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Modelling coupled within host and population dynamics of [Formula: see text] and [Formula: see text] HIV infection.
Manda, Edna Chilenje; Chirove, Faraimunashe.
Affiliation
  • Manda EC; University of KwaZulu-Natal, Pietermaritzburg, South Africa. lil2eddy@gmail.com.
  • Chirove F; University of KwaZulu-Natal, Pietermaritzburg, South Africa.
J Math Biol ; 76(5): 1123-1158, 2018 04.
Article in En | MEDLINE | ID: mdl-28762130
ABSTRACT
Most existing models have considered the immunological processes occurring within the host and the epidemiological processes occurring at population level as decoupled systems. We present a new model using continuous systems of non linear ordinary differential equations by directly linking the within host dynamics capturing the interactions between Langerhans cells, CD4[Formula see text] T-cells, R5 HIV and X4 HIV and the without host dynamics of a basic compartmental HIV/AIDS model. The model captures the biological theories of the cells that take part in HIV transmission. The study incorporates in its analysis the differences in time scales of the fast within host dynamics and the slow without host dynamics. In the mathematical analysis, important thresholds, the reproduction numbers, were computed which are useful in predicting the progression of the infection both within the host and without the host. The study results showed that the model exhibits four within host equilibrium points inclusive of three endemic equilibria whose effects translate into different scenarios at the population level. All the endemic equilibria were shown to be globally stable using Lyapunov functions and this is an important result in linking the within host dynamics to the population dynamics, because the disease free equilibrium point ceases to exist. The effects of linking were observed on the endemic equilibrium points of both the within host and population dynamics. Linking the two dynamics was shown to increase in the viral load within the host and increase in the epidemic levels in the population dynamics.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / Models, Biological Type of study: Prognostic_studies Limits: Humans Language: En Journal: J Math Biol Year: 2018 Document type: Article Affiliation country: Sudáfrica

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / Models, Biological Type of study: Prognostic_studies Limits: Humans Language: En Journal: J Math Biol Year: 2018 Document type: Article Affiliation country: Sudáfrica