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Coffee berry disease (CBD) is a fungal disease caused by Colletotrichum kahawae. CBD is a major constraint to coffee production to Kenya and Africa at large. In this research paper, we formulate a mathematical model of the dynamics of the coffee berry disease. The model consists of coffee plant population in a plantation and Colletotrichum kahawae pathogen population. We derived the basic reproduction number R k 0 , and analyzed the dynamical behaviors of both disease-free equilibrium and endemic equilibrium by the theory of ordinary differential equations. Using the MATLAB ode45 solver, we carried out numerical simulation, and the findings are consistent with the theoretical results. [ABSTRACT FROM AUTHOR]

Self-medication is an important initial response to illness in Africa. This mode of medication is often done with the help of African traditional medicines. Because of the misconception that African traditional medicines can cure/prevent all diseases, some Africans may opt for COVID-19 prevention and management by self-medicating. Thus to efficiently predict the dynamics of COVID-19 in Africa, the role of the self-medicated population needs to be taken into account. In this paper, we formulate and analyse a mathematical model for the dynamics of COVID-19 in Cameroon. The model is represented by a system of compartmental age-structured ODEs that takes into account the self-medicated population and subdivides the human population into two age classes relative to their current immune system strength. We use our model to propose policy measures that could be implemented in the course of an epidemic in order to better handle cases of self-medication. [ABSTRACT FROM AUTHOR]

This paper explores the use of continuous-time Markov chain theory to describe poverty dynamics. It is shown how poverty measures can be derived beyond the commonly reported headcounts and transition probabilities. The added measures include the stationary situation, the mean sojourn time in a given poverty state and an index for mobility. Probit regression is employed to identify the most influential factors on the transition probabilities. Moreover, sensitivity analysis shows that the results are robust against perturbations of the transition matrix. We illustrate the approach with pseudo-panel data constructed from a repeated cross-section survey in Mozambique, using a pairwise matching method to connect households in the 2003 sample to similar households in 2009. Results reflect high and persistent poverty levels with considerable movements into and out of poverty. An estimated 57 percent of the poor in the first wave remained poor in the second wave and 43 percent moved out. Likewise, 64 percent remained non-poor and 36 percent moved in. The corresponding stationary poverty headcount is 45 percent with respective mean sojourn time of 6.9 years in poverty and 8.4 years out of poverty. Conditioning the Markov chain on covariates identified by probit regressions indicates that poverty dynamics are responsive to household characteristics and livelihoods. [ABSTRACT FROM AUTHOR]