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Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

Computers, Materials & Continua 2023年第2期74卷 2345-2361页

作者： Fazal Dayan Dumitru Baleanu Nauman Ahmed Jan Awrejcewicz Muhammad Rafiq Ali Raza Muhammad Ozair Ahmad Department of Mathematics School of ScienceUniversity of Management and TechnologyLahore54000Pakistan Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung40402Taiwan Institute of Space Sciences Magurele-Bucharest077125Romania Department of Mathematics and Statistics University of LahoreLahore54000Pakistan Department of Automation Biomechanics and MechatronicsLodz University of Technology1/15 Stefanowskiego St.90-924LodzPoland Department of Mathematics Faculty of Science&TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan

The application of fuzzy theory is vital in all scientific disciplines.The construction of mathematical models with fuzziness is little studied in the literature.With this in mind and for a better understanding of the disease,an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classicalmodel ofmalaria transmission.The parametersβandδ,being function of the malaria virus load,are considered fuzzy numbers.Three steady states and the reproduction number of the model are analyzed in fuzzy senses.A numerical technique is developed in a fuzzy environment to solve the studied model,which retains essential properties such as positivity and dynamic consistency.Moreover,numerical simulations are carried out to illustrate the analytical results of the developed technique.Unlike most of the classical methods in the literature,the proposed approach converges unconditionally and can be considered a reliable tool for studying malaria disease dynamics.

关键词： sier model fuzzy parameters malaria NSFD scheme stability

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

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Computer modeling in Engineering & Sciences 2020年第12期125卷 991-1031页

作者： Avaneesh Singh Manish Kumar Bajpai PDPM Indian Institute of Information Technology Design and ManufacturingJabalpur482005India

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 studiedCOVID-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 modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.

关键词： COVID-19 coronavirus sier model SEIHCRD model parameter estimation mathematical model India Brazil United Kingdom United States Spain Italy hospital beds ICU beds basic reproduction number case fatality rate

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