A stochastic epidemic model of COVID-19 disease
To model the evolution of diseases with extended latency periods and the presence of asymptomatic patients like COVID-19, we define a simple discrete time stochastic SIR-type epidemic model. We include both latent periods as well as the presence of quarantine areas, to capture the evolutionary dynam...
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| Published in | AIMS mathematics Vol. 5; no. 6; pp. 7661 - 7677 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
AIMS Press
01.11.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2473-6988 2473-6988 |
| DOI | 10.3934/math.2020490 |
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| Abstract | To model the evolution of diseases with extended latency periods and the presence of asymptomatic patients like COVID-19, we define a simple discrete time stochastic SIR-type epidemic model. We include both latent periods as well as the presence of quarantine areas, to capture the evolutionary dynamics of such diseases. |
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| AbstractList | To model the evolution of diseases with extended latency periods and the presence of asymptomatic patients like COVID-19, we define a simple discrete time stochastic SIR-type epidemic model. We include both latent periods as well as the presence of quarantine areas, to capture the evolutionary dynamics of such diseases. |
| Author | Rovira, Carles Bardina, Xavier Ferrante, Marco |
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| CitedBy_id | crossref_primary_10_1007_s10198_022_01491_5 crossref_primary_10_1007_s10729_021_09561_5 crossref_primary_10_1007_s00477_021_02065_2 crossref_primary_10_3934_math_20231181 crossref_primary_10_3390_axioms10010018 crossref_primary_10_3934_mbe_2021095 crossref_primary_10_1007_s12190_021_01658_y crossref_primary_10_1016_j_chaos_2020_110381 crossref_primary_10_1371_journal_pone_0250029 crossref_primary_10_3390_math10091583 crossref_primary_10_1016_j_ejor_2021_12_037 crossref_primary_10_1016_j_ejor_2021_11_012 crossref_primary_10_3390_ijerph19063707 crossref_primary_10_1016_j_rinp_2021_104311 |
| Cites_doi | 10.1007/s11538-009-9487-6 10.1016/j.mbs.2006.09.018 |
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| CorporateAuthor | 2 Dipartimento di Matematica “Tullio Levi-Civita”, Università degli Studi di Padova, Via Trieste 63, 35121-Padova, Italy 3 Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Gran Via 585, 08007-Barcelona 1 Departament de Matemàtiques, Universitat Autonòma de Barcelona, 08193-Bellaterra |
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| References | 11 13 4 H. C. Tuckwell, R. J. Williams (9) G. Huang, Y. Takeuchi, W. Ma (8) 10 |
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| Title | A stochastic epidemic model of COVID-19 disease |
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