Serodiagnosis of Samonella Infection using a Logistic Regression Model
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Abstract
Abstract - Salmonella infection remains a major global
health problem and worsened by lack of appropriate
diagnostic tools, which have not significantly improved,
particularly in low-income nations . Salmonella typhi is the
most common causative agent of typhoid fever and the
prevalence of this illness has been on the increase
specifically in areas of poor personal hygiene and
sanitation.. This study was carried out to further improve the
diagnosis of salmonella infection, through a mathematical
regression model. An analysis was performed using the
logistic regression approach and the predictability of the
model was done by extracting fifteen (15) typhoid
observations from the obtained samples; for the model to
predict their status. The model was able to accurately predict
66.7% of the observations. This study showed an increased
prevalence in typhoid fever including a significant
correlation between typhoid fever and other parameters. The
global burden of this illness can be minimized by proper
vaccination, and prompt but appropriate diagnosis and
treatment.Further studies also needs to be carried out to
further improve diagnosis and treatment regimen
Keywords: Salmonella infection, Typhoid fever,Diagnosis,
logistic regressio