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 in | European journal of epidemiology Vol. 21; no. 3; pp. 181 - 189 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Dordrecht
Springer
01.03.2006
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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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. |
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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 (<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 10.1016/S0033-3506(97)00044-9 10.1017/S0950268898001939 10.1080/03610929708831995 10.1111/j.1467-985X.2004.apm10.x 10.2105/AJPH.80.9.1080 10.3201/eid0303.970322 10.3201/eid0812.010514 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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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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