An Analysis of Corona Virus Disease (COVID-19) Predictors: Logistic Regression Model Approach

摘要

Although Corona Virus disease (COVID-19) is a contagious disease cause by severe acute respiratory syndrome which affects mostly people whose immune system are weak or not resistance to the disease, there exists no vaccine that is 100% effective for its cure though efforts are being intensify by researchers in discovering the vaccine as well as model for prediction of Corona Virus Disease. In this era of advanced information and communication technology, as well as evidence-based medicine, statistical modeling has become as necessary the medical practitioners who are interested in lasting solution to diagnosed problems. In this work a logistic regressions model has been proposed to serve the purpose. The data was obtained from Nigeria Centre for Disease Control (NCDC) and was analyzed using binary logistic regression model in which Corona Virus disease was considered as categorical dependant variable (COVID-19 status: chance of being positive or negative) and the predictors considered are; Age, any of either Headache or Vomiting, Fever, Sore throat/runny nose, Any of Cold, cough or sweating, Loss of Smell or taste, and Breathing Difficulties. The results shows the significant predictors for predicting Corona Virus Diseases are; Loss of Smell or taste, Breathing Difficulties, Fever, Sore throat or runny nose, Age, any of either Headache or Vomiting, and Any of Cold, cough or sweating. The logit model obtained was: Logit (P(y=1)) = -3.748 + 0.356 Age +2.938 any of either Headache or Vomiting + 0.752 Fever + 2.792 Sore throat or runny nose - 0.028 Any of Cold, cough or sweating + 1.872 Loss of Smell or taste + 0.844 Breathing Difficulties. So also from the same results, it was found among predictors that; Sex/Gender, Temperature 37.5 degree and Fatigue or Muscle Pain were not good predictors of Corona Virus disease.