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36. Gazzola M, Argentina M, Mahadevan L (2014) Scaling macroscopic aquatic locomotion.
Nat Phys 10:758–761
37. Nesteruk I (2019) Maximal speed of underwater locomotion. Innov Biosyst Bioeng 3
(3):152–167. https://doi.org/10.20535/ibb.2019.3.3.177976
38. Nesteruk I (2020) Stabilization of the coronavirus pandemic in Italy and global prospects.
[Preprint.] MEDRXIV. https://medrxiv.org/cgi/content/short/2020.03.28.20045898v1
39. Nesteruk I, Kydybyn I, Demelmair G (2020) Coronavirus pandemic dynamics in March.
2020. What can we expect in April?. [Preprint.] ResearchGate. https://doi.org/10.13140/rg.
2.2.36305.28009
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[Preprint.] ResearchGate. https://doi.org/10.13140/rg.2.2.21570.32961. https://www.
researchgate.net/publication/340917471_Corona_pandemic_global_stabilization
41. Nesteruk I, Kydybyn I, Demelmair G (2020) Global stabilization trends Of Covid-19
pandemic. KPI Sci News 2:55–62. https://doi.org/10.20535/kpi-sn.2020.2.205124
42. Nesteruk I (2020) How can we estimate the dangers of the coronavirus epidemic in Europe?
[Preprint.] ResearchGate. https://doi.org/10.13140/rg.2.2.32072.06402
43. Nesteruk I (2020) Coronavirus epidemic outbreak in Europe. Comparison with the
dynamics in mainland China. KPI Sci News 1:15–17. https://doi.org/10.20535/kpi-sn.2020.
1.198043
44. Distante C, Gadelha Pereira I (2020) Garcia Goncalves LM, Piscitelli P, Miani A (2020)
Forecasting Covid-19 outbreak progression in Italian regions: a model based on neural
network training from Chinese data. medRxiv
45. Hamzah F, Binti A, Lau C, Nazri H, Ligot DV, Lee G, Tan CL (2020) Corona tracker:
worldwide COVID-19 outbreak data analysis and prediction. Bull World Health Organ
1:32
46. Fanelli D, Piazza F (2020) Analysis and forecast of COVID-19 spreading in China, Italy
France. Chaos Solitons Fractals 134:109761
47. Webb GF, Magal P, Liu Z, Seydi O (2020) A model to predict COVID-19 epidemics with
applications to South Korea, Italy, and Spain. medRxiv
48. Bastos SB (2020) In: Cajueiro DO (ed) Modeling and forecasting the early evolution of the
Covid-19 pandemic in Brazil. arXiv:2003.14288
49. Nesteruk I (2020) Comparison of the coronavirus pandemic dynamics in Europe, USA
and South Korea. [Preprint.] MEDRXIV. https://medrxiv.org/cgi/content/short/2020.03.18.
20038133v1
50. Nesteruk I (2020) Comparison of the coronavirus epidemic dynamics in Italy and mainland
China [Preprint.] ResearchGate. https://doi.org/10.13140/rg.2.2.19152.87049
51. Nesteruk I (2020) Comparison of the coronavirus pandemic dynamics in Ukraine and
neighboring countries. [Preprint.] ResearchGate. https://doi.org/10.13140/rg.2.2.31170.
53448
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53. Kermack WD, McKendrick AG (1927) A contribution to the mathematical theory of
epidemics. J Roy Stat Soc Ser A 115:700–721
54. Murray JD (2002) Mathematical biology I/II. Springer, New York
55. Bailey NTJ (1957) The mathematical theory of epidemics. Griffin Book Co
56. Langemann D, Nesteruk I, Prestin J (2016) Comparison of mathematical models for the
dynamics of the Chernivtsi children disease. Math Comput Simul 123:68–79
57. Grant A (2020) Dynamics of COVID-19 epidemics: SEIR models underestimate peak
infection rates and overestimate epidemic duration. medRxiv
58. Loli Piccolomiini E, Zama F (2020) Monitoring Italian COVID-19 spread by an adaptive
SEIRD model. medRxiv
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167