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Negative Binomial Regression Model of Typhoid Fever Trajectory in Saboba District of Ghana

Abstract

Typhoid fever has always been a major health problem, and therefore, timely and accurate information about its occurrence rate is imperative. The main objective of the research was to model the prevalence of typhoid fever in Saboba district given the demographic age groupings, gender and time. Data on the incidence of typhoid fever in Saboba district (2009 – 2013) were obtained from the Saboba District Health Information Management database. Statistical Analysis System (SAS) was used to analyze the acquired data.  Based on the model diagnostics, the Negative Binomial regression model was emerged as superior to the Poisson regression model. This is because it was able to accommodate the over-dispersion that existed in the dataset.

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