Heterogeneity of COVID-19 Risk Perception: A Socio-Mathematical Model

Abstract

The perception of risk has been a key element in the experiences, containment and differential impact of the COVID-19 pandemic worldwide. The complexity of this phenomenon requires the interdisciplinary integration of theoretical and methodological aspects, as this integration informs the objective of developing a mathematical proposal based on a conceptual model located within the social theory of risk at the micro-social level. The mathematical risk model used here was developed from a secondary analysis of a study of 12,649 individuals on the experiences of the COVID-19 pandemic in a population in which the quantity and quality of the information made it possible to define a risk factor and its relationship to emotions and the sources of information used. Four sequential strategies were used to construct the model: choosing the variables for the questionnaire that theoretically corresponded to the conceptual model, constructing the risk vector and initial grouping of individuals by perception of risk, modeling by using principal component analysis and applying network methods. The theoretical model of risk, proposed and constructed through the analysis of groupings by quartiles and by networks in the studied population from a social and mathematical perspective, demonstrates the heterogeneity of risk perception as manifested by differences in perception by age, gender, expression of feelings and media consulted in a university community. The knowledge and methodology generated in these analyses contribute to the body of knowledge informing the response to future epidemiological contingencies.