Thermostated Susceptible-Infected-Susceptible epidemic model

The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Alrebdi, H.I. [verfasserIn] Steklain, Andre [verfasserIn] Amorim, Edgard P.M. [verfasserIn] Zotos, Euaggelos [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Epidemic SIS epidemic model Hamiltonian epidemic model

Übergeordnetes Werk:	Enthalten in: Applied mathematics and computation - New York, NY : Elsevier, 1975, 441
Übergeordnetes Werk:	volume:441

DOI / URN:	10.1016/j.amc.2022.127701

Katalog-ID:	ELV008862362

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520			\|a The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model.
650		4	\|a Epidemic
650		4	\|a SIS epidemic model
650		4	\|a Hamiltonian epidemic model
700	1		\|a Steklain, Andre \|e verfasserin \|0 (orcid)0000-0001-5964-2137 \|4 aut
700	1		\|a Amorim, Edgard P.M. \|e verfasserin \|0 (orcid)0000-0001-7235-7904 \|4 aut
700	1		\|a Zotos, Euaggelos \|e verfasserin \|0 (orcid)0000-0002-1565-4467 \|4 aut
773	0	8	\|i Enthalten in \|t Applied mathematics and computation \|d New York, NY : Elsevier, 1975 \|g 441 \|h Online-Ressource \|w (DE-627)26555022X \|w (DE-600)1465428-3 \|w (DE-576)078314976 \|7 nnns
773	1	8	\|g volume:441
912			\|a GBV_USEFLAG_U
912			\|a SYSFLAG_U
912			\|a GBV_ELV
912			\|a SSG-OPC-MAT
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_32
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_150
912			\|a GBV_ILN_151
912			\|a GBV_ILN_224
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
912			\|a GBV_ILN_2005
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_2027
912			\|a GBV_ILN_2034
912			\|a GBV_ILN_2038
912			\|a GBV_ILN_2044
912			\|a GBV_ILN_2048
912			\|a GBV_ILN_2049
912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2056
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_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_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4242
912			\|a GBV_ILN_4251
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4326
912			\|a GBV_ILN_4333
912			\|a GBV_ILN_4334
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4393
936	b	k	\|a 31.80 \|j Angewandte Mathematik
936	b	k	\|a 31.76 \|j Numerische Mathematik
951			\|a AR
952			\|d 441

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author_variant	h a ha a s as e p a ep epa e z ez
matchkey_str	alrebdihisteklainandreamorimedgardpmzoto:2022----:hrottducpilifcesset
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allfields	10.1016/j.amc.2022.127701 doi (DE-627)ELV008862362 (ELSEVIER)S0096-3003(22)00769-X DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 31.76 bkl Alrebdi, H.I. verfasserin aut Thermostated Susceptible-Infected-Susceptible epidemic model 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model. Epidemic SIS epidemic model Hamiltonian epidemic model Steklain, Andre verfasserin (orcid)0000-0001-5964-2137 aut Amorim, Edgard P.M. verfasserin (orcid)0000-0001-7235-7904 aut Zotos, Euaggelos verfasserin (orcid)0000-0002-1565-4467 aut Enthalten in Applied mathematics and computation New York, NY : Elsevier, 1975 441 Online-Ressource (DE-627)26555022X (DE-600)1465428-3 (DE-576)078314976 nnns volume:441 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.80 Angewandte Mathematik 31.76 Numerische Mathematik AR 441
spelling	10.1016/j.amc.2022.127701 doi (DE-627)ELV008862362 (ELSEVIER)S0096-3003(22)00769-X DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 31.76 bkl Alrebdi, H.I. verfasserin aut Thermostated Susceptible-Infected-Susceptible epidemic model 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model. Epidemic SIS epidemic model Hamiltonian epidemic model Steklain, Andre verfasserin (orcid)0000-0001-5964-2137 aut Amorim, Edgard P.M. verfasserin (orcid)0000-0001-7235-7904 aut Zotos, Euaggelos verfasserin (orcid)0000-0002-1565-4467 aut Enthalten in Applied mathematics and computation New York, NY : Elsevier, 1975 441 Online-Ressource (DE-627)26555022X (DE-600)1465428-3 (DE-576)078314976 nnns volume:441 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.80 Angewandte Mathematik 31.76 Numerische Mathematik AR 441
allfields_unstemmed	10.1016/j.amc.2022.127701 doi (DE-627)ELV008862362 (ELSEVIER)S0096-3003(22)00769-X DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 31.76 bkl Alrebdi, H.I. verfasserin aut Thermostated Susceptible-Infected-Susceptible epidemic model 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model. Epidemic SIS epidemic model Hamiltonian epidemic model Steklain, Andre verfasserin (orcid)0000-0001-5964-2137 aut Amorim, Edgard P.M. verfasserin (orcid)0000-0001-7235-7904 aut Zotos, Euaggelos verfasserin (orcid)0000-0002-1565-4467 aut Enthalten in Applied mathematics and computation New York, NY : Elsevier, 1975 441 Online-Ressource (DE-627)26555022X (DE-600)1465428-3 (DE-576)078314976 nnns volume:441 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.80 Angewandte Mathematik 31.76 Numerische Mathematik AR 441
allfieldsGer	10.1016/j.amc.2022.127701 doi (DE-627)ELV008862362 (ELSEVIER)S0096-3003(22)00769-X DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 31.76 bkl Alrebdi, H.I. verfasserin aut Thermostated Susceptible-Infected-Susceptible epidemic model 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model. Epidemic SIS epidemic model Hamiltonian epidemic model Steklain, Andre verfasserin (orcid)0000-0001-5964-2137 aut Amorim, Edgard P.M. verfasserin (orcid)0000-0001-7235-7904 aut Zotos, Euaggelos verfasserin (orcid)0000-0002-1565-4467 aut Enthalten in Applied mathematics and computation New York, NY : Elsevier, 1975 441 Online-Ressource (DE-627)26555022X (DE-600)1465428-3 (DE-576)078314976 nnns volume:441 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.80 Angewandte Mathematik 31.76 Numerische Mathematik AR 441
allfieldsSound	10.1016/j.amc.2022.127701 doi (DE-627)ELV008862362 (ELSEVIER)S0096-3003(22)00769-X DE-627 ger DE-627 rda eng 510 DE-600 31.80 bkl 31.76 bkl Alrebdi, H.I. verfasserin aut Thermostated Susceptible-Infected-Susceptible epidemic model 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model. Epidemic SIS epidemic model Hamiltonian epidemic model Steklain, Andre verfasserin (orcid)0000-0001-5964-2137 aut Amorim, Edgard P.M. verfasserin (orcid)0000-0001-7235-7904 aut Zotos, Euaggelos verfasserin (orcid)0000-0002-1565-4467 aut Enthalten in Applied mathematics and computation New York, NY : Elsevier, 1975 441 Online-Ressource (DE-627)26555022X (DE-600)1465428-3 (DE-576)078314976 nnns volume:441 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OPC-MAT GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 31.80 Angewandte Mathematik 31.76 Numerische Mathematik AR 441
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authorswithroles_txt_mv	Alrebdi, H.I. @@aut@@ Steklain, Andre @@aut@@ Amorim, Edgard P.M. @@aut@@ Zotos, Euaggelos @@aut@@
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author	Alrebdi, H.I.
spellingShingle	Alrebdi, H.I. ddc 510 bkl 31.80 bkl 31.76 misc Epidemic misc SIS epidemic model misc Hamiltonian epidemic model Thermostated Susceptible-Infected-Susceptible epidemic model
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topic_title	510 DE-600 31.80 bkl 31.76 bkl Thermostated Susceptible-Infected-Susceptible epidemic model Epidemic SIS epidemic model Hamiltonian epidemic model
topic	ddc 510 bkl 31.80 bkl 31.76 misc Epidemic misc SIS epidemic model misc Hamiltonian epidemic model
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title	Thermostated Susceptible-Infected-Susceptible epidemic model
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title_full	Thermostated Susceptible-Infected-Susceptible epidemic model
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title_sort	thermostated susceptible-infected-susceptible epidemic model
title_auth	Thermostated Susceptible-Infected-Susceptible epidemic model
abstract	The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model.
abstractGer	The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model.
abstract_unstemmed	The evolution of epidemics based on the Susceptible-Infected-Susceptible (SIS) model relies on the density of infected individuals ρ . Recent results show that the mean density 〈 ρ 〉 and its variance σ 2 can be regarded as canonical variables and obey Hamilton’s equations. Using the Hamiltonian formulation, we study the SIS system coupled to a Nosé thermal bath. We reinterpret classical parameters like temperature in an epidemiological context. In contrast to classical epidemiological models, the thermal bath modifies the dynamical behavior of the system by introducing fluctuations, such as those seen in some infectious waves. We study the stability and show that 〈 ρ 〉 tends to be half of the value predicted by the original SIS model.
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title_short	Thermostated Susceptible-Infected-Susceptible epidemic model
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author2	Steklain, Andre Amorim, Edgard P.M. Zotos, Euaggelos
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doi_str	10.1016/j.amc.2022.127701
up_date	2024-07-06T21:09:41.792Z
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Thermostated Susceptible-Infected-Susceptible epidemic model

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