Dynamics analysis and simulation of a modified HIV infection model with a saturated infection rate.
This paper studies a modified human immunodeficiency virus (HIV) infection differential equation model with a saturated infection rate. It is proved that if the basic virus reproductive number R 0 of the model is less than one, then the infection-free equilibrium point of the model is globally asymptotically stable; if R 0 of the model is more than one, then the endemic infection equilibrium point of the model is globally asymptotically stable. Based on the clinical data from HIV drug resistance database of Stanford University, using the proposed model simulates the dynamics of the two groups of patients' anti-HIV infection treatment. The numerical simulation results are in agreement with the evolutions of the patients' HIV RNA levels. It can be assumed that if an HIV infected individual's basic virus reproductive number R 0 < 1 then this person will recover automatically; if an antiretroviral therapy makes an HIV infected individual's R 0 < 1, this person will be cured eventually; if an antiretroviral therapy fails to suppress an HIV infected individual's HIV RNA load to be of unpredictable level, the time that the patient's HIV RNA level has achieved the minimum value may be the starting time that drug resistance has appeared.
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Qilin
0000-0002-2178-5236
Q
Sun
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China ; School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Lequan
0000-0002-4414-3818
L
Min
D000465:Algorithms; D015496:CD4-Positive T-Lymphocytes / Q000166:cytology; D003198:Computer Simulation; D024882:Drug Resistance, Viral; D015658:HIV Infections / Q000175:diagnosis* / Q000188:drug therapy / Q000635:transmission*; D015497:HIV-1; D006801:Humans; D008490:Medical Informatics; D008962:Models, Theoretical; D012367:RNA, Viral / Q000235:genetics; D012984:Software; D019562:Viral Load
D012367:RNA, Viral