Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic
We fit an SARS-CoV-2 model to US data of COVID-19 cases and deaths. We conclude that the model is not structurally identifiable. We make the model identifiable by prefixing some of the parameters from external information. Practical identifiability of the model through Monte Carlo simulations reveals that two of the parameters may not be practically identifiable. With thus identified parameters, we set up an optimal control problem with social distancing and isolation as control variables. We investigate two scenarios: the controls are applied for the entire duration and the controls are applied only for the period of time. Our results show that if the controls are applied early in the epidemic, the reduction in the infected classes is at least an order of magnitude higher compared to when controls are applied with 2-week delay. Further, removing the controls before the pandemic ends leads to rebound of the infected classes..
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:16 |
|---|---|
| Enthalten in: |
Journal of Biological Dynamics - 16(2022), 1, Seite 412-438 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Necibe Tuncer [VerfasserIn] |
|---|
| Links: |
doi.org [kostenfrei] |
|---|
| doi: |
10.1080/17513758.2022.2078899 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
DOAJ022211675 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | DOAJ022211675 | ||
| 003 | DE-627 | ||
| 005 | 20230307054229.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 230226s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1080/17513758.2022.2078899 |2 doi | |
| 035 | |a (DE-627)DOAJ022211675 | ||
| 035 | |a (DE-599)DOAJ3f6701af34d44a30bee2b5d9a8c2a985 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 050 | 0 | |a GE1-350 | |
| 050 | 0 | |a QH301-705.5 | |
| 100 | 0 | |a Necibe Tuncer |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Parameter identifiability and optimal control of an SARS-CoV-2 model early in the pandemic |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a Computermedien |b c |2 rdamedia | ||
| 338 | |a Online-Ressource |b cr |2 rdacarrier | ||
| 520 | |a We fit an SARS-CoV-2 model to US data of COVID-19 cases and deaths. We conclude that the model is not structurally identifiable. We make the model identifiable by prefixing some of the parameters from external information. Practical identifiability of the model through Monte Carlo simulations reveals that two of the parameters may not be practically identifiable. With thus identified parameters, we set up an optimal control problem with social distancing and isolation as control variables. We investigate two scenarios: the controls are applied for the entire duration and the controls are applied only for the period of time. Our results show that if the controls are applied early in the epidemic, the reduction in the infected classes is at least an order of magnitude higher compared to when controls are applied with 2-week delay. Further, removing the controls before the pandemic ends leads to rebound of the infected classes. | ||
| 650 | 4 | |a Practical and structural identifiability | |
| 650 | 4 | |a Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) | |
| 650 | 4 | |a Coronavirus disease 2019 (COVID-19) | |
| 650 | 4 | |a outbreak | |
| 650 | 4 | |a epidemic model | |
| 650 | 4 | |a mass-action incidence | |
| 653 | 0 | |a Environmental sciences | |
| 653 | 0 | |a Biology (General) | |
| 700 | 0 | |a Archana Timsina |e verfasserin |4 aut | |
| 700 | 0 | |a Miriam Nuno |e verfasserin |4 aut | |
| 700 | 0 | |a Gerardo Chowell |e verfasserin |4 aut | |
| 700 | 0 | |a Maia Martcheva |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i In |t Journal of Biological Dynamics |d Taylor & Francis Group, 2016 |g 16(2022), 1, Seite 412-438 |w (DE-627)DOAJ000061980 |x 17513766 |7 nnns |
| 773 | 1 | 8 | |g volume:16 |g year:2022 |g number:1 |g pages:412-438 |
| 856 | 4 | 0 | |u https://doi.org/10.1080/17513758.2022.2078899 |z kostenfrei |
| 856 | 4 | 0 | |u https://doaj.org/article/3f6701af34d44a30bee2b5d9a8c2a985 |z kostenfrei |
| 856 | 4 | 0 | |u https://www.tandfonline.com/doi/10.1080/17513758.2022.2078899 |z kostenfrei |
| 856 | 4 | 2 | |u https://doaj.org/toc/1751-3758 |y Journal toc |z kostenfrei |
| 856 | 4 | 2 | |u https://doaj.org/toc/1751-3766 |y Journal toc |z kostenfrei |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_DOAJ | ||
| 951 | |a AR | ||
| 952 | |d 16 |j 2022 |e 1 |h 412-438 | ||