Global dynamics and sensitivity analysis of seir model with infectious force in latent and infectious periods

บทความในวารสาร


ผู้เขียน/บรรณาธิการ


กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง


รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่งSirijampa A., Chinviriyasit S.

ผู้เผยแพร่Pushpa

ปีที่เผยแพร่ (ค.ศ.)2016

วารสารFar East Journal of Mathematical Sciences (0972-0871)

Volume number100

Issue number8

หน้าแรก1169

หน้าสุดท้าย1194

จำนวนหน้า26

นอก0972-0871

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84990852423&doi=10.17654%2fMS100081169&partnerID=40&md5=57dd7a5ef27bfd3994d971f31e9f2093

ภาษาEnglish-Great Britain (EN-GB)


ดูบนเว็บไซต์ของสำนักพิมพ์


บทคัดย่อ

The dynamical features of an SEIR model with infectious force in latent and infectious periods is investigated for studying the impact of recovery rate of latent on the spread of influenza in a homogeneous population with constant immigration of susceptibles. The threshold value called the basic reproduction number R0 is derived and proved to be a sharp threshold which completely determines the global dynamics and the outcome of the disease. Using global stability analysis of the model, it is shown that if R0 ≤ 1, then the disease-free equilibrium is globally asymptotically stable and then the disease always dies out. If R0 > 1, then there exists a unique endemic equilibrium and the change of variable is introduced in order to prove the global asymptotic stability of this equilibrium, which can reduce a four-dimensional system to a three-dimensional asymptotic autonomous system with limit equation. The model analysis has been applied to compare the theoretical results with the known Brazil influenza data. The sensitivity analysis has been performed to determine the relative importance of different parameters in transmission and prevalence of influenza. Numerical simulations are carried out to investigate the influence of the key parameters on the spread of the disease. © 2016 Pushpa Publishing House, Allahabad, India.


คำสำคัญ

SEIR epidemic model


อัพเดทล่าสุด 2023-04-10 ถึง 07:36