Estimation of Malaria Mortality in Developing Countries

Abstract

This chapter considered monitoring human health condition as vital variable for well-being of man/society required input data for effective daily planning. Researchers have contributed to prediction of incidence/recovery rate for malaria mortality. Modified state-estimation model based (matrix-formulation, weighted sum of squares of errors) was applied. The instrument (sphygmomanometer, etc.) is manipulated for study under investigation to examined existing state of system. Four (4) measurements data were analyzed from different geographical locations for patients with malaria endemic cases. Physician measurement data are implemented into modified state-estimation equations to estimate degree of error(s) to classify as bad measurement. Results shows bad data estimation attributed to poor instrument calibration, aging, and poor physician measurement. These reveal discrepancies between actual (true-measurement) and patient-physical measurements. Four vital measurements include blood pressure (Bp), blood sugar level (BSL), body temperature (BT), and Plasmodium ViVax with relied validation test following chi-square distribution for 2-degree freedom with 99% significance level suspected as error measurement. Model-matrix coded in MATLAB gives state-estimation results x1=8.5225andx2=13.235, indicating strong variation between actual and physical measurements for some patients having low pulse rate under the measurement of blood pressure (Bp). Essentially, physicians’ measurements must be revalidated for accuracy before drugs prescription/administration to avoid under- or over-dose since patients’ body chemistry varies significantly for different persons.