In this paper, we present a mathematical model for the study of resistance to tuberculosis treatment using fractional derivatives in the Caputo sense. This model takes into account the relationship between Tuberculosis, HIV/AIDS, and diabetes and differentiates resistance cases into MDR-TB (multidrug-resistant tuberculosis) and XDR-TB (extensively drug-resistant tuberculosis). We present the basic results associated with the model and study the behavior of the disease-free equilibrium points in the different sub-populations, TB-Only, TB-HIV/AIDS, and TB-Diabetes. We performed computational simulations for different fractional orders (α-values) using an Adams-Bashforth-Moulton type predictor-corrector PECE method. Among the results obtained, we have that the MDR-TB cases in all sub-populations decrease at the beginning of the study for the different α-values. In XDR-TB cases in the TB-Only sub-population, there is a decrease in the number of cases. XDR-TB cases in the TB-HIV/AIDS sub-population have differentiated behavior depending on α. This knowledge helps to design an effective control strategy. The XDR-TB cases in diabetics increased throughout the study period and outperformed all resistant compartments for the different α-values. We recommend special attention to the control of this compartment due to this growth.
Zika virus is primarily transmitted to people through the bite of an infected mosquito from the Aedes genus, mainly Aedes aegypti in tropical regions. Aedes mosquitoes usually bite during the day, peaking during early morning and late afternoon/evening. This is the same mosquito that transmits dengue, chikungunya and yellow fever. Zika is transmitted to humans primarily through bites from infected Aedes aegypti and Aedes albopictus mosquitoes. The transmission is in both directions, that is, infected mosquitoes infect humans and infected humans infect mosquitoes. Sexual transmission of Zika virus is also possible. Other modes of transmission such as blood transfusion are being investigated. In this work are presented mathematical models to predict the behavior of the ZIKA epidemic over time, using ordinary differential equations [6, 14] and ordinary differential equations with temporal delay [11]. The delay is the time it takes humans and mosquitoes to develop the virus, become infected and participate in the transmission dynamics [9, 11]. The computer simulations are performed for Suriname and El Salvador, which have different characteristics, Suriname have higher rate the infection of human to mosquito and El Salvador have from mosquito to human, and this allows us to adapt the models to different epidemiological conditions. The data of the parameters and initial conditions were extracted from [5, 12, 13, 16].
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