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Towards a predictive model for prevention of the risk of COVID-19 infection
1Department of Urban and Environmental Studies, El Colegio de la Frontera Norte, Baja California, Mexico.
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.
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