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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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  • Bianca Cox
  • Françoise Wuillaume
  • Herman Oyen
  • Sophie Maes

Abstract

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. Copyright Swiss School of Public Health 2010

Suggested Citation

  • Bianca Cox & Françoise Wuillaume & Herman Oyen & Sophie Maes, 2010. "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," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 55(4), pages 251-259, August.
    • Handle: RePEc:spr:ijphth:v:55:y:2010:i:4:p:251-259
    DOI: 10.1007/s00038-010-0135-6
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    References listed on IDEAS

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    1. Christian Sonesson & David Bock, 2003. "A review and discussion of prospective statistical surveillance in public health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(1), pages 5-21, February.
    2. C. P. Farrington & N. J. Andrews & A. D. Beale & M. A. Catchpole, 1996. "A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 547-563, May.
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    Cited by:

    1. Mengmeng Li & Shaohua Gu & Peng Bi & Jun Yang & Qiyong Liu, 2015. "Heat Waves and Morbidity: Current Knowledge and Further Direction-A Comprehensive Literature Review," IJERPH, MDPI, vol. 12(5), pages 1-28, May.
    2. Corrado Magnani & Danila Azzolina & Elisa Gallo & Daniela Ferrante & Dario Gregori, 2020. "How Large Was the Mortality Increase Directly and Indirectly Caused by the COVID-19 Epidemic? An Analysis on All-Causes Mortality Data in Italy," IJERPH, MDPI, vol. 17(10), pages 1-11, May.
    3. Johan Verbeeck & Christel Faes & Thomas Neyens & Niel Hens & Geert Verbeke & Patrick Deboosere & Geert Molenberghs, 2023. "A linear mixed model to estimate COVID‐19‐induced excess mortality," Biometrics, The International Biometric Society, vol. 79(1), pages 417-425, March.

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