GrippeBelgiqueV4, Main, Exploration, bibRecord, 000071

Monitoring of all-cause mortality in Belgium (Be-MOMO): a new and automated system for the early detection and quantification of the mortality impact of public health events.

Identifieur interne : 000071 ( Main/Exploration ); précédent : 000070; suivant : 000072

Monitoring of all-cause mortality in Belgium (Be-MOMO): a new and automated system for the early detection and quantification of the mortality impact of public health events.

Auteurs : Bianca Cox [Belgique] ; Françoise Wuillaume ; Herman Van Oyen ; Sophie Maes

Source :

International journal of public health [ 1661-8564 ] ; 2010.

RBID : pubmed:20376690

Descripteurs français

KwdFr :
- Adulte d'âge moyen, Belgique (épidémiologie), Climat, Facteurs de risque, Femelle, Flambées de maladies, Grippe humaine (mortalité), Grippe humaine (épidémiologie), Humains, Mortalité (tendances), Mâle, Pollution de l'air (), Répartition par âge, Sujet âgé, Sujet âgé de 80 ans ou plus, Surveillance sentinelle, Température.
MESH :
- mortalité : Grippe humaine.
- tendances : Mortalité.
- épidémiologie : Belgique, Grippe humaine.
- Adulte d'âge moyen, Climat, Facteurs de risque, Femelle, Flambées de maladies, Humains, Mâle, Pollution de l'air, Répartition par âge, Sujet âgé, Sujet âgé de 80 ans ou plus, Surveillance sentinelle, Température.
Wicri :
- geographic : Belgique.

English descriptors

KwdEn :
- Age Distribution, Aged, Aged, 80 and over, Air Pollution (statistics & numerical data), Belgium (epidemiology), Climate, Disease Outbreaks, Female, Humans, Influenza, Human (epidemiology), Influenza, Human (mortality), Male, Middle Aged, Mortality (trends), Risk Factors, Sentinel Surveillance, Temperature.
MESH :
- geographic , epidemiology : Belgium.
- epidemiology : Influenza, Human.
- mortality : Influenza, Human.
- statistics & numerical data : Air Pollution.
- trends : Mortality.
- Age Distribution, Aged, Aged, 80 and over, Climate, Disease Outbreaks, Female, Humans, Male, Middle Aged, Risk Factors, Sentinel Surveillance, Temperature.

Abstract

OBJECTIVES

Be-MOMO is the monitoring of all-cause death registry data in Belgium. The new methods are described and the detection and quantification of outbreaks is presented for the period April 2006-March 2007. Sensitivity, specificity and timeliness are illustrated by means of a temporal comparison with known health events.

METHODS

Relevant events are identified from important mortality risks: climate, air pollution and influenza. Baselines and thresholds for deaths by gender, age group, day and week are estimated by the method of Farrington et al. (J R Stat Soc Ser A, 159:547-563, 1996). By adding seasonal terms to the basic model, a complete 5-year reference period can be used, while a reduction of noise allows the application to daily counts.

RESULTS

Ignoring two false positives, all flags could be classified into five distinct outbreaks, coinciding with four heat periods and an influenza epidemic. Negative deviations from expected mortality in autumn and winter might reflect a displacement of mortality by the heat waves. Still, significant positive excess was found during five influenza weeks. Correcting for the delay in registration of deaths, outbreaks could be detected as soon as 1-2 weeks after the event.

CONCLUSION

The sensitivity of Be-MOMO to different health threats suggests its potential usefulness in early warning: mortality thresholds and baselines might serve as rapid tools for detecting and quantifying outbreaks, crucial for public health decision-making and evaluation of measures.

DOI: 10.1007/s00038-010-0135-6
PubMed: 20376690

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<term>Femelle</term>
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<term>Grippe humaine (mortalité)</term>
<term>Grippe humaine (épidémiologie)</term>
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<term>Facteurs de risque</term>
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<term>Flambées de maladies</term>
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<p>Be-MOMO is the monitoring of all-cause death registry data in Belgium. The new methods are described and the detection and quantification of outbreaks is presented for the period April 2006-March 2007. Sensitivity, specificity and timeliness are illustrated by means of a temporal comparison with known health events.</p>
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<p>Relevant events are identified from important mortality risks: climate, air pollution and influenza. Baselines and thresholds for deaths by gender, age group, day and week are estimated by the method of Farrington et al. (J R Stat Soc Ser A, 159:547-563, 1996). By adding seasonal terms to the basic model, a complete 5-year reference period can be used, while a reduction of noise allows the application to daily counts.</p>
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<p>Ignoring two false positives, all flags could be classified into five distinct outbreaks, coinciding with four heat periods and an influenza epidemic. Negative deviations from expected mortality in autumn and winter might reflect a displacement of mortality by the heat waves. Still, significant positive excess was found during five influenza weeks. Correcting for the delay in registration of deaths, outbreaks could be detected as soon as 1-2 weeks after the event.</p>
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<p>The sensitivity of Be-MOMO to different health threats suggests its potential usefulness in early warning: mortality thresholds and baselines might serve as rapid tools for detecting and quantifying outbreaks, crucial for public health decision-making and evaluation of measures.</p>
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	Attention, ce site est en cours de développement ! Attention, site généré par des moyens informatiques à partir de corpus bruts. Les informations ne sont donc pas validées.

Corpus GrippeBelgiqueV4

Monitoring of all-cause mortality in Belgium (Be-MOMO): a new and automated system for the early detection and quantification of the mortality impact of public health events.

Monitoring of all-cause mortality in Belgium (Be-MOMO): a new and automated system for the early detection and quantification of the mortality impact of public health events.

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