MULTIDIMENSIONAL MODELING TO FIND THE MOST EFFICIENT FACTORS OF COVID-19 PANDEMIC OVER THE PUBLIC HEALTH WITH PRINCIPAL COMPONENTS ANALYSIS METHOD

Abstract

We aim at to investigate the most efficient factors of the correlations formed from factors loading generated from the variables formed from the data about the factors which affected the public health during COVID-19 pandemic and to analyze the results obtained. For this study, we have conducted a cross-sectional inquiry using the Web based random sampling method during the pandemic which began in Turkey on March 2020. At first sight, the inquiry can be thought in the form of four main elements (categories): (1) Demographic features of the participants, (2) Risk and danger perception of the pandemic, (3) Individual and social protection from the pandemic, and (4) Examination of the physiological and psychological effects of the pandemic. Before carrying out simply statistical modeling analysis from the data, we have observed easily that there is a multidirectional and complicated pressure psychology ruling in the community. In order to reach a premise like this and/or information which will let us think like this, we have found convenient to work with factor analysis methods which are multivariable statistical models . We even have found that some results for hindering the distribution of the virus are continually discussed but they are not scientifically established. For example, we have found that individual and social protection actions are successfully taken into account. Women are taking the actions with a higher rate than men. Also, the well educated people are taking actions with a higher rate than those who are low educated. We have revealed that the inactive life during the pandemic process, the increasing carbohydrate consumption caused weight increases. The economic problems together with job losses due to the pandemic of COVID-19 created serious concerns which led to psychological and physiological disorders.