1. Younes AB, Hasan Z. COVID-19: modeling, prediction, and control. Appl Sci 2020;10:3666.
3. Hsiang S, Allen D, Annan-Phan S, Bell K, Bolliger I, Chong T,
et al. The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Nature 2020;584:262–267.
4. Ferguson NM, Laydon D, Nedjati-Gilani G, Imai N, Ainslie K, Baguelin M, et al. Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand. London: Imperial College, 2020.
5. Brzezinski A, Deiana G, Kecht V, Van Dijcke D. The COVID-19 Pandemic: Government vs. Community Action across the United States. INET Oxford Working Paper No. 2020-06. Oxford: Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, 2020.
6. Graham BS. Rapid COVID-19 vaccine development. Science 2020;368:945–946.
8. Thanh Le T, Andreadakis Z, Kumar A, Gomez Roman R, Tollefsen S, Saville M,
et al. The COVID-19 vaccine development landscape. Nat Rev Drug Discov 2020;19:305–306.
11. de la Fuente-Mella H, Rubilar R, Chahuan-Jimenez K, Leiva V. Modeling COVID-19 cases statistically and evaluating their effect on the economy of countries. Mathematics 2021;9:1558.
13. Biggerstaff M, Cowling BJ, Cucunuba ZM, Dinh L, Ferguson NM, Gao H,
et al. Early insights from statistical and mathematical modeling of key epidemiologic parameters of COVID-19. Emerg Infect Dis 2020;26:e1–e14.
18. Singh RK, Rani M, Bhagavathula AS, Sah R, Rodriguez-Morales AJ, Kalita H,
et al. Prediction of the COVID-19 pandemic for the top 15 affected countries: advanced autoregressive integrated moving average (ARIMA) model. JMIR Public Health Surveill 2020;6:e19115.
21. Kapoor A, Ben X, Liu L, Perozzi B, Barnes M, Blais M,
et al. Examining COVID-19 forecasting using spatio-temporal graph neural networks. Preprint at
https://arxiv.org/abs/2007.03113 (2020).
22. Fritz C, Dorigatti E, Rugamer D. Combining graph neural networks and spatio-temporal disease models to predict COVID-19 cases in Germany. Sci Rep 2022;12:3930.
23. Rauf HT, Lali MI, Khan MA, Kadry S, Alolaiyan H, Razaq A,
et al. Time series forecasting of COVID-19 transmission in Asia Pacific countries using deep neural networks. Pers Ubiquitous Comput 2021 Jan 10 [Epub].
https://doi.org/10.1007/s00779-020-01494-0.
29. Kermack WO, McKendrick AG. A contribution to the mathematical theory of epidemics. Proc R Soc Lond Ser A Contain Pap Math Phys Character 1927;115:700–721.
30. Shankar S, Mohakuda SS, Kumar A, Nazneen PS, Yadav AK, Chatterjee K,
et al. Systematic review of predictive mathematical models of COVID-19 epidemic. Med J Armed Forces India 2021;77(Suppl 2):S385–S392.
31. Kucharski AJ, Russell TW, Diamond C, Liu Y, Edmunds J, Funk S,
et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect Dis 2020;20:553–558.
33. Volpert V, Banerjee M, Petrovskii S. On a quarantine model of coronavirus infection and data analysis. Math Model Nat Phenom 2020;15:24.
34. Kochanczyk M, Grabowski F, Lipniacki T. Dynamics of COVID-19 pandemic at constant and time-dependent contact rates. Math Model Nat Phenom 2020;15:28.
37. Hellewell J, Abbott S, Gimma A, Bosse NI, Jarvis CI, Russell TW,
et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob Health 2020;8:e488–e496.
39. Cakir Z, Savas HB. A mathematical modelling approach in the spread of the novel 2019 coronavirus SARS-CoV-2 (COVID-19) pandemic. Electron J Gen Med 2020;17:em205.
40. Bouchnita A, Jebrane A. A multi-scale model quantifies the impact of limited movement of the population and mandatory wearing of face masks in containing the COVID-19 epidemic in Morocco. Math Model Nat Phenom 2020;15:31.
42. Roosa K, Lee Y, Luo R, Kirpich A, Rothenberg R, Hyman JM,
et al. Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020. Infect Dis Model 2020;5:256–263.
44. Ritchie H, Mathieu E, Rodes-Guirao L, Appel C, Giattino C, Ortiz-Ospina E,
et al. Coronavirus (COVID-19) vaccinations. Oxford: University of Oxford, 2020. Accessed 2022 Jan 22. Available from:
https://ourworldindata.org/covid-vaccinations.
46. Darby AC, Hiscox JA. Covid-19: variants and vaccination. BMJ 2021;372:n771.
51. He J, Chen G, Jiang Y, Jin R, Shortridge A, Agusti S,
et al. Comparative infection modeling and control of COVID-19 transmission patterns in China, South Korea, Italy and Iran. Sci Total Environ 2020;747:141447.
52. Reis RF, de Melo Quintela B, de Oliveira Campos J, Gomes JM, Rocha BM, Lobosco M,
et al. Characterization of the COVID-19 pandemic and the impact of uncertainties, mitigation strategies, and underreporting of cases in South Korea, Italy, and Brazil. Chaos Solitons Fractals 2020;136:109888.
53. Amiri Mehra AH, Shafieirad M, Abbasi Z, Zamani I. Parameter estimation and prediction of COVID-19 epidemic turning point and ending time of a case study on SIR/SQAIR epidemic models. Comput Math Methods Med 2020;2020:1465923.
55. Domingo E, Holland JJ. RNA virus mutations and fitness for survival. Annu Rev Microbiol 1997;51:151–178.
59. Kim S, Seo YB, Jung E. Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changes in Korea. Epidemiol Health 2020;42:e2020026.
60. Brauer F. Compartmental models in epidemiology. In: Mathematical Epidemiology (Brauer F, van den Driessche P, Wu J, eds.). Berlin: Springer Berlin Heidelberg, 2008. pp. 19–79.
62. Hale T, Petherick A, Phillips T, Webster S. Variation in Government Responses to COVID-19. Blavatnik School of Government Working Paper 31. Oxford: Blavatnik School of Government, 2020.
65. Ganyani T, Kremer C, Chen D, Torneri A, Faes C, Wallinga J,
et al. Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020. Euro Surveill 2020;25:2000257.
68. Ritchie H, Mathieu E, Rodes-Guirao L, Appel C, Giattino C, Ortiz-Ospina E,
et al. Coronavirus pandemic (COVID-19). Oxford: University of Oxford, 2020. Accessed 2022 Jan 4. Available from:
https://ourworldindata.org/coronavirus.
70. Mathieu E, Ritchie H, Ortiz-Ospina E, Roser M, Hasell J, Appel C,
et al. A global database of COVID-19 vaccinations. Nat Hum Behav 2021;5:947–953.