Cenni su teoria ed utilizzo di modelli matematici per le epidemie
Matematica, cultura e società, Série 1, Tome 5 (2020) no. 1, pp. 5-15.

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In questa nota divulgativa presento alcuni aspetti della teoria matematica delle epidemie, con particolare attenzione al caso di una nuova infezione emergente, come nel caso del COVID-19. Parto della definizione di numero di riproduzione di base $R_0$, e presento la sua relazione col tasso di crescita esponenziale all'inizio di un'epidemia e con le possibilità di controllo in semplici modelli deterministici. Discuto poi i corrispondenti modelli stocastici, mostrando come in questo caso $R_0$ sia legato alla probabilità che esploda un'epidemia a partire dall'introduzione di pochi infetti. Infine accenno alla struttura dei modelli complessi che vengono attualmente usati come supporto previsionale alle azioni delle autorità sanitarie.
In this note I present some aspects of the mathematical theory of epidemics, with particular attention to the case of a new emerging infection, as in the case of COVID-19. I start with the definition of basic reproduction number $R_0$, and present its relationship with the exponential growth rate at the beginning of an epidemic and with potential for control in simple deterministic models. I then discuss the corresponding stochastic models, showing that in this case the probability that the introduction of a few infected individduals results into an epidemic outbreak depends on the value of $R_0$. Finally, I will mention the structure of complex models that are currently used as support for the actions of the health authorities.
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Pugliese, Andrea. Cenni su teoria ed utilizzo di modelli matematici per le epidemie. Matematica, cultura e società, Série 1, Tome 5 (2020) no. 1, pp. 5-15. http://geodesic.mathdoc.fr/item/RUMI_2020_1_5_1_a1/

[1]Aguiar, M., Kooi, B., and Stollenwerk, N.Epidemiology of Dengue Fever: A Model with Temporary Cross Immunity and Possible Secondary Infection Shows Bifurcations and Chaotic Behaviour in Wide Parameter Regions. Math. Model. Nat. Phenom.3 (2008), 48-70. | fulltext EuDML | DOI | MR | Zbl

[2]Ajelli, M., Gonçalves, B., Balcan, et al. Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models. BMC Infect. Dis.10 (2010), 190.

[3]Ajelli, M., Merler, S., Pugliese, A., and Rizzo, C.Model predictions and evaluation of possible control strategies for the 2009 H1N1v influenza pandemic in Italy. Epidemiol. Infect.139 (2011), 68-79. | DOI | MR

[4]Ball, F., Mollison, D., and Scalia-Tomba, G.Epidemics with two levels of mixing. Ann. Appl. Probab.7 (2001), 46-89. | DOI | MR | Zbl

[5]Ballard, P. G., Bean, N. G., and Ross, J. V.The probability of epidemic fade-out is non-monotonic in transmission rate for the Markovian SIR model with demography. Journal of Theoretical Biology393 (2016), 170-178. | DOI | MR | Zbl

[6]Diekmann, O., Heesterbeek, J. A. P., and Metz, J. A. J.On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. J. Math. Biol.28 (1990), 365-382. | DOI | MR | Zbl

[7]Ferguson, N. M., Cummings, D. A. T., Cauchemez, S., et al. Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature437, 7056 (2005), 209-214.

[8]Groppi, M., and Della Marca, R.Modelli epidemiologici e vaccinazioni:da Bernoulli a oggi. Matematica, Cultura e Società. Rivista dell'Unione Matematica Italiana3, 1 (2018), 45-59. | fulltext bdim | fulltext EuDML | MR

[9]Hellewell, J., Abbott, S., Gimma, A., et al. Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts. medRxiv (Jan 2020), https://www.medrxiv.org/content/10.1101/2020.02.08.20021162v1.

[10]Hethcote, H. W.Qualitative analysis of communicable disease models. Math. Biosci.28 (1976), 335-356. | DOI | MR | Zbl

[11]Iannelli, M., and Milner, F.The Basic Approach to Age-structured Population Dynamics. Models, Methods and Numerics. Springer, 2017. | DOI | MR | Zbl

[12]Kermack, W. O., and Mckendrick, A. G.A contributions to the mathematical theory of epidemics. Proc. R. Soc. London A115 (1927), 700-721. Reprinted in Bull. Math. Biol.53 (1991), 33-55. | Zbl

[13]Li, Q., Guan, X., Wu, P., et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus Infected Pneumonia. New England Journal of Medicine (Jan 2020), https://www.nejm.org/doi/full/10.1056/NEJMoa2001316.

[14]MANFREDI, P., and D'ONOFRIO, A., Eds. Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases. Springer-VerlagNew York, 2013. | DOI | MR

[15]Pellis, L., Ball, F., and Trapman, P.Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of $R_0$. Math. Biosci.235, 1 (2012), 85-97. | DOI | MR | Zbl

[16]Rasmussen, D. A., Volz, E. M., and Koelle, K.Phylodynamic Inference for Structured Epidemiological Models. PLOS Computational Biology10, 4, e1003570.

[17]Schwartz, I. B., and Smith, H. L.Infinite subharmonic bifurcations in an SEIR epidemic model. J. Math. Biol.18 (1983), 233-253. | DOI | MR | Zbl

[18]Wu, J. T., Leung, K., and Leung, G. M.Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet395, 10225 (Feb 2020), 689-697, https://doi.org/10.1016/S0140-6736(20)30260-9.

[19]Wu, Z., and Mcgoogan, J. M.Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA (Feb 2020), https://jamanetwork.com/ journals/jama/fullarticle/2762130.

[20]Cereda, D., Tirani, M., Rovida, F. et al. The early phase of the COVID-19 outbreak in Lombardy, Italy, arXiv:2003.09320 https://arxiv.org/abs/2003.09320.

[21]Ganyani, T., Kremer, C., Chen, D., Torneri, A., Faes, C., Wallinga, J., Hens, N., Estimating the generation interval for COVID-19 based on symptom onset data. medRxiv [Preprint] https://doi.org/10.1101/2020.03.05.20031815.

[22]Linton, N.M., Kobayashi, T., Yang, Y., Hayashi, K., Akhmetzhanov, A.R., Jung, S., Yuan, B., Kinoshita, R., Nishiura, H.. Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data. Journal of Clinical Medicine, 9(2):538 (2020).