No abstract

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.

Given any linear stationary iterative methods in the form z^(i+1)=Jz^(i)+f, where J is the iteration matrix, a significant improvements of the iteration matrix will decrease the spectral radius and enhances the rate of convergence of the particular method while solving system of linear equations in the form Az=b. This motivates us to refine the Extended Accelerated Over-Relaxation (EAOR) method called Refinement of Extended Accelerated Over-Relaxation (REAOR) so as to accelerate the convergence rate of the method. In this paper, a refinement of Extended Accelerated Over-Relaxation method that would minimize the spectral radius, when compared to EAOR method, is proposed. The method is a 3-parameter generalization of the refinement of Accelerated Over-Relaxation (RAOR) method, refinement of Successive Over-Relaxation (RSOR) method, refinement of Gauss-Seidel (RGS) method and refinement of Jacobi (RJ) method. We investigated the convergence of the method for weak irreducible diagonally dominant matrix, matrix or matrix and presented some numerical examples to check the performance of the method. The results indicate the superiority of the method over some existing methods.

group of antibiotics represented , 50% of the total quantity of antibiotics used while watch group of antibiotics constituted approximately 50%. Reserve group antibiotics were not prescribed on the day of the survey. Conclusions: Antibiotics are overused among hospitalized patients. There was excessive use of antibiotics in the watch group which are associated with a high risk of antibiotic resistance, and lesser use of the access group antibiotics that have lower risk of resistance in comparison to other countries. Antimicrobial stewardship program that prioritizes reducing antibiotic overuse, reduce the excessive use of watch group antibiotics and promotes assess to reserve group antibiotics when they are needed is recommended.

This study used a multivariate negative binomial model to capture the Spatiotemporal endemic-epidemic of infectious disease and explore the spatial and temporal patterns of cholera outbreaks in Nigeria. The model for the epidemic part measured spatial weights for the disease spread across the geographical neighboring regions and the endemic part accounted for temporal variation of disease incidence. Weekly count data on cholera from the Nigeria Department of Disease Control and Monitoring Epidemiology (NCDC SED) between January 1st and November 19th, 2018 was used to illustrate the model. In fitting the model, the study has shown that the model with seasonality and autoregressive components provided an adequate fit for the cholera count data and also perform better than the model without seasonality and autoregression for modelling the Spatiotemporal dependency structure of cholera disease