Surveillance of COVID-19 vaccine effectiveness : A real-time case-control study in southern Sweden
(2022) In Epidemiology and Infection 150.- Abstract
The extensive register infrastructure available for coronavirus disease 2019 surveillance in Scania county, Sweden, makes it possible to classify individual cases with respect to hospitalisation and disease severity, stratify on time since last dose and demographic factors, account for prior infection and extract data for population controls automatically. In the present study, we developed a case-control sampling design to surveil vaccine effectiveness (VE) in this ethnically and socioeconomically diverse population with more than 1.3 million inhabitants. The first surveillance results show that estimated VE against hospitalisation and severe disease 0-3 months after the last dose remained stable during the study period, but waned... (More)
The extensive register infrastructure available for coronavirus disease 2019 surveillance in Scania county, Sweden, makes it possible to classify individual cases with respect to hospitalisation and disease severity, stratify on time since last dose and demographic factors, account for prior infection and extract data for population controls automatically. In the present study, we developed a case-control sampling design to surveil vaccine effectiveness (VE) in this ethnically and socioeconomically diverse population with more than 1.3 million inhabitants. The first surveillance results show that estimated VE against hospitalisation and severe disease 0-3 months after the last dose remained stable during the study period, but waned markedly 6 months after the last dose in persons aged 65 years or over.
(Less)
- author
- Björk, Jonas LU ; Bonander, Carl ; Moghaddassi, Mahnaz LU ; Rasmussen, Magnus LU ; Malmqvist, Ulf LU ; Kahn, Fredrik LU and Inghammar, Malin LU
- organization
- publishing date
- 2022-03
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- COVID-19 vaccines, epidemiologic methods, epidemiological monitoring, vaccine effectiveness
- in
- Epidemiology and Infection
- volume
- 150
- article number
- e59
- publisher
- Cambridge University Press
- external identifiers
-
- pmid:35232506
- scopus:85125802346
- ISSN
- 0950-2688
- DOI
- 10.1017/S0950268822000425
- project
- Improved preparedness for future pandemics and other health crises through large-scale disease surveillance
- language
- English
- LU publication?
- yes
- id
- 93fdffee-f1cb-4cd0-8714-e6b1ce826d4b
- date added to LUP
- 2022-04-26 11:27:05
- date last changed
- 2024-09-19 21:19:12
@article{93fdffee-f1cb-4cd0-8714-e6b1ce826d4b, abstract = {{<p>The extensive register infrastructure available for coronavirus disease 2019 surveillance in Scania county, Sweden, makes it possible to classify individual cases with respect to hospitalisation and disease severity, stratify on time since last dose and demographic factors, account for prior infection and extract data for population controls automatically. In the present study, we developed a case-control sampling design to surveil vaccine effectiveness (VE) in this ethnically and socioeconomically diverse population with more than 1.3 million inhabitants. The first surveillance results show that estimated VE against hospitalisation and severe disease 0-3 months after the last dose remained stable during the study period, but waned markedly 6 months after the last dose in persons aged 65 years or over. </p>}}, author = {{Björk, Jonas and Bonander, Carl and Moghaddassi, Mahnaz and Rasmussen, Magnus and Malmqvist, Ulf and Kahn, Fredrik and Inghammar, Malin}}, issn = {{0950-2688}}, keywords = {{COVID-19 vaccines; epidemiologic methods; epidemiological monitoring; vaccine effectiveness}}, language = {{eng}}, publisher = {{Cambridge University Press}}, series = {{Epidemiology and Infection}}, title = {{Surveillance of COVID-19 vaccine effectiveness : A real-time case-control study in southern Sweden}}, url = {{http://dx.doi.org/10.1017/S0950268822000425}}, doi = {{10.1017/S0950268822000425}}, volume = {{150}}, year = {{2022}}, }