Article
Public, Environmental & Occupational Health
Farman Hassan, Saleh Albahli, Ali Javed, Aun Irtaza
Summary: Covid-19 has become a global pandemic, and timely detection and control are crucial. The proposed new techniques and methods for analyzing, predicting, and detecting COVID-19 infection can improve accuracy and effectively respond to the outbreak.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Engineering, Electrical & Electronic
M. K. Arti
Summary: This paper investigates the mathematical modeling of COVID-19 spread in practical scenarios in various countries and proposes a model to characterize the disease and predict future waves. The proposed Gaussian mixture model shows a close match with available data, demonstrating the correctness of the model.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2022)
Article
Chemistry, Multidisciplinary
Cristina-Maria Stancioi, Iulia Adina Stefan, Violeta Briciu, Vlad Muresan, Iulia Clitan, Mihail Abrudean, Mihaela-Ligia Unguresan, Radu Miron, Ecaterina Stativa, Michaela Nanu, Adriana Topan, Daniela Oana Toader, Ioana Nanu
Summary: The COVID-19 pandemic has greatly impacted daily activities and the research focuses on developing mathematical models for prediction and simulation of disease spread. Five main input parameters and four output parameters were identified. Three mathematical models were tested and the optimal solution was chosen based on fit values and complexity analysis.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Multidisciplinary
W. E. Raslan
Summary: In this study, the concept of fractional derivatives was utilized to enhance a mathematical model for predicting the transmission of COVID-19 in Egypt. Results showed good agreement with actual data, and highlighted the importance of precautionary measures in influencing model behavior, emphasizing the need for an extended quarantine period.
AIN SHAMS ENGINEERING JOURNAL
(2021)
Article
Engineering, Chemical
Ateekh Ur Rehman, Syed Hammad Mian, Yusuf Siraj Usmani, Mustufa Haider Abidi, Muneer Khan Mohammed
Summary: The global COVID-19 pandemic, which began in 2020, has highlighted the importance of robust healthcare inventory management. The lack of medical resources has led to many casualties worldwide, emphasizing the need to accurately simulate the demand for medical goods and estimate the incidence of infections. Modeling various aspects of the pandemic, such as susceptibility, exposure, hospitalization, etc., is crucial for effective healthcare inventory management. This research examines different inventory policies and recommends the most cost-effective strategies based on the dynamics of the virus and the percentage of hospitalized individuals. The findings indicate that the just-in-time policy is ideal in the absence or partial lockdown, while the periodic order policy is best during a complete lockdown. The periodic order and reorder policies are also effective when social awareness is high or vaccination efficacy is uncertain. This effort aims to develop optimal healthcare inventory management strategies to ensure the availability of necessary healthcare resources at minimal cost.
Article
Computer Science, Artificial Intelligence
Sujata Dash, Chinmay Chakraborty, Sourav K. Giri, Subhendu Kumar Pani
Summary: Covid-19, caused by the novel coronavirus, is a highly contagious epidemic that WHO declared as a pandemic in March 2020. Researchers are utilizing intelligent computing models like the Facebook Prophet to forecast the outbreak of the virus and the peak date of confirmed cases, aiding in planning and management of healthcare systems and infrastructure.
PATTERN RECOGNITION LETTERS
(2021)
Article
Engineering, Industrial
Soheyl Khalilpourazari, Hossein Hashemi Doulabi
Summary: This research develops a method based on the Stochastic Fractal Search algorithm and a mathematical model to predict the COVID-19 pandemic, and performs sensitivity analyses to explore the effects of changes in transmission rates on the future number of cases. The results show that asymptomatic cases play a significant role in the transmission of the virus, and increasing testing capacity can effectively limit community transmission.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Cardiac & Cardiovascular Systems
Manuela De Michele, Joshua Kahan, Irene Berto, Oscar G. Schiavo, Marta Iacobucci, Danilo Toni, Alexander E. Merkler
Summary: The risk of stroke and cerebrovascular disease complicating SARS-CoV-2 infection has been extensively reported. The rapid development and mass vaccination of DNA and mRNA vaccines against SARS-CoV-2 have led to rare but catastrophic cases of thrombosis. This review provides an overview of stroke and cerebrovascular complications of SARS-CoV-2 infection, as well as vaccinations, with a focus on vaccine-induced immune thrombotic thrombocytopenia. A therapeutic protocol is proposed based on available data.
CIRCULATION RESEARCH
(2022)
Article
Multidisciplinary Sciences
Serena Cabaro, Vittoria D'Esposito, Tiziana Di Matola, Silvia Sale, Michele Cennamo, Daniela Terracciano, Valentina Parisi, Francesco Oriente, Giuseppe Portella, Francesco Beguinot, Luigi Atripaldi, Mario Sansone, Pietro Formisano
Summary: Research has found that there is a trend of increasing multiple cytokines in COVID-19 patients, and machine learning approach can be helpful in identifying predictive factors. IL-6 is identified as the most robust predictor of infection, able to distinguish moderate COVID-19 patients from healthy controls effectively.
SCIENTIFIC REPORTS
(2021)
Article
Public, Environmental & Occupational Health
Nick Scott, Romesh G. Abeysuriya, Dominic Delport, Rachel Sacks-Davis, Jonathan Nolan, Daniel West, Brett Sutton, Euan M. Wallace, Margaret Hellard
Summary: This study used the agent-based model Covasim to simulate the impact of policy interventions on COVID-19 outbreaks and epidemic waves. The results showed the importance of understanding outbreak risk and the benefits of early lockdown and gradual easing of restrictions. As vaccination coverage increased, the focus shifted to controlling community transmission and the need for other public health measures alongside vaccines.
Article
Materials Science, Multidisciplinary
Haneen Alabdulrazzaq, Mohammed N. Alenezi, Yasmeen Rawajfih, Bareeq A. Alghannam, Abeer A. Al-Hassan, Fawaz S. Al-Anzi
Summary: The study aimed to test the accuracy of ARIMA best-fit model predictions with actual values using Kuwait as a case study over a relatively long period of time. The results showed that despite the dynamic nature of the disease and constant revisions made by the Kuwaiti government, the actual values for most of the observed time period were well within bounds of the selected ARIMA model predictions at 95% confidence interval. Pearson's correlation coefficient between forecast points and actual recorded data was found to be 0.996, indicating high correlation and satisfactory accuracy of the ARIMA model prediction.
RESULTS IN PHYSICS
(2021)
Article
Multidisciplinary Sciences
Adam Spannaus, Theodore Papamarkou, Samantha Erwin, J. Blair Christian
Summary: The role of epidemiological models in informing public health officials during a public health emergency is crucial. Traditional models fail to capture the time-varying effects of mitigation strategies and under-reporting of active cases, resulting in biased estimation of parameters. To address this, the researchers extended the SIR and SEIR models with two time-varying parameters and performed Bayesian inference using real COVID-19 data. Their approach provided more realistic parameter estimates and reduced uncertainty in 1-week ahead predictions.
SCIENTIFIC REPORTS
(2022)
Article
Materials Science, Multidisciplinary
Edward Acheampong, Eric Okyere, Samuel Iddi, Rachel L. Gomes, Joseph H. K. Bonney, Joshua Kiddy K. Asamoah, Jonathan A. D. Wattis
Summary: This study develops a modified compartmental model to describe the dynamics of SARS-CoV-2 transmission in Ghana and performs a detailed analysis of the model. The study shows that the disease-free equilibrium is globally asymptotically stable when the basic reproduction number (R0) is less than 1. The model is parameterized using reported data and shows good agreement. Additionally, the testing rate has a significant influence on R0.
RESULTS IN PHYSICS
(2022)
Article
Immunology
Nabila Shaikh, Puck T. Pelzer, Sanne M. Thysen, Partho Roy, Rebecca C. Harris, Richard G. White
Summary: The COVID-19 disruptions resulted in a 25% reduction in global BCG coverage and could lead to additional paediatric TB deaths if catch-up vaccinations are not implemented. Catch-up vaccination is crucial in minimizing excess paediatric TB mortality.
Article
Materials Science, Multidisciplinary
Pushpendra Kumar, Vedat Suat Erturk, Marina Murillo-Arcila
Summary: This study introduces a new SEIRS dynamic model incorporating vaccine rate and utilizes Atangana-Baleanu fractional derivative to explore the disease model dynamics. Real data from Spain is used for parameter values, and Predictor-Corrector algorithm is employed to derive model solutions. The main aim is to demonstrate the significant role of vaccines during the critical period of COVID-19.
RESULTS IN PHYSICS
(2021)
Article
Computer Science, Artificial Intelligence
Antoni Wilinski
EXPERT SYSTEMS WITH APPLICATIONS
(2019)
Article
Computer Science, Artificial Intelligence
Antoni Wilinski, Eryk Szwarc
Summary: "This article presents models of the spread of SARS-CoV-2 coronavirus in individual countries and globally based on statistical characteristics. It categorizes the epidemic spread in countries based on the relative variability of confirmed cases, predicting four phases of epidemic spread: growth, duration, suppression, and re-outbreak. The authors have developed Matlab software for simulating the spread of coronavirus in any country using data from CSSE."
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Education & Educational Research
Antoni Wilinski, Mariia Skulysh, M. K. Arti, Irena Bach-Dabrowska, Abayomi O. Agbeyangi, Hina Zahra, Hubert Krason, Jolanta Dobska, Lukasz Kupracz
Summary: The study aimed to determine students' predispositions to work in the IT sector through voluntary self-assessment of preferences. The results showed that a large percentage of students have predispositions to work in the IT market.
INFORMATICS IN EDUCATION
(2022)
Article
Computer Science, Cybernetics
Antoni Wilinski, M. K. Arti, Lukasz Kupracz
Summary: This article introduces a criterion for comparing the number of COVID-19 deaths in different countries, and applies it to global and individual country data analysis. The method is universal and applicable to any country or group of countries.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Business, Finance
Antoni Wilinski, Mateusz Sochanowski, Wojciech Nowicki
Summary: This article introduces an investment strategy based on the difference between two moving averages, allowing short-term prediction through pattern extraction, and uses machine learning to optimize strategy parameters. Satisfactory results were obtained in testing this strategy.
DATA SCIENCE IN FINANCE AND ECONOMICS
(2022)
Article
Computer Science, Artificial Intelligence
Antoni Wilinski, Boris Kovalerchuk
COGNITIVE SYSTEMS RESEARCH
(2017)
Article
Education & Educational Research
Antoni Wilinski, Lukasz Kupracz
INFORMATICS IN EDUCATION
(2020)
