Prediction studies of the epidemic peak of coronavirus disease in Brazil via new generalised Caputo type fractional derivatives

Kumar, Pushpendra; Ertürk, Vedat Suat; Abboubakar, Hamadjam; Nisar, Kottakkaran Sooppy

doi:10.1016/j.aej.2021.01.032

Cited by 51 publications

(23 citation statements)

References 28 publications

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“…A compartmental mathematical model was formulated to predict the evolution of the virus in Cameroon and to analyze the reported cases in Brazil [43,44]. The results achieved using these compartmental mathematical models indicated that the dynamics of COVID-19 disease are influenced by variations in the value of R 0 .…”

Section: Discussionmentioning

confidence: 99%

Predicting the Number of COVID-19 Infections and Deaths in USA

Felix

Ozigbu

Conserve

et al. 2022

Preprint

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Background: Uncertainties surrounding the 2019 novel coronavirus (COVID-19) remain a major global health challenge and requires attention. Researchers and medical experts have made remarkable efforts to reduce the number of cases and prevent future outbreaks through vaccines and other measures. However, there is little evidence on how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection entropy can be applied in predicting the possible number of infections and deaths. In addition, more studies on how the COVID-19 infection density contributes to the rise in infections are needed. This study demonstrates how the SARS-COV-2 daily infection entropy can be applied in predicting the number of infections within a given period. In addition, the infection density within a given population attributes to an increase in the number of COVID-19 cases and, consequently, the new variants. Result: Using the COVID-19 initial data reported by Johns Hopkins University, World Health Organization and Global Initiative on Sharing All Influenza Data, the result shows that the original SAR-COV-2 strain has R0<1 with an initial infection growth rate entropy of 9.11 bits for the United States. At close proximity the average infection time for an infected individual to infect others within a susceptible population is approximately 7 minutes. Assuming no vaccines were available, in the United States, the number of infections could range between 41,220,199 and 82,440,398 in late March 2022 with approximately, 1,211,036 deaths. However, with the available vaccines, nearly 48 Million COVID-19 cases and 706, 437 deaths have been prevented. Conclusion: The proposed technique will contribute to the ongoing investigation of the COVID-19 pandemic and a blueprint to address the uncertainties surrounding the pandemic.

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Section: Discussionmentioning

confidence: 99%

Predicting the Number of COVID-19 Infections and Deaths in USA

Felix

Ozigbu

Conserve

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…Several mathematical models have been devised to predict the epidemiologic trend of the COVID-19 outbreak, including stochastic/mathematical (integer derivative [15] , [16] or fractional-order [17] , [18] , [19] ) models, mass-action, (spatial) structured metapopulation, agent-based networked, and other compartmentalized models [20] , among others. According to a systematic survey of the literature, synthesizing 242 studies, 46.1% of studies used compartmental models, 31.8% statistical models (growth models and time series), 6.7%, 4.7%, 3.3%, 2.3% and 1.3% Artificial Intelligence-, Bayesian approach-, hybrid, network- and individual agent-based models, respectively [21] .…”

Section: Introductionmentioning

confidence: 99%

Lessons drawn from China and South Korea for managing COVID-19 epidemic: Insights from a comparative modeling study

et al. 2022

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We conducted a comparative study of the COVID-19 epidemic in three different settings: mainland China, the Guangdong province of China and South Korea, by formulating two disease transmission dynamics models which incorporate epidemic characteristics and setting-specific interventions, and fitting the models to multi-source data to identify initial and effective reproduction numbers and evaluate effectiveness of interventions. We estimated the initial basic reproduction number for South Korea, the Guangdong province and mainland China as 2.6 (95% confidence interval (CI): (2.5, 2.7)), 3.0 (95%CI: (2.6, 3.3)) and 3.8 (95%CI: (3.5,4.2)), respectively, given a serial interval with mean of 5 days with standard deviation of 3 days. We found that the effective reproduction number for the Guangdong province and mainland China has fallen below the threshold 1 since February 8th and 18th respectively, while the effective reproduction number for South Korea remains high until March 2nd Moreover our model-based analysis shows that the COVID-19 epidemics in South Korean is almost under control with the cumulative confirmed cases tending to be stable as of April 14th. Through sensitivity analysis, we show that a coherent and integrated approach with stringent public health interventions is the key to the success of containing the epidemic in China and especially its provinces outside its epicenter. In comparison, we find that the extremely high detection rate is the key factor determining the success in controlling the COVID-19 epidemics in South Korea. The experience of outbreak control in mainland China and South Korea should be a guiding reference for the rest of the world.

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“…Recently, scientists around the globe have done outstanding investigations on the transmission dynamics, forecasting, control tactics, and estimation for the infection of COVID-19. Several mathematicians have given the number of articles to define the structure of COVID-19, in which some are [1] , [2] , [3] , [4] , [5] , [6] , [7] . Ameen et al in [8] studied the structure of Coronavirus-19 with a fresh dynamical model.…”

Section: Introductionmentioning

confidence: 99%

Fractional dynamics of 2019-nCOV in Spain at different transmission rate with an idea of optimal control problem formulation

Kumar

Ertürk

Nisar

et al. 2022

Alexandria Engineering Journal

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In this article, we studied the fractional dynamics of the most dangerous deathly disease which outbreaks have been recorded all over the world, called 2019-nCOV or COVID-19. We used the numerical values of the given parameters based on the real data of the 2019-nCOV cases in Spain for the time duration of 25 February to 9 October 2020. We performed our observations with the help of the Atangana-Baleanu (AB) non-integer order derivative. We analysed the optimal control problem in a fractional sense for giving the information on all necessary health care issues. We applied the Predictor-Corrector method to do the important graphical simulations. Also, we provided the analysis related to the existence of a unique solution and the stability of the proposed scheme. The aim and the main contribution of this research is to analyse the structure of novel coronavirus in Spain at different transmission rate and to indicate the danger of this deathly disease for future with the introduction of some optimal controls and health care measures.

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Prediction studies of the epidemic peak of coronavirus disease in Brazil via new generalised Caputo type fractional derivatives

Cited by 51 publications

References 28 publications

Predicting the Number of COVID-19 Infections and Deaths in USA

Predicting the Number of COVID-19 Infections and Deaths in USA

Lessons drawn from China and South Korea for managing COVID-19 epidemic: Insights from a comparative modeling study

Fractional dynamics of 2019-nCOV in Spain at different transmission rate with an idea of optimal control problem formulation

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