Estimating incidence curves of several infections using symptom surveillance data

PLoS One. 2011;6(8):e23380. doi: 10.1371/journal.pone.0023380. Epub 2011 Aug 24.


We introduce a method for estimating incidence curves of several co-circulating infectious pathogens, where each infection has its own probabilities of particular symptom profiles. Our deconvolution method utilizes weekly surveillance data on symptoms from a defined population as well as additional data on symptoms from a sample of virologically confirmed infectious episodes. We illustrate this method by numerical simulations and by using data from a survey conducted on the University of Michigan campus. Last, we describe the data needs to make such estimates accurate.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Communicable Diseases / complications
  • Communicable Diseases / epidemiology*
  • Disease Outbreaks / statistics & numerical data
  • Fever / complications
  • Fever / epidemiology
  • Health Surveys*
  • Humans
  • Incidence
  • Influenza, Human / complications
  • Influenza, Human / epidemiology*
  • Michigan / epidemiology
  • Population Surveillance*
  • Universities