[1] Amouch M, Karim N. Modeling the dynamic of COVID-19 with different types of transmissions[J]. Chaos, Solitons & Fractals, 2021, 150: 111188.
[2] Pei S, Makse H A. Spreading dynamics in complex networks[J]. Journal of Statistical Mechanics: Theory and Experiment, 2013, 2013(12): P12002.
[3] Kermack W O, Mckendrick A G, Walker G T. A contribution to the mathematical theory of epidemics[J]. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 1997, 115(772): 700-721.
[4] Geng X, Katul G G, Gerges F, et al. A kernel-modulated SIR model for Covid-19 contagious spread from county to continent[J]. Proceedings of the National Academy of Sciences, 2021, 118(21): e2023321118.
[5] Ram V, Schaposnik L P. A modified age-structured SIR model for COVID-19 type viruses[J]. Scientific Reports, 2021, 11(1): 15194.
[6] Cai M, Karniadakis G E, Li C. Fractional SEIR model and data-driven predictions of COVID-19 dynamics of omicron variant[J]. Chaos: an Interdisciplinary Journal of Nonlinear Science, 2022, 32(7): 071101.
[7] Kiselev I N, Akberdin I R, Kolpakov F A. Delay-differential SEIR modeling for improved modelling of infection dynamics[J]. Scientific Reports, 2023, 13(1): 13439.
[8] Wang J, Wang Z, Yu P, et al. The SEIR dynamic evolutionary model with markov chains in hyper networks[J]. Sustainability, 2022, 14(20): 13036.
[9] Zhang J, Jin T. A stochastic semi-parametric SEIR model with infectivity in an incubation period[J]. Mathematics, 2024, 12(10): 1580.
[10] Basnarkov L. SEAIR Epidemic spreading model of COVID-19[J]. Chaos, Solitons & Fractals, 2021, 142: 110394.
[11] Ndaïrou F, Area I, Nieto J J, et al. Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan[J]. Chaos, Solitons & Fractals, 2020, 135: 109846.
[12] Babaei A, Ahmadi M, Jafari H, et al. A mathematical model to examine the effect of quarantine on the spread of coronavirus[J]. Chaos, Solitons & Fractals, 2021, 142: 110418.
[13] Tyagi S, Martha S C, Abbas S, et al. Mathematical modeling and analysis for controlling the spread of infectious diseases[J]. Chaos, Solitons & Fractals, 2021, 144: 110707.
[14] Garira W, Maregere B. The transmission mechanism theory of disease dynamics: its aims, assumptions and limitations[J]. Infectious Disease Modelling, 2023, 8(1): 122-144.
[15] Wang X, Lyu Y, Yao C, et al. Simulating the spread of infection in networks with quantum computers[J]. Physical Review Applied, 2023, 19(6): 064035.
[16] Gomatam R V. Quantum theory and the observation problem[J]. Journal of Consciousness Studies, 1999, 6(11/12):173-190.
[17] Schubert D, Richter J, Jin F, et al. Quantum versus classical dynamics in spin models: chains, ladders, and square lattices[J]. Physical Review B, 2021, 104(5): 054415.
[18] Yanofsky N S. An introduction to Quantum computing[DB/OL].[2024-06-09]. http://link.springer.com/10.1007/978-94-007-0080-2_10.
[19] Wang Y. Quantum computation and quantum information[J]. Statistical Science, 2012, 27(3): 373-394.
[20] Galindo A, Martín-delgado M A. Information and computation: classical and quantum aspects[J]. Reviews of Modern Physics, 2002, 74(2): 347-423.
[21] Javadi-abhari A, Treinish M, Krsulich K, et al. Quantum Computing with Qiskit[M/OL].[2024-06-09]. http://arxiv.org/abs/2405.08810.
[22] Jones T C, Biele G, Mühlemann B, et al. Estimating infectiousness throughout SARS-CoV-2 infection course[J]. Science, 2021, 373(6551): eabi5273.
[23] Alene M, Yismaw L, Assemie M A, et al. Serial interval and incubation period of COVID-19: a systematic review and meta-analysis[J]. BMC Infectious Diseases, 2021, 21(1): 257.
[24] Tindale L C, Stockdale J E, Coombe M, et al. Evidence for transmission of COVID-19 prior to symptom onset[DB/OL].[2024-01-02]. https://elifesciences.org/articles/57149.
[25] Memoli M J, Athota R, Reed S, et al. The natural history of influenza infection in the severely immunocompromised vs nonimmunocompromised hosts[J]. Clinical Infectious Diseases, 2014, 58(2): 214-224.
[26] Chen X, Liu S, Goraya M U, et al. Host immune response to influenza a virus infection[J]. Frontiers in Immunology, 2018, 9: 320.
[27] Lessler J, Reich N G, Brookmeyer R, et al. Incubation periods of acute respiratory viral infections: a systematic review[J]. The Lancet Infectious Diseases, 2009, 9(5): 291-300.
[28] Gendelman H E, Narayan O, Molineaux S, et al. Slow, persistent replication of lentiviruses: role of tissue macrophages and macrophage precursors in bone marrow.[J]. Proceedings of the National Academy of Sciences, 1985, 82(20): 7086-7090.
[29] Telo Da Gama M M, Nunes A. Epidemics in small world networks[J]. The European Physical Journal B-Condensed Matter and Complex Systems, 2006, 50(1): 205-208.
[30] Barabási A L, Albert R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439): 509-512.
[31] Harapan H, Itoh N, Yufika A, et al. Coronavirus disease 2019 (COVID-19): a literature review[J]. Journal of Infection and Public Health, 2020, 13(5): 667-673.
[32] Gunzler D D, Sehgal A R. Time-Varying COVID-19 Reproduction Number in the United States[M/OL]. (2020-04-15)[2024-06-01]. http://medrxiv.org/lookup/doi/10.1101/2020.04.10.20060863.
[33] Alimohamadi Y, Taghdir M, Sepandi M. Estimate of the basic reproduction number for COVID-19: a systematic review and meta-analysis[J]. Journal of Preventive Medicine and Public Health, 2020, 53: 151-157.
[34] Linton N, Kobayashi T, Yang Y, et al. Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data[J]. Journal of Clinical Medicine, 2020, 9(2): 538.
[35] Tolossa T, Wakuma B, Seyoum Gebre D, et al. Time to recovery from COVID-19 and its predictors among patients admitted to treatment center of wollega university referral hospital, western ethiopia: survival analysis of retrospective cohort study[J]. Plos One, 2021, 16(6): e0252389.
