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Surveillance of COVID-19 vaccine effectiveness : A real-time case-control study in southern Sweden

Björk, Jonas LU ; Bonander, Carl ; Moghaddassi, Mahnaz LU ; Rasmussen, Magnus LU ; Malmqvist, Ulf LU ; Kahn, Fredrik LU and Inghammar, Malin LU (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.

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author
; ; ; ; ; and
organization
publishing date
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
  • scopus:85125802346
  • pmid:35232506
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
2024-06-13 12:07:28
@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}},
}