Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages
COVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematic...
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-03-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2023452?viewType=HTML?viewType=HTML |
| _version_ | 1797842329024856064 |
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| author | Stefanie Fuderer Christina Kuttler Michael Hoelscher Ludwig Christian Hinske Noemi Castelletti |
| author_facet | Stefanie Fuderer Christina Kuttler Michael Hoelscher Ludwig Christian Hinske Noemi Castelletti |
| author_sort | Stefanie Fuderer |
| collection | DOAJ |
| description | COVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematical model of SEIR type that incorporates both non-pharmaceutical interventions and vaccinations. We analyzed incidence and hospitalization data from Munich hospitals and used a two-step approach to fit the model parameters: first, we modeled incidence without hospitalization, and then we extended the model to include hospitalization compartments using the previous estimates as a starting point. For the first two waves, changes in key parameters, such as contact reduction and increasing vaccinations, were enough to represent the data. For wave three, the introduction of vaccination compartments was essential. In wave four, reducing contacts and increasing vaccinations were critical parameters for controlling infections. The importance of hospitalization data was highlighted, as it should have been included as a crucial parameter from the outset, along with incidence, to avoid miscommunication with the public. The emergence of milder variants like Omicron and a significant proportion of vaccinated people has made this fact even more evident. |
| first_indexed | 2024-04-09T16:46:07Z |
| format | Article |
| id | doaj.art-b19e2514b5104fcf8d39b87b28e57951 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-04-09T16:46:07Z |
| publishDate | 2023-03-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-b19e2514b5104fcf8d39b87b28e579512023-04-23T01:20:49ZengAIMS PressMathematical Biosciences and Engineering1551-00182023-03-01206103041033810.3934/mbe.2023452Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stagesStefanie Fuderer 0Christina Kuttler1Michael Hoelscher2Ludwig Christian Hinske3Noemi Castelletti41. Department of Mathematics, Technical University of Munich, Garching, Germany1. Department of Mathematics, Technical University of Munich, Garching, Germany2. Division of Infectious Diseases and Tropical Medicine, Medical Center of the University of Munich, Munich, Germany 3. German Center for Infection Research (DZIF), partner site Munich, Munich, Germany 4. Center for International Health (CIH), University Hospital, Munich, Germany5. Department of Anesthesiology, University Hospital, Munich, Germany2. Division of Infectious Diseases and Tropical Medicine, Medical Center of the University of Munich, Munich, Germany6. Institute of Radiation Medicine, Helmholtz Zentrum München, Neuherberg, GermanyCOVID-19 has been spreading widely since January 2020, prompting the implementation of non-pharmaceutical interventions and vaccinations to prevent overwhelming the healthcare system. Our study models four waves of the epidemic in Munich over two years using a deterministic, biology-based mathematical model of SEIR type that incorporates both non-pharmaceutical interventions and vaccinations. We analyzed incidence and hospitalization data from Munich hospitals and used a two-step approach to fit the model parameters: first, we modeled incidence without hospitalization, and then we extended the model to include hospitalization compartments using the previous estimates as a starting point. For the first two waves, changes in key parameters, such as contact reduction and increasing vaccinations, were enough to represent the data. For wave three, the introduction of vaccination compartments was essential. In wave four, reducing contacts and increasing vaccinations were critical parameters for controlling infections. The importance of hospitalization data was highlighted, as it should have been included as a crucial parameter from the outset, along with incidence, to avoid miscommunication with the public. The emergence of milder variants like Omicron and a significant proportion of vaccinated people has made this fact even more evident.https://www.aimspress.com/article/doi/10.3934/mbe.2023452?viewType=HTML?viewType=HTMLsars-cov-2modelingdifferential equationhospitalizationpredictiondata analysis |
| spellingShingle | Stefanie Fuderer Christina Kuttler Michael Hoelscher Ludwig Christian Hinske Noemi Castelletti Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages Mathematical Biosciences and Engineering sars-cov-2 modeling differential equation hospitalization prediction data analysis |
| title | Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages |
| title_full | Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages |
| title_fullStr | Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages |
| title_full_unstemmed | Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages |
| title_short | Data suggested hospitalization as critical indicator of the severity of the COVID-19 pandemic, even at its early stages |
| title_sort | data suggested hospitalization as critical indicator of the severity of the covid 19 pandemic even at its early stages |
| topic | sars-cov-2 modeling differential equation hospitalization prediction data analysis |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2023452?viewType=HTML?viewType=HTML |
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