Coronavirus Cases Research Articles

Bayesian Hidden Markov Modelling of Blood Type Distribution for Covid-19 Cases Using Poisson Distribution

This paper proposes a model to describe the blood types distribution of new Coronavirus (COVID-19) cases using the Bayesian Poisson - Hidden Markov Model (BP-HMM). With the help of the Gibbs sampler algorithm, using OpenBugs, the study first identifies the number of hidden states fitting European (EU) and African (AF) data sets of COVID-19 cases by blood type frequency. The study then compares the state-dependent mean of infection within and across the two geographical areas. The study findings show that the number of hidden states and infection rate within and across the two geographical areas differ according to blood type. 

Evaluation of immunogenicity-induced DNA vaccines against different SARS-CoV-2 variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 and caused the coronavirus disease 2019 (COVID-19) pandemic worldwide. As of September 2023, the number of confirmed coronavirus cases has reached over 770 million and caused nearly 7 million deaths. The World Health Organization assigned and informed the characterization of variants of concern (VOCs) to help control the COVID-19 pandemic through global monitoring of circulating viruses. Although many vaccines have been proposed, developing an effective vaccine against variants is still essential to reach the endemic stage of COVID-19. We designed five DNA vaccine candidates composed of the first isolated genotype and major SARS-CoV-2 strains from isolated Korean patients classified as VOCs, such as Alpha, Beta, Gamma, and Delta. To evaluate the immunogenicity of each genotype via homologous and heterologous vaccination, mice were immunized twice within a 3-week interval, and the blood and spleen were collected 1 week after the final vaccination to analyze the immune responses. The group vaccinated with DNA vaccine candidates based on the S genotype and the Alpha and Beta variants elicited both humoral and cellular immune responses, with higher total IgG levels and neutralizing antibody responses than the other groups. In particular, the vaccine candidate based on the Alpha variant induced a highly diverse cytokine response. Additionally, we found that the group subjected to homologous vaccination with the S genotype and heterologous vaccination with S/Alpha induced high total IgG levels and a neutralization antibody response. Homologous vaccination with the S genotype and heterologous vaccination with S/Alpha and S/Beta significantly induced IFN-γ immune responses. The immunogenicity after homologous vaccination with S and Alpha and heterologous vaccination with the S/Alpha candidate was better than that of the other groups, indicating the potential for developing novel DNA vaccines against different SARS-CoV-2 variants.

“Long GFC”? The global financial crisis, health care, and COVID‐19 deaths

AbstractDo financial crises affect long‐term public health? To answer this question, we examined the relationship between the 2007–2009 Global Financial Crisis (GFC) and the 2020–2022 COVID‐19 pandemic. Specifically, we examined the relationship between the financial losses derived from the GFC, and the health outcomes associated with the first wave of the pandemic. European countries that were more affected by the financial crisis had more deaths relative to coronavirus cases. An analogous relationship emerged across Spanish provinces and US states. Part of the transmission from finances to health outcomes appears to have occurred through cross‐sectional differences in health care facilities.

Disparities on African Americans Amid Global Calamity

Coronavirus has struck the entire world, and its effects are tragic for all. At the same time, coronavirus outbreaks in the United States for Blacks are more widespread. Tens of thousands of African Americans have lost lives, while uncertainty is abundant throughout the pandemic. The number of casualties from this crisis continues to rise for African Americans and is disproportionate in comparison to other ethnic and racial groups. There is a historical and contemporary epoch for African Americans linked to the existing state of coronavirus in this population. Critical race theory is utilized in the narrative and shows how the injustice of racism transformed the disparate health experiences in African Americans’ coronavirus cases. Racism should be examined as a basic serious account for determinants of health that necessitate multiple manifestations of disparities. Social workers’ responses to intertwined racism and health are indicated regarding the phenomena of coronavirus on this population.

Advances in artificial intelligence for accurate and timely diagnosis of COVID-19: A comprehensive review of medical imaging analysis

In December 2019, the first case of coronavirus 2019 (COVID-19) appeared in China, quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective disease management. While reverse transcription polymerase chain reaction (RT-PCR) is the standard diagnostic test, it may yield false negative and misleading results. Artificial intelligence (AI) systems are accelerating the transformation of the medical field, particularly in early detection and diagnosis. Recent research has combined AI with medical imaging modalities, such as chest X-ray (CXR) and computed tomography (CT), to detect the virus, aiding doctors in making decisions and reducing misdiagnosis rates. In this article, we conducted a systematic review of high-quality articles published in high-impact journals that examined convolutional neural network (CNN)-based methods for detecting COVID-19 from radiographic or CT images and discussed associated issues. We synthesized publicly available datasets and evaluation measures, including accuracy, sensitivity, specificity, and F1 score, for each system used for automatic diagnosis of COVID-19 using several well-performing CNN architectures. Furthermore, we identified key research questions and future directions in this field. Our results show that the use of AI for COVID-19 diagnosis from radiographic and CT images has considerable potential to improve diagnostic accuracy and reduce false negative rates. Nevertheless, important challenges must be addressed, such as limited access to datasets and the need for rigorous model validation. Additionally, the generalization of models to different populations and contexts needs to be examined. Our findings underscore the need for future research directions, including the exploration of deep learning for smaller datasets, enhancing model performance for complex cases, and designing practical AI systems for deployment in clinical settings.

Coronavirus Disease 2019 in Rheumatic Patients with Inflammatory Disorders: A Descriptive Study from a High Infection Incidence Region of Northern Spain.

Since the first confirmed case of severe acute respiratory syndrome coronavirus 2 in Spain in January 2020, the susceptibility of patients with rheumatic disease has remained unclear. In this report, we will describe the main features of coronavirus disease 2019 (COVID-19) that occurred in rheumatic patients with inflammatory disorders and try to identify features associated with severe disease. We included all rheumatic patients with immune-mediated diseases followed at 6 centers belonging to the public healthcare system in the Basque Country (Spain) and diagnosed with COVID-19 from March 1, 2020, to May 31, 2020. In total, 131 patients were included in this study. The most frequent rheumatic disease was rheumatoid arthritis (46.6%), and the main comorbidities were arterial hypertension (45%). Fortyseven percent were taking glucocorticoids (GC) (62 patients), 61.8% were under treatment with conventional synthetic disease-modifying antirheumatic drugs (csDMARD), and 25 patients (19.1%) were receiving targeted therapies (TT). Thirty-eight percent of patients required hospital admission, 2.3% required transfer to intensive care uni, and the rate of mortality was 9.2%. Associated factors in univariate analysis for a bad outcome were older age, use of GC, obesity, previous cardiovascular disease, and lymphopenia. Use of GC and lymphopenia remained within the multivariate model. The frequency of COVID-19 seems to be similar in rheumatic patients as in the general population. Advanced age, obesity, heart disease, glucocorticoids, and low levels of lymphocytes were more common among the patients with a bad outcome. Neither exposure to csDMARD nor TT was associated with severe cases.

Application of Geographic Information Systems in the Study of COVID-19 in Morocco

Introduction: The 2019 coronavirus disease (COVID-19) was first identified as a respiratory disease that originated in Wuhan, Hubei Province, China. The WHO declared the COVID-19 outbreak a public health emergency of international concern on 30 January 2020. Morocco reported its first coronavirus case on 2 March 2020. During the week of 9-15 March 2020, Morocco took steps to limit the spread of the epidemic. This article describes the use of spatial data applications in epidemiological research in Morocco, specifically its response to the COVID-19 epidemic. Methods: To conduct this study, we relied on the use and analysis of data provided by the Moroccan Ministry of Health for the study period from May to July 2021, as well as the geographical and administrative map of the Kingdom of Morocco. Spatial analysis of COVID-19 was performed using ArcGIS 10.8 and QGIS, a geographic information processing software. Health data for the 12 regions of the Moroccan territory were presented in the number of COVID-19 cases as a discrete quantitative variable and over time as a continuous time variable. Results: According to a map created using GIS, the concentration of COVID-19 cases appeared to be highest in the Casablanca Settat region. Depending on the number of documented COVID-19 cases, regions were ranked as follows: Casablanca-Settat> Rabat-Sale-Kenitra> Marrakech-Safi > Fes-Meknes > Tangier-Tetouan-Alhouceima>Oriental>Souss-Massa > Béni Mellal-Khenifra> Draa-Tafilalet> Laayoune-Sakia El Hamra >Guelmim-Oued Noun > Dakhla-Oued Eddahab. The increase in cases in major cities was due to several factors, including demographic, social and environmental factors. This demonstrated the need to consider demographic contributions to environmental health. Demographic factors helped us understand the health of our environment empirically. Geography improved health decision-making and accountability. Incorporating the geographic context of the spread of COVID-19 helped decision-makers understand the impact of location on strategies and goals to combat this pandemic. Conclusion: This study identified areas with high and low COVID-19 clusters and hotspots. The produced maps can serve as an excellent management tool to control and effectively eliminate the COVID-19 pandemic, contributing to investments in epidemiological surveillance programs.

The Effect of Covid-19 on Voters in the Medan Tuntungan District Election in 2020

The Covid Sickness (Coronavirus) flare-up that happens in all nations in this present reality is progressively widespread. This instance of pneumonia of obscure etiology or Coronavirus was first recognized in Wuhan City, Hubei Area, China on December 31, 2019. Medan City is one of the regions that held regional elections for the mayoral election, In the 2020 Medan city election, Medan was included in the red zone area where one of the areas with a positive number of covid-19 reached 4,261 people with this number Medan city accounting for 75 percent of corona virus cases in North Sumatra. But in fact, with the large number of positive Covid-19 cases in the city of Medan, there is no decrease in public enthusiasm to come to the Polling Station (TPS) compared to previous elections in Medan. This study uses a type of quantitative research because this study seeks to analyze whether there is an influence of the COVID-19 pandemic on voter participation in Medan Tuntungan sub-district. This type of research is a type of descriptive research. Influence of Covid-19 on Voters in the Medan Tuntungan District Election in 2020 is as follows: Voter participation in Medan Tuntungan District is also influenced by other variables outside the Covid-19 pandemic variable, which is 83.8%, so it is appropriate if research related to voter participation is carried out again using other variables outside the Covid-19 pandemic variable.

Performance Assessment of DL Model in Iraq for Covid-19 Patient Severity Prediction from X-Ray Scan Images

The livelihoods of many people are greatly affected by the covid-19 virus, and the high death rate has led to a global pandemic. With early detection, the possibility of spreading coronavirus (covid-19) can be reduced. The way people live their lives and the global economic and social systems have undergone a major transformation. It is difficult to treat almost all cases of coronavirus due to limited medical infrastructure, causing the death toll to rise rapidly. Therefore, thousands of lives could be saved if their occurrence and severity could be predicted in advance, allowing the rapid adoption of appropriate treatments. Deep learning (DL) is crucial for determining the severity of the lungs in patients with Covid-19. The severity of lung disease among Covid-19 patients is determined using a variety of techniques, including X-rays, CT scans and MRI scans. The prediction result depends highly on how well each stage of lung disease detection performs. The low prediction accuracy leads to a major reason: the large size of the storage model. To address this problem, in order to increase predicting accuracy, it is suggested that the new deep transfer learning model be enhanced by the incorporation of a novel attention mechanism. VGG16 is used as the foundation model for a brand-new deep transfer learning model. We suggest adding a convolutional block attention module (GhostNet) to the conventional suggested network model and upgrading a new model for this purpose in order to improve the accuracy of forecasting the severity of lung illness among Covid-19 patients.

Persistent Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia in Patients Treated With Anti-CD20 Monoclonal Antibodies.

We report 8 cases of persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia in patients previously treated with anti-CD20 monoclonal antibodies. Polymerase chain reaction of nasopharyngeal swabs for SARS-CoV-2 was negative in most cases; viral cell cultures confirmed that viable SARS-Co-2 virus was present. Four patients were treated with anti-SARS-CoV-2 hyperimmune globulins with rapid resolution of disease.

Predicting Consumer Service Price Evolution during the COVID-19 Pandemic: An Optimized Machine Learning Approach

This research analyzes the impact of the COVID-19 pandemic on consumer service pricing within the European Union, focusing on the Transportation, Accommodation, and Food Service sectors. Our study employs various machine learning models, including multilayer perceptron, XGBoost, CatBoost, and random forest, along with genetic algorithms for comprehensive hyperparameter tuning and price evolution forecasting. We incorporate coronavirus cases and deaths as factors to enhance prediction accuracy. The dataset comprises monthly reports of COVID-19 cases and deaths, alongside managerial survey responses regarding company estimations. Applying genetic algorithms for hyperparameter optimization across all models results in significant enhancements, yielding optimized models that exhibit RMSE score reductions ranging from 3.35% to 5.67%. Additionally, the study demonstrates that XGBoost yields more accurate predictions, achieving an RMSE score of 17.07.

First cases of SARS-CoV-2 BA.2.86 in Denmark, 2023.

We describe 10 cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant BA.2.86 detected in Denmark, including molecular characteristics and results from wastewater surveillance that indicate that the variant is circulating in the country at a low level. This new variant with many spike gene mutations was classified as a variant under monitoring by the World Health Organization on 17 August 2023. Further global monitoring of COVID-19, BA.2.86 and other SARS-CoV-2 variants is highly warranted.

The Fear of Covid-19 and Professional Commitment in Nursing Students Switching from Online Education to Face-to-face Education: A Cross-sectional Study

Background/Purpose: During the coronavirus pandemic, courses were offered online in departments of nursing, and hence, clinical practices were interrupted. Along with the fall in coronavirus cases, the decision to switch from online education to face-to-face education was taken. This research was carried out to determine the fear of coronavirus and professional commitment levels of nursing students who switched from online education to face-to-face education.
 Methods: Descriptive cross-sectional research was performed with 340 nursing students. The research data were gathered online with the Personal Data Form, the Fear of COVID-19 Scale (FCV-19S), and the Nursing Professional Commitment Scale (NPCS).
 Results: The mean of nursing students’ FCV-19S scores was found as 16.44±6.03 whilst the mean of their NPCS scores was identified as 79.67±10.53. It was identified that there was no statistically significant relationship between nursing students’ FCV-19S and NPCS scores (p>0.05).
 Conclusion: It was discerned that nursing students had a fear of coronavirus below the average while they exhibited moderate professional commitment, and there was no statistically significant relationship between the fear of coronavirus and professional commitment.

What Got You through Lockdown?

What Got You through Lockdown?

Characterization of mild or asymptomatic patient admitted with Omicron variant of COVID-19 infection in Tibetan mobile cabin hospital China, August-October 2022.

Prior to August 7, 2022, there had been no positive cases of novel coronavirus in Tibet for 920 consecutive days. However, with the first case of Omicron variant infection, the disease rapidly spread and was prevalent in Tibet for nearly 3 months, from August 7th to November 1st. With the spread of the epidemic, the local government responded quickly and established several mobile cabin hospitals to treat patients with mild and asymptomatic Omicron infection. However, the epidemiological and clinical characteristics of these patients are unknown. This is a retrospective study including a total of 14,264 mild and asymptomatic cases with Omicron infection in Tibet between August to October, 2022. The clinical data and epidemiological characteristics of COVID-19 cases admitted to Tibet mobile cabin hospitals were collected by using standardized forms from mobile cabin hospital database system, including demographic characteristics, onset symptoms, medication use, past medical history, hospitalization time, and discharge time. In terms of statistical analysis, multivariate Cox regression model was used to analyze the relationship between case characteristics and the length of stay in hospital. Among 14,264 patients infected with Omicron, the average length of hospital stay was six (4-8, Interquartile range) days. Fifty percent of the patients were discharged by the 6th day, and 90% were discharged by the 10th day. Patients of all ages are generally susceptible to COVID-19, and there was no difference in discharge time, but the average length of hospital stay of Tibetan patients with COVID-19 was longer than that of Han patients. According to the statistics of clinical symptoms, sore throat (38.7%) and fever (19.4%) were the most common symptoms, while muscle pain (17.4%), cough (16.6%), and expectoration (13.2%) were also common. In addition, patients with chronic gastritis had significantly longer hospital stays. Based on the experience of Tibet mobile cabin hospitals and data analysis, we believe that patients of all ages are generally susceptible to Omicron. Compared with other novel coronavirus strains, Omicron infected patients had a shorter hospital stay, and treatment of symptoms is expected to shorten the time of nucleic acid negative conversion.

Postacute coronavirus disease‐2019 syndrome: Review of the literature and role of the pharmacist

AbstractSevere acute respiratory syndrome coronavirus (SARS‐CoV‐2) has resulted in over 500 million confirmed cases of coronavirus disease‐2019 (COVID‐19) worldwide, causing over 6 million deaths. A wide disease spectrum has been described for COVID‐19 infections with a newer focus on the long‐term impacts termed Postacute COVID‐19 syndrome (PACS). PACS is not formally defined but occurs 4 weeks to 6 months after the acute infection impacting the neurologic, cardiovascular, respiratory, gastrointestinal, endocrine, renal, dermatologic, and hematologic organ systems to varying degrees. Nearly one third of patients will experience a neuropsychiatric manifestation within 6 months of a COVID‐19 diagnosis with anxiety, depression, and posttraumatic stress disorder (PTSD) being the most common symptoms. There is much similarity between PACS and Postintensive care syndrome (PICS). Long‐term follow‐up is necessary to ensure intensive care unit (ICU) survivors are cared for appropriately. The development of PICS clinics across the world has set a groundwork for better managing PACS. The inclusion of clinical pharmacists in these clinics has repeatedly improved outcomes. Implementation of the ABCDEF Bundle prevents the occurrence of PICS and PACS, making it an important discussion point for the entire health care team. Epidemiologic data is still emerging with the National Institute of Health (NIH) researching COVID to enhance recovery (RECOVER) research initiative contributing to our understanding of PACS and how to best manage it. The purpose of this review paper is to characterize PACS and recommend prevention, potential monitoring, and treatment, as well as to highlight the role of the clinical pharmacist in the management of this population.

Statistical study for Covid-19 spread during the armed crisis faced by Ukrainians

Russia and Ukraine got into an armed conflict on 24th February 2022. In addition, the World Health Organisation still warns of a fast growth in infections and deaths. Infectious disease remains a serious issue in Ukraine and poorly governed cities, such as those in armed conflicts. During this period of security instability, the coronavirus situation in Ukraine is alarming and needs more attention. In this context, our focus in the current work is to model COVID-19 spread risk from Ukrainian international refugees in neighboring countries. This study aims to estimate the number of daily coronavirus cases among Ukrainian international refugees for informed decisions for the pandemics' spread risk. For that reason, we used “Coronavirus Pandemic (COVID-19)” data from “Our World in Data” (from 2020-03-03 to 2022-02-22) and the data about Ukrainian International Refugees provided by United Nations High Commissioner for Refugees related (from 2022-02-22 to 2022-03-11). We performed ARIMA, TBATS, and ETS and selected the best model. Through a cross-validation process, the findings revealed that around 6 individuals [95% CI: 5%–7%] over 10,000 Ukrainian international refugees are likely COVID-19 cases. ARIMA is the best model to fit the Ukrainian daily number of cases among the refugees fleeing the crisis. On average, they are daily 100 possible COVID-19 cases among Ukrainian international refugees and authorities and humanitarian actors need be informed decisions to control the pandemic and support refugees effectively.

EFFECT OF COVID-19 ON GASTROINTESTINAL TRACT AND LIVER, MANIFESTATIONS, PROGNOSIS, MECHANISMS, TREATMENT, AND CHALLENGES: A COMPREHENSIVE REVIEW

Background: The first case of coronavirus was found in December 2019 in Wuhan a city in China since then it has severe impact all over the world. The typical signs and symptoms of coronavirus patients consist of cough, fever, lethargy, and shortness of breath (SOB). Objectives: The current review contains summarized and complete information on the effect of coronavirus on GIT, Liver and its manifestations, prognosis, mechanisms, treatment, and challenges. Methodology: The data was collected via an electronic search of numerous scientific sources including Google scholar, PubMed, and Science Direct. Results: The main complaints in COVID-19 positive patients are linked to the respiratory system but many patients also complained of gastrointestinal problems like vomiting, abdominal pain, diarrhoea, and in some cases, anorexia, increased acidity, and bloating. The mechanisms of GI damage in corona-virus patients are direct virus-mediated cytotoxic damage in the intestinal epithelium, dysregulation of the RAAS in the intestinal epithelium, malabsorption of tryptophan in the intestinal epithelium. Various scientific studies also report that COVID-19 patients had abnormal levels of ALT and AST suggesting a possible liver injury. The possible mechanisms of liver damage in corona-virus patients are direct hepatic infection by corona-virus, cytokine storm, and drug-induced damage. The prognosis is poor in both GI and liver abnormalities in corona-virus patients. According to some studies, patients with considerable liver injury should be treated with anti-inflammatory, hepatoprotective, and jaundice-decreasing agents. Natural plants and herbs can be used in coronavirus patients with GI and liver abnormalities. However, further research is necessary in this area for a complete assessment of the effect of coronavirus infection on GI and liver abnormalities and appropriate testing of therapeutic agents used against these abnormalities. Conclusion: In a nutshell, our results conclude that both gastrointestinal symptoms and liver damage are not unusual in patients with coronavirus infection. Severe coronavirus patients had a greater risk of developing gastrointestinal symptoms and liver damage.

The First Case Series of Malaria Overlapped with COVID-19 in Iran

Introduction: Although indigenous malaria cases have dramatically declined over the past decades, the COVID pandemic has continued to affect the programs designed to combat malaria, particularly in those countries where hydroxychloroquine and chloroquine have been used as medications for treating COVID. Two immigrants entered Iran illegally from neighboring countries (i.e., Afghanistan and Pakistan). This study mainly aimed to assess the effects of coronavirus disease (COVID-19) on these cases from all aspects (i.e., case-finding, diagnosis, and treatment). Case Presentation: Both cases presented with common symptoms such as fever and shaking chills. In addition, they had no sign of COVID-19, and their oxygen level and CT images were normal in some cases, but they were mistakenly treated as COVID-19 patients long after the onset of malaria symptoms. One of the suspected coronavirus cases was given chloroquine on a voluntary basis for one day, which may have been responsible for the possible relapse in vivax or resistance of plasmodium vivax to chloroquine and the recurrence of parasitemia in falciparum. Conclusions: The active case detection of malaria was affected by the COVID-19 pandemic. Case finding was dramatically decreased with the onset of coronavirus, thereby causing a spurt in malaria incidence. Moreover, the malaria treatment strategy was negatively affected by the misdiagnosis of COVID-19.

Covid-19 Pandemic and ICT Performance in Nigerian Banks: Financial Transaction Perspective

The global outbreak and spread of coronavirus disease (COVID-19) have been referred to as the most dangerous pandemic since World War II. The speed of the spread and the severity of the damage caused by the virus has traumatized the global economy affecting both banks and customers. With the lockdown imposed by the government to restrict the movement of people and activities caused by the increased level of coronavirus cases in Nigeria, the fate of the financial users of about 40 million became unknown. Given the analysis of data on trends of COVID-19 infections from the World Health Organization and Nigerian Centres for Disease Control and Prevention, the study assessed the current situation. It indicated some specific concepts that the banking sector should consider and address while taking the necessary measures to cope with the new change. The study used an ex-post-facto research design, enabling the researcher to measure the effect or relationship between the dependent variable and explanatory variables using time-series secondary data. The data collected was reviewed, and validated by CBN, the Nigeria Bureau of Statistics, and the Nigerian Inter-Bank Settlement System (NIBSS) websites. The study concluded that the ICT volume of e-payment has no significant effect on operational efficiency in Nigeria Banks, and the ICT value of e-payment significantly affects operational efficiency in Nigeria Banks during the coronavirus lockdown.