Publication: COVID-19 epidemic in Spain in the first wave: Estimation of the epidemic curve inferred from seroprevalence data and simulation of scenarios based on SEIR model
| dc.contributor.author | Prado-Galbarro, Francisco Javier | |
| dc.contributor.author | Cruz-Cruz, Copytzy | |
| dc.contributor.author | Gamiño-Arroyo, Ana Estela | |
| dc.contributor.author | Sanchez-Piedra, Carlos | |
| dc.date.accessioned | 2023-04-12T09:00:46Z | |
| dc.date.available | 2023-04-12T09:00:46Z | |
| dc.date.issued | 2022-06 | |
| dc.description.abstract | The COVID-19 pandemic represents one of the most severe challenges in the recent history of public health. The aim of this study is to estimate the transmission rate parameter (β) and to predict the epidemic progression in Spain. We integrated data from Our World in Data. Our model considered a mean time from in fection to death to be 24 days and the results of the seroprevalence survey in Spain. We calculated β using a SEIR model estimated by least squares. We also used a SEIR model to evaluate four scenarios: 1) model 1: no containment measures, 2) model 2: containment measures from the beginning of the epidemic, 3) model 3: mild measures since the 20th day, 4) model 4: strict containment measures since the 20th day. The estimated β parameter was 1.087. We calculated 41,210,330 infected people and 725,302 deaths in model 1; 165,036 infected people and 2,905 deaths in model 2; 4,640,400 infected people and 81,671 deaths in model 3; and, 62.012 infected people and 1,091 deaths in model 4. Peak of the epidemic varied from 69th day in model 1 to 216th day in model 4. Containment measures prevented a scenario with a signifi cant increase in deaths and infected people. Our fi ndings showed that, by stricter interven tions such as quarantine and isolation could lead to reduce the potential peak number of COVID-19 cases and delay the time of peak infection. | es_ES |
| dc.description.peerreviewed | Sí | es_ES |
| dc.format.number | 2 | es_ES |
| dc.format.page | 59-72 | es_ES |
| dc.identifier.citation | Romanian Statistical Review. 2022;2:59-72. | es_ES |
| dc.identifier.e-issn | 1844-7694 | es_ES |
| dc.identifier.issn | 1018-046X | es_ES |
| dc.identifier.journal | Romanian Statistical Review | es_ES |
| dc.identifier.uri | http://hdl.handle.net/20.500.12105/15775 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | National Institute of Statistics (Rumania) | es_ES |
| dc.relation.publisherversion | https://www.revistadestatistica.ro/wp-content/uploads/2022/06/05_RRS_2_2022.pdf | es_ES |
| dc.repisalud.centro | ISCIII::Agencia de Evaluación de Tecnologías Sanitarias | es_ES |
| dc.repisalud.institucion | ISCIII | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.rights.license | Atribución 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Public health | es_ES |
| dc.subject | COVID-19 | es_ES |
| dc.subject | Epidemiology | es_ES |
| dc.subject | Health policy | es_ES |
| dc.title | COVID-19 epidemic in Spain in the first wave: Estimation of the epidemic curve inferred from seroprevalence data and simulation of scenarios based on SEIR model | es_ES |
| dc.type | research article | es_ES |
| dc.type.hasVersion | VoR | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | ae804cbd-0d7c-4887-b50b-965b0da079e0 | |
| relation.isAuthorOfPublication | ce5eab34-c59b-49bd-9177-b83f0c99cfdb | |
| relation.isAuthorOfPublication | e7f8497a-6626-4d87-ac50-d664e12f29e6 | |
| relation.isAuthorOfPublication.latestForDiscovery | ce5eab34-c59b-49bd-9177-b83f0c99cfdb |
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