Introduction:

The scarcity of person-centered applications aimed at developing awareness on the risk posed by the COVID-19 pandemic, stimulates the exploration and creation of preventive tools that are accessible to the population.

Objective:

To develop a predictive model that allows evaluating the risk of mortality in the event of SARS-CoV-2 virus infection.

Methods:

Exploration of public data from 16,000 COVID-19-positive patients to generate an efficient discriminant model, evaluated with a score function and expressed by a self-rated preventive interest questionnaire.

Results:

A useful linear function was obtained with a discriminant capacity of 0.845; internal validation with bootstrap and external validation, with 25 % of tested patients showing marginal differences.

Conclusion:

The predictive model with statistical support, based on 15 accessible questions, can become a structured prevention tool.