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Resumen: The containment of epidemic spreading is a major challenge in science. Vaccination, whenever available, is the best way to prevent the spreading, because it eventually immunizes individuals. However, vaccines are not perfect, and total immunization is not guaranteed. Imperfect immunization has driven the emergence of antivaccine movements that totally alter the predictions about the epidemic incidence. Here, we propose a mathematically solvable mean-field vaccination model to mimic the spontaneous adoption of vaccines against influenzalike diseases and the expected epidemic incidence. The results are in agreement with extensive Monte Carlo simulations of the epidemics and vaccination coevolutionary processes. Interestingly, the results reveal a nonmonotonic behavior on the vaccination coverage that increases with the imperfection of the vaccine and after decreases. This apparent counterintuitive behavior is analyzed and understood from stability principles of the proposed mathematical model.
Idioma: Inglés
DOI: 10.1103/PhysRevE.97.032308
Año: 2018
Publicado en: Physical Review E 97, 3 (2018), 032308 [6 pp]
ISSN: 2470-0045
Factor impacto JCR: 2.353 (2018)
Categ. JCR: PHYSICS, MATHEMATICAL rank: 7 / 55 = 0.127 (2018) - Q1 - T1
Categ. JCR: PHYSICS, FLUIDS & PLASMAS rank: 14 / 32 = 0.438 (2018) - Q2 - T2
Factor impacto SCIMAGO: 0.992 - Condensed Matter Physics (Q1) - Statistics and Probability (Q1) - Statistical and Nonlinear Physics (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/E19
Financiación: info:eu-repo/grantAgreement/ES/FIS/2015-71582-C2
Financiación: info:eu-repo/grantAgreement/ES/MINECO/FIS2014-55867-P
Financiación: info:eu-repo/grantAgreement/ES/MINECO/RYC-2012-01043
Tipo y forma: Article (Published version)
Área (Departamento): Área Física Materia Condensada (Dpto. Física Materia Condensa.)

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