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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 *** proposed SEIHCRD model is an extension of the SEIR ***-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and *** 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 *** estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic *** calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category *** calculates two types of Case fatality rate one is CFR daily,and the other is total *** 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 *** SEIHCRD model outperforms the classic ARXmodel and the ARIMA ***,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target *** 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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Study of Non-Pharmacological Interventions on COVID-19 Spread

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Computer Modeling in Engineering & Sciences 2020年第12期125卷 967-990页

作者： avaneesh singh Saroj Kumar Chandra Manish Kumar Bajpai PDPM Indian Institute of Information Technology Design and ManufacturingJabalpur482005India

COVID-19 disease has emerged as one of the life threatening threat to the society.A novel beta coronavirus causes *** began as unidentified pneumonia of unknown etiology in Wuhan City,Hubei province in China emerged in December *** vaccine has been produced till *** models are used to study the impact of different measures used to decrease *** models have been designed to estimate the numbers of spreaders in different scenarios in the present *** the present manuscript,three different mathematical models have been proposed with different scenarios,such as screening,quarantine,andNPIs,to estimate the number of virus *** analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other *** every people suffering fromCOVID-19 disease are *** screening and quarantine with NPIs have been implemented to study their impact on the *** has been found that NPI measures can reduce the number of *** NPI measures reduce the spread function’s growth and provide decision makers more time to prepare with in dealing with the disease.

关键词： Coronavirus COVID-19 mathematical modelling epidemic

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