A logistic regression model on some malaria intervention strategies: a case study of Obuasi Municipality

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October 13, 2015
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Some medical experts and researchers have in recent times expressed interest in Malaria due to its life threatening nature and debilitating effect especially on pregnant women and children. This study seeks to model the risk of reduction in malaria reporting by children under five years in the Obuasi Municipality given the types of interventions. Data gathered from a baseline survey across 22 clusters on a maximum of 508 sampled children is being modeled by means of logistic regression. The data was restricted to a 5-year span (2009 - 2014) because of the vested interest in the under 5- year group. A paired t-test which compares the p-value of 0.00 to a threshold p-value of 0.05 was used to establish whether there is a significant difference between the two sets of data on clinical visits in the past and in the current year. The same test was used to establish that there was a mean reduction of 1:36 (with 1.53 standard deviation) in malaria reporting. Our analysis also provides some parameter estimates for our model. These are tested using Wald statistics and form the basis of our model equation. Again since our analysis of parameter estimates reveals that the parameter 1:2330 corresponding to the use of both IRS and ITN interventions only, has the least p-value of 0:0052 < 0:05, we conclude that children who experience both interventions are likely to risk reduction in malaria reporting and therefore contribute significantly to model.
A thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the Degree of Master of Science in Industrial Mathematics,