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A Simple Matrix Model of Epidemic Outbreak Involving Vaccination of Two Age Groups

  
06 mar 2025
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AGUR, Z.—DANON, Y. L.—ANDERSON, R. M.—COJOCARU, L.— MAY, R. M.: Measles immunization strategies for an epidemiologically heterogeneous population: the israeli case study,the Israelicasestudy.In: Proc.R.Soc.Lond. Ser. B: Vol. 252 (1993), no. 1334, pp. 81–84, https://doi.org/10.1098/rspb.1993.0049. Search in Google Scholar

ALLEN, L. J.—VAN DEN DRIESSCHE, P.: The basic reproduction number in some discrete-time epidemic models, J. Difference Equ. Appl. 14 (2008), 1127–1147, https://doi.org/10.1080/10236190802332308. Search in Google Scholar

BISWAS, R. K.—AFIAZ, A.—HUQ, S.—FARZANA, M.—KABIR, E.: Public opinion on COVID-19 vaccine prioritization in bangladesh: Who gets the vaccine and whom do you leave out?, Vaccine, 41 (2023), n. 34, 5018–5028, https://doi.org/10.1016/j.vaccine.2023.06.050. Search in Google Scholar

BOTSFORD, L.—WHITE, J.—HASTINGS, A.: Population Dynamics for Conservation, Oxford University Press, Oxford, 2019. Search in Google Scholar

CASWELL, H.: Matrix Population Models: Construction, Analysis, and Interpretation, Sinauer Associates, Oxford University press, 2001. Search in Google Scholar

CHOE, S.—LEE, S.: Modeling optimal treatment strategies in a heterogeneous mixing model, Theor. Biol. Med. Model. 12 (2015), no. 1, Paper no. 28, https://tbiomed.biomedcentral.com/articles/10.1186/s12976-015-0026-x. Search in Google Scholar

CUSHING, J.—DIEKMANN, O.: The many guises of R0 (a didactic note), Journal of Theoretical Biology 404 (2016), 295–302, https://doi.org/10.1016/j.jtbi.2016.06.017 Search in Google Scholar

DEL VALLE, S.—HYMAN, J.—HETHCOTE, H.—EUBANK, S.: Mixing patterns between age groups in social networks,Social Networks 29 (2007), 539–554, https://doi.org/10.1016/j.socnet.2007.04.005. Search in Google Scholar

EYAL, N.—GHEAUS, A.—GOSSERIES, A.—MAGALHAES, M.—NGOSSO, T.— STEUWER, B.—TANGCHAROENSATHIEN, V.—TRIFAN, I.—WILLIAMS, A.: Coronavirus disease 2019 (COVID-19) vaccine prioritization in low- and middle-income countries may justifiably depart from high-income countries’ age priorities,Clin.Infect. Dis. 75 (2022), pp. S93–S97, https://doi.org/10.1093/cid/ciac398. Search in Google Scholar

GHOSH, D.—SANTRA, P. K.—MAHAPATRA, G. S. —ELSONBATY, A.— ELSADANY, A. A.: A discrete-time epidemic model for the analysis of transmission of COVID19 based upon data of epidemiological parameters, Eur. Phys. J. Spec. Top. 231 (2022), 3461–3470, https://doi.org/10.1140/epjs/s11734-022-00537-2. Search in Google Scholar

HERNANDEZ ACOSTA, R. A.—ESQUER GARRIGOS, Z. —MARCELIN, J. R.– –VIJAYVARGIYA, P.: COVID-19 pathogenesis and clinical manifestations, Infect. Dis. Clin. North Am. 36 (2022), 231–249, https://doi.org/10.1016/j.idc.2022.01.003. Search in Google Scholar

HETHCOTE, H. W.—VAN ARK, J. W.: Epidemiological models for heterogeneous populations: proportionate mixing, parameter estimation, and immunization programs, Mathematical Biosciences 84 (1987), 85–118, https://doi.org/10.1016/0025-5564(87)90044-7. Search in Google Scholar

HILL, A. N.—GLASSER, J. W.—FENG, Z.: Implications for infectious disease models of heterogeneous mixing on control thresholds,J.Math. Biol. 86 (2023), no. 4, Paper no. 53, https://doi.org/10.1007/s00285-023-01886-9. Search in Google Scholar

HILL, A. N.—LONGINI, I. M., JR.: The critical vaccination fraction for heterogeneous epidemic models, Math. Biosci. 181 (2003), 85–106, https://doi.org/10.1016/S0025-5564(02)00129-3. Search in Google Scholar

HOGBEN, L.: Handbook of Linear Algebra. 2nd ed. Chapman and Hall/CRC, New York, 2014, https://www.routledge.com/Handbook-of-Linear-Algebra/Hogben/p//book/9781466507289. Search in Google Scholar

HU, B.—GUO, H.—ZHOU, P.—SHI, Z.-L.: Characteristics of SARS-CoV-2 and COVID-19, Nature Reviews Microbiology, 19 (2021), 141–154, https://doi.org/10.1038/s41579-020-00459-7. Search in Google Scholar

JENTSCH, P. C.—ANAND, M.—BAUCH, C. T.: Prioritising COVID-19 vaccination in changing social and epidemiological landscapes: a mathematical modelling study, The Lancet Infectious Diseases, 21 (2021), 1097–1106, https://doi.org/10.1016/S1473-3099(21)00057-8. Search in Google Scholar

JOHNSON, C. R.—BRU, R.: The spectral radius of a product of nonnegative matrices, Linear Algebra and its App. 141 (1990), 227–240, https://doi.org/10.1016/0024-3795(90)90320-C. Search in Google Scholar

LEBRETON, J.: Age, stages, and the role of generation time in matrix models,(Special Issue on Theoretical Ecology and Mathematical Modelling: Problems and Methods.) Ecological Modelling 188 (2005), 22–29, https://doi.org/10.1016/j.ecolmodel.2005.05.003. Search in Google Scholar

LI, C.-K.—SCHNEIDER, H.: Applications of Perron-Frobenius theory to population dynamics, J. Math. Biol. 44 (2002), https://doi.org/10.1007/s002850100132. Search in Google Scholar

MONTO, A. S.—DAVENPORT, F. M.—NAPIER, J. A.—FRANCIS, T., JR.: Effect of vaccination of a school-age population upon the course of an A2-Hong kong influenza epidemic, Bull. World Health Organ. 41 (1969), 537–542. Search in Google Scholar

MUNZERT, S.—RAMIREZ-RUIZ, S.—ÇALI,B.—STOETZER,L. F. —GOHDES,A.– –LOWE, W.: Prioritization preferences for COVID-19 vaccination are consistent across five countries, Humanit. Soc. Sci. Commun. 9 (2022), Paper no. 439, https://doi.org/10.1057/s41599-022-01392-1. Search in Google Scholar

NANCY HERNÁNDEZ-CERÓN, Z. F.— VAN DEN DRIESSCHE, P.: Reproduction numbers for discrete-time epidemic models with arbitrary stage distributions, J. Difference Equ. Appl. 19 (2013), 1671–1693, https://doi.org/10.1080/10236198.2013.772597. Search in Google Scholar

PREM, K.—COOK, A. R.—JIT, M.: Projecting social contact matrices in 152 countries using contact surveys and demographic data, PLoS Comput. Biol. 13 (2017), Paper no. e1005697, https://doi.org/10.1371/journal.pcbi.1005697. Search in Google Scholar

SSENTONGO, P.—SSENTONGO, A. E.—VOLETI, N.—GROFF, D.—SUN, A. —BA, D. M.—NUNEZ, J.—PARENT, L. J.—CHINCHILLI, V. M.—PAULES, C. I.: SARS--CoV-2 vaccine effectiveness against infection, symptomatic and severe COVID-19: a systematic review and meta-analysis, BMC Infectious Diseases, 22 (2022), Paper no. 439, https://doi.org/10.1186/s12879-022-07418-y. Search in Google Scholar

SWAN, D. A.—BRACIS, C.—JANES, H.—MOORE, M.—MATRAJT, L. —REEVES, D. B.—BURNS, E.—DONNELL, D.—COHEN, M. S. —SCHIFFER, J. T.—DIMITROV, D.: COVID-19 vaccines that reduce symptoms but do not block infection need higher coverage and faster rollout to achieve population impact, Sci. Rep. 11 (2021), Paper no. 15531, https://doi.org/10.1038/s41598-021-94719-y. Search in Google Scholar

WALLINGA, J.—LIPSITCH, M.: How generation intervals shape the relationship between growth rates and reproductive numbers, Proc. Biol. Sci. Vol. 274 (2007), pp. 599–604, https://doi.org/10.1098/rspb.2006.3754. Search in Google Scholar

WHO: https://www.who.int/emergencies/diseases/novel-coronavirus-2019. Search in Google Scholar

WONG, L. P.—LIN, Y.—ALIAS, H.—BAKAR, S. A.—ZHAO, Q.—HU, Z.: COVID-19 anti-vaccine sentiments: Analyses of comments from social media, Healthcare (Basel), 9 (2021), Paper no. 1530, https://doi.org/10.3390/healthcare9111530. Search in Google Scholar

YANG, C.—YANG, Y.—LI, Y.: Assessing vaccination priorities for different ages and age-specific vaccination strategies of COVID-19 using an SEIR modelling approach, PLoS One, 16 (2021), Paper no. e0261236, https://doi.org/10.1371/journal.pone.0261236. Search in Google Scholar

Lingua:
Inglese
Frequenza di pubblicazione:
3 volte all'anno
Argomenti della rivista:
Matematica, Matematica generale