Potential use of multiple surveillance data in the forecast of hospital admissions

Authors

  • Eric H. Lau The University of Hong Kong
  • Dennis K.M. Ip The University of Hong Kong
  • Benjamin J. Cowling The University of Hong Kong

DOI:

https://doi.org/10.5210/ojphi.v5i1.4559

Abstract

A sudden surge in hospital admissions in public hospital during influenza peak season has been a challenge to the healthcare and manpower planning. In this study we explore the potential use of multiple routinely collected syndromic data in the forecast of hospital admissions. The derived influenza activity based on multiple surveillance data have higher correlations with respiratory disease and P&I admission and may potentially useful to forecast surge.

Author Biography

Eric H. Lau, The University of Hong Kong

Eric is interested in the methodology and application of statistical and mathematical modelling of infectious diseases. He is currently working on infectious disease surveillance, statistical and mathematical modelling of tuberculosis, scarlet fever and community-acquired methicillin resistant staphylococcus aureus and influenza in human and poultry.

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Published

2013-03-24

How to Cite

Lau, E. H., Ip, D. K., & Cowling, B. J. (2013). Potential use of multiple surveillance data in the forecast of hospital admissions. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4559

Issue

Vol. 5 No. 1 (2013)

Section

Poster Presentations

License

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