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Pandemic management by a spatio–temporal mathematical model

  • Teddy Lazebnik ORCID logo EMAIL logo , Svetlana Bunimovich-Mendrazitsky ORCID logo und Labib Shami
Veröffentlicht/Copyright: 9. August 2021
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Abstract

Many researchers have tried to predict the impact of the COVID-19 outbreak on morbidity, in order to help policy-makers find optimal isolation policies. However, despite the development and use of many models and sophisticated tools, these forecasting attempts have largely failed. We present a model that considers the severity of the disease and the heterogeneity of contacts between the population in complex space–time dynamics. Using mathematical and computational methods, the applied tool was developed to analyze and manage the COVID-19 pandemic (from an epidemiological point of view), with a particular focus on population heterogeneity in terms of age, susceptibility, and symptom severity. We show improved strategies to prevent an epidemic outbreak. We evaluated the model in three countries, obtaining an average mean square error of 0.067 over a full month of the basic reproduction number (R 0). The goal of this study is to create a theoretical framework for crisis management that integrates accumulated epidemiological considerations. An applied result is an open-source program for predicting the outcome of an isolation strategy for future researchers and developers who can use and extend our model.

MSC 2010: 34-04; 65-05; 68U20

Corresponding author: Teddy Lazebnik, Department of Mathematics, Ariel University, Ariel, Israel, E-mail:

A.O. Teddy Lazebnik contributed equally to this work with A.T. Svetlana Bunimovich-Mendrazitsky.


  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

[1] J. Chen, T. Qi, L. Liu, et al.., “Clinical progression of patients with Covid-19 in Shanghai, China,” J. Infect., vol. 80, pp. e1–e6, 2020. https://doi.org/10.1016/j.jinf.2020.03.004.Suche in Google Scholar PubMed PubMed Central

[2] Eurosurveillanc Editorial Team, “Note from the editors: world health organization declares novel coronavirus (2019-ncov) sixth public health emergency of international concern,” Euro Surveill., vol. 25, p. 200131e, 2020. https://doi.org/10.2807/1560-7917.es.2020.25.5.200131e.Suche in Google Scholar PubMed PubMed Central

[3] World Health Organization, WHO coronavirus disease (covid-19) dashboard (2020).Suche in Google Scholar

[4] A. Desvars-Larrive, E. Dervic, N. Haug, et al.., “A structured open dataset of government interventions in response to Covid-19,” Sci. Data, vol. 7, pp. 285, 2020. https://doi.org/10.1038/s41597-020-00609-9.Suche in Google Scholar PubMed PubMed Central

[5] B. W. Head, “Three lenses of evidence-based policy,” Aust. J. Publ. Adm., vol. 67, pp. 1–11, 2007.10.1111/j.1467-8500.2007.00564.xSuche in Google Scholar

[6] J. C. Miller, “Mathematical models of sir disease spread with combined non-sexual and sexual transmission routes,” Infect. Dis. Model., vol. 2, pp. 35–55, 2017. https://doi.org/10.1016/j.idm.2016.12.003.Suche in Google Scholar PubMed PubMed Central

[7] C. Scoglio and F. D. Sahneh, “Epidemic spread in human networks,” in IEEE Conference on Decision and Control and European Control Conference, 2011.Suche in Google Scholar

[8] A. R. Tuite, D. N. Fisman, and A. L. Greer, “Mathematical modelling of Covid-19 transmission and mitigation strategies in the population of Ontario, Canada,” Can. Med. Assoc. J., vol. 192, pp. E497–E505, 2020.10.1503/cmaj.200476Suche in Google Scholar

[9] T. Lazebnik and S. Bunimovich-Mendrazitsky, “The signature features of Covid-19 pandemic in a hybrid mathematical model – implications for optimal work–school lockdown policy,” Adv. Theory Simulat., vol. 4, p. 2000298, 2021. https://doi.org/10.1002/adts.202000298.Suche in Google Scholar PubMed PubMed Central

[10] W. O. Kermack and A. G. McKendrick, “A contribution to the mathematical theory of epidemics,” Proc. R. Soc. A, vol. 115, 1927. https://doi.org/10.1098/rspa.1927.0118.Suche in Google Scholar

[11] S. Zhao, L. Stone, D. Gao, et al.., “Imitation dynamics in the mitigation of the novel coronavirus disease (Covid-19) outbreak in Wuhan, China from 2019 to 2020,” Ann. Transl. Med., vol. 8, p. 488, 2020.10.21037/atm.2020.03.168Suche in Google Scholar

[12] C. Jiehao, X. Jin, L. Daojiong, et al.., “A case series of children with 2019 novel coronavirus infection: clinical and epidemiological features,” Clin. Infect. Dis., vol. 71, pp. 1547–1551, 2020. https://doi.org/10.1093/cid/ciaa198.Suche in Google Scholar PubMed PubMed Central

[13] J. She, L. Liu, and W. Liu, “Covid-19 epidemic: disease characteristics in children,” J. Med. Virol., vol. 92, pp. 747–754, 2020.10.1002/jmv.25807Suche in Google Scholar

[14] Y. Dong, X. Mo, Y. Hu, et al.., “Epidemiological characteristics of 2143 pediatric patients with 2019 coronavirus disease in China,” Pediatrics, vol. 58, pp. 712–713, 2020.10.1016/j.jemermed.2020.04.006Suche in Google Scholar

[15] I. Voinsky, G. Baristaite, and D. Gurwitz, “Effects of age and sex on recovery from Covid-19: analysis of 5769 israeli patients,” J. Infect., vol. 81, pp. e102–e103, 2020. https://doi.org/10.1016/j.jinf.2020.05.026.Suche in Google Scholar PubMed PubMed Central

[16] A. A. Kelvin and S. Helperin, “Covid-19 in children: the link in the transmission chain,” Lancet, vol. 20, pp. 633–634, 2020. https://doi.org/10.1016/s1473-3099(20)30236-x.Suche in Google Scholar

[17] J. He, Y. Guo, R. Mao, and J. Zhang, “Proportion of asymptomatic coronavirus disease 2019: a systematic review and meta-analysis,” J. Med. Virol., vol. 93, pp. 1–11, 2020. https://doi.org/10.1002/jmv.26326.Suche in Google Scholar PubMed PubMed Central

[18] A. Viguerie, G. Lorenzo, F. Auricchio, et al.., “Simulating the spread of Covid-19 via a spatially-resolved susceptible–exposed–infected–recovered–deceased (seird) model with heterogeneous diffusion,” Appl. Math. Lett., vol. 111, p. 106617, 2020. https://doi.org/10.1016/j.aml.2020.106617.Suche in Google Scholar PubMed PubMed Central

[19] K. O’Dowd, K. M. Nair, P. Forouzandeh, et al.., “Face masks and respirators in the fight against the Covid-19 pandemic: a review of current materials, advances and future perspectives,” Materials, vol. 13, p. 3363, 2020.10.3390/ma13153363Suche in Google Scholar

[20] T. Li, Y. Liu, M. Li, X. Qian, and S. Y. Dai, “Mask or no mask for Covid-19: a public health and market study,” PloS One, vol. 15, 2020, Art no. e0237691. https://doi.org/10.1371/journal.pone.0237691.Suche in Google Scholar PubMed PubMed Central

[21] M. N. Saidana, M. A. Shboolb, O. S. Arabeyyatc, S. T. Al-Shihabib, Y. Al Abdallatb, M. A. Barghashb, and H. Saidand, “Estimation of the probable outbreak size of novel coronavirus (Covid-19) in social gathering events and industrial activities,” Int. J. Infect. Dis., vol. 98, pp. 321–327, 2020. https://doi.org/10.1016/j.ijid.2020.06.105.Suche in Google Scholar PubMed PubMed Central

[22] D. Acemoglu, V. Chernozhukov, I. Werning, and M. D. Whinston, “Optimal targeted lockdowns in a multi-group sir model,” in Working Paper 27102, National Bureau of Economic Research, 2020.10.3386/w27102Suche in Google Scholar

[23] Z. A. Bethune and A. Korinek, “Covid-19 infection externalities: trading off lives vs. livelihoods,” in Working Paper 27009, National Bureau of Economic Research, 2020.10.3386/w27009Suche in Google Scholar

[24] M. Bodenstein, G. Corsetti, and L. Guerrieri, “Social distancing and supply disruptions in a pandemic,” Econ. Res., 2020. https://doi.org/10.17016/feds.2020.031.Suche in Google Scholar

[25] D. Krueger, H. Uhlig, and T. Xie, “Macroeconomic dynamics and reallocation in an epidemic: evaluating the ‘Swedish Solution’,” in Working Paper 27047, National Bureau of Economic Research, 2020.10.3386/w27047Suche in Google Scholar

[26] G. Quaas, “The reproduction number in the classical epidemiological model,” in Working Paper 167, Universität Leipzig, Wirtschaftswissenschaftliche Fakultät, Leipzig, 2020.Suche in Google Scholar

[27] Y. Dong, X. Mo, Y. Hu, et al.., “Epidemiology of Covid-19 among children in China,” Pediatrics, vol. 145, p. e20200702, 2020. https://doi.org/10.1542/peds.2020-0702.Suche in Google Scholar PubMed

[28] H. Nishiura and T. Kobayashi, “Estimation of the asymptomatic ratio of novel coronavirus infections (Covid-19),” Int. J. Infect. Dis., vol. 94, pp. 154–155, 2020. https://doi.org/10.1016/j.ijid.2020.03.020.Suche in Google Scholar PubMed PubMed Central

[29] M. R. Mehra, S. S. Desai, S. Kuy, T. D. Henry, and A. N. Patel, “Cardiovascular disease, drug therapy, and mortality in Covid-19,” N. Engl. J. Med., vol. 382, p. e102, 2020. https://doi.org/10.1056/NEJMoa2007621.Suche in Google Scholar PubMed PubMed Central

[30] W. Yang, D. Zhang, L. Peng, C. Zhuge, and L. Liu, “Rational evaluation of various epidemic models based on the Covid-19 data of China,” arXiv, 2020.10.1101/2020.03.12.20034595Suche in Google Scholar

[31] B. C. Haskell, “The method of steepest descent for non-linear minimization problems,” Q. Appl. Math., vol. 2, pp. 258–261, 1944.10.1090/qam/10667Suche in Google Scholar

[32] A. Björck, “Numerical methods for least squares problems,” SIAM J. Sci. Stat. Comput., 1996. https://doi.org/10.1137/1.9781611971484.Suche in Google Scholar

[33] L. Shanock, B. Baran, W. Gentry, S. C. Pattison, and E. D. Heggestad, “Polynomial regression with response surface analysis: a powerful approach for examining moderation and overcoming limitations of difference scores,” J. Bus. Psychol., pp. 543–554, 2010. https://doi.org/10.1007/s10869-010-9183-4.Suche in Google Scholar

[34] R. J. C. Calderon-Anyosa and J. S. Kaufman, “Impact of Covid-19 lockdown policy on homicide, suicide, and motor vehicle deaths in Peru,” Prev. Med., vol. 143, p. 106331, 2021. https://doi.org/10.1016/j.ypmed.2020.106331.Suche in Google Scholar PubMed PubMed Central

[35] D. Ding, B. Del Pozo Cruz, M. A. Green, and A. E. Bauman, “Is the Covid-19 lockdown nudging people to be more active: a big data analysis,” Br. J. Sports Med., vol. 54, pp. 1183–1184, 2020. https://doi.org/10.1136/bjsports-2020-102575.Suche in Google Scholar PubMed

[36] B. E. Oruc, A. Baxter, P. Keskinocak, J. Asplund, and N. Serban, Homebound by Covid19: The Benets and Consequences of Non-pharmaceutical Intervention Strategies, Research Square, 2020.10.21203/rs.3.rs-51320/v1Suche in Google Scholar

[37] A. Baxter, B. E. Oruc, P. Keskinocak, J. Asplund, and N. Serban, “Evaluating scenarios for school reopening under Covid19,” medRxiv, 2020.10.21203/rs.3.rs-54082/v1Suche in Google Scholar

[38] T. Lazebnik, L. Shami, and S. Bunimovich-Mendrazitsky, “Spatio-temporal influence of non-pharmaceutical interventions policies on pandemic dynamics and the economy: the case of Covid-19,” Epidemiologic-Economic, 2021. https://doi.org/10.1080/1331677x.2021.1925573.Suche in Google Scholar


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/ijnsns-2021-0063).


Received: 2021-02-14
Revised: 2021-06-08
Accepted: 2021-07-20
Published Online: 2021-08-09

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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