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Global dynamics of a staged progression model for infectious diseases
1.  Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1, Canada 
2.  Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta T6G 2G1, Canada 
[1] 
James M. Hyman, Jia Li. Epidemic models with differential susceptibility and staged progression and their dynamics. Mathematical Biosciences & Engineering, 2009, 6 (2) : 321332. doi: 10.3934/mbe.2009.6.321 
[2] 
Andrey V. Melnik, Andrei Korobeinikov. Global asymptotic properties of staged models with multiple progression pathways for infectious diseases. Mathematical Biosciences & Engineering, 2011, 8 (4) : 10191034. doi: 10.3934/mbe.2011.8.1019 
[3] 
Praveen Kumar Gupta, Ajoy Dutta. Numerical solution with analysis of HIV/AIDS dynamics model with effect of fusion and cure rate. Numerical Algebra, Control & Optimization, 2019, 9 (4) : 393399. doi: 10.3934/naco.2019038 
[4] 
Brandy Rapatski, Petra Klepac, Stephen Dueck, Maoxing Liu, Leda Ivic Weiss. Mathematical epidemiology of HIV/AIDS in cuba during the period 19862000. Mathematical Biosciences & Engineering, 2006, 3 (3) : 545556. doi: 10.3934/mbe.2006.3.545 
[5] 
Nirav Dalal, David Greenhalgh, Xuerong Mao. Mathematical modelling of internal HIV dynamics. Discrete & Continuous Dynamical Systems  B, 2009, 12 (2) : 305321. doi: 10.3934/dcdsb.2009.12.305 
[6] 
Cristiana J. Silva, Delfim F. M. Torres. A TBHIV/AIDS coinfection model and optimal control treatment. Discrete & Continuous Dynamical Systems  A, 2015, 35 (9) : 46394663. doi: 10.3934/dcds.2015.35.4639 
[7] 
Arni S. R. Srinivasa Rao, Kurien Thomas, Kurapati Sudhakar, Philip K. Maini. HIV/AIDS epidemic in India and predicting the impact of the national response: Mathematical modeling and analysis. Mathematical Biosciences & Engineering, 2009, 6 (4) : 779813. doi: 10.3934/mbe.2009.6.779 
[8] 
Esther Chigidi, Edward M. Lungu. HIV model incorporating differential progression for treatmentnaive and treatmentexperienced infectives. Mathematical Biosciences & Engineering, 2009, 6 (3) : 427450. doi: 10.3934/mbe.2009.6.427 
[9] 
Gigi Thomas, Edward M. Lungu. A twosex model for the influence of heavy alcohol consumption on the spread of HIV/AIDS. Mathematical Biosciences & Engineering, 2010, 7 (4) : 871904. doi: 10.3934/mbe.2010.7.871 
[10] 
Helen Moore, Weiqing Gu. A mathematical model for treatmentresistant mutations of HIV. Mathematical Biosciences & Engineering, 2005, 2 (2) : 363380. doi: 10.3934/mbe.2005.2.363 
[11] 
Jinliang Wang, Jiying Lang, Yuming Chen. Global dynamics of an agestructured HIV infection model incorporating latency and celltocell transmission. Discrete & Continuous Dynamical Systems  B, 2017, 22 (10) : 37213747. doi: 10.3934/dcdsb.2017186 
[12] 
Zhaohui Yuan, Xingfu Zou. Global threshold dynamics in an HIV virus model with nonlinear infection rate and distributed invasion and production delays. Mathematical Biosciences & Engineering, 2013, 10 (2) : 483498. doi: 10.3934/mbe.2013.10.483 
[13] 
Yu Yang, Yueping Dong, Yasuhiro Takeuchi. Global dynamics of a latent HIV infection model with general incidence function and multiple delays. Discrete & Continuous Dynamical Systems  B, 2019, 24 (2) : 783800. doi: 10.3934/dcdsb.2018207 
[14] 
Oluwaseun Sharomi, Chandra N. Podder, Abba B. Gumel, Baojun Song. Mathematical analysis of the transmission dynamics of HIV/TB coinfection in the presence of treatment. Mathematical Biosciences & Engineering, 2008, 5 (1) : 145174. doi: 10.3934/mbe.2008.5.145 
[15] 
Zindoga Mukandavire, Abba B. Gumel, Winston Garira, Jean Michel Tchuenche. Mathematical analysis of a model for HIVmalaria coinfection. Mathematical Biosciences & Engineering, 2009, 6 (2) : 333362. doi: 10.3934/mbe.2009.6.333 
[16] 
Xinyue Fan, ClaudeMichel Brauner, Linda Wittkop. Mathematical analysis of a HIV model with quadratic logistic growth term. Discrete & Continuous Dynamical Systems  B, 2012, 17 (7) : 23592385. doi: 10.3934/dcdsb.2012.17.2359 
[17] 
Shingo Iwami, Shinji Nakaoka, Yasuhiro Takeuchi. Mathematical analysis of a HIV model with frequency dependence and viral diversity. Mathematical Biosciences & Engineering, 2008, 5 (3) : 457476. doi: 10.3934/mbe.2008.5.457 
[18] 
Tyson Loudon, Stephen Pankavich. Mathematical analysis and dynamic active subspaces for a long term model of HIV. Mathematical Biosciences & Engineering, 2017, 14 (3) : 709733. doi: 10.3934/mbe.2017040 
[19] 
Cristiana J. Silva, Delfim F. M. Torres. Modeling and optimal control of HIV/AIDS prevention through PrEP. Discrete & Continuous Dynamical Systems  S, 2018, 11 (1) : 119141. doi: 10.3934/dcdss.2018008 
[20] 
Christopher M. KribsZaleta, Melanie Lee, Christine Román, Shari Wiley, Carlos M. HernándezSuárez. The Effect of the HIV/AIDS Epidemic on Africa's Truck Drivers. Mathematical Biosciences & Engineering, 2005, 2 (4) : 771788. doi: 10.3934/mbe.2005.2.771 
2018 Impact Factor: 1.313
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