Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter.
We develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2021-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0244474 |
| _version_ | 1818737478544130048 |
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| author | Francisco Arroyo-Marioli Francisco Bullano Simas Kucinskas Carlos Rondón-Moreno |
| author_facet | Francisco Arroyo-Marioli Francisco Bullano Simas Kucinskas Carlos Rondón-Moreno |
| author_sort | Francisco Arroyo-Marioli |
| collection | DOAJ |
| description | We develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Formula: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries. |
| first_indexed | 2024-12-18T00:53:41Z |
| format | Article |
| id | doaj.art-7e70c19d888244659b685f032fb2b1c2 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-18T00:53:41Z |
| publishDate | 2021-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-7e70c19d888244659b685f032fb2b1c22022-12-21T21:26:34ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01161e024447410.1371/journal.pone.0244474Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter.Francisco Arroyo-MarioliFrancisco BullanoSimas KucinskasCarlos Rondón-MorenoWe develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Formula: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.https://doi.org/10.1371/journal.pone.0244474 |
| spellingShingle | Francisco Arroyo-Marioli Francisco Bullano Simas Kucinskas Carlos Rondón-Moreno Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. PLoS ONE |
| title | Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. |
| title_full | Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. |
| title_fullStr | Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. |
| title_full_unstemmed | Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. |
| title_short | Tracking [Formula: see text] of COVID-19: A new real-time estimation using the Kalman filter. |
| title_sort | tracking formula see text of covid 19 a new real time estimation using the kalman filter |
| url | https://doi.org/10.1371/journal.pone.0244474 |
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