Optimal Control Applied to Vaccination and Testing Policies for COVID-19
In this paper, several policies for controlling the spread of SARS-CoV-2 are determined under the assumption that a limited number of effective COVID-19 vaccines and tests are available. These policies are calculated for different vaccination scenarios representing vaccine supply and administration...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/23/3100 |
| _version_ | 1797507410958483456 |
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| author | Alberto Olivares Ernesto Staffetti |
| author_facet | Alberto Olivares Ernesto Staffetti |
| author_sort | Alberto Olivares |
| collection | DOAJ |
| description | In this paper, several policies for controlling the spread of SARS-CoV-2 are determined under the assumption that a limited number of effective COVID-19 vaccines and tests are available. These policies are calculated for different vaccination scenarios representing vaccine supply and administration restrictions, plus their impacts on the disease transmission are analyzed. The policies are determined by solving optimal control problems of a compartmental epidemic model, in which the control variables are the vaccination rate and the testing rate for the detection of asymptomatic infected people. A combination of the proportion of threatened and deceased people together with the cost of vaccination of susceptible people, and detection of asymptomatic infected people, is taken as the objective functional to be minimized, whereas different types of algebraic constraints are considered to represent several vaccination scenarios. A direct transcription method is employed to solve these optimal control problems. More specifically, the Hermite–Simpson collocation technique is used. The results of the numerical experiments show that the optimal control approach offers healthcare system managers a helpful resource for designing vaccination programs and testing plans to prevent COVID-19 transmission. |
| first_indexed | 2024-03-10T04:48:06Z |
| format | Article |
| id | doaj.art-2526dbddc4d54562afa7176276516394 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T04:48:06Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-2526dbddc4d54562afa71762765163942023-11-23T02:46:03ZengMDPI AGMathematics2227-73902021-12-01923310010.3390/math9233100Optimal Control Applied to Vaccination and Testing Policies for COVID-19Alberto Olivares0Ernesto Staffetti1Campus de Fuenlabrada, School of Telecommunication Engineering, Universidad Rey Juan Carlos, Camino del Molino 5, 28942 Madrid, SpainCampus de Fuenlabrada, School of Telecommunication Engineering, Universidad Rey Juan Carlos, Camino del Molino 5, 28942 Madrid, SpainIn this paper, several policies for controlling the spread of SARS-CoV-2 are determined under the assumption that a limited number of effective COVID-19 vaccines and tests are available. These policies are calculated for different vaccination scenarios representing vaccine supply and administration restrictions, plus their impacts on the disease transmission are analyzed. The policies are determined by solving optimal control problems of a compartmental epidemic model, in which the control variables are the vaccination rate and the testing rate for the detection of asymptomatic infected people. A combination of the proportion of threatened and deceased people together with the cost of vaccination of susceptible people, and detection of asymptomatic infected people, is taken as the objective functional to be minimized, whereas different types of algebraic constraints are considered to represent several vaccination scenarios. A direct transcription method is employed to solve these optimal control problems. More specifically, the Hermite–Simpson collocation technique is used. The results of the numerical experiments show that the optimal control approach offers healthcare system managers a helpful resource for designing vaccination programs and testing plans to prevent COVID-19 transmission.https://www.mdpi.com/2227-7390/9/23/3100optimal controlvaccination and testing policiesCOVID-19 transmissionepidemic compartmental modelsensitivity analysis |
| spellingShingle | Alberto Olivares Ernesto Staffetti Optimal Control Applied to Vaccination and Testing Policies for COVID-19 Mathematics optimal control vaccination and testing policies COVID-19 transmission epidemic compartmental model sensitivity analysis |
| title | Optimal Control Applied to Vaccination and Testing Policies for COVID-19 |
| title_full | Optimal Control Applied to Vaccination and Testing Policies for COVID-19 |
| title_fullStr | Optimal Control Applied to Vaccination and Testing Policies for COVID-19 |
| title_full_unstemmed | Optimal Control Applied to Vaccination and Testing Policies for COVID-19 |
| title_short | Optimal Control Applied to Vaccination and Testing Policies for COVID-19 |
| title_sort | optimal control applied to vaccination and testing policies for covid 19 |
| topic | optimal control vaccination and testing policies COVID-19 transmission epidemic compartmental model sensitivity analysis |
| url | https://www.mdpi.com/2227-7390/9/23/3100 |
| work_keys_str_mv | AT albertoolivares optimalcontrolappliedtovaccinationandtestingpoliciesforcovid19 AT ernestostaffetti optimalcontrolappliedtovaccinationandtestingpoliciesforcovid19 |