Faraimunashe Chirove

A Stochastic Tick-Borne Disease Model: Exploring the Probability of Pathogen Persistence

We formulate and analyse a stochastic epidemic model for the transmission dynamics of a tick-borne disease in a single population using a continuous-time Markov chain approach. The stochastic model is based on an existing deterministic metapopulation tick-borne disease model. We compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in tick-borne disease dynamics. The probability of disease extinction and that of a major outbreak are computed and approximated using the multitype Galton–Watson branching process and numerical simulations, respectively. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that a disease outbreak is more likely if the disease is introduced by infected deer as opposed to infected ticks. These insights demonstrate the importance of host movement in the expansion of tick-borne diseases into new geographic areas.

Modelling the role of multi-transmission routes in the epidemiology of bovine tuberculosis in cattle and buffalo populations

A mathematical model that describes the transmission dynamics of bovine tuberculosis (BTB) in both buffalo and cattle populations is proposed. The model incorporates cross-infection and contaminated environment transmission routes. A full analysis of the model is undertaken. The reproduction number of the entire model is comprised of cross-infection and contaminated parameters. This underscores the importance of including both cross-infection and contaminated environment transmission routes. Crucially our simulations suggest that the disease has a more devastating effect on cattle populations than on buffalo populations when all transmission routes are involved. This has important implications for agriculture and tourism.

Analysis of Combined Langerhans and CD

We develop a mathematical model that captures the combined infection of Langerhans cells and CD

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T Cells HIV Infection

T cells and their contribution to early HIV infection within the host. Mathematical analysis of the mathematical model revealed a threshold parameter denoted by alternative reproduction ratio with three different cycles of generations of secondary HIV infections, namely (i) cycle from infected CD

Effects of replicative fitness on competing HIV strains

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Modelling coupled within host and population dynamics of R5 and X4 HIV infection

T cells to free virus and back to infected CD

Trans-Allelic Model for Prediction of Peptide:MHC-II Interactions

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Modeling the effects of insecticides resistance on malaria vector control in endemic regions of Kenya

T cells, (ii) cycle from infected CD

Pre-exposure prophylaxis and antiretroviral treatment interventions with drug resistance

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