Using Unstated Cases to Correct for COVID-19 Pandemic Outbreak and Its Impact on Easing the Intervention for Qatar

Sallahi, Narjiss; Park, Heesoo; El-Mellouhi, Fedwa; Rachdi, Mustapha; Ouassou, Idir; Belhaouari, Samir Brahim; Arredouani, Abdelilah; Bensmail, Halima

doi:10.3390/biology10060463

Cited by 5 publications

(4 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…COVID-19 has been spread rapidly all over the globe. In this pandemic, the COVID-19 vaccination can be considered as a safe corner to save a human life and to avoid deaths and infections from COVID-19 [37]. Different research has been made on the COVID-19 vaccination since the vaccination was introduced.…”

Section: Discussionmentioning

confidence: 99%

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier

Zaidi

Tariq

Belhaouari

2021

Data

Self Cite

View full text Add to dashboard Cite

Machine learning (ML)-based prediction is considered an important technique for improving decision making during the planning process. Modern ML models are used for prediction, prioritization, and decision making. Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. This study focuses on the future prediction of the effectiveness of the COVID-19 vaccine effectiveness which has been presented as a light in the dark. People bear several reservations, including concerns about the efficacy of the COVID-19 vaccine. Under these presumptions, the COVID-19 vaccine would either lower the risk of developing the malady after injection, or the vaccine would impose side effects, affecting their existing health condition. In this regard, people have publicly expressed their concerns regarding the vaccine. This study intends to estimate what perception the masses will establish about the role of the COVID-19 vaccine in the future. Specifically, this study exhibits people’s predilection toward the COVID-19 vaccine and its results based on the reviews. Five models, e.g., random forest (RF), a support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), and an artificial neural network (ANN), were used for forecasting the overall predilection toward the COVID-19 vaccine. A voting classifier was used at the end of this study to determine the accuracy of all the classifiers. The results prove that the SVM produces the best forecasting results and that artificial neural networks (ANNs) produce the worst prediction toward the individual aptitude to be vaccinated by the COVID-19 vaccine. When using the voting classifier, the proposed system provided an overall accuracy of 89.9% for the random dataset and 45.7% for the date-wise dataset. Thus, the results show that the studied prediction technique is a promising and encouraging procedure for studying the future trends of the COVID-19 vaccine.

show abstract

Section: Discussionmentioning

confidence: 99%

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier

Zaidi

Tariq

Belhaouari

2021

Data

Self Cite

View full text Add to dashboard Cite

show abstract

“…SARS affects mainly the respiratory system of the patients and the main syndromes which are common between patients are fever, dry cough, dyspnea, headache, and hypoxemia (Koichi 2020). Several studies have been proposed to model this infection without involving other variables and using well known compartment models (Oshinubi et al 2021), (Demongeot et al 2021) and (Sallahi et al 2021). Other models use time series and non-parametric approach such as functional data analysis and (Demongeot et al 2022) to name a few.…”

Section: Introductionmentioning

confidence: 99%

Effect of temperature on the spread of Covid-19 in Qatar, Kuwait and other Gulf countries

Fawzy

AlAwadhi

Rachdi

et al. 2022

KJS publishes peer-review articles in Mathematics, Computer Sci

Self Cite

View full text Add to dashboard Cite

Background: COVID-19 has emerged as a serious pandemic that emerged during since the end of 2019. The dissemination and survival of coronaviruses have been demonstrated to be affected by ambient temperature in epidemiological and laboratory research. The goal of this investigation was to see if temperature plays a role in Methods: Between March 29, 2020, and September 29, 2020, daily confirmed cases and meteoro-logical parameters in many Gulf countries were collected. Using a generalized additive model, we investigated the nonlinear relationship between mean temperature and COVID-19 confirmed cases.. To further investigate the association, we employed a piecewise linear regression. Results: According to the exposure-response curves, the association between mean temperature and COVID-19 cases was nearly linear in the window of 21-30degreeC while it is almost flat beyond that window. When the number was below 21degreeC (lag 0-14), each 1degreeC increase was associated with a 4:861 percent (95 percent CI: 3:209 􀀀 6:513) increase in mean temperature (lag 0-14). Our sensitiv-ity analysis confirmed these conclusions. Conclusions: Our findings show a positive linear association between mean temperature and the number of COVID-19 cases with a threshold of 21degreeC. There is little evidence that COVID-19 case numbers would rise as the weather becomes colder, which has important consequences for making health strategy and decision.

show abstract

“…Для разработки модифицированной математической модели распространения вируса SARS-СoV-2 с самого начала пандемии использовались данные зарегистрированных как симптоматических, так и бессимптомных случаев заболевания. Для моделирования динамики передачи вируса в некоторых странах Персидского залива, Европы, городах Нью-Йорке и Москве для построения модели принимались во внимание количество незарегистрированных прогнозируемых случаев и подчеркивалась важность их учета для оценки и прогноза распространения SARS-СoV-2, определения объема и уровня необходимых мер, которые должны быть заблаговременно приняты для борьбы с COVID-19 [20][21][22].…”

unclassified

“…1. Модель распространения вируса SARS-СoV-2 (адаптировано из [20]) Figure 1. Model of the spread of the SARS-СoV-2 virus (adapted from [20])…”

unclassified

Respiratory viral infections, SARS-СoV-2 and chronic obstructive pulmonary disease

Zaryanova

Осипова

Osipova

2022

Pulʹmonologiâ (Mosk.)

View full text Add to dashboard Cite

Further study of the distribution, pathogenesis of viral infection, the role of respiratory viruses in the formation and exacerbation of chronic lung diseases will allow the development of new methods of protection, the creation of modern pharmaceutical approaches for the treatment and prevention of COVID-19.The aim. The article presents an analytical review of the scientific literature in PubMed, Google Scholar, medRxiv, bioRxiv which was conducted to study and evaluate the mechanisms, pathogenesis, and clinical picture of respiratory viral infections, including Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-СoV-2).Conclusion. Understanding the specific mechanisms of the development of the host’s immune response to respiratory viruses allows a better understanding of the course of a new coronavirus infection, including in patients with COPD, since respiratory tract infections are closely associated with the formation and exacerbation of COPD. Respiratory viruses activate immune responses and exacerbate underlying inflammation in COPD. SARS-СoV-2 leads to a dysregulated immune response and, in severe cases, an overactive immune response, causing the development of a cytokine storm and acute respiratory distress syndrome (ARDS). Unlike seasonal respiratory viruses, SARS-СoV-2 circulates throughout the year and can be a source of frequent and severe exacerbations in patients with COPD which require further monitoring and research.

show abstract

Using Unstated Cases to Correct for COVID-19 Pandemic Outbreak and Its Impact on Easing the Intervention for Qatar

Cited by 5 publications

References 41 publications

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier

Effect of temperature on the spread of Covid-19 in Qatar, Kuwait and other Gulf countries

Respiratory viral infections, SARS-СoV-2 and chronic obstructive pulmonary disease

Contact Info

Product

Resources

About