Artikel ; Online: A general modeling framework for quantitative tracking, accurate prediction of ICU, and assessing vaccination for COVID-19 in Chile
Frontiers in Public Health, Vol
2023 Band 11
Abstract: BackgroundOne 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 ... ...
Abstract | BackgroundOne 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 methodsEpidemiological modeling of the present work relies on delay differential 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.ResultsWe show the framework's calibration capabilities for several processed COVID-19 datasets of different 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.ConclusionThis 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-19 or any transmissible disease in any country and help ... |
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Schlagwörter | COVID-19 ; predictive modeling ; epidemiological modeling ; time delays ; vaccination ; practical identifiability ; Public aspects of medicine ; RA1-1270 |
Thema/Rubrik (Code) | 006 |
Sprache | Englisch |
Erscheinungsdatum | 2023-03-01T00:00:00Z |
Verlag | Frontiers Media S.A. |
Dokumenttyp | Artikel ; Online |
Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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