Effect of data quality on estimates of farm infectiousness trends in the UK 2001 foot-and-mouth disease epidemic

Nicholas J. Savill, Darren J. Shaw, Rob Deardon, Michael J. Tildesley, Matthew J. Keeling, Mark E.J. Woolhouse, Stephen P. Brooks, Bryan T. Grenfell

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Most of the mathematical models that were developed to study the UK 2001 foot-and-mouth disease epidemic assumed that the infectiousness of infected premises was constant over their infectious periods. However, there is some controversy over whether this assumption is appropriate. Uncertainty about which farm infected which in 2001 means that the only method to determine if there were trends in farm infectiousness is the fitting of mechanistic mathematical models to the epidemic data. The parameter values that are estimated using this technique, however, may be influenced by missing and inaccurate data. In particular to the UK 2001 epidemic, this includes unreported infectives, inaccurate farm infection dates and unknown farm latent periods. Here, we show that such data degradation prevents successful determination of trends in farm infectiousness.

Original languageEnglish (US)
Pages (from-to)235-241
Number of pages7
JournalJournal of the Royal Society Interface
Volume4
Issue number13
DOIs
StatePublished - Apr 22 2007

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Bioengineering
  • Biomaterials
  • Biochemistry
  • Biomedical Engineering

Keywords

  • Epidemiology
  • Foot-and-mouth disease
  • Mathematical model

Fingerprint Dive into the research topics of 'Effect of data quality on estimates of farm infectiousness trends in the UK 2001 foot-and-mouth disease epidemic'. Together they form a unique fingerprint.

Cite this