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  • Open Access

    ARTICLE

    Sensitivity Analysis of COVID-19 in Mediterranean Island

    Ahmet Savasan1, Bilgen Kaymakamzade1,2, Nezihal Gokbulut1,2,*, Evren Hincal1,2, Elcin Yoldascan3

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 133-148, 2022, DOI:10.32604/cmes.2022.017815

    Abstract The aim of this study is to examine the progress of the worldwide pandemic Covid-19. As authors, we have decided to analyze the situation of COVID-19 on Mediterranean island with accurate data. For this purpose, a mathematical model is constructed and proposed by dividing the whole population into sensible and suitable compartments. The study captures the dates February 01 till May 15, 2021. For the control of the spread of disease, vaccination and infection rates are compared and calculated. During calculations and comparison, MatLab software is used. All of the data that are used are taken from the Ministry of… More >

  • Open Access

    ARTICLE

    A Binomial Model Approach: Comparing the R0 Values of SARS-CoV-2 rRT-PCR Data from Laboratories across Northern Cyprus

    Nazife Sultanoglu1,2,*, Nezihal Gokbulut3, Tamer Sanlidag2, Evren Hincal2,3, Bilgen Kaymakamzade2,3, Murat Sayan2,4

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 717-729, 2021, DOI:10.32604/cmes.2021.016297

    Abstract Northern Cyprus has implemented relatively strict measures in the battle against the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The measures were introduced at the beginning of the COVID-19 pandemic, in order to prevent the spread of the disease. One of these measures was the use of two separate real-time reverse transcription polymerase chain reaction (rRT-PCR) tests for SARS-CoV-2 referred to as the double screening procedure, which was adopted following the re-opening of the sea, air and land borders for passengers after the first lockdown. The rRT-PCR double screening procedure involved reporting a negative rRT-PCR test which was… More >

  • Open Access

    ARTICLE

    SEIHCRD Model for COVID-19 Spread Scenarios, Disease Predictions and Estimates the Basic Reproduction Number, Case Fatality Rate, Hospital, and ICU Beds Requirement

    Avaneesh Singh*, Manish Kumar Bajpai

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 991-1031, 2020, DOI:10.32604/cmes.2020.012503

    Abstract We have proposed a new mathematical method, the SEIHCRD model, which has an excellent potential to predict the incidence of COVID-19 diseases. Our proposed SEIHCRD model is an extension of the SEIR model. Three-compartments have added death, hospitalized, and critical, which improves the basic understanding of disease spread and results. We have studied COVID-19 cases of six countries, where the impact of this disease in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. After estimating model parameters based on available clinical data, the model will propagate and forecast dynamic evolution. The model calculates the… More >

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