Estimating the population effectiveness of interventions against COVID-19 in France: A modelling study
| dc.rights.license | open | en_US |
| hal.structure.identifier | Statistics In System biology and Translational Medicine [SISTM] | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | GANSER, Iris | |
| dc.contributor.author | BUCKERIDGE, David L | |
| dc.contributor.author | HEFFERNAN, Jane | |
| hal.structure.identifier | Statistics In System biology and Translational Medicine [SISTM] | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | PRAGUE, Melanie | |
| hal.structure.identifier | Statistics In System biology and Translational Medicine [SISTM] | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | THIEBAUT, Rodolphe | |
| dc.date.accessioned | 2024-03-15T09:15:07Z | |
| dc.date.available | 2024-03-15T09:15:07Z | |
| dc.date.issued | 2024-03-01 | |
| dc.identifier.issn | 1878-0067 (Electronic) 1878-0067 (Linking) | en_US |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/188807 | |
| dc.description.abstractEn | BACKGROUND: Non-pharmaceutical interventions (NPIs) and vaccines have been widely used to manage the COVID-19 pandemic. However, uncertainty persists regarding the effectiveness of these interventions due to data quality issues, methodological challenges, and differing contextual factors. Accurate estimation of their effects is crucial for future epidemic preparedness. METHODS: To address this, we developed a population-based mechanistic model that includes the impact of NPIs and vaccines on SARS-CoV-2 transmission and hospitalization rates. Our statistical approach estimated all parameters in one step, accurately propagating uncertainty. We fitted the model to comprehensive epidemiological data in France from March 2020 to October 2021. With the same model, we simulated scenarios of vaccine rollout. RESULTS: The first lockdown was the most effective, reducing transmission by 84 % (95 % confidence interval (CI) 83-85). Subsequent lockdowns had diminished effectiveness (reduction of 74 % (69-77) and 11 % (9-18), respectively). A 6 pm curfew was more effective than one at 8 pm (68 % (66-69) vs. 48 % (45-49) reduction), while school closures reduced transmission by 15 % (12-18). In a scenario without vaccines before November 2021, we predicted 159,000 or 168 % (95 % prediction interval (PI) 70-315) more deaths and 1,488,000 or 300 % (133-492) more hospitalizations. If a vaccine had been available after 100 days, over 71,000 deaths (16,507-204,249) and 384,000 (88,579-1,020,386) hospitalizations could have been averted. CONCLUSION: Our results highlight the substantial impact of NPIs, including lockdowns and curfews, in controlling the COVID-19 pandemic. We also demonstrate the value of the 100 days objective of the Coalition for Epidemic Preparedness Innovations (CEPI) initiative for vaccine availability. | |
| dc.description.sponsorship | Initiative for the creation of a Vaccine Research Institute - ANR-10-LABX-0077 | en_US |
| dc.language.iso | EN | en_US |
| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
| dc.subject.en | COVID-19 | |
| dc.subject.en | Dynamics | |
| dc.subject.en | Epidemics | |
| dc.subject.en | Mathematical model | |
| dc.subject.en | Non-pharmaceutical interventions | |
| dc.subject.en | SARS-CoV2 | |
| dc.subject.en | Vaccines | |
| dc.title.en | Estimating the population effectiveness of interventions against COVID-19 in France: A modelling study | |
| dc.title.alternative | Epidemics | en_US |
| dc.type | Article de revue | en_US |
| dc.identifier.doi | 10.1016/j.epidem.2024.100744 | en_US |
| dc.subject.hal | Sciences du Vivant [q-bio]/Santé publique et épidémiologie | en_US |
| dc.identifier.pubmed | 38324970 | en_US |
| bordeaux.journal | Epidemics | en_US |
| bordeaux.page | 100744 | en_US |
| bordeaux.volume | 46 | en_US |
| bordeaux.hal.laboratories | Bordeaux Population Health Research Center (BPH) - UMR 1219 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | INSERM | en_US |
| bordeaux.institution | INRIA | en_US |
| bordeaux.team | SISTM_BPH | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| hal.identifier | hal-04505758 | |
| hal.version | 1 | |
| hal.date.transferred | 2024-03-15T09:15:11Z | |
| hal.popular | non | en_US |
| hal.audience | Internationale | en_US |
| hal.export | true | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Epidemics&rft.date=2024-03-01&rft.volume=46&rft.spage=100744&rft.epage=100744&rft.eissn=1878-0067%20(Electronic)%201878-0067%20(Linking)&rft.issn=1878-0067%20(Electronic)%201878-0067%20(Linking)&rft.au=GANSER,%20Iris&BUCKERIDGE,%20David%20L&HEFFERNAN,%20Jane&PRAGUE,%20Melanie&THIEBAUT,%20Rodolphe&rft.genre=article |
