The management of blood bank is an integral part of health delivery system and it is centred on the donation and transfusion of blood. The four major classification of blood is considered in the formulation of Markov model with a first-order dependence. The data of blood transfused in a city hospital was studied and the result revealed that the blood that is donated and received by the same blood group constitute the major blood needed in the hospital with 100%, 99.1%, 98.3%, and 98.5% for blood groups AB,B,A and O respectively. There will be a little variation in the blood needed for transfusion in the future on the basis of the present when the initial values of the transition probabilities P12 (t), P13 (t), P14 (t), P24 (t), and P34 (t) (t = 0) are 0.00354, 0.00202, 0.00865, 0.01653 and 0.00884 respectively. The information about blood bank inventory is important for a successful health care delivery. If such information is available in every city hospital, it may be possible to move blood from one hospital to another during emergency.
This paper demonstrates the application of Markov chain model with non-stationary transition probabilities to study data of the Reservoir elevation of Shiroro dam in the dry and raining seasons. The result indicates an optimal of 40% and 49% transition probabilities at equilibrium for dry season and wet season respectively. The result confirms the reality on the ground that higher reservoir elevation is obtained more during the raining season. Conversely, the lower reservoir elevation is experienced largely in the dry season. The variation of the reservoir elevation directly affects the hydro electric power generation and the availability of the other dam resources. Markov chain model could be used as a predictive device for studying reservoir elevation of Shiroro dam. These predictions might be used for the management of the dam resources.
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