title: Prediction of gastrointestinal disease with over-the-counter diarrheal remedy sales records in the San Francisco Bay Area.
abstract: BACKGROUND
  Water utilities continue to be interested in implementing syndromic surveillance for the enhanced detection of waterborne disease outbreaks. The authors evaluated the ability of sales of over-the-counter diarrheal remedies available from the National Retail Data Monitor to predict endemic and epidemic gastrointestinal disease in the San Francisco Bay Area.
  
  
  METHODS
  Time series models were fit to weekly diarrheal remedy sales and diarrheal illness case counts. Cross-correlations between the pre-whitened residual series were calculated. Diarrheal remedy sales model residuals were regressed on the number of weekly outbreaks and outbreak-associated cases. Diarrheal remedy sales models were used to auto-forecast one week-ahead sales. The sensitivity and specificity of signals, generated by observed diarrheal remedy sales exceeding the upper 95% forecast confidence interval, in predicting weekly outbreaks were calculated.
  
  
  RESULTS
  No significant correlations were identified between weekly diarrheal remedy sales and diarrhea illness case counts, outbreak counts, or the number of outbreak-associated cases. Signals generated by forecasting with the diarrheal remedy sales model did not coincide with outbreak weeks more reliably than signals chosen randomly.
  
  
  CONCLUSIONS
  This work does not support the implementation of syndromic surveillance for gastrointestinal disease with data available though the National Retail Data Monitor.
authors.affiliation: Department of Public Health, City and County of San Francisco, San Francisco, California 94102, USA. michelle.kirian@sfdph.org
authors.forename: Michelle L
authors.initials: ML
authors.lastname: Kirian
authors.forename: June M
authors.initials: JM
authors.lastname: Weintraub
mesh_terms: D000328:Adult; D017250:Caliciviridae Infections / Q000453:epidemiology; D003132:Commerce / Q000706:statistics & numerical data*; D003967:Diarrhea / Q000188:drug therapy / Q000453:epidemiology*; D004196:Disease Outbreaks; D005544:Forecasting / Q000379:methods; D005767:Gastrointestinal Diseases / Q000188:drug therapy / Q000453:epidemiology* / Q000382:microbiology; D006801:Humans; D018803:Models, Economic; D004366:Nonprescription Drugs / Q000191:economics; D029322:Norovirus; D011159:Population Surveillance / Q000379:methods*; D012495:San Francisco / Q000453:epidemiology
chemical_list: D004366:Nonprescription Drugs