Global stability of novel coronavirus model using fractional derivative

Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of pa...
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Autor*in:	Kumari, Preety [verfasserIn] Singh, Harendra Pal Singh, Swarn

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Extended RK-method Adams–Bashforth Fractional order COVID-19 model Existence-uniqueness Global stability

Anmerkung:	© The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Computational and applied mathematics - Berlin : Springer, 2003, 42(2023), 8 vom: 30. Okt.
Übergeordnetes Werk:	volume:42 ; year:2023 ; number:8 ; day:30 ; month:10

Links:	Volltext

DOI / URN:	10.1007/s40314-023-02413-8

Katalog-ID:	SPR053580338

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520			\|a Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way.
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650		4	\|a COVID-19 model \|7 (dpeaa)DE-He213
650		4	\|a Existence-uniqueness \|7 (dpeaa)DE-He213
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700	1		\|a Singh, Harendra Pal \|4 aut
700	1		\|a Singh, Swarn \|4 aut
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912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_74
912			\|a GBV_ILN_90
912			\|a GBV_ILN_95
912			\|a GBV_ILN_100
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
912			\|a GBV_ILN_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_152
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_171
912			\|a GBV_ILN_187
912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
912			\|a GBV_ILN_230
912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
912			\|a GBV_ILN_2006
912			\|a GBV_ILN_2007
912			\|a GBV_ILN_2008
912			\|a GBV_ILN_2009
912			\|a GBV_ILN_2010
912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
912			\|a GBV_ILN_2021
912			\|a GBV_ILN_2025
912			\|a GBV_ILN_2026
912			\|a GBV_ILN_2027
912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2037
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2039
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2056
912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2059
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
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912			\|a GBV_ILN_4035
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912			\|a GBV_ILN_4125
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912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4328
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4336
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author_variant	p k pk h p s hp hps s s ss
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allfields	10.1007/s40314-023-02413-8 doi (DE-627)SPR053580338 (SPR)s40314-023-02413-8-e DE-627 ger DE-627 rakwb eng Kumari, Preety verfasserin aut Global stability of novel coronavirus model using fractional derivative 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. Extended RK-method (dpeaa)DE-He213 Adams–Bashforth (dpeaa)DE-He213 Fractional order (dpeaa)DE-He213 COVID-19 model (dpeaa)DE-He213 Existence-uniqueness (dpeaa)DE-He213 Global stability (dpeaa)DE-He213 Singh, Harendra Pal aut Singh, Swarn aut Enthalten in Computational and applied mathematics Berlin : Springer, 2003 42(2023), 8 vom: 30. Okt. (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:42 year:2023 number:8 day:30 month:10 https://dx.doi.org/10.1007/s40314-023-02413-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 42 2023 8 30 10
spelling	10.1007/s40314-023-02413-8 doi (DE-627)SPR053580338 (SPR)s40314-023-02413-8-e DE-627 ger DE-627 rakwb eng Kumari, Preety verfasserin aut Global stability of novel coronavirus model using fractional derivative 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. Extended RK-method (dpeaa)DE-He213 Adams–Bashforth (dpeaa)DE-He213 Fractional order (dpeaa)DE-He213 COVID-19 model (dpeaa)DE-He213 Existence-uniqueness (dpeaa)DE-He213 Global stability (dpeaa)DE-He213 Singh, Harendra Pal aut Singh, Swarn aut Enthalten in Computational and applied mathematics Berlin : Springer, 2003 42(2023), 8 vom: 30. Okt. (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:42 year:2023 number:8 day:30 month:10 https://dx.doi.org/10.1007/s40314-023-02413-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 42 2023 8 30 10
allfields_unstemmed	10.1007/s40314-023-02413-8 doi (DE-627)SPR053580338 (SPR)s40314-023-02413-8-e DE-627 ger DE-627 rakwb eng Kumari, Preety verfasserin aut Global stability of novel coronavirus model using fractional derivative 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. Extended RK-method (dpeaa)DE-He213 Adams–Bashforth (dpeaa)DE-He213 Fractional order (dpeaa)DE-He213 COVID-19 model (dpeaa)DE-He213 Existence-uniqueness (dpeaa)DE-He213 Global stability (dpeaa)DE-He213 Singh, Harendra Pal aut Singh, Swarn aut Enthalten in Computational and applied mathematics Berlin : Springer, 2003 42(2023), 8 vom: 30. Okt. (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:42 year:2023 number:8 day:30 month:10 https://dx.doi.org/10.1007/s40314-023-02413-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 42 2023 8 30 10
allfieldsGer	10.1007/s40314-023-02413-8 doi (DE-627)SPR053580338 (SPR)s40314-023-02413-8-e DE-627 ger DE-627 rakwb eng Kumari, Preety verfasserin aut Global stability of novel coronavirus model using fractional derivative 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. Extended RK-method (dpeaa)DE-He213 Adams–Bashforth (dpeaa)DE-He213 Fractional order (dpeaa)DE-He213 COVID-19 model (dpeaa)DE-He213 Existence-uniqueness (dpeaa)DE-He213 Global stability (dpeaa)DE-He213 Singh, Harendra Pal aut Singh, Swarn aut Enthalten in Computational and applied mathematics Berlin : Springer, 2003 42(2023), 8 vom: 30. Okt. (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:42 year:2023 number:8 day:30 month:10 https://dx.doi.org/10.1007/s40314-023-02413-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 42 2023 8 30 10
allfieldsSound	10.1007/s40314-023-02413-8 doi (DE-627)SPR053580338 (SPR)s40314-023-02413-8-e DE-627 ger DE-627 rakwb eng Kumari, Preety verfasserin aut Global stability of novel coronavirus model using fractional derivative 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. Extended RK-method (dpeaa)DE-He213 Adams–Bashforth (dpeaa)DE-He213 Fractional order (dpeaa)DE-He213 COVID-19 model (dpeaa)DE-He213 Existence-uniqueness (dpeaa)DE-He213 Global stability (dpeaa)DE-He213 Singh, Harendra Pal aut Singh, Swarn aut Enthalten in Computational and applied mathematics Berlin : Springer, 2003 42(2023), 8 vom: 30. Okt. (DE-627)47617502X (DE-600)2171678-X 1807-0302 nnns volume:42 year:2023 number:8 day:30 month:10 https://dx.doi.org/10.1007/s40314-023-02413-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 42 2023 8 30 10
language	English
source	Enthalten in Computational and applied mathematics 42(2023), 8 vom: 30. Okt. volume:42 year:2023 number:8 day:30 month:10
sourceStr	Enthalten in Computational and applied mathematics 42(2023), 8 vom: 30. Okt. volume:42 year:2023 number:8 day:30 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Extended RK-method Adams–Bashforth Fractional order COVID-19 model Existence-uniqueness Global stability
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container_title	Computational and applied mathematics
authorswithroles_txt_mv	Kumari, Preety @@aut@@ Singh, Harendra Pal @@aut@@ Singh, Swarn @@aut@@
publishDateDaySort_date	2023-10-30T00:00:00Z
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author	Kumari, Preety
spellingShingle	Kumari, Preety misc Extended RK-method misc Adams–Bashforth misc Fractional order misc COVID-19 model misc Existence-uniqueness misc Global stability Global stability of novel coronavirus model using fractional derivative
authorStr	Kumari, Preety
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topic_title	Global stability of novel coronavirus model using fractional derivative Extended RK-method (dpeaa)DE-He213 Adams–Bashforth (dpeaa)DE-He213 Fractional order (dpeaa)DE-He213 COVID-19 model (dpeaa)DE-He213 Existence-uniqueness (dpeaa)DE-He213 Global stability (dpeaa)DE-He213
topic	misc Extended RK-method misc Adams–Bashforth misc Fractional order misc COVID-19 model misc Existence-uniqueness misc Global stability
topic_unstemmed	misc Extended RK-method misc Adams–Bashforth misc Fractional order misc COVID-19 model misc Existence-uniqueness misc Global stability
topic_browse	misc Extended RK-method misc Adams–Bashforth misc Fractional order misc COVID-19 model misc Existence-uniqueness misc Global stability
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title	Global stability of novel coronavirus model using fractional derivative
ctrlnum	(DE-627)SPR053580338 (SPR)s40314-023-02413-8-e
title_full	Global stability of novel coronavirus model using fractional derivative
author_sort	Kumari, Preety
journal	Computational and applied mathematics
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author_browse	Kumari, Preety Singh, Harendra Pal Singh, Swarn
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doi_str_mv	10.1007/s40314-023-02413-8
title_sort	global stability of novel coronavirus model using fractional derivative
title_auth	Global stability of novel coronavirus model using fractional derivative
abstract	Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. Additionally, various control measures are also shown graphically. The simulated results show the effectiveness of fractional order derivatives and control parameters which may help government officials and individuals manage the pandemic in a better way. © The Author(s) under exclusive licence to Sociedade Brasileira de Matemática Aplicada e Computacional 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	Global stability of novel coronavirus model using fractional derivative
url	https://dx.doi.org/10.1007/s40314-023-02413-8
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author2	Singh, Harendra Pal Singh, Swarn
author2Str	Singh, Harendra Pal Singh, Swarn
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doi_str	10.1007/s40314-023-02413-8
up_date	2024-07-03T20:33:04.334Z
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Mathematical modeling plays a crucial role in disease modeling. Therefore, in this work, a mathematical model for novel coronavirus is proposed using Caputo-Fabrizio (CF) fractional derivative, while considering the issue of dimensional mismatch for proposed model. This model consists of paramount compartments such as asymptomatic and quarantined. Subsequently, existence and uniqueness of proposed model are shown with the help of fixed-point theorem. The boundedness of solutions is also established using Laplace transform. The local and global stability of disease-free equilibrium point (DFE) of the proposed fractional order model is evaluated. The model is numerically solved using the three-point Adams–Bashforth method (ABM). The predicted results are validated through real data for India. For finding the best-fitted parameters which describe the coronavirus scenario, LSQCURVEFIT function in MATLAB is employed. To determine the reliability of the applied technique, we conduct a comparative analysis of ABM method with Euler method. Notably, the results show the efficiency of ABM method. At the same time, sensitivity analysis for parameters in accordance with reproduction number is conferred. Furthermore, numerical results for distinct values of fractional order derivatives are accomplished. This study also shows the long-term trajectories for recovered, active and death cases. The obtained results of the proposed model are in line with real data for fractional order. 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