Aplicación de sistemas fuzzy para la toma de decisiones del Plan Paso a Paso: análisis de los indicadores para la comuna de Valdivia / Artificial intelligence fuzzy system for the design of confinements during quarantines

BACKGROUND: Different modalities of quarantines were one of the main measures implemented worldwide to avoid the spread of SARS-CoV2 virus. AIM: To analyze and compare retrospectively the implementation of the Step- to-Step plan devised by the Chilean Ministry of Health during the pandemic. To propose a decision-making path based on an artificial intelligence fuzzy system to determine confinements in specific territories. MATERIAL AND METHODS: The Step-to-Step Plan threshold values such hospital network capacity, epidemic spreading, testing and contact tracing capability were modeled using fuzzy numbers and fuzzy rule-based systems. RESULTS: Ministry of Health's decision-making opportuneness were unrelated with the Step-to-Step Plan indicators for deconfinement. Such disagreements undermined epidemiological indicators. CONCLUSIONS: Using an artificial intelligence system could improve decision-making transparency, emergency governance, and risk communication to the population.

[Artificial intelligence fuzzy system for the design of confinements during quarantines]. / Aplicación de sistemas fuzzy para la toma de decisiones del Plan Paso a Paso: análisis de los indicadores para la comuna de Valdivia.

BACKGROUND: Different modalities of quarantines were one of the main measures implemented worldwide to avoid the spread of SARS-CoV2 virus. AIM: To analyze and compare retrospectively the implementation of the Step- to-Step plan devised by the Chilean Ministry of Health during the pandemic. To propose a decision-making path based on an artificial intelligence fuzzy system to determine confinements in specific territories. MATERIAL AND METHODS: The Step-to-Step Plan threshold values such hospital network capacity, epidemic spreading, testing and contact tracing capability were modeled using fuzzy numbers and fuzzy rule-based systems. RESULTS: Ministry of Health's decision-making opportuneness were unrelated with the Step-to-Step Plan indicators for deconfinement. Such disagreements undermined epidemiological indicators. CONCLUSIONS: Using an artificial intelligence system could improve decision-making transparency, emergency governance, and risk communication to the population.