Mathematical modelling of the spread of COVID-19, taking into account the distribution of asymptomatic cases between actually asymptomatic and pre-symptomatic cases
Matematičeskaâ biologiâ i bioinformatika, Tome 19 (2024) no. 1, pp. 52-60

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The possibility of representation in a dynamic model of the three types of SARS-CoV-2 infection: asymptomatic, pre-symptomatic and symptomatic is studied. Furthermore, a compartmental model was proposed, with a branching of asymptomatic cases into pre-symptomatic and actually asymptomatic cases. Verification of the proposed model using data from the first wave of COVID-19 in St. Petersburg and the proportion of actually asymptomatic cases among all asymptomatic cases demonstrated adequate model behavior. The contribution of pre-symptomatic cases to the total number of symptomatic cases was studied. The need to account for the high proportion of asymptomatic carriers in strict quarantine was identified.
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I. D. Kolesin; E. M. Zhitkova. Mathematical modelling of the spread of COVID-19, taking into account the distribution of asymptomatic cases between actually asymptomatic and pre-symptomatic cases. Matematičeskaâ biologiâ i bioinformatika, Tome 19 (2024) no. 1, pp. 52-60. http://geodesic.mathdoc.fr/item/MBB_2024_19_1_a1/

[1] A. Yu. Popova, E. B. Ezhlova, A. A. Melnikova, N. S. Bashketova, R. K. Fridman, L. V. Lyalina, V. S. Smirnov, I. G. Chkhindzheriya, T. A. Grechaninova, K. A. Agapov i dr, “Populyatsionnyi immunitet k SARS-CoV-2 sredi naseleniya Sankt Peterburga v period epidemii COVID-19”, Problemy osobo opasnykh infektsii, 3 (2020), 124–130 | DOI | DOI

[2] A. Yu. Popova, E. B. Ezhlova, A. A. Melnikova, O. A. Istorik, O. S. Mosevich, L. V. Lyalina, V. S. Smirnov, M. A. Chernyi, N. S. Balabysheva, I. S. Loginova i dr, “Otsenka populyatsionnogo immuniteta k SARS-CoV-2 sredi naseleniya Leningradskoi oblasti v period epidemii COVID-19”, Problemy osobo opasnykh infektsii, 3 (2020), 114–123 | DOI | DOI

[3] P. Sah, M. C. Fitzpatrick, C. F. Zimmer, A. P. Galvani, “Asymptomatic SARS-CoV-2 infection: A systematic review and meta-analysis”, Proc. of the National Academy of Sciences, 118:34 (2021) | DOI | DOI

[4] M. Alene, L. Yismaw, M. A. Assemie, Ketema D.B, B. Mengist, B. Kassie, T. Y. Birhan, “Magnitude of asymptomatic COVID-19 cases throughout the course of infection: A systematic review and meta-analysis”, PloS One, 16:3 (2021) | DOI | Zbl | DOI | Zbl

[5] W. Gao, J. Lv, Y. Pang, L. Li, “Role of asymptomatic and pre-symptomatic infections in covid-19 pandemic”, BMJ, 375 (2021), n2342 | DOI | DOI

[6] D. P. Oran, E. J. Topol, “The Proportion of SARS-CoV-2 Infections That Are Asymptomatic: A Systematic Review”, Ann. Intern. Med, 174:5 (2021), 655–662 | DOI | DOI

[7] A. J. Kucharski, T. W. Russell, C. Diamond, Y. Liu, J. Edmunds, S. Funk, R. M. Eggo, “Centre for Mathematical Modelling of Infectious Diseases COVID-19 working group. Early dynamics of transmission and control of COVID-19: a mathematical modelling study”, Lancet Infect. Dis., 20:5 (2020), 553–558 | DOI | MR | DOI | MR

[8] M. N. Asatryan, E. R. Gerasimuk, D. Yu. Logunov, T. A. Semenenko, A. L. Gintsburg, “Prognozirovanie dinamiki zabolevaemosti COVID-19 i planirovanie meropriyatii po vaktsinoprofilaktike naseleniya Moskvy na osnove matematicheskogo modelirovaniya”, Zhurnal mikrobiologii, epidemiologii i immunobiologii, 97:4 (2020), 289–302 | DOI | DOI

[9] S. E. Eikenberry, M. Mancuso, E. Iboi, T. Phan, K. Eikenberry, Y. Kuang, E. Kostelich, A. B. Gumel, “To mask or not to mask: Modeling the potential for face mask use by the general public to curtail the COVID-19 pandemic”, Infectious disease modeling, 5 (2020), 293–308 | DOI | MR | DOI | MR

[10] J. L. Gevertz, J. M. Greene, C. H. Sanchez-Tapia, E. D. Sontag, “A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing”, Journal of Theoretical Biology, 510 (2021), 110539 | DOI | MR | DOI | MR

[11] X. Qiu, A. I. Nergiz, A. E. Maraolo, I. I. Bogoch, N. Low, M. Cevik, “The role of asymptomatic and pre-symptomatic infection in SARS-CoV-2 transmission-a living systematic review”, Clin. Microbiol. Infect, 27:4 (2021), 511–519 | DOI | MR | DOI | MR

[12] P. Wu, Liu F, Z. Chang, Y. Lin, M. Ren, C. Zheng, Y. Li, Z. Peng, Y. Qin, J. Yu et al, “Assessing Asymptomatic, Presymptomatic, and Symptomatic Transmission Risk of Severe Acute Respiratory Syndrome Coronavirus 2”, Clinical Infectious Diseases, 73:6 (2021), e1314-e1320 | DOI | DOI

[13] X. Hao, S. Cheng, D. Wu, T. Wu, X. Lin, C. Wang, “Reconstruction of the full transmission dynamics of COVID-19 in Wuhan”, Nature, 584 (2020), 420–424 | DOI | MR | DOI | MR

[14] L. Mayorga, C. Garcia Samartino, G. Flores, S. Masuelli, M. V. Sanchez, L. S. Mayorga, C. G. Sanchez, “A modelling study highlights the power of detecting and isolating asymptomatic or very mildly affected individuals for COVID-19 epidemic management”, BMC Public Health, 20 (2020), 1809 | DOI | DOI

[15] S. Flaxman, S. Mishra, A. Gandy, H. J.T. Unwin, T. A. Mellan, H. Coupland, C. Whittaker, H. Zhu, T. Berah, J. W. Eaton et al, “Estimating the effects of non pharmaceutical interventions on COVID-19 in Europe”, Nature, 584 (2020), 257–261 | DOI | DOI

[16] J. F. Oliveira, D. C.P. Jorge, R. V. Veiga, M. S. Rodrigues, M. F. Torquato, N. B. da Silva, R. L. Fiaccone, L. L. Cardim, F. A.C. Pereira, C. P. de Castro et al, “Mathematical modeling of COVID-19 in 14.8 million individuals in Bahia”, Brazil. Nat. Commun, 12 (2021), 333 | DOI | DOI

[17] N. V. Pertsev, K. K. Loginov, A. N. Lukashev, Yu. A. Vakulenko, “Stokhasticheskoe modelirovanie dinamiki rasprostraneniya Kovid-uchetom neodnorodnosti naseleniya po immunologicheskim, klinicheskim i epidemiologicheskim kriteriyam”, Mat. biol. i bioinf., 17:1 (2022), 43–81, 19 pp. | DOI | MR | DOI | MR

[18] Kiselevskaya-Babinina V.Ya., Romanyukha A.A., Sannikova T.E., “Matematicheskaya model techeniya COVID-19 i prognoz tyazhesti infektsii”, Matem. modelirovanie, 35:5 (2023), 31–46 | DOI | Zbl | DOI | Zbl

[19] A. Smirnova, M. Baroonian, “Reconstruction of incidence reporting rate for SARS-CoV 2 Delta variant of COVID-19 pandemic in the US”, Infectious Disease Modelling, 9:1 (2024), 70–83 | DOI | DOI

[20] Y. Wang, K. Zheng, W. Gao, J. Lv, C. Yu, L. Wang, Z. Wang, B. Wang, C. Liao, L. Li, “Asymptomatic and pre-symptomatic infection in Coronavirus Disease 2019 pandemic”, Med. Rev. (Berl.), 2:1 (2022), 66–88 | DOI | MR | DOI | MR

[21] G. Giordano, F. Blanchini, R. Bruno, P. Colaneri, A. Di Filippo, A. Di Matteo, M. Colaneri, “Modelling the COVID-19 epidemic and implementation of population wide interventions in Italy”, Nat. Med, 26 (2020), 855–860 | DOI | DOI

[22] S. I. Kabanikhin, O. I. Krivorotko, “Matematicheskoe modelirovanie epidemii ukhanskogo koronovirusa COVID-19 i obratnye zadachi”, Zhurnal vychislitelnoi matematiki i matematicheskoi fiziki, 60:11 (2020), 1950–1961 | DOI | Zbl | DOI | Zbl

[23] I. D. Kolesin, E. M. Zhitkova, “Suschestvoval li period skrytogo razvitiya COVID 19 v Sankt-Peterburge? Rezultaty matematicheskogo modelirovaniya i fakty”, Matem. modelirovanie, 35:5 (2023), 104–116 | DOI | Zbl | DOI | Zbl