Publicación: A GENERAL MODELING FRAMEWORK FOR QUANTITATIVE TRACKING, ACCURATE PREDICTION OF ICU, AND ASSESSING VACCINATION FOR COVID-19 IN CHILE
Fecha
2023
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FRONTIERS IN PUBLIC HEALTH
Resumen
BACKGROUND: ONE OF THE MAIN LESSONS OF THE COVID-19 PANDEMIC IS THAT WE MUST
PREPARE TO FACE ANOTHER PANDEMIC LIKE IT. CONSEQUENTLY, THIS ARTICLE AIMS TO DEVELOP A GENERAL FRAMEWORK CONSISTING OF EPIDEMIOLOGICAL MODELING AND A PRACTICAL IDENTIFIABILITY APPROACH TO ASSESS COMBINED VACCINATION AND NON-PHARMACEUTICAL INTERVENTION (NPI) STRATEGIES FOR THE DYNAMICS OF ANY TRANSMISSIBLE DISEASE.
MATERIALS AND METHODS: EPIDEMIOLOGICAL MODELING OF THE PRESENT WORK RELIES
ON DELAY DIFERENTIAL EQUATIONS DESCRIBING TIME VARIATION AND TRANSITIONS BETWEEN
SUITABLE COMPARTMENTS. THE PRACTICAL IDENTIFIABILITY APPROACH RELIES ON PARAMETER
OPTIMIZATION, A PARAMETRIC BOOTSTRAP TECHNIQUE, AND DATA PROCESSING. WE
IMPLEMENTED A CAREFUL PARAMETER OPTIMIZATION ALGORITHM BY SEARCHING FOR SUITABLE
INITIALIZATION ACCORDING TO EACH PROCESSED DATASET. IN ADDITION, WE IMPLEMENTED A
PARAMETRIC BOOTSTRAP TECHNIQUE TO ACCURATELY PREDICT THE ICU CURVE TREND IN THE
MEDIUM TERM AND ASSESS VACCINATION.
RESULTS: WE SHOW THE FRAMEWORK?S CALIBRATION CAPABILITIES FOR SEVERAL PROCESSED
COVID-19 DATASETS OF DI
ERENT REGIONS OF CHILE. WE FOUND A UNIQUE RANGE OF
PARAMETERS THAT WORKS WELL FOR EVERY DATASET AND PROVIDES OVERALL NUMERICAL
STABILITY AND CONVERGENCE FOR PARAMETER OPTIMIZATION. CONSEQUENTLY, THE
FRAMEWORK PRODUCES OUTSTANDING RESULTS CONCERNING QUANTITATIVE TRACKING OF
COVID-19 DYNAMICS. IN ADDITION, IT ALLOWS US TO ACCURATELY PREDICT THE ICU CURVE
TREND IN THE MEDIUM TERM AND ASSESS VACCINATION. FINALLY, IT IS REPRODUCIBLE SINCE
WE PROVIDE OPEN-SOURCE CODES THAT CONSIDER PARAMETER INITIALIZATION STANDARDIZED
FOR EVERY DATASET.
CONCLUSION: THIS WORK ATTEMPTS TO IMPLEMENT A HOLISTIC AND GENERAL MODELING
FRAMEWORK FOR QUANTITATIVE TRACKING OF THE DYNAMICS OF ANY TRANSMISSIBLE DISEASE,
FOCUSING ON ACCURATELY PREDICTING THE ICU CURVE TREND IN THE MEDIUM TERM
AND ASSESSING VACCINATION. THE SCIENTIFIC COMMUNITY COULD ADAPT IT TO EVALUATE
THE IMPACT OF COMBINED VACCINATION AND NPIS STRATEGIES FOR COVID
Descripción
Palabras clave
vaccination, time delays, predictive modeling, practical identifiability, parametric bootstrap, parameter optimization, epidemiological modeling, COVID-19
