[1] Ciotti M, Ciccozzi M, Terrinoni A, et al. The COVID-19 pandemic
[J]. Critical reviews in clinical， laboratory sciences, 2020, 57(6): 365-388.

[2] Lipsitch M, Swerdlow D L, Finelli L. Defining the epidemiology of Covid-19—studies needed
[J]. New England journal of medicine, 2020, 382(13): 1194-1196.

[3] Bulut C, Kato Y. Epidemiology of COVID-19
[J]. Turkish journal of medical sciences, 2020, 50(9): 563-570.

[4] Mandal M, Jana S, Nandi S K, et al. A model based study on the dynamics of COVID-19: Prediction and control
[J]. Chaos, Solitons & Fractals, 2020, 136: 109889.

[5] Carcione J M, Santos J E, Bagaini C, et al. A simulation of a COVID-19 epidemic based on a deterministic SEIR model
[J]. Frontiers in public health, 2020, 8: 230.

[6] Ivorra B, Ferrández M R, Vela-Pérez M, et al. Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China
[J]. Communications in nonlinear science and numerical simulation, 2020, 88: 105303.

[7] Rapolu T, Nutakki B, Rani T S, et al. A time-dependent seird model for forecasting the COVID-19 transmission dynamics
[J]. medRxiv, 2020: 2020.05. 29.20113571.

[8] Oran D P, Topol E J. Prevalence of asymptomatic SARS-CoV-2 infection: a narrative review
[J]. Annals of internal medicine, 2020, 173(5): 362-367.

[9] Paltiel A D, Zheng A, Walensky R P. Assessment of SARS-CoV-2 screening strategies to permit the safe reopening of college campuses in the United States
[J]. JAMA network open, 2020, 3(7): e2016818-e2016818.

[10] Denny T N, Andrews L, Bonsignori M, et al. Implementation of a pooled surveillance testing program for asymptomatic SARS-CoV-2 infections on a college campus—Duke University, Durham, North Carolina, August 2–October 11, 2020
[J]. Morbidity and Mortality Weekly Report, 2020, 69(46): 1743.

[11] Li R, Pei S, Chen B, et al. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)
[J]. Science, 2020, 368(6490): 489-493.

[12] Fracchia J A, Motta J, Miller L S, et al. Evaluation of asymptomatic microhematuria
[J]. Urology, 1995, 46(4): 484-489.

[13] Lassas M, Siltanen S. Foreword: inverse problems in biology
[J]. Journal of mathematical biology, 2013, 67: 1-1.

[14] Jameson A, Kreindler E. Inverse problem of linear optimal control
[J]. SIAM Journal on Control, 1973, 11(1): 1-19. 

[15] Stevens M, Sunseri I, Alexanderian A. Hyper-differential sensitivity analysis for inverse problems governed by ODEs with application to COVID-19 modeling
[J]. Mathematical Biosciences, 2022, 351: 108887.

[16] Vogel C R. Computational methods for inverse problems
[M]. Society for Industrial and Applied Mathematics, 2002.

[17] Kaipio J, Somersalo E. Statistical and computational inverse problems
[M]. Springer Science & Business Media, 2006.

[18] Liu X, Hewings G, Wang S, et al. Modelling the situation of COVID-19 and effects of different containment strategies in China with dynamic differential equations and parameters estimation
[J]. MedRxiv, 2020: 2020.03. 09.20033498.

[19] Marinov T T, Marinova R S. Dynamics of COVID-19 using inverse problem for coefficient identification in SIR epidemic models
[J]. Chaos, Solitons & Fractals: X, 2020, 5: 100041.

[20] Godio A, Pace F, Vergnano A. SEIR modeling of the Italian epidemic of SARS-CoV-2 using computational swarm intelligence
[J]. International journal of environmental research and public health, 2020, 17(10): 3535.

[21] Krivorot’ko O I, Kabanikhin S I, Zyat’kov N Y, et al. Mathematical modeling and forecasting of COVID-19 in Moscow and Novosibirsk region
[J]. Numerical Analysis and Applications, 2020, 13: 332-348.

[22] Katoch S, Chauhan S S, Kumar V. A review on genetic algorithm: past, present, and future
[J]. Multimedia Tools and Applications, 2021, 80: 8091-8126.

[23] Wei X, Duan X, Chen L, et al. Optimal multi-objective distributed generation location and capacity by elite strategy genetic algorithm considering timing characteristics
[C]//E3S Web of Conferences. EDP Sciences, 2020, 185: 01018.

[24] Raue A, Becker V, Klingmüller U, et al. Identifiability and observability analysis for experimental design in nonlinear dynamical models
[J]. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2010, 20(4): 045105.

[25] Krivorotko O I, Andornaya D V, Kabanikhin S I. Sensitivity analysis and practical identifiability of some mathematical models in biology
[J]. Journal of Applied and Industrial Mathematics, 2020, 14: 115-130.

[26] Long J, Khaliq A Q M, Furati K M. Identification and prediction of time-varying parameters of COVID-19 model: a data-driven deep learning approach
[J]. International journal of computer mathematics, 2021, 98(8): 1617-1632.