机构:
Kabale Univ, Fac Sci, POB 317, Kabale, Uganda
South African Ctr Epidemiol Modelling & Anal, 19 Jonkershoek, ZA-7600 Cape Town, Western Cape, South AfricaKabale Univ, Fac Sci, POB 317, Kabale, Uganda
Ssebuliba, Doreen Mbabazi
[1
,2
]
Ouifki, Rachid
论文数: 0引用数: 0
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机构:
South African Ctr Epidemiol Modelling & Anal, 19 Jonkershoek, ZA-7600 Cape Town, Western Cape, South Africa
Univ Pretoria, Dept Math & Appl Math, Private Bag X20, ZA-0028 Pretoria, South AfricaKabale Univ, Fac Sci, POB 317, Kabale, Uganda
Ouifki, Rachid
[2
,3
]
机构:
[1] Kabale Univ, Fac Sci, POB 317, Kabale, Uganda
[2] South African Ctr Epidemiol Modelling & Anal, 19 Jonkershoek, ZA-7600 Cape Town, Western Cape, South Africa
[3] Univ Pretoria, Dept Math & Appl Math, Private Bag X20, ZA-0028 Pretoria, South Africa
Poor living conditions, overcrowding and strain diversity are some of the factors that influence mixed infection in Tuberculosis (TB) at the population level. We formulate a mathematical model for mixed infection in TB using nonlinear ordinary differential equations where such factors were represented as probabilities of acquiring mixed infection. A qualitative analysis of the model shows that it exhibits multiple endemic equilibria and backward bifurcation for certain parameter values. The reactivation rate and transmission rate of individuals with mixed infection were of importance as well as the probabilities for latent individuals to acquire mixed infection. We calculate the prevalence of mixed infection from the model and the effect of mixed infection on TB incidence, TB prevalence and Mycobacterium tuberculosis (MTB) infection rate. Numerical simulations show that mixed infection may explain high TB incidences in areas which have a high strain diversity, poor living conditions and are overcrowded even without HIV.