Potent Molecular Feature-based Neutralizing Monoclonal Antibodies as Promising Therapeutics Against SARS-CoV-2 Infection

The 2019-2020 winter was marked by the emergence of a new coronavirus (SARS-CoV-2) related disease (COVID-19), which started in Wuhan, China. Its high human-to-human transmission ability led to a worldwide spread within few weeks and has caused substantial human loss. Mechanical antiviral control approach, drug repositioning, and use of COVID-19 convalescent plasmas (CPs) were the first line strategies utilized to mitigate the viral spread, yet insufficient. The urgent need to contain this deadly pandemic has led searchers and pharmaceutical companies to develop vaccines. However, not all vaccines manufactured are safe. Besides, an alternative and effective treatment option for such an infectious disease would include pure anti-viral neutralizing monoclonal antibodies (NmAbs), which can block the virus at specific molecular targets from entering cells by inhibiting virus-cell structural complex formation, with more safety and efficiency than the CP. Indeed, there is a lot of molecular evidence about the protector effect and the use of molecular feature-based NmAbs as promising therapeutics to contain COVID-19. Thus, from the scientific publication database screening, we here retrieved antibody-related papers and summarized the repertory of characterized NmAbs against SARS-CoV-2, their molecular neutralization mechanisms, and their immunotherapeutic pros and cons. About 500 anti-SARS-CoV-2 NmAbs, characterized through competitive binding assays and neutralization efficacy, were reported at the writing time (January 2021). All NmAbs bind respectively to SARS-CoV-2 S and exhibit high molecular neutralizing effects against wild-type and/or pseudotyped virus. Overall, we defined six NmAb groups blocking SARS-CoV-2 through different molecular neutralization mechanisms, from which five potential neutralization sites on SARS-CoV-2 S protein are described. Therefore, more efforts are needed to develop NmAbs-based cocktails to mitigate COVID-19.

Aspects of Epidemiology, Pathology, Virology, Immunology, Transmission, Prevention, Prognosis, Diagnosis, and Treatment of COVID-19 Pandemic: A Narrative Review

Undoubtedly, COVID-19 pandemic is one of the largest pandemics and one of the biggest international challenges for health-care system of various countries in the world. This is a narrative review study based on the studies published related with different aspects of COVID-19. The highest numbers of active cases are in the USA, Brazil, India, Russia, South Africa, as well as Colombia and the disease surveillance system must operate more quickly, timely, effectively, and sensitively in these countries. What is clear is that the SARS-CoV-2 basic reproduction number is significantly higher than one and its transmission power is extremely high. In general, it can be stated that mortality and fatality risk due to COVID-19 in men, age increase, severity of disease, systemic disease, as well as inadequate access to the sufficient health-care services will increase. There is currently no specific treatment and effective vaccine for COVID-19. The novel coronavirus pandemic is more consistent with the epidemiological triangle model, which emphasizes that the disease is the result of the interaction of three factors of host, agent, and environment. Therefore, prevention and treatment activities should focus on cutting the virus transmission chain. The main way to deal with viral epidemics is prevention. The emerging of this ruthless virus has once again reminded us that communicable diseases should never be underestimated and forgotten. Considering the rapid transmission of COVID-19, the health-care authorities and workers should consider timely detection and safeguards to prevent the transmission to healthy individuals.

Introduction on Coronavirus Disease (COVID-19) Pandemic: The Global Challenge

By driving the ongoing pandemic of coronavirus disease 2019 (COVID-19), coronaviruses have become a significant change in twenty-first-century medicine, healthcare systems, education, and the global economy. This chapter rapidly reviews the origin, immunopathogenesis, epidemiology, diagnosis, clinical manifestations, and potential therapeutics of COVID-19. It would also explore the effects of the introduction of a single virus, the so-called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), on the public health preparedness planning.

Impact of high dose of baricitinib in severe COVID-19 pneumonia: a prospective cohort study in Bangladesh

PURPOSE

Hyperinflammation in severe COVID-19 infection increases the risk of respiratory failure and one of the cogent reasons of mortality associated with COVID-19. Baricitinib, a janus kinases inhibitor, can potentially suppress inflammatory cascades in severe COVID-19 pneumonia.

METHODS

The objective of this study was to compare the clinical outcomes of high dose of baricitinib with its usual dose in patients with severe COVID-19 pneumonia. This prospective cohort study was conducted on 238 adult patients with severe COVID-19 pneumonia. Eight milligram and 4 mg of baricitinib was given orally to 122 patients in the high dose (HD) group and 116 patients the usual dose (UD) group, respectively daily for 14 days, and clinical outcomes were compared among the groups.

RESULTS

Blood oxygen saturation level was stabilized (≥94% on room air) earlier in the HD group compared to the UD group [5 (IQR: 4-5)/8 (IQR: 6-9), P < 0.05]. Patients in the HD group required intensive care unit (ICU) and intubation supports more in the UD group than that in patients of the HD group [17.2%/9%, P < 0.05; 11.2%/4.1%, P > 0.05; N = 116/122, respectively]. The 30-day mortality and 60-day rehospitalization rate were higher in the UD group than the HD group [6%/3.3%, P < 0.01; 11.9%/7.6%, P > 0.05; N = 116/122, respectively].

CONCLUSION

The daily high dose of baricitinib in severe COVID-19 results in early stabilization of the respiratory functions, declined requirements of critical care supports, reduced rehospitalization with mortality rate compared to its daily usual dose.

Clinical characteristics of children infected with SARS-CoV-2 in Italy

Background

Since December 2019 coronavirus disease (COVID-19) emerged in Wuhan and spread rapidly worldwide. Despite the high number of people affected, data on clinical features and prognostic factors in children and adolescents are limited. We propose a retrospective study aimed to evaluate clinical characteristics of children infected with SARS-CoV-2 in Italy.

Methods

A pediatric population admitted with COVID-19 to Bambino Gesù Children’s Hospital of Rome (Italy) in the period from the end of February to July 2020 has been studied. Medical history, comorbidities, symptoms and laboratory findings were obtained from patients’ electronic medical records.

Results

In 66 patients (35 males and 31 females) we found that: i) fever and cough were the dominant symptoms, while vomit and convulsions were rare symptoms; and ii) all ages of childhood were susceptible to COVID-19. Furthermore, we found that, compared to females, males with COVID-19, although not significantly, had higher values of inflammatory markers such as C-reactive protein (CRP) and ESR. Conversely, we found that COVID-19 positive females were older than males and required more days of hospitalization. Both males and females COVID-19 positives had procalcitonin values within the normal range and D-Dimer values slightly higher than the normal range. With regard to this latter marker, the value measured in females, although not significant, was higher than that measured in males. Interestingly, the presence of leukopenia was found in both sexes.

Conclusions

Compared to the adults we found that COVID-19 infection in children is a non-severe inflammatory disease in both males and females. In any case, many detailed studies should be conducted.

Ongoing COVID-19 Pandemic: A Concise but Updated Comprehensive Review

An ongoing global outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously temporarily named 2019-nCoV) was reported in Wuhan, China at the end of 2019. SARS-CoV-2 has become a pandemic and a major public health concern. As of 18 January 2021, the virus has spread all over the world, resulting in over 99,026 cases in China and more than 95 million cases in another 216 countries. After three months of efforts, Chinese authorities have managed to control the outbreak by implementing aggressive and effective measures; by striking contrast, the number of confirmed patients outside China is still rapidly climbing following an exponential growth trend, especially in some European and American countries. To date, no specific therapeutic drugs still exist for COVID-19. Therefore, it is of utmost importance to understand the updated comprehensive summary regarding COVID-19, in the hopes of providing a reference for the intervention and prevention of the COVID‐19 epidemic for public health authorities and healthcare workers around the world.

Caputo SIR model for COVID-19 under optimized fractional order

Everyone is talking about coronavirus from the last couple of months due to its exponential spread throughout the globe. Lives have become paralyzed, and as many as 180 countries have been so far affected with 928,287 (14 September 2020) deaths within a couple of months. Ironically, 29,185,779 are still active cases. Having seen such a drastic situation, a relatively simple epidemiological SIR model with Caputo derivative is suggested unlike more sophisticated models being proposed nowadays in the current literature. The major aim of the present research study is to look for possibilities and extents to which the SIR model fits the real data for the cases chosen from 1 April to 15 March 2020, Pakistan. To further analyze qualitative behavior of the Caputo SIR model, uniqueness conditions under the Banach contraction principle are discussed and stability analysis with basic reproduction number is investigated using Ulam-Hyers and its generalized version. The best parameters have been obtained via the nonlinear least-squares curve fitting technique. The infectious compartment of the Caputo SIR model fits the real data better than the classical version of the SIR model (Brauer et al. in Mathematical Models in Epidemiology 2019). Average absolute relative error under the Caputo operator is about 48% smaller than the one obtained in the classical case ( ν = 1 ). Time series and 3D contour plots offer social distancing to be the most effective measure to control the epidemic.

Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China

BACKGROUND

Based on differences in populations and prevention and control measures, the spread of new coronary pneumonia in different countries and regions also differs. This study aimed to calculate the transmissibility of coronavirus disease 2019 (COVID-19), and to evaluate the effectiveness of measures to control the disease in Jilin Province, China.

METHODS

The data of reported COVID-19 cases were collected, including imported and local cases from Jilin Province as of March 14, 2019. A Susceptible-Exposed-Infectious-Asymptomatic-Recovered/Removed (SEIAR) model was developed to fit the data, and the effective reproduction number (Reff) was calculated at different stages in the province. Finally, the effectiveness of the measures was assessed.

RESULTS

A total of 97 COVID-19 infections were reported in Jilin Province, among which 45 were imported infections (including one asymptomatic infection) and 52 were local infections (including three asymptomatic infections). The model fit the reported data well (R2 = 0.593, P < 0.001). The Reff of COVID-19 before and after February 1, 2020 was 1.64 and 0.05, respectively. Without the intervention taken on February 1, 2020, the predicted cases would have reached a peak of 177,011 on October 22, 2020 (284 days from the first case). The projected number of cases until the end of the outbreak (on October 9, 2021) would have been 17,129,367, with a total attack rate of 63.66%. Based on the comparison between the predicted incidence of the model and the actual incidence, the comprehensive intervention measures implemented in Jilin Province on February 1 reduced the incidence of cases by 99.99%. Therefore, according to the current measures and implementation efforts, Jilin Province can achieve good control of the virus's spread.

CONCLUSIONS

COVID-19 has a moderate transmissibility in Jilin Province, China. The interventions implemented in the province had proven effective; increasing social distancing and a rapid response by the prevention and control system will help control the spread of the disease.