Potential for global spread of a novel coronavirus from China

The important issue of awareness of disaster response to the COVID-19

This study aimed to analyze the community's disaster response awareness during the Covid-19 pandemic during the implementation of The Large-Scale Social Restrictions (LSSR) in Gresik. Self-awareness was observed using Peter L. Berger and Thomas Luck man's Social Construction Theory through a dialectical process of internalization, objectification, and externalization. The results showed that there had been no good awareness in efforts to prevent the spread of Covid-19 in Gresik. Socially, the community had not taken the dangers of Covid-19 seriously. There was also an inconsistency between knowledge and reality related to disaster response. In coping with the dialectical process, the community had not implemented a disaster-aware culture by obeying the existing regulations. At least, the sociocultural environment determined a person's construction for self-identification, interaction, and adjustment to the social changes that occurred. Hence, the sociocultural construction of the community had never made the disease outbreak a serious problem and considered it as well as God's reminder even though infected cases continued to increase. A situation was indeed difficult for the Task Force to succeed in the Large-Scale Social Restrictions (LSSR) to Community Activities Restrictions Enforcement (CARE) suppressed the increase of Covid-19 positive cases in Gresik, Indonesia. This research sees that the government's policies in handling Covid- 19 are not enough, it needs more optimal involvement of community and religious leaders, to provide education on the importance of maintaining health protocols and building self-awareness of the dangers of Covid.

Chest Physiotherapy Interventions for Children During SARS-COV-2 Pandemic

Since the first case of Severe Acute Respiratory Syndrome Coronavirus-2/Coronavirus Disease 2019 (SARS-COV-2/COVID-19) was discovered in Wuhan, China, it spread to vast limits globally and became a public health disaster, affecting nearly all countries around the globe. Along with mainstream medical treatment, alternative medicine desperately was the need of the hour for youngsters to manage their symptoms while being self-quarantined and ultimately to improve their chances of survival and recovery from COVID-19. Since the beginning of SARS-COV-2, few studies address the clinical-functional presentation of viral infection and management with physiotherapy for children. Major online electronic databases PubMed, PEDro, and Google Scholar were researched to identify, organize and commission the current review. To create a search strategy, Medical Subject Headings and Descriptors of Science and Health were utilized. The authors looked for other studies by screening the references list of the potentially pertinent papers. These computerized searches turned up studies and those studies' bibliographies with pertinent citations were examined. Personal protective equipment was a crucial component for protection and contact precaution. Following hypoxia, effective oxygen therapy is administered right away. When necessary, under the right circumstances, nasal high-flow oxygen therapy, non-invasive ventilation, lung-protective breathing methods, and prone positioning can be used. Children with SARS-CoV-2/COVID-19 may benefit from physiotherapy interventions with a focus on ventilatory management, airway clearance procedures, early activities, and mobilization.

Exposure to the Death of Others during the COVID-19 Pandemic: Growing Mistrust in Medical Institutions as a Result of Personal Loss

BACKGROUND AND AIMS

The prominence of death during the COVID-19 pandemic was heightened by the potential of personally knowing someone who lost their life to the virus. The terror management theory (TMT) suggests that the salient presence of death has a pronounced effect on behavior and may result in the ossification of beliefs and actions aligned with one's worldview (i.e., the mortality salience hypothesis). In this study, we evaluated how death exposure early in the COVID-19 pandemic could enact the process of firming up held beliefs and attitudes related to health and safety. Specifically, we tested the hypothesis that exposure to a personal loss during the pandemic would strengthen participants' baseline attitudes and behaviors regarding COVID-19 safety guidelines.

METHOD

Data were analyzed from a prospective, regional survey administered at two time points during the pandemic, June-July 2020 and May 2021, in five United States northeastern states. Baseline and follow-up surveys were administered approximately 12 months apart, with adherence to public guidance and death exposure measured at both timepoints and other safety measures at follow-up only.

FINDINGS

Our results indicated that there were significant main effects of death exposure on guideline adherence and support for COVID-related public policy. Contrary to the mortality salience hypothesis, death exposures after baseline were related to higher medical mistrust at follow-up for those high in adherence at baseline, rather than those with low adherence.

CONCLUSION

Our results offer some conflicting evidence to the mortality salience hypothesis. Rather than entrench people in their worldviews, death in the context of the COVID-19 pandemic appeared to sway people away from their initial stances. This finding has important implications for TMT literature and for the COVID-19 pandemic response.

The impact of COVID-19 infection before the vaccination era on the hospitalized patients requiring hemodialysis: a single-center retrospective cohort

Due to effective vaccinations, the COVID-19 (coronavirus disease 2019) infection that caused the pandemic has a milder clinical course. We aimed to assess the mortality of hospitalized COVID-19 patients before the vaccination era. We investigated the mortality in those patients between 1 October 2020 and 31 May 2021 who received hemodialysis treatment [patients with previously normal renal function (nCKD), patients with chronic kidney disease previously not requiring hemodialysis (CKDnonHD), chronic kidney disease (CKD), and patients on regular hemodialysis (pHD)]. In addition, participants were followed up for all-cause mortality in the National Health Service database until 1 December 2021. In our center, 83 of 108 (76.9%) were included in the analysis due to missing covariates. Over a median of 26 (interquartile range 11-266) days of follow-up, 20 of 22 (90.9%) of nCKD, 23 of 24 (95.8%) of CKDnonHD, and 17 of 37 (45.9%) pHD patients died (p < 0.001). In general, patients with nCKD had fewer comorbidities but more severe presentations. In contrast, the patients with pHD had the least severe symptoms (p < 0.001). In a model adjusted for independent predictors of all-cause mortality (C-reactive protein and serum albumin), CKDnonHD patients had increased mortality [hazard ratio (HR) 1.91, 95% confidence interval (CI), 1.02-3.60], while pHD patients had decreased mortality (HR 0.41, 95% CI 0.20-0.81) compared to nCKD patients. After further adjustment for the need for intensive care, the difference in mortality between the nCKD and pHD groups became non-significant. Despite the limitations of our study, it seems that the survival of previously hemodialysis patients was significantly better.

Maritime transportation and people mobility in the early diffusion of COVID-19 in Croatia

Introduction

The outbreak of COVID-19 in Europe began in early 2020, leading to the emergence of several waves of infection with varying timings across European countries. The largest wave of infection occurred in August-September. Croatia, known for being a hotspot of tourism in the Mediterranean region, raised concerns that it might have played a role in incubating the pandemic during the summer of 2020.

Methods

To investigate this possibility, we conducted a data-driven study to examine the potential influence of passenger mobility to and within Croatia, utilizing various modes of transportation. To achieve this, we integrated observational datasets into the "epidemic Renormalization Group" modeling framework.

Results

By comparing the models with epidemiological data, we found that in the case of Croatia in 2020, neither maritime nor train transportation played a prominent role in propagating the infection. Instead, our analysis highlighted the leading role of both road and airborne mobility in the transmission of the virus.

Discussion

The proposed framework serves to test hypotheses concerning the causation of infectious waves, offering the capacity to rule out unrelated factors from consideration.

Association of the corona virus (Covid-19) epidemic with environmental risk factors

The current outbreak of the novel coronavirus SARS-CoV-2 (coronavirus disease 2019; previously 2019-nCoV), epicenter in Hubei Province (Wuhan), People's Republic of China, has spread too many other countries. The transmission of the corona virus occurs when people are in the incubation stage and do not have any symptoms. Therefore, the role of environmental factors such as temperature and wind speed becomes very important. The study of Acute Respiratory Syndrome (SARS) indicates that there is a significant relationship between temperature and virus transmission and three important factors, namely temperature, humidity and wind speed, cause SARS transmission. Daily data on the incidence and mortality of Covid-19 disease were collected from World Health Organization (WHO) website and World Meter website (WMW) for several major cities in Iran and the world. Data were collected from February 2020 to September 2021. Meteorological data including temperature, air pressure, wind speed, dew point and air quality index (AQI) index are extracted from the website of the World Meteorological Organization (WMO), The National Aeronautics and Space Administration (NASA) and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Statistical analysis carried out for significance relationships. The correlation coefficient between the number of infected people in one day and the environmental variables in the countries was different from each other. The relationship between AQI and number of infected was significant in all cities. In Canberra, Madrid and Paris, a significant inverse relationship was observed between the number of infected people in one day and wind speed. There is a significant positive relationship between the number of infected people in a day and the dew point in the cities of Canberra, Wellington and Washington. The relationship between the number of infected people in one day and Pressure was significantly reversed in Madrid and Washington, but positive in Canberra, Brasilia, Paris and Wuhan. There was significant relationship between Dew point and prevalence. Wind speed showed a significant relationship in USA, Madrid and Paris. AQI was strongly associated with the prevalence of covid19. The purpose of this study is to investigate some environmental factors in the transmission of the corona virus.

Digital public health leadership in the global fight for health security

The COVID-19 pandemic highlighted the need to prioritise mature digital health and data governance at both national and supranational levels to guarantee future health security. The Riyadh Declaration on Digital Health was a call to action to create the infrastructure needed to share effective digital health evidence-based practices and high-quality, real-time data locally and globally to provide actionable information to more health systems and countries. The declaration proposed nine key recommendations for data and digital health that need to be adopted by the global health community to address future pandemics and health threats. Here, we expand on each recommendation and provide an evidence-based roadmap for their implementation. This policy document serves as a resource and toolkit that all stakeholders in digital health and disaster preparedness can follow to develop digital infrastructure and protocols in readiness for future health threats through robust digital public health leadership.

Does 2x2 airplane passenger contact tracing for infectious respiratory pathogens work? A systematic review of the evidence

We critically appraised the literature regarding in-flight transmission of a range of respiratory infections to provide an evidence base for public health policies for contact tracing passengers, given the limited pathogen-specific data for SARS-CoV-2 currently available. Using PubMed, Web of Science, and other databases including preprints, we systematically reviewed evidence of in-flight transmission of infectious respiratory illnesses. A meta-analysis was conducted where total numbers of persons on board a specific flight was known, to calculate a pooled Attack Rate (AR) for a range of pathogens. The quality of the evidence provided was assessed using a bias assessment tool developed for in-flight transmission investigations of influenza which was modelled on the PRISMA statement and the Newcastle-Ottawa scale. We identified 103 publications detailing 165 flight investigations. Overall, 43.7% (72/165) of investigations provided evidence for in-flight transmission. H1N1 influenza A virus had the highest reported pooled attack rate per 100 persons (AR = 1.17), followed by SARS-CoV-2 (AR = 0.54) and SARS-CoV (AR = 0.32), Mycobacterium tuberculosis (TB, AR = 0.25), and measles virus (AR = 0.09). There was high heterogeneity in estimates between studies, except for TB. Of the 72 investigations that provided evidence for in-flight transmission, 27 investigations were assessed as having a high level of evidence, 23 as medium, and 22 as low. One third of the investigations that reported on proximity of cases showed transmission occurring beyond the 2x2 seating area. We suggest that for emerging pathogens, in the absence of pathogen-specific evidence, the 2x2 system should not be used for contact tracing. Instead, alternate contact tracing protocols and close contact definitions for enclosed areas, such as the same cabin on an aircraft or other forms of transport, should be considered as part of a whole of journey approach.

Fighting cytokine storm and immunomodulatory deficiency: By using natural products therapy up to now

A novel coronavirus strain (COVID-19) caused severe illness and mortality worldwide from 31 December 2019 to 21 March 2023. As of this writing, 761,071,826 million cases have been diagnosed worldwide, with 6,879,677 million deaths accorded by WHO organization and has spread to 228 countries. The number of deaths is closely connected to the growth of innate immune cells in the lungs, mainly macrophages, which generate inflammatory cytokines (especially IL-6 and IL-1β) that induce "cytokine storm syndrome" (CSS), multi-organ failure, and death. We focus on promising natural products and their biologically active chemical constituents as potential phytopharmaceuticals that target virus-induced pro-inflammatory cytokines. Successful therapy for this condition is currently rare, and the introduction of an effective vaccine might take months. Blocking viral entrance and replication and regulating humoral and cellular immunity in the uninfected population are the most often employed treatment approaches for viral infections. Unfortunately, no presently FDA-approved medicine can prevent or reduce SARS-CoV-2 access and reproduction. Until now, the most important element in disease severity has been the host's immune response activation or suppression. Several medicines have been adapted for COVID-19 patients, including arbidol, favipiravir, ribavirin, lopinavir, ritonavir, hydroxychloroquine, chloroquine, dexamethasone, and anti-inflammatory pharmaceutical drugs, such as tocilizumab, glucocorticoids, anakinra (IL-1β cytokine inhibition), and siltuximab (IL-6 cytokine inhibition). However, these synthetic medications and therapies have several side effects, including heart failure, permanent retinal damage in the case of hydroxyl-chloroquine, and liver destruction in the case of remdesivir. This review summarizes four strategies for fighting cytokine storms and immunomodulatory deficiency induced by COVID-19 using natural product therapy as a potential therapeutic measure to control cytokine storms.

Knowledge, Attitudes, and Practices Toward COVID-19 Among Rural Residents of Hebei Province: A Cross-Sectional Survey

OBJECTIVE

Coronavirus disease (COVID-19) has spread worldwide due to high infectivity. The social sexual environment in rural areas of China and the weak basic medical facilities may affect the treatment and transmission of the disease. The aim of this study was to understand the knowledge, attitudes, and practices (KAP) related to COVID-19 among residents in rural areas experiencing the epidemic and the factors, to provide a basis for further epidemic prevention and control.

METHODS

The COVID-19 KAP of rural residents in Hebei Province was collected by the snowball sampling method. The COVID-19 KAP questionnaire was distributed on social platforms such as WeChat and QQ through a network questionnaire.

RESULTS

The overall level of COVID-19 KAP in rural residents was good, but in terms of knowledge, the correct rate of isolation was 73.2%, the correct rates of 2 disinfection items were 72.3% and 77.4%, and the correct rate of hand-washing was 70.7%; 54.5% residents felt panic; 81.0% disinfected household items; and 84.9% washed their hands correctly. Residents still needed to strengthen these aspects. A binary logistic analysis showed that age, education, and participation in training were factors affecting the level of COVID-19 KAP.

CONCLUSIONS

This study found that rural residents had good levels of COVID-19 KAP, but there were gaps in specific issues that warrant attention. We advocate training on COVID-19 for rural residents.

The impact of air travel on the precocity and severity of COVID-19 deaths in sub-national areas across 45 countries

Human travel fed the worldwide spread of COVID-19, but it remains unclear whether the volume of incoming air passengers and the centrality of airports in the global airline network made some regions more vulnerable to earlier and higher mortality. We assess whether the precocity and severity of COVID-19 deaths were contingent on these measures of air travel intensity, adjusting for differences in local non-pharmaceutical interventions and pre-pandemic structural characteristics of 502 sub-national areas on five continents in April-October 2020. Ordinary least squares (OLS) models of precocity (i.e., the timing of the 1st and 10th death outbreaks) reveal that neither airport centrality nor the volume of incoming passengers are impactful once we consider pre-pandemic demographic characteristics of the areas. We assess severity (i.e., the weekly death incidence of COVID-19) through the estimation of a generalized linear mixed model, employing a negative binomial link function. Results suggest that COVID-19 death incidence was insensitive to airport centrality, with no substantial changes over time. Higher air passenger volume tends to coincide with more COVID-19 deaths, but this relation weakened as the pandemic proceeded. Different models prove that either the lack of airports in a region or total travel bans did reduce mortality significantly. We conclude that COVID-19 importation through air travel followed a 'travel as spark' principle, whereby the absence of air travel reduced epidemic risk drastically. However, once some travel occurred, its impact on the severity of the pandemic was only in part associated with the number of incoming passengers, and not at all with the position of airports in the global network of airline connections.

Impacts of COVID-19 Restrictions on Regional and Local Air Quality Across Selected West African Cities

The emergence of COVID-19 brought with it panic and a sense of urgency causing governments to impose strict restrictions on human activities and vehicular movements. With anthropogenic emissions, especially waste management (domestic and municipal), traffic, and industrial activities, said to be a significant contributor to ambient air pollution, this study assessed the impacts of the imposed restrictions on the concentrations and size distribution of atmospheric aerosols and concentration of gaseous pollutants over West African subregion and seven major COVID-19 epicenters in the subregion. Satellite retrievals and reanalysis data sets were used to study the impact of the restrictions on Aerosol Optical Depth (AOD) and atmospheric concentrations NO₂, SO₂, CO, and O₃. The anomalies were computed for 2020 relative to 2017-2019 (the reference years). In 2020 relative to the reference years, for area-averaged AOD levels, there was a consequential mean percentage change between -6.7% ± 21.0% and 19.2% ± 27.9% in the epicenters and -10.1% ± 15.4% over the subregion. The levels of NO₂ and SO₂ also reduced substantially at the epicenters, especially during the periods when the restrictions were highly enforced. However, the atmospheric levels of CO and ozone increased slightly in 2020 compared to the reference years. This study shows that "a one cap fits all" policy cannot reduced the level of air pollutants and that traffic and industrial processes are not the predominant sources of CO in major cities in the subregion.

Covid-19: Early Cases and Disease Spread

The emergence and global spread of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is critical to understanding how to prevent or control a future viral pandemic. We review the tools used for this retrospective search, their limits, and results obtained from China, France, Italy and the USA. We examine possible scenarios for the emergence of SARS-CoV-2 in the human population. We consider the Chinese city of Wuhan where the first cases of atypical pneumonia were attributed to SARS-CoV-2 and from where the disease spread worldwide. Possible superspreading events include the Wuhan-based 7^th Military World Games on October 18–27, 2019 and the Chinese New Year holidays from January 25 to February 2, 2020. Several clues point to an early regional circulation of SARS-CoV-2 in northern Italy (Lombardi) as soon as September/October 2019 and in France in November/December 2019, if not before. With the goal of preventing future pandemics, we call for additional retrospective studies designed to trace the origin of SARS-CoV-2.

Lessons Learned from the COVID-19 Pandemic and How Blood Operators Can Prepare for the Next Pandemic

Humans interact with virus-infected animal hosts, travel globally, and maintain social networks that allow for novel viruses to emerge and develop pandemic potential. There are key lessons-learned from the coronavirus diseases 2019 (COVID-19) pandemic that blood operators can apply to the next pandemic. Warning signals to the COVID-19 pandemic included outbreaks of Severe acute respiratory syndrome-related coronavirus-1 (SARS-CoV-1) and Middle East respiratory syndrome-related coronavirus (MERS-CoV) in the prior two decades. It will be critical to quickly determine whether there is a risk of blood-borne transmission of a new pandemic virus. Prior to the next pandemic blood operators should be prepared for changes in activities, policies, and procedures at all levels of the organization. Blood operators can utilize “Plan-Do-Study-Act” cycles spanning from: vigilance for emerging viruses, surveillance activities and studies, operational continuity, donor engagement and trust, and laboratory testing if required. Occupational health and donor safety issues will be key areas of focus even if the next pandemic virus is not transfusion transmitted. Blood operators may also be requested to engage in new activities such as the development of therapeutics or supporting public health surveillance activities. Activities such as scenario development, tabletop exercises, and drills will allow blood operators to prepare for the unknowns of the next pandemic.

A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological drivers

COVID-19 pandemic has become a global major public health concern. Examining the meteorological risk factors and accurately predicting the incidence of the COVID-19 pandemic is an extremely important challenge. Therefore, in this study, we analyzed the relationship between meteorological factors and COVID-19 transmission in SAARC countries. We also compared the predictive accuracy of Autoregressive Integrated Moving Average (ARIMAX) and eXtreme Gradient Boosting (XGBoost) methods for precise modelling of COVID-19 incidence. We compiled a daily dataset including confirmed COVID-19 case counts, minimum and maximum temperature (°C), relative humidity (%), surface pressure (kPa), precipitation (mm/day) and maximum wind speed (m/s) from the onset of the disease to January 29, 2022, in each country. The data were divided into training and test sets. The training data were used to fit ARIMAX model for examining significant meteorological risk factors. All significant factors were then used as covariates in ARIMAX and XGBoost models to predict the COVID-19 confirmed cases. We found that maximum temperature had a positive impact on the COVID-19 transmission in Afghanistan (β = 11.91, 95% CI: 4.77, 19.05) and India (β = 0.18, 95% CI: 0.01, 0.35). Surface pressure had a positive influence in Pakistan (β = 25.77, 95% CI: 7.85, 43.69) and Sri Lanka (β = 411.63, 95% CI: 49.04, 774.23). We also found that the XGBoost model can help improve prediction of COVID-19 cases in SAARC countries over the ARIMAX model. The study findings will help the scientific communities and policymakers to establish a more accurate early warning system to control the spread of the pandemic.

The Shopping Behavior of International Students in Poland during COVID-19 Pandemic

The purpose of this research is to analyze the shopping behavior of international students (Asian vs. European) studying in Poland. Participants were recruited from universities located in Warsaw between June and September 2020. A total of 806 questionnaires were collected, 87 of which were eliminated due to non-response. The research sample consisted of 719 people. We conducted an exploratory factor analysis and cluster analysis for the entire study population and separately for European and Asian students. In exploratory factor analysis, two factors were extracted for the entire population, while three factors each were extracted for the European and Asian student groups. In cluster analysis, we obtained four clusters each for the entire study population and the group of European and Asian students. Our study found that among Asian students, compared to European students, there was a greater change in shopping behavior during the COVID-19 pandemic, expressed by a greater preference for online shopping, greater purchases of fruits and vegetables, purchases of local products, and shorter shopping time.

COVID-19 vaccine hesitancy among pregnant women: a systematic review and meta-analysis

OBJECTIVE

The aim of this study was to perform a systematic review and meta-analysis to estimate the vaccines' acceptance level and to find the factors influencing pregnant women's vaccination decisions, with the goal of assisting in the development of interventions and promoting more research in this area.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, Embase, CINAHL and PubMed.

ELIGIBILITY CRITERIA

Studies providing any kind of quantitative assessment of overall COVID-19 vaccination acceptance among pregnant women in any country or region across the globe.

DATA EXTRACTION AND SYNTHESIS

The pooled prevalence of COVID-19 vaccine acceptance among pregnant women was calculated using the random-effects model. Subgroup (sensitivity) analysis was performed to determine the overall COVID-19 vaccine acceptance level to understand the sources of substantial heterogeneity.

RESULTS

Out of the 375 studies identified, 17 studies from four continents assessing 25 147 participants (pregnant women) were included in this study. Among the participants, only 49% (95% CI 42% to 56%, p<0.001) had COVID-19 vaccine acceptance. High-income countries (47%; 95% CI 38% to 55%, p<0.001), participants with fewer than 12 years of education (38%; 95% CI 19% to 58%, p<0.001) and multiparous women (48%; 95% CI 31% to 66%, p<0.001) had lower COVID-19 vaccine acceptance. Overall heterogeneity was high (I² ≥98%), and publication bias was present (p<0.001). A very weak positive correlation between COVID-19 knowledge and COVID-19 vaccine acceptance was observed (r=0.164; 95% CI -0.946 to 0.972; p=0.8359).

CONCLUSION

Overall, COVID-19 vaccine acceptance among pregnant women was low across the studies and considerably low among some specific subgroups of participants. These research findings have implications for the development of effective interventions that could increase the COVID-19 vaccine acceptance level among pregnant women to attain herd immunity.

PROSPERO REGISTRATION NUMBER

CRD42021277754.

How Has the COVID-19 Pandemic Influenced the Tourism Behaviour of International Students in Poland?

Nearly 20 years after the SARS (Severe Acute Respiratory Syndrome) epidemic, we are facing another COVID-19 pandemic. Therefore, the aim of our study was to analyse the impact of the COVID-19 pandemic on the tourism behaviour of international students in Poland. We paid attention to the overall impact of the pandemic on life, travel, choice of tourist destination, tourism activity, ecotourism preference, and health and safety issues. We formulated two research questions: What areas of international student tourism behaviour were affected by the COVID-19 pandemic? What differences in travel behaviour occurred between international students from Europe and Asia? Participants were recruited from universities located in Warsaw between June and September 2020. A total of 806 questionnaires were collected, 87 of which were eliminated due to non-response. The research sample consisted of 719 people. Six factors were identified in the survey results: tourism inclination, impact on tourist destination, hygiene and accommodation, impact on life, impact on tourism, and mode of tourism. Impact on life and impact on tourism were attributed to the general impact dimension; tourism inclination and mode of tourism can be summarized as attitude and preference. Food and accommodation were assigned to hygiene and safety dimensions. In almost all aspects, the impact of the COVID-19 pandemic on people’s lives was greater for Asian respondents. Asian respondents were more likely to say that they would avoid COVID-19-affected areas when choosing tourist destinations in the future, and avoid travelling to crowded large cities after COVID-19 ended. European survey participants’ responses were more moderate.

Epidemic trend analysis of SARS-CoV-2 in South Asian Association for Regional Cooperation countries using modified susceptible-infected-recovered predictive model

A novel coronavirus causing the severe and fatal respiratory syndrome was identified in China, is now producing outbreaks in more than 200 countries around the world, and became pandemic by the time. In this article, a modified version of the well-known mathematical epidemic model susceptible-infected-recovered (SIR) is used to analyze the epidemic's course of COVID-19 in eight different countries of the South Asian Association for Regional Cooperation (SAARC). To achieve this goal, the parameters of the SIR model are identified by using publicly available data for the corresponding countries: Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka. Based on the prediction model, we estimated the epidemic trend of COVID-19 outbreak in SAARC countries for 20, 90, and 180 days, respectively. A short-mid-long term prediction model has been designed to understand the early dynamics of the COVID-19 epidemic in the southeast Asian region. The maximum and minimum basic reproduction numbers (R 0 = 1.33 and 1.07) for SAARC countries are predicted to be in Pakistan and Bhutan. We equate simulation results with real data in the SAARC countries on the COVID-19 outbreak, and predicted different scenarios using the modified SIR prediction model. Our results should provide policymakers with a method for evaluating the impacts of possible interventions, including lockdown and social distancing, as well as testing and contact tracking.

Hospitalized COVID-19 Patients with Severe Acute Respiratory Syndrome: A Population-Based Registry Analysis to Assess Clinical Findings, Pharmacological Treatment and Survival

Background and Objectives: One of the most serious clinical outcomes in hospitalized patients with COVID-19 is severe acute respiratory syndrome (SARS). The aim is to analyze pharmacological treatment, survival and the main mortality predictors. Materials and Methods: A real-world data study from COVID-19-hospitalized patients with SARS from 1 March to 31 May 2020 has been carried out. Variables such as hospital length of stay, ventilation type and clinical outcomes have been taken into account. Results: In Castile and Leon, 14.03% of the 7307 in-hospital COVID-19 patients developed SARS, with a mortality rate of 42.53%. SARS prevalence was doubled in males compared to females, and 78.54% had an age of 65 years or more. The most commonly used medicines were antibiotics (89.27%), antimalarials (68.1%) and corticosteroids (55.9%). Survival of patients developing SARS was lower compared to patients without this complication (12 vs. 13 days). The main death predictors were disseminated intravascular coagulation (DIC) (OR: 13.87) and age (>65 years) (OR: 7.35). Conclusions: Patients older than 65 years who develop DIC have a higher probability of hospital death. Tocilizumab and steroids have been linked to a lower incidence of hospital death, being the main treatment for COVID-19 hospitalized patients with SARS.

Development of a nomogram to assess the impact of the myocardial injury on the prognosis of COVID-19 patients

Coronavirus disease 2019 (COVID-19) has been spreading worldwide. Many COVID-19 patients were accompanied by myocardial injury during the course of the disease. To evaluate the association of cardiac injury with clinical outcomes in COVID-19 patients, we recruited 261 COVID-19 cases admitted to Tongji Hospital of Huazhong University of Science and Technology in this study. Compared with patients without myocardial injury, those with myocardial injury were older, with shorter hospital stays and lower survival rates. They also had higher levels of inflammatory biomarkers (Interleukin-6,8,10 and C-reactive protein), coagulation biomarkers, liver and kidney function markers. Kaplan-Meier analysis demonstrated that patients with myocardial injury had a higher mortality rate. The multivariate Cox regression model and the nomogram revealed that myocardial injury, co-morbidity, and abnormal procalcitonin (PCT) levels were independent risk factors of the mortality of COVID-19 patients. The linear correlation analysis and the ROC curve suggested a predictive value of the neutrophil-lymphocyte ratio (NLR) in cardiac injury. Summarily, myocardial injury in COVID-19 patients is associated with a higher mortality risk. Attention should be paid to monitoring myocardial injury in patients with significantly elevated myocardial markers and NLR at admission.

Ten GIS-Based Solutions for Managing and Controlling COVID-19 Pandemic Outbreak

The coronavirus (COVID-19) pandemic has caused disastrous results in most countries of the world. It has rapidly spread across the globe with over 156 million cumulative confirmed cases and 3.264 million deaths to date, according to World Health Organization (WHO) Coronavirus Disease (COVID-19) Dashboard. With these huge amounts of causalities in the world, Geographic Information Systems (GIS) as a computer-based analyzer could help governments, experts, medical staff, and citizens to prevent and respond to the incidence. On the other hand, the COVID-19 pandemic involves many unknown parameters where most of them have a spatial dimension. Thus, spatial analysis and GIS could provide appropriate decision-making tools, predictive models, statistical methods, and new technologies for COVID-19 outbreak control, also help the people for avoiding direct contact and preserving social distance. This article aims to review the most promising categories of GIS-based solutions in this domain. We divided the solutions into ten classes including spatio-temporal analysis, SDSS approaches, geo-business, context-aware recommendation systems, participatory GIS and volunteered geographic information (VGI), internet of things (IoT), location-based service (LBS), web mapping, satellite imagery-based analysis, and waste management. The main contribution of this paper is proposing different geospatial guidelines that could provide reliable and useful protocols for COVID-19 outbreak control to minimize causalities, restrict incidence, establish effective urban communication, provide new approaches for business in lockdown situations, telehealth treatment, patient monitoring, adaptive decision making, and visualize trend analysis.

Implication of in silico studies in the search for novel inhibitors against SARS-CoV-2

Corona Virus Disease-19 (COVID-19) is a pandemic disease mainly caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It had spread from Wuhan, China, in late 2019 and spread over 222 countries and territories all over the world. Earlier, at the very beginning of COVID-19 infection, there were no approved medicines or vaccines for combating this disease, which adversely affected a lot of individuals worldwide. Although frequent mutation leads to the generation of more deadly variants of SARS-CoV-2, researchers have developed several highly effective vaccines that were approved for emergency use by the World Health Organization (WHO), such as mRNA-1273 by Moderna, BNT162b2 by Pfizer/BioNTech, Ad26.COV2.S by Janssen, AZD1222 by Oxford/AstraZeneca, Covishield by the Serum Institute of India, BBIBP-CorV by Sinopharm, coronaVac by Sinovac, and Covaxin by Bharat Biotech, and the first US Food and Drug Administration-approved antiviral drug Veklury (remdesivir) for the treatment of COVID-19. Several waves of COVID-19 have already occurred worldwide, and good-quality vaccines and medicines should be available for ongoing as well as upcoming waves of the pandemic. Therefore, in silico studies have become an excellent tool for identifying possible ligands that could lead to the development of safer medicines or vaccines. Various phytoconstituents from plants and herbs with antiviral properties are studied further to obtain inhibitors of SARS-CoV-2. In silico screening of various molecular databases like PubChem, ZINC, Asinex Biol-Design Library, and so on has been performed extensively for finding effective ligands against targets. Herein, in silico studies carried out by various researchers are summarized so that one can easily find the best molecule for further in vitro and in vivo studies.

Are leading urban centers predisposed to global risks- A analysis of the global south from COVID-19 perspective

COVID-19 initially spread among prominent global cities and soon to the urban centers of countries across the globe. While cities are the hotbeds of activities, they also seem highly exposed to global risks including the pandemic. Using the case of COVID-19 and the World Risk Index framework, this paper examines if the leading cities from the global south are inherently vulnerable and exposed to global risks and can they exacerbate the overall risk of their respective nations. Compared against their respective national averages, most of the 20 cities from 10 countries analyzed in this paper, have higher exposure, lower adaptive capacity, higher coping capacity and varied susceptibility. As this relative understanding is based on respective national averages which are often lower than the global standards, even high performance on certain indicators may still result in elevated predisposition. This paper concludes that the leading urban centers from the global south are highly likely to be predisposed to global risks due to their inherent vulnerability and exposure, and many of the drivers of this predisposition are related to the process of urbanization itself. This predisposition can enhance the overall exposure and vulnerability of the nation in which they are located.

Correlation between vaccine coverage and the COVID‐19 pandemic throughout the world: based on real‐world data

The aim of the study was to examine the correlation between COVID‐19 vaccine coverage rates and outcomes of the COVID‐19 epidemic in the case of COVID‐19 variants based on real‐world data. The data came from Our World in Data, which is building the international COVID‐19 vaccination data set and is an open‐source data set for everyone to use. The vaccination data set uses the most recent official numbers from governments and health ministries worldwide. We assessed the correlation between COVID‐19 vaccine coverage rates and outcomes of the COVID‐19 epidemic with existing variants by performing temporal analysis and spatial analysis. Overall, new cases per million population, the reproduction rate of COVID‐19, new deaths from all causes per million population, excess mortality attributed to COVID‐19 pandemic, and hospital patients or intensive care unit (ICU) patients per million population were not decreased with the time course. However, at the same time point, new cases per million population, the reproduction rate of COVID‐19, new deaths per million population, and hospital patients or ICU patients per million population gradually decreased as the rate of vaccination coverage increased. High coverage percentages of COVID‐19 vaccination were negatively correlated with the reproduction rate of COVID‐19 (correlation coefficient −0.116) and ICU patients per million of the local population (correlation coefficient −0.055). Currently, there is no effective treatment for the COVID‐19 pandemic, and prevention of the COVID‐19 pandemic mainly depends on vaccines, especially when the rate of COVID‐19 vaccine coverage is over 60%. The benefits of preventing severe disease and preventing transmission of infection are likely to be obvious.

(1)

Our research suggested that a high rate of COVID‐19 vaccine coverage was negatively correlated with the reproduction rate and intensive care unit patients per million.

(2)

Our research mainly strengthens the belief that COVID‐19 vaccine coverage could prevent severe disease and prevent transmission of infection in the case of COVID‐19 variants, especially when the rate of COVID‐19 vaccine coverage was over 60%.

Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019–2020 Flu Season: A Retrospective Longitudinal Study

Background. Previous studies examining the early spread of COVID-19 have used influenza-like illnesses (ILIs) to determine the early spread of COVID-19. We used COVID-19 case definition to identify COVID-like symptoms (CLS) independently of other influenza-like illnesses (ILIs). Methods. Using data from Emergency Department (ED) visits at VA Medical Centers in CA, TX, and FL, we compared weekly rates of CLS, ILIs, and non-influenza ILIs encounters during five consecutive flu seasons (2015–2020) and estimated the risk of developing each illness during the first 23 weeks of the 2019–2020 season compared to previous seasons. Results. Patients with CLS were significantly more likely to visit the ED during the first 23 weeks of the 2019–2020 compared to prior seasons, while ED visits for influenza and non-influenza ILIs did not differ substantially. Adjusted CLS risk was significantly lower for all seasons relative to the 2019–2020 season: RR15–16 = 0.72, 0.75, 0.72; RR16–17 = 0.81, 0.77, 0.79; RR17–18 = 0.80, 0.89, 0.83; RR18–19 = 0.82, 0.96, 0.81, in CA, TX, and FL, respectively. Conclusions. The observed increase in ED visits for CLS indicates the likely spread of COVID-19 in the US earlier than previously reported. VA data could potentially help identify emerging infectious diseases and supplement existing syndromic surveillance systems.

Impact of lockdown and crop stubble burning on air quality of India: a case study from wheat-growing region

The emergence of COVID-19 has brought the entire planet to a halt. Many countries, including India, were compelled to shut down most urban, industrial, social and other activities as a result of the pandemic. Due to a series of complete lockdowns imposed in India from March 24 to May 17, 2020, and state-wise local level restrictions afterward, have resulted in significant reduction of emissions of numerous atmospheric pollutants. The objective of this study is to analyse the change in concentration of various pollutants such as nitrogen oxide (NO₂), carbon monoxide (CO) and aerosol optical depth (AOD) due to lockdown and also to quantify the contribution of crop stubble burning to air pollution. The Sentinel-5P based NO₂ and CO observations for 2019 and 2020 and Moderate Resolution Imaging Spectroradiometer (MODIS)-based AOD observations for 2016-2020 were used for detecting the variations. The obtained results showed a significant decrease in NO₂ levels during various stages of lockdown. Small decrease in CO levels was observed across most part of the India. With a few exceptions, such as coastal and desert regions, there was a moderate decrease in AOD levels. Furthermore, to study the contribution of NO₂, CO and AOD from crop stubble burning, MODIS observations on active fire events were obtained from Visible Infrared Imaging Radiometer Suite (VIIRS). The burning of crop stubble increased NO₂ emissions by 22 to 80%. CO levels, on the other hand, have risen by 7 to 25%. A considerable variation in AOD was reported, ranging from 1 to 426%.

Classi-Fly: Inferring Aircraft Categories from Open Data

In recent years, air traffic communication data has become easy to access, enabling novel research in many fields. Exploiting this new data source, a wide range of applications have emerged, from weather forecasting to stock market prediction, or the collection of intelligence about military and government movements. Typically, these applications require knowledge about the metadata of the aircraft, specifically its operator and the aircraft category.

armasuisse Science + Technology , the R&D agency for the Swiss Armed Forces, has been developing Classi-Fly, a novel approach to obtain metadata about aircraft based on their movement patterns. We validate Classi-Fly using several hundred thousand flights collected through open source means, in conjunction with ground truth from publicly available aircraft registries containing more than 2 million aircraft. We show that we can obtain the correct aircraft category with an accuracy of greater than 88%. In cases, where no metadata is available, this approach can be used to create the data necessary for applications working with air traffic communication. Finally, we show that it is feasible to automatically detect particular sensitive aircraft such as police and surveillance aircraft using this method.

Liver function in COVID-19 infection

Coronavirus disease 2019 (COVID-19) disease affects multiple organs, including anomalies in liver function. In this review we summarize the knowledge about liver injury found during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with special attention paid to possible mechanisms of liver damage and abnormalities in liver function tests allowing for the evaluation of the severity of liver disease. Abnormalities in liver function observed in COVID-19 disease are associated with the age and sex of patients, severity of liver injury, presence of comorbidity and pre-treatment. The method of antiviral treatment can also impact on liver function, which manifests as increasing values in liver function tests. Therefore, analysis of variations in liver function tests is necessary in evaluating the progression of liver injury to severe disease.

Potential Contribution of Climate Conditions on COVID-19 Pandemic Transmission over West and North African Countries

COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a very contagious disease that has killed many people worldwide. According to data from the World Health Organization (WHO), the spread of the disease appears to be slower in Africa. Although several studies have been published on the relationship between meteorological parameters and COVID-19 transmission, the effects of climate conditions on COVID-19 remain largely unexplored and without consensus. However, the transmission of COVID-19 and sensitivity to climate conditions are also not fully understood in Africa. Here, using available epidemiological data over 275 days (i.e., from 1 March to 30 November 2020) taken from the European Center for Disease Prevention and Control of the European Union database and daily data of surface air temperature specific humidity and water vapor from the National Center for Environmental Prediction (NCEP), this paper investigates the potential contribution of climate conditions on COVID-19 transmission over 16 selected countries throughout three climatic regions of Africa (i.e., Sahel, Maghreb, and Gulf of Guinea). The results highlight statistically significant inverse correlations between COVID-19 cases and temperature over the Maghreb and the Gulf of Guinea regions. In contrast, positive correlations are found over the Sahel area, especially in the central part, including Niger and Mali. Correlations with specific humidity and water vapor parameters display significant and positive values over the Sahelian and the Gulf of Guinea countries and negative values over the Maghreb countries. Then, the COVID-19 pandemic transmission is influenced differently across the three climatic regions: (i) cold and dry environmental conditions over the Maghreb; (ii) warm and humid conditions over the Sahel; and (iii) cold and humid conditions over the Gulf of Guinea. In addition, for all three climatic regions, even though the climate impact has been found to be significant, its effect appears to display a secondary role based on the explanatory power variance compared to non-climatic factors assumed to be dominated by socio-economic factors and early strong public health measures.

Teleaudiology practice in COVID-19 pandemic in Egypt and Saudi Arabia

Objective

To evaluate the audiologists’ attitudes and practice towards teleaudiology, as well as to assess the audiological services provided in Egypt and Saudi Arabia during the COVID-19 pandemic.

Methods

A cross sectional study was conducted among 112 audiologists who were recruited through convenience sampling . Multinomial logistic regression was used to test the association between practice of tele audiology as a dependent variable and some independent variables.

Results

25.4% of the studied sample were practicing tele audiology. Participants’ age and attitude toward telemedicine were the independent predictors of tele audiology practice at p value ≤ 0.05.

Conclusion

The tele audiology practice is essential. Therefore, raising the knowledge of audiologist about the great value of practicing tele audiology is very important, infrastructure, equipment, and technology especially telecommunication should be improved and facilitated for both audiologist and patients.

Recent Advances in Aptasensor for Cytokine Detection: A Review

Cytokines are proteins secreted by immune cells. They promote cell signal transduction and are involved in cell replication, death, and recovery. Cytokines are immune modulators, but their excessive secretion causes uncontrolled inflammation that attacks normal cells. Considering the properties of cytokines, monitoring the secretion of cytokines in vivo is of great value for medical and biological research. In this review, we offer a report on recent studies for cytokine detection, especially studies on aptasensors using aptamers. Aptamers are single strand nucleic acids that form a stable three-dimensional structure and have been receiving attention due to various characteristics such as simple production methods, low molecular weight, and ease of modification while performing a physiological role similar to antibodies.

Level of resilience in nurses working at COVID-19 referral centers in Iran

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has led many healthcare systems to become overwhelmed, and caused many frontline providers to feel fatigued and exhausted and experience severe emotional trauma. Nurses are the largest group of the world's frontline providers and it is clear that their resilience to threatening factors is critical in the current crisis. Therefore, the purpose of this study was to determine the level of resilience in nurses working in COVID-19 centers in Iran.

METHODS

A cross-sectional study was conducted with 250 nurses working at three COVID-19 centers in northwest Iran. The participants were recruited using simple random sampling. The Connor-Davidson Resilience Scale was used to collect the data.

RESULTS

The highest level of resilience was related to spiritual influences, while the lowest was the trust in their instincts and tolerance of negative emotions. Furthermore, the level of resilience was significantly higher in nurses with better family support (p < 0.01).

CONCLUSION

Given the role of resilience in nurses' mental health, it is vital to support the nursing staff in critical situations and improve their resilience by focusing particularly on psychological and spiritual support.

Clinical Features of Early Stage COVID-19 in a Primary Care Setting

Background: The coronavirus disease 2019 (COVID-19) pandemic remains a global healthcare crisis. Nevertheless, the majority of COVID-19 cases involve mild to moderate symptoms in the early stages. The lack of information relating to these cases necessitates further investigation.

Methods: Patients visiting the outpatient clinic at the Kamagaya General Hospital were screened by interview and body temperature check. After initial screening, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was suspected in 481 patients who then underwent blood tests and the loop-mediated isothermal amplification (LAMP) test for SARS-CoV-2. Clinical characteristics between positive and negative SARS-CoV-2 groups were compared. Further, the novel predictive value of routine blood test results for SARS-CoV-2 infection was evaluated using ROC analysis.

Results: A total of 15,560 patients visited our hospital during the study period. After exclusion and initial screening by interview, 481 patients underwent the LAMP test and routine blood tests. Of these patients, 69 (14.3%) were positive for SARS-CoV-2 and diagnosed with COVID-19 (positive group), and 412 (85.7%) were negative (negative group). The median period between the first onset of symptoms and visit to our hospital was 3.4 and 2.9 days in the negative and positive groups, respectively. Cough (p = 0.014), rhinorrhea (p = 0.039), and taste disorders (p < 0.001) were significantly more common in the positive group, while gastrointestinal symptoms in the negative group (p = 0.043). The white blood cell count (p < 0.001), neutrophil count (p < 0.001), and percentage of neutrophils (p < 0.001) were higher in the negative group. The percentage of monocytes (p < 0.001) and the levels of ferritin (p < 0.001) were higher in the positive group. As per the predictive values for COVID-19 using blood tests, the values for the area under the curve for the neutrophil-to-monocyte ratio (NMR), white blood cell-to-hemoglobin ratio (WHR), and the product of the two (NMWH) were 0.857, 0.837, and 0.887, respectively.

Conclusion: Symptoms in early stage COVID-19 patients were similar to those in previous reports. Some blood test results were not consistent with previous reports. NMR, WHR, and NMWH are novel diagnostic scores in early-stage mild-symptom COVID-19 patients in primary care settings.

COVID-19 pandemic and potential of artificial intelligence

OBJECTIVE

To evaluate the potential of artificial intelligence in combating COVID-19 pandemic.

METHODS

PubMed, Embase, Cochrane Library and Google Scholar were searched for the term "Artificial intelligence and COVID-19" up to March 31, 2021.

RESULTS

Artificial intelligence (AI) is a potential tool to contain the current pandemic. AI can be used in many fields such as early detection and respective diagnosis, supervision of treatment, projection of cases and mortality, contact tracing of individuals, development of drugs and vaccines, reduces workload on health workers, prevention of disease, analysis of mental health of people amid pandemic.

CONCLUSIONS

AI is being updated and being improved, second by second to be able to interpret like actual human minds. This advancement in AI may lead to a completely different future of COVID-19 pandemic where most of the simpler works may be done by AI and only essential works could be done by health workers in order to increase patient care in current scenario of COVID-19 outbreak. But again one of the main constraint is of limited trustworthy and noise free sources of information. So the need for the hour is to make a free data system where most of the analysed data could be available to feed AI, which could effectively halt the current pandemic.

Liver abscess with necrosis in post COVID-19: A case report

INTRODUCTION

Coronavirus disease 2019 (COVID-19) is an acute respiratory tract infection caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2). Recent evidences mentioned the possibility of COVID-19 as a systemic infectious and inflammatory disease. Signs and symptoms of liver and gastrointestinal system are often found in post-acute COVID-19 patients. However, there are only few data found about liver abscess and necrosis in post COVID-19 patients.

CASE PRESENTATION

A 49-year-old man admitted to the hospital with dyspnea, nausea, loss of appetite and epigastric pain, post confirmed SARS CoV-2 severe pneumonia 1 month ago in ICU with noninvasive ventilator (NIV), enoxaparin, tocilizumab, azithromycin, levofloxacin, hydroxychloroquine, and no preexisting liver condition. Swab PCR result was negative. The result of abdominal computed tomography (CT) scan with contrast was liver abscess formation with hemorrhages measuring about 16 × 12 × 11 cm & 10 × 9x9 cm occupying most of the right lobe liver. The patient underwent exploratory laparotomy, there were multiple liver abscesses in segment 8 with parenchymal liver necrosis and abscesses in segment 7 of liver. Necrosectomy and liver abscess drainage was performed.

CLINICAL DISCUSSION

Pathophysiology of liver damage in post COVID-19 are direct cytotoxicity of SARS-CoV2, immune-mediated due to severe systemic inflammatory response syndrome (SIRS) in COVID-19, hypoxemia, vascular changes due to coagulopathy, endothelitis or congestion from right heart failure, and drug-induced liver injury (DILI).

CONCLUSION

The possible pathophysiology of liver abscess and necrosis in post COVID-19 should be considered in monitoring and management for both COVID-19 patients and post COVID-19 patients.

Pandemic Analytics: How Countries are Leveraging Big Data Analytics and Artificial Intelligence to Fight COVID-19?

Emergence of coronavirus in December 2019 and its spread across the world in the following months has made it a global health concern. The uncertainty about its evolution, transmission and effect of SARS-CoV-2, has left the countries and their governments in a worrisome state. Ambiguity about the strategies that would work towards mitigating the impact of virus has prompted them to use data-driven methods. Several countries started applying big data and advanced analytics technology for management of the crisis. This study aims to understand how different nations have employed analytics to deal with COVID-19. This paper reviews various strategies employed by different governments and organizations across nations that use advanced analytics to tackle pandemic. In the current emergency of corona virus, there have been several measures that organizations have taken to mitigate its impact, thanks to the evolution of computing technology. Big data and analytical tools provide various solutions like detection of existing COVID-19 cases, prediction of future outbreak, anticipation of potential preventive and therapeutic agents, and assistance in informed decision-making. This review discusses the big data analytics and artificial intelligence approaches that policy makers, researchers, epidemiologists and private organizations have adopted. By examining the different ways and areas where data analytics has been utilized, this study provides the other nations with the progressive scheme to address the pandemic.

Prognostic Role and Diagnostic Power of Seven Indicators in COVID-19 Patients

The prognostic role and diagnostic ability of coronavirus disease 2019 (COVID-19) disease indicators are not elucidated, thus, the current study aimed to investigate the prognostic role and diagnostic ability of several COVID-19 disease indicators including the levels of oxygen saturation, leukocytes, lymphocytes, albumin, C-reactive protein (CRP), interleukin-6 (IL-6), and D-dimer in patients with COVID-19. The levels of oxygen saturation, lymphocytes, and albumin were significantly higher in the common and severe clinical type patients compared with those in critical type patients. However, levels of leukocytes, CRP, IL-6, and D-dimer were significantly lower in the common and severe type patients compared with those in critical type patients (P < 0.001). Moreover, the current study demonstrated that the seven indicators have good diagnostic and prognostic powers in patients with COVID-19. Furthermore, a two-indicator (CRP and D-dimer) prognostic signature in training and testing datasets was constructed and validated to better understand the prognostic role of the indicators in COVID-19 patients. The patients were classified into high-risk and low-risk groups based on the median-risk scores. The findings of the Kaplan–Meier curve analysis indicated a significant divergence between the high-risk and low-risk groups. The findings of the receiver operating curve (ROC) analysis indicated the good performance of the signature in the prognosis prediction of COVID-19. In addition, a nomogram was constructed to assist clinicians in developing clinical decision-making for COVID-19 patients. In conclusion, the findings of the current study demonstrated that the seven indicators are potential diagnostic markers for COVID-19 and a two-indicator prognostic signature identification may improve clinical management for COVID-19 patients.

In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: an approach to prevent virus assembly

Currently, there is no specific treatment to cure COVID-19. Many medicinal plants have antiviral, antioxidant, antibacterial, antifungal, anticancer, wound healing etc. Therefore, the aim of the current study was to screen for potent inhibitors of N-terminal domain (NTD) of nucleocapsid phosphoprotein of SARS-CoV-2. The structure of NTD of RNA binding domain of nucleocapsid phosphoprotein of SARS coronavirus 2 was retrieved from the Protein Data Bank (PDB 6VYO) and the structures of 100 different phytocompounds were retrieved from Pubchem. The receptor protein and ligands were prepared using Schrodinger's Protein Preparation Wizard. Molecular docking was done by using the Schrodinger's maestro 12.0 software. Drug likeness and toxicity of active phytocompounds was predicted by using Swiss adme, admetSAR and protox II online servers. Molecular dynamic simulation of the best three protein- ligand complexes (alizarin, aloe-emodin and anthrarufin) was performed to study the interaction stability. We have identified three potential active sites (named as A, B, C) on receptor protein for efficient binding of the phytocompounds. We found that, among 100 phytocompounds, emodin, aloe-emodin, anthrarufin, alizarine, and dantron of Rheum emodi showed good binding affinity at all the three active sites of RNA binding domain of nucleocapsid phosphoprotein of COVID-19.The binding energies of emodin, aloe-emodin, anthrarufin, alizarine, and dantron were -8.299, -8.508, -8.456, -8.441, and -8.322 Kcal mol^-1 respectively (site A), -7.714, -6.433, -6.354, -6.598, and -6.99 Kcal mol^-1 respectively (site B), and -8.299, 8.508, 8.538, 8.841, and 8.322 Kcal mol^-1 respectively (site C). All the active phytocompounds follows the drug likeness properties, non-carcinogenic, and non-toxic. Theses phytocompounds (alone or in combination) could be developed into effective therapy against COVID-19. From MD simulation data, we found that all three complexes of 6VYO with alizarin, aloe-emodin and anthrarufin were stable up to 50 ns. These phytocompounds can be tested further for in vitro or in vivo and used as a potential drug to cure SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: an approach to prevent virus assembly

Currently, there is no specific treatment to cure COVID-19. Many medicinal plants have antiviral, antioxidant, antibacterial, antifungal, anticancer, wound healing etc. Therefore, the aim of the current study was to screen for potent inhibitors of N-terminal domain (NTD) of nucleocapsid phosphoprotein of SARS-CoV-2. The structure of NTD of RNA binding domain of nucleocapsid phosphoprotein of SARS coronavirus 2 was retrieved from the Protein Data Bank (PDB 6VYO) and the structures of 100 different phytocompounds were retrieved from Pubchem. The receptor protein and ligands were prepared using Schrodinger's Protein Preparation Wizard. Molecular docking was done by using the Schrodinger's maestro 12.0 software. Drug likeness and toxicity of active phytocompounds was predicted by using Swiss adme, admetSAR and protox II online servers. Molecular dynamic simulation of the best three protein- ligand complexes (alizarin, aloe-emodin and anthrarufin) was performed to study the interaction stability. We have identified three potential active sites (named as A, B, C) on receptor protein for efficient binding of the phytocompounds. We found that, among 100 phytocompounds, emodin, aloe-emodin, anthrarufin, alizarine, and dantron of Rheum emodi showed good binding affinity at all the three active sites of RNA binding domain of nucleocapsid phosphoprotein of COVID-19.The binding energies of emodin, aloe-emodin, anthrarufin, alizarine, and dantron were -8.299, -8.508, -8.456, -8.441, and -8.322 Kcal mol^-1 respectively (site A), -7.714, -6.433, -6.354, -6.598, and -6.99 Kcal mol^-1 respectively (site B), and -8.299, 8.508, 8.538, 8.841, and 8.322 Kcal mol^-1 respectively (site C). All the active phytocompounds follows the drug likeness properties, non-carcinogenic, and non-toxic. Theses phytocompounds (alone or in combination) could be developed into effective therapy against COVID-19. From MD simulation data, we found that all three complexes of 6VYO with alizarin, aloe-emodin and anthrarufin were stable up to 50 ns. These phytocompounds can be tested further for in vitro or in vivo and used as a potential drug to cure SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

Cardiovascular manifestations in COVID-19 patients: A systematic review and meta-analysis

Since December 2019, the COVID-19 pandemic has affected the global population, and one of the major causes of mortality in infected patients is cardiovascular diseases (CVDs).For this systematic review and meta-analysis, we systematically searched Google Scholar, Scopus, PubMed, Web of Science, and Cochrane databases for all articles published by April 2, 2020. Observational studies (cohort and cross-sectional designs) were included in this meta-analysis if they reported at least one of the related cardiovascular symptoms or laboratory findings in COVID-19 patients. Furthermore, we did not use any language, age, diagnostic COVID-19 criteria, and hospitalization criteria restrictions. The following keywords alone or in combination with OR and AND operators were used for searching the literature: "Wuhan coronavirus", "COVID-19", "coronavirus disease 2019", "SARS-CoV-2", "2019 novel coronavirus" "cardiovascular disease", "CVD", "hypertension", "systolic pressure", "dyspnea", "hemoptysis", and "arrhythmia". Study characteristics, exposure history, laboratory findings, clinical manifestations, and comorbidities were extracted from the retrieved articles. Sixteen studies were selected which involved 4754 patients, including 2103 female and 2639 male patients. Among clinical cardiac manifestations, chest pain and arrhythmia were found to have the highest incidence proportion. In addition, elevated lactate dehydrogenase (LDH) and D-dimer levels were the most common cardiovascular laboratory findings. Finally, hypertension, chronic heart failure, and coronary heart disease were the most frequently reported comorbidities. The findings suggest that COVID-19 can cause various cardiovascular symptoms and laboratory findings. It is also worth noting that cardiovascular comorbidities like hypertension have a notable prevalence among COVID-19 patients.

Early Warning Diagnostics for Emerging Infectious Diseases in Developing into Late-Stage Pandemics

The spread of infectious diseases due to travel and trade can be seen throughout history, whether from early settlers or traveling businessmen. Increased globalization has allowed infectious diseases to quickly spread to different parts of the world and cause widespread infection. Posthoc analysis of more recent outbreaks-SARS, MERS, swine flu, and COVID-19-has demonstrated that the causative viruses were circulating through populations for days or weeks before they were first detected, allowing disease to spread before quarantines, contact tracing, and travel restrictions could be implemented. Earlier detection of future novel pathogens could decrease the time before countermeasures are enacted. In this Account, we examined a variety of novel technologies from the past 10 years that may allow for earlier detection of infectious diseases. We have arranged these technologies chronologically from pre-human predictive technologies to population-level screening tools. The earliest detection methods utilize artificial intelligence to analyze factors such as climate variation and zoonotic spillover as well as specific species and geographies to identify where the infection risk is high. Artificial intelligence can also be used to monitor health records, social media, and various publicly available data to identify disease outbreaks faster than traditional epidemiology. Secondary to predictive measures is monitoring infection in specific sentinel animal species, where domestic animals or wildlife are indicators of potential disease hotspots. These hotspots inform public health officials about geographic areas where infection risk in humans is high. Further along the timeline, once the disease has begun to infect humans, wastewater epidemiology can be used for unbiased sampling of large populations. This method has already been shown to precede spikes in COVID-19 diagnoses by 1 to 2 weeks. As total infections increase in humans, bioaerosol sampling in high-traffic areas can be used for disease monitoring, such as within an airport. Finally, as disease spreads more quickly between humans, rapid diagnostic technologies such as lateral flow assays and nucleic acid amplification become very important. Minimally invasive point-of-care methods can allow for quick adoption and use within a population. These individual diagnostic methods then transfer to higher-throughput methods for more intensive population screening as an infection spreads. There are many promising early warning technologies being developed. However, no single technology listed herein will prevent every future outbreak. A combination of technologies from across our infection timeline would offer the most benefit in preventing future widespread disease outbreaks and pandemics.

The Role of the Smartphone in the Diagnosis of Vestibular Hypofunction: A Clinical Strategy for Teleconsultation during the COVID-19 Pandemic and Beyond

Introduction  Vestibular disorders (VDs) are highly prevalent in primary care. Although in general they comprise conditions that are not life-threatening, they are associated with significant functional and physical disability. However, the current coronavirus disease 2019 (COVID-19) pandemic has imposed limitations on the standard treatment of benign conditions, including VDs. In this context, other resources may aid in the diagnosis and management of patients with VDs. It is well known that teleconsultation and teletreatment are both safe and effective alternatives to manage a variety of conditions, and we maintain that VDs should be among these. Objective  To develop a preliminary model of clinical guidelines for the evaluation by teleconsultation of patients with suspected diagnosis of vestibular hypofunction during the COVID-19 pandemic and beyond. Methods  A bibliographic review of the diagnostic feasibility in VDs by teleconsultation was carried out in the LILACS, SciELO, MEDLINE, and PubMed databases; books and specialized websites were also consulted. The legal, regulatory, and technical issues involving digital consultations were reviewed. Results  We found 6 field studies published between 1990 and 2020 in which the efficiency of teleconsultations was observed in the contexts of epidemics and environmental disorders and disadvantageous geographical conditions. After reviewing them, we proposed a strategy to examine and address vestibular complaints related to vestibular hypofunction. Conclusion  The creation of a digital vestibular management algorithm for the identification, counseling, initial intervention, monitoring and targeting of people with possible vestibular hypofunction seems to be feasible, and it will provide a reasonable alternative to in-person evaluations during the COVID-19 pandemic and beyond.

COVID-19 transmission and the safety of air travel during the pandemic: a scoping review

PURPOSE OF REVIEW

To examine the literature assessing safety of air travel relating to coronavirus disease 2019 (COVID-19) transmission from January 2020 to May 2021. The COVID-19 pandemic has had an unprecedented impact on air travel and global mobility, and various efforts are being implemented to determine a safe way forward. As the pandemic evolves, so do the challenges that force various stakeholders, including the aviation industry, health authorities, and governments, to reassess and adapt their practices to ensure the safety of travellers.

RECENT FINDINGS

The literature was reviewed for multiple aspects of air travel safety during the COVID-19 pandemic. Recurring themes that surfaced included the pivotal role of commercial air travel in the geographic spread of COVID-19, the efficacy of travel restrictions and quarantines, inflight transmission risk and the role of preventive measures, the utility of pre and post flight testing, the development of effective vaccines and subsequent challenges of vaccine passports, and the ongoing threat of novel highly transmissible variants.

SUMMARY

Much uncertainty lies ahead within the domains of these findings, and ongoing research, discourse and review will be necessary to navigate and determine the future direction and safety of air travel. Recovery will be slow, necessitating innovative, multipronged and collaborative solutions.

Distance Learning during the COVID-19 Pandemic. A Comparison between European Countries

COVID-19 has shaped and changed our normalities, and, with the discovery of new variants, the long-COVID syndrome, and stress disorders, the end of the pandemic seems distant. The current scenario is impacting all aspects of our lives. In particular, many studies reported that the pandemic resulted in increased psychiatric disorders and grief-related symptoms in adolescents. The project developed between Italy and Slovenia investigated students’ experiences during the lockdown and, in particular, reported the perception of distanced learning, producing a transparent qualitative analysis that can inform future research and open to discussions on learning strategies. A survey was conducted with secondary school students in Southern Italy between 1 April and 31 May 2020 and in Central Slovenia between 16 March and 28 February 2021. Qualitative and quantitative data were collected based on students’ perception of distanced learning, via an online survey platform. The results focused on three main aspects: learning experience, relationships with peers and teachers, and anxiety levels. The data showed similarities and differences in the two cohorts and suggested strategies to improve education (e.g., with blended approaches) to prepare students, teachers, and tutors for the challenges of returning to classes. In particular, data showed that it is recommended to foster collaboration between EU countries and to work to prevent students’ social isolation.