AN ORDINAL LOGISTIC REGRESSION MODEL FOR ANALYZING RISK ZONE STATUS OF COVID-19 SPREAD

Abstract

Coronavirus disease 2019 (COVID-19) is a new type of virus that has been found to have infected human since it first appeared in Wuhan, China, in December 2019. This study aims to determine the factors that influence the risk zone status of COVID-19 spread in Indonesia using ordinal logistic regression. The ordinal logistic regression model in this study uses proportional odds model because the researcher assumes probability of predictor variable coefficients is the same for each respond category. The response variable is secondary data from the COVID-19 Handling Task Force, namely the status of the risk zone for the spread of COVID-19 who has 4 categorical levels, namely high, medium, low, and no cases. Predictor variables are elderly population, COVID-19 referral hospital, diabetes mellitus, hypertension, hand washing behavior, male population, and smoking habits. Based on results of the analysis, variables that significantly affect the risk zone status of COVID-19 spread in Indonesia are elderly population and diabetes mellitus. The Odds proportional figure shows that the higher percentage of the elderly population, the higher chance of an area with high-risk zone status (OR=1.171). The higher percentage of comorbidities diabetes mellitus, the higher chance of an area with high-risk zone status (OR=1.569).