Modified SIR Compartmental Epidemic Model with
Russian journal of nonlinear dynamics, Tome 17 (2021) no. 3, pp. 275-287.

Voir la notice de l'article provenant de la source Math-Net.Ru

The rapid spread of SARS-CoV-2/COVID-19 in the first months of 2020 overburdened health systems worldwide. The absence of vaccines led public authorities to respond to the pandemic by adopting nonpharmaceutical interventions, mainly social distancing policies. Yet concerns have been raised on the economic impact of such measures. Considering the impracticability of conducting controlled experiments to assess the effectiveness of such interventions, mathematical models have played an essential role in helping decision makers. Here we present a simple modified SIR (susceptible-infectious-recovered) model that includes social distancing and two extra compartments (hospitalized and dead due to the disease). Our model also incorporates the potential increase in the mortality rate due to the health system saturation. Results from numerical experiments corroborate the striking role of social distancing policies in lowering and delaying the epidemic peak, thus reducing the demand for intensive health care and the overall mortality. We also probed into optimal social distancing policies that avoid the health system saturation and minimize the economic downturn.
Keywords: epidemiology, infectious diseases, SARS-CoV-2, mathematical modeling, computational simulation, differential equations.
@article{ND_2021_17_3_a2,
     author = {V. R. da Silva and O. H. Menin},
     title = {Modified {SIR} {Compartmental} {Epidemic} {Model} with},
     journal = {Russian journal of nonlinear dynamics},
     pages = {275--287},
     publisher = {mathdoc},
     volume = {17},
     number = {3},
     year = {2021},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ND_2021_17_3_a2/}
}
TY  - JOUR
AU  - V. R. da Silva
AU  - O. H. Menin
TI  - Modified SIR Compartmental Epidemic Model with
JO  - Russian journal of nonlinear dynamics
PY  - 2021
SP  - 275
EP  - 287
VL  - 17
IS  - 3
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/ND_2021_17_3_a2/
LA  - en
ID  - ND_2021_17_3_a2
ER  - 
%0 Journal Article
%A V. R. da Silva
%A O. H. Menin
%T Modified SIR Compartmental Epidemic Model with
%J Russian journal of nonlinear dynamics
%D 2021
%P 275-287
%V 17
%N 3
%I mathdoc
%U http://geodesic.mathdoc.fr/item/ND_2021_17_3_a2/
%G en
%F ND_2021_17_3_a2
V. R. da Silva; O. H. Menin. Modified SIR Compartmental Epidemic Model with. Russian journal of nonlinear dynamics, Tome 17 (2021) no. 3, pp. 275-287. http://geodesic.mathdoc.fr/item/ND_2021_17_3_a2/

[1] Oldstone, M. B. A., Viruses, Plagues, and History: Past, Present, and Future, Oxford Univ. Press, New York, 2010, 383 pp.

[2] Quammen, D., Spillover: Animal Infections and the Next Human Pandemic, Norton, New York, 2012, 592 pp.

[3] Weekly operational update on COVID-19 - 20 November 2020 } {\tt https://www.who.int/publications/m/item/weekly-operational-update-on-covid-19—20-november-2020

[4] Kraemer, M. U. G., Yang, Ch.-H., Gutierrez, B., Wu, Ch.-H., Klein, B., Pigott, D. M., Open COVID-19 Data Working Group, du Plessis, L., Faria, N. R., Li, R., Hanage, W. P., Brownstein, J. S., Layan, M., Vespignani, A., Tian, H., Dye, Ch., Pybus, O. G., and Scarpino, S. V., “The Effect of Human Mobility and Control Measures on the {COVID-19} Epidemic in China”, Science, 368:6490 (2020), 493–497 | DOI

[5] Situation Report - 1 Coronavirus disease 2019 (COVID-19) } {\tt https://www.who.int/publications/m/item/situation-report—10

[6] World Health Organization, Coronavirus Disease 2019 (COVID-19): Situation Report-51 }, 2020 {\tt https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200311-sitrep-51-covid-19.pdf?sfvrsn=1ba62e57_10

[7] Cui, J., Li, F., and Shi, Z. L., “Origin and Evolution of Pathogenic Coronaviruses”, Nat. Rev. Microbiol., 17:3 (2019), 181–192 | DOI

[8] Kissler, S. M., Tedijanto, Ch., Goldstein, E., Grad, Y. H., and Lipsitch, M., “Projecting the Transmission Dynamics of SARS-CoV-2 through the Postpandemic Period”, Science, 368:6493 (2020), 860–868 | DOI

[9] Iyengar, K., Bahl, S., Vaishya, R., and Vaish, A., “Challenges and Solutions in Meeting Up the Urgent Requirement of Ventilators for COVID-19 Patients”, Diabetes Metab. Syndr. Clin. Res. Rev., 14:4 (2020), 499–501 | DOI

[10] Qiu, H., Tong, Zh., Ma, P., Hu, M., Peng, Zh., Wu, W., Du, B., and China Critical Care Clinical Trials Group (CCCCTG), “Intensive Care during the Coronavirus Epidemic”, Intensive Care Med., 46:4 (2020), 576–578 | DOI

[11] Anderson, R. M., Heesterbeek, H., Klinkenberg, D., and Hollingsworth, T. D., “How Will Country-Based Mitigation Measures Influence the Course of the COVID-19 Epidemic?”, The Lancet, 395:10228 (2020), 931–934 | DOI

[12] Kenyon, C., “Flattening-the-Curve Associated with Reduced COVID-19 Case Fatality Rates- an Ecological Analysis of 65 Countries”, J. Infect., 81:1 (2020), e98–e99 | DOI

[13] Bauch, C. T., “Estimating the COVID-19 R Number: A Bargain with the Devil?”, Lancet Infect. Dis., 21:2 (2021), 151–153 | DOI

[14] Li, Y., Campbell, H., Kulkarni, D., Harpur, A., Nundy, M., Wang, X., Nair, H., and Usher Network for COVID-19 Evidence Reviews (UNCOVER) Group, “The Temporal Association of Introducing and Lifting Non-Pharmaceutical Interventions with the Time-Varying Reproduction Number (R) of SARS-CoV-2: A Modelling Study across 131 Countries”, Lancet Infect. Dis., 21:2 (2021), 193–202 | DOI

[15] Thunström, L., Newbold, S. C., Finnoff, D., Ashworth, M., and Shogren, J. F., “The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19”, J. Benefit-Cost Analysis, 11:2 (2020), 179–195 | DOI

[16] Nicola, M., Alsaf, Z., Sohrabi, C., Kerwan, A., Al-Jabir, A., Iosifidis, Ch., Agha, M., and Agha, R., “The Socio-Economic Implications of the Coronavirus Pandemic (COVID-19): A Review”, Int. J. Surg. Open, 78 (2020), 185–193

[17] “COVID-19 in Brazil: “So What?””, The Lancet, 395 (2020), 10235, 1461 pp.

[18] Vespignani, A., Tian, H., Dye, C., Smith, J. O. L., Eggo, R. M., Shrestha, M., Scarpino, S. V., Gutierrez, B., Kraemer, M. U. G., Wu, J., Leung, K., and Leung, G. M., Nature Rev. Phys., 2:6 (2020), 279–281 | DOI

[19] Nakamura, G., Grammaticos, B., and Badoual, M., “Confinement Strategies in a Simple SIR Model”, Regul. Chaotic Dyn., 25:6 (2020), 509–521 | DOI | Zbl

[20] Pedro, S. A., Ndjomatchoua, F. T., Jentsch, P., Tchuenche, J. M., Anand, M., and Bauch, Ch. T., “Conditions for a Second Wave of COVID-19 due to Interactions between Disease Dynamics and Social Processes”, Front. Phys., 8 (2020), 5/4514, 9 pp. | DOI

[21] Block, P., Hoffman, M., Raabe, I. J., Dowd, J. B., Rahal, C., Kashyap, R., and Mills, M. C., “Social Network-Based Distancing Strategies to Flatten the COVID-19 Curve in a Post-Lockdown World”, Nat. Hum. Behav., 4 (2020), 588–596 | DOI

[22] Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Coupland, H., Mellan, T. A., Zhu, H., Berah, T., Eaton, J. W., Guzman, P. N. P., et al., Report 13: Estimating the Number of Infections and the Impact of Non-Pharmaceutical Interventions on COVID-19 in $11$ European Countries, Imperial College London }, 2020 {\tt https://spiral.imperial.ac.uk/handle/10044/1/77731

[23] Kucharski, A. J., Russell, T. W., Diamond, Ch., Liu, Y., Edmunds, J., Funk, S., Eggo, R. M., “on behalf of the Centre for Mathematical Modelling of Infectious Diseases COVID-19 Working Group”, Lancet Infect. Dis., 20:5 (2020), 553–558 | DOI

[24] Kermack, W. O. and McKendrick, A. G., Contributions to the Mathematical Theory of Epidemics, Proc. Roy. Soc. Edinburgh Sect. A, 115:772 (1927), 700–721 | Zbl

[25] Keeling, M. J. and Rohani, P., Modeling Infectious Diseases in Humans and Animals, Princeton Univ. Press, Princeton, 2007, 384 pp.

[26] Fine, P., Eames, K., and Heymann, D. L., ““Herd Immunity”: A Rough Guide”, Clin. Infect. Dis., 52:7 (2011), 911–916 | DOI

[27] Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G. S., Wallinga, J., Heijne, J., Sadkowska-Todys, M., Rosinska, M., and Edmunds, W. J., “Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases”, PLoS Med., 5:3 (2008), e74, 11 pp. | DOI

[28] Prin, M. and Wunsch, H., “International Comparisons of Intensive Care: Informing Outcomes and Improving Standards”, Curr. Opin. Crit. Care, 18:6 (2012), 700–706 | DOI

[29] Rhodes, A., Ferdinande, P., Flaatten, H., Guidet, B., Metnitz, P. G., and Moreno, R. P., “The Variability of Critical Care Bed Numbers in Europe”, Intensive Care Med., 38:10 (2012), 1647–1653 | DOI