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A GENERAL MODELING FRAMEWORK FOR QUANTITATIVE TRACKING, ACCURATE PREDICTION OF ICU, AND ASSESSING VACCINATION FOR COVID-19 IN CHILE

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dc.creatorPATRICIO ANDRÉS CUMSILLE ATALA
dc.date2023
dc.date.accessioned2025-01-10T15:37:45Z
dc.date.available2025-01-10T15:37:45Z
dc.date.issued2023
dc.description.abstractBACKGROUND: 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
dc.formatapplication/pdf
dc.identifier.doi10.3389/fpubh.2023.1111641
dc.identifier.issn2296-2565
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/12914
dc.languagespa
dc.publisherFRONTIERS IN PUBLIC HEALTH
dc.relation.uri10.3389/fpubh.2023.1111641
dc.rightsPUBLICADA
dc.subjectvaccination
dc.subjecttime delays
dc.subjectpredictive modeling
dc.subjectpractical identifiability
dc.subjectparametric bootstrap
dc.subjectparameter optimization
dc.subjectepidemiological modeling
dc.subjectCOVID-19
dc.titleA GENERAL MODELING FRAMEWORK FOR QUANTITATIVE TRACKING, ACCURATE PREDICTION OF ICU, AND ASSESSING VACCINATION FOR COVID-19 IN CHILE
dc.typeARTÍCULO
dspace.entity.typePublication
oaire.fundingReferenceUBB- UNIVERSIDAD DEL BÍO-BÍO
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE CIENCIAS BASICAS
ubb.SedeCHILLÁN
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