Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA
<jats:p> In the wake of the rapid surge in the COVID-19-infected cases seen in Southern and West-Central USA in the period of June-July 2020, there is an urgent need to develop robust, data-driven models to quantify the effect which early reopening had on the infected case count i...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2023
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| Online Access: | https://hdl.handle.net/1721.1/150781 |
| _version_ | 1811094835219660800 |
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| author | Dandekar, Raj Wang, Emma Barbastathis, George Rackauckas, Chris |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Dandekar, Raj Wang, Emma Barbastathis, George Rackauckas, Chris |
| author_sort | Dandekar, Raj |
| collection | MIT |
| description | <jats:p>
In the wake of the rapid surge in the COVID-19-infected cases seen in Southern and West-Central USA in the period of June-July 2020, there is an urgent need to develop robust, data-driven models to quantify the effect which early reopening had on the infected case count increase. In particular, it is imperative to address the question: How many infected cases could have been prevented, had the worst affected states not reopened early? To address this question, we have developed a novel COVID-19 model by augmenting the classical SIR epidemiological model with a neural network module. The model decomposes the contribution of quarantine strength to the infection time series, allowing us to quantify the role of quarantine control and the associated reopening policies in the US states which showed a major surge in infections. We show that the upsurge in the infected cases seen in these states is strongly corelated with a drop in the quarantine/lockdown strength diagnosed by our model. Further, our results demonstrate that in the event of a stricter lockdown without early reopening, the number of active infected cases recorded on 14 July could have been reduced by more than
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<mml:mn>40</mml:mn>
<mml:mi>%</mml:mi>
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in all states considered, with the actual number of infections reduced being more than
<jats:inline-formula>
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll">
<mml:mn>100,000</mml:mn>
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for the states of Florida and Texas. As we continue our fight against COVID-19, our proposed model can be used as a valuable asset to simulate the effect of several reopening strategies on the infected count evolution, for any region under consideration.
</jats:p> |
| first_indexed | 2024-09-23T16:06:15Z |
| format | Article |
| id | mit-1721.1/150781 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:06:15Z |
| publishDate | 2023 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | dspace |
| spelling | mit-1721.1/1507812023-05-20T03:03:23Z Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA Dandekar, Raj Wang, Emma Barbastathis, George Rackauckas, Chris Massachusetts Institute of Technology. Department of Mechanical Engineering <jats:p> In the wake of the rapid surge in the COVID-19-infected cases seen in Southern and West-Central USA in the period of June-July 2020, there is an urgent need to develop robust, data-driven models to quantify the effect which early reopening had on the infected case count increase. In particular, it is imperative to address the question: How many infected cases could have been prevented, had the worst affected states not reopened early? To address this question, we have developed a novel COVID-19 model by augmenting the classical SIR epidemiological model with a neural network module. The model decomposes the contribution of quarantine strength to the infection time series, allowing us to quantify the role of quarantine control and the associated reopening policies in the US states which showed a major surge in infections. We show that the upsurge in the infected cases seen in these states is strongly corelated with a drop in the quarantine/lockdown strength diagnosed by our model. Further, our results demonstrate that in the event of a stricter lockdown without early reopening, the number of active infected cases recorded on 14 July could have been reduced by more than <jats:inline-formula> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>40</mml:mn> <mml:mi>%</mml:mi> </mml:math> </jats:inline-formula> in all states considered, with the actual number of infections reduced being more than <jats:inline-formula> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>100,000</mml:mn> </mml:math> </jats:inline-formula> for the states of Florida and Texas. As we continue our fight against COVID-19, our proposed model can be used as a valuable asset to simulate the effect of several reopening strategies on the infected count evolution, for any region under consideration. </jats:p> 2023-05-19T14:00:58Z 2023-05-19T14:00:58Z 2021 2023-05-19T13:58:47Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/150781 Dandekar, Raj, Wang, Emma, Barbastathis, George and Rackauckas, Chris. 2021. "Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA." Health Data Science, 2021. en 10.34133/2021/9798302 Health Data Science Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf American Association for the Advancement of Science (AAAS) AAAS |
| spellingShingle | Dandekar, Raj Wang, Emma Barbastathis, George Rackauckas, Chris Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA |
| title | Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA |
| title_full | Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA |
| title_fullStr | Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA |
| title_full_unstemmed | Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA |
| title_short | Implications of Delayed Reopening in Controlling the COVID-19 Surge in Southern and West-Central USA |
| title_sort | implications of delayed reopening in controlling the covid 19 surge in southern and west central usa |
| url | https://hdl.handle.net/1721.1/150781 |
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