Zobrazeno 1 - 10
of 4 002
pro vyhledávání: '"SIR Model"'
Publikováno v:
Mathematical and Computer Modelling of Dynamical Systems, Vol 30, Iss 1, Pp 758-791 (2024)
In this manuscript, we carried out a thorough analysis of the general SIR model for epidemics. We broadened the model to include vaccination, treatment, and incidence rate. The vaccination rate is a testament to the alternatives made by individuals w
Externí odkaz:
https://doaj.org/article/66d0d746f13b4f08b90370763053f0f4
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract In this paper, we propose a numerical algorithm to obtain the optimal epidemic parameters for a time-dependent Susceptible-Unidentified infected-Confirmed (tSUC) model. The tSUC model was developed to investigate the epidemiology of unconfir
Externí odkaz:
https://doaj.org/article/3f7b0e61a3eb4d99a18074146538d2be
Publikováno v:
Infectious Disease Modelling, Vol 9, Iss 3, Pp 713-727 (2024)
Rocky Mountain spotted fever (RMSF) is a fatal tick-borne zoonotic disease that has emerged as an epidemic in western North America since the turn of the 21st century. Along the US south-western border and across northern Mexico, the brown dog tick,
Externí odkaz:
https://doaj.org/article/0f64b6d72f974130b4faaa74354900d0
Autor:
Bernd Kugelmann, Roland Pulch
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Mathematical modelling of a dengue epidemic with two serotypes including a temporary cross-immunity yields a nonlinear system consisting of ordinary differential equations (ODEs). We investigate an optimal control problem, where the integral
Externí odkaz:
https://doaj.org/article/24d916914738429e885fae34f088fb3e
Publikováno v:
Applied Mathematics in Science and Engineering, Vol 32, Iss 1 (2024)
The outbreak of COVID-19 causes a serious threat to human health and life around the world and puts enormous pressure on the healthcare system. The lockdown policy has effectively reduced the number of cases and suppressed the spread of the COVID-19
Externí odkaz:
https://doaj.org/article/9c439f42e008407ca18df0a11368874f
Publikováno v:
Royal Society Open Science, Vol 11, Iss 11 (2024)
The size of fruit bat colonies ranges from dozens to hundreds of thousands of individuals, depending on the species. While a deterministic modelling approach is appropriate for large colonies, the role of population fluctuations can be all-important
Externí odkaz:
https://doaj.org/article/467d590bc83443519fb8483a99cbd732
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 25, Iss 1 (2024)
We present two slightly different constructions of a SIR model in which both the time taken to remove the individual from the infectious compartment and the infectivity have a memory according to Mittag-Leffler distributions. The second construction
Externí odkaz:
https://doaj.org/article/71f10fd2b01041b8a97d8f0d55eda6c9
Publikováno v:
Trends in Computational and Applied Mathematics, Vol 25, Iss 1 (2024)
We investigate the problem of determining time dependent parameters for discrete-time epidemiological compartmental models such as the Susceptible-Infected-Recovered (SIR). We show how to determine parameters based on minimal error type iterative sch
Externí odkaz:
https://doaj.org/article/879f5c19860c402f8fdf6f1d19553875
Autor:
Dimiter Prodanov
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
IntroductionThe SIR (Susceptible-Infected-Recovered) model is one of the simplest and most widely used frameworks for understanding epidemic outbreaks.MethodsA second-order dynamical system for the R variable is formulated using an infinite exponenti
Externí odkaz:
https://doaj.org/article/baa3ec47ec424d2caa469db66f1f2f40
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Analyzing the important nodes of complex systems by complex network theory can effectively solve the scientific bottlenecks in various aspects of these systems, and how to excavate important nodes has become a hot topic in complex network re
Externí odkaz:
https://doaj.org/article/4e49aa5f20614328936d06c92b930f84