Description of a New All Cause Mortality Surveillance System in Sweden as a Warning System Using Threshold Detection Algorithms

A warning system has been set up to detect unusual weekly clusters of deaths by age group and municipality using all-cause Swedish death registry data. The technique for monitoring deaths by age group (<1, 1-24, 25-44, 45-64 and 65 plus) and week uses a compound smoothing technique, which calcula...

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Published inEuropean journal of epidemiology Vol. 21; no. 3; pp. 181 - 189
Main Authors Sartorius, B., Jacobsen, H., Törner, A., Giesecke, J.
Format Journal Article
LanguageEnglish
Published Dordrecht Springer 01.03.2006
Springer Nature B.V
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Abstract A warning system has been set up to detect unusual weekly clusters of deaths by age group and municipality using all-cause Swedish death registry data. The technique for monitoring deaths by age group (<1, 1-24, 25-44, 45-64 and 65 plus) and week uses a compound smoothing technique, which calculates a baseline of expected events from retrospective data. Due to insufficient baseline data for the geographical component of the system a different algorithm, based on the Poisson distribution, was chosen to calculate expected weekly number of deaths per municipality, adjusting for municipalities with inherently higher mortality rates. This system was designed and tested during 2004 and implemented from the beginning of 2005. Threshold settings have been adjusted to provide a realistic number of weekly alerts. An evaluation of the system will be performed prospectively from the beginning of 2005 due to the lack of a gold standard for retrospective performance evaluation.
AbstractList A warning system has been set up to detect unusual weekly clusters of deaths by age group and municipality using all-cause Swedish death registry data. The technique for monitoring deaths by age group (&lt;1, 1-24, 25-44, 45-64 and 65 plus) and week uses a compound smoothing technique, which calculates a baseline of expected events from retrospective data. Due to insufficient baseline data for the geographical component of the system a different algorithm, based on the Poisson distribution, was chosen to calculate expected weekly number of deaths per municipality, adjusting for municipalities with inherently higher mortality rates. This system was designed and tested during 2004 and implemented from the beginning of 2005. Threshold settings have been adjusted to provide a realistic number of weekly alerts. An evaluation of the system will be performed prospectively from the beginning of 2005 due to the lack of a gold standard for retrospective performance evaluation.
A warning system has been set up to detect unusual weekly clusters of deaths by age group and municipality using all-cause Swedish death registry data. The technique for monitoring deaths by age group (<1, 1-24, 25-44, 45-64 and 65 plus) and week uses a compound smoothing technique, which calculates a baseline of expected events from retrospective data. Due to insufficient baseline data for the geographical component of the system a different algorithm, based on the Poisson distribution, was chosen to calculate expected weekly number of deaths per municipality, adjusting for municipalities with inherently higher mortality rates. This system was designed and tested during 2004 and implemented from the beginning of 2005. Threshold settings have been adjusted to provide a realistic number of weekly alerts. An evaluation of the system will be performed prospectively from the beginning of 2005 due to the lack of a gold standard for retrospective performance evaluation. [PUBLICATION ABSTRACT]
A warning system has been set up to detect unusual weekly clusters of deaths by age group and municipality using all-cause Swedish death registry data. The technique for monitoring deaths by age group (<1, 1-24, 25-44, 45-64 and 65 plus) and week uses a compound smoothing technique, which calculates a baseline of expected events from retrospective data. Due to insufficient baseline data for the geographical component of the system a different algorithm, based on the Poisson distribution, was chosen to calculate expected weekly number of deaths per municipality, adjusting for municipalities with inherently higher mortality rates. This system was designed and tested during 2004 and implemented from the beginning of 2005. Threshold settings have been adjusted to provide a realistic number of weekly alerts. An evaluation of the system will be performed prospectively from the beginning of 2005 due to the lack of a gold standard for retrospective performance evaluation.
Author Giesecke, J.
Sartorius, B.
Jacobsen, H.
Törner, A.
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Cites_doi 10.1186/1472-6947-5-19
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10.1097/00001648-199707000-00007
10.2307/2983331
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Keywords Human
Warning
Threshold detection
Mortality
Algorithm
Decision tree
Epidemiology
Warning signal
Warning threshold
All-cause mortality surveillance
Surveillance
Cause
Detection threshold
Death
Detection algorithms
Public health
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Snippet A warning system has been set up to detect unusual weekly clusters of deaths by age group and municipality using all-cause Swedish death registry data. The...
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StartPage 181
SubjectTerms Adolescent
Age Distribution
Age groups
Aged
Aged, 80 and over
Algorithms
Biological and medical sciences
Cause of Death
Child
Child, Preschool
Cluster Analysis
Death
Disease outbreaks
Disease Outbreaks - statistics & numerical data
Epidemiology
Fatalities
Female
Geographic Information Systems
Geography - statistics & numerical data
Humans
Infant
Infant, Newborn
Infectious diseases
Male
Medical sciences
Medicin och hälsovetenskap
Middle Aged
Miscellaneous
Monitoring systems
Mortality
Mortality - trends
Poisson Distribution
Population Surveillance - methods
Public Health Informatics
Public health. Hygiene
Public health. Hygiene-occupational medicine
Registries
Standard deviation
Statistical median
Statistics
Surveillance
Sweden - epidemiology
Title Description of a New All Cause Mortality Surveillance System in Sweden as a Warning System Using Threshold Detection Algorithms
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Volume 21
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