Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: A dynamic intensity model
| dc.contributor.author | Boldea, O. | |
| dc.contributor.author | Cornea-Madeira, A. | |
| dc.contributor.author | Madeira, J. | |
| dc.date.accessioned | 2023-12-15T15:37:53Z | |
| dc.date.available | 2023-12-15T15:37:53Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2023-12-15T15:38:24Z | |
| dc.description.abstract | In this paper, we estimate the path of daily SARS-CoV-2 infections in England from the beginning of the pandemic until the end of 2021. We employ a dynamic intensity model, where the mean intensity conditional on the past depends both on past intensity of infections and past realized infections. The model parameters are time-varying, and we employ a multiplicative specification along with logistic transition functions to disentangle the time-varying effects of nonpharmaceutical policy interventions, of different variants, and of protection (waning) of vaccines/boosters. Our model results indicate that earlier interventions and vaccinations are key to containing an infection wave. We consider several scenarios that account for more infectious variants and different protection levels of vaccines/boosters. These scenarios suggest that, as vaccine protection wanes, containing a new wave in infections and an associated increase in hospitalizations in the near future may require further booster campaigns and/or nonpharmaceutical interventions. | eng |
| dc.description.version | info:eu-repo/semantics/publishedVersion | |
| dc.identifier.citation | Boldea, O., Cornea-Madeira, A., & Madeira, J. (2023). Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: A dynamic intensity model. Econometrics Journal, 26(3), 444-466. https://dx.doi.org/10.1093/ectj/utad004 | |
| dc.identifier.doi | 10.1093/ectj/utad004 | |
| dc.identifier.issn | 1368-4221 | |
| dc.identifier.uri | http://hdl.handle.net/10071/30012 | |
| dc.language.iso | eng | |
| dc.number | 3 | |
| dc.pagination | 444 - 466 | |
| dc.peerreviewed | yes | |
| dc.publisher | Oxford University Press | |
| dc.rights | open access | |
| dc.subject | COVID-19 | eng |
| dc.subject | Bayesian Hamiltonian Monte Carlo | eng |
| dc.subject | NPI | eng |
| dc.subject | Vaccines | eng |
| dc.subject | Booster | eng |
| dc.subject | Variants of concern | eng |
| dc.subject | Omicron | eng |
| dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Matemáticas | por |
| dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Economia e Gestão | por |
| dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Sociologia | por |
| dc.title | Disentangling the effect of measures, variants, and vaccines on SARS-CoV-2 infections in England: A dynamic intensity model | eng |
| dc.type | article | |
| dc.volume | 26 | |
| dspace.entity.type | Publication | en |
| iscte.alternateIdentifiers.wos | WOS:WOS:000935814600001 | |
| iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-96161 | |
| iscte.journal | Econometrics Journal | |
| iscte.subject.ods | Saúde de qualidade | por |
| iscte.subject.ods | Trabalho digno e crescimento económico | por |
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