Prediction of gastrointestinal disease with over-the-counter diarrheal remedy sales records in the San Francisco Bay Area

• Published in: BMC medical informatics and decision making 2010-07, Vol.10 (1), p.39-39, Article 39
• Main Authors: Kirian, Michelle L, Weintraub, June M
• Format: Article
• Language: English
• Subjects: Adult; Antidiarrheals; Caliciviridae Infections - epidemiology; Commerce - statistics & numerical data; Diagnosis; Diarrhea - drug therapy; Diarrhea - epidemiology; Disease Outbreaks; Drug therapy; Forecasting - methods; Gastrointestinal diseases; Gastrointestinal Diseases - drug therapy; Gastrointestinal Diseases - epidemiology; Gastrointestinal Diseases - microbiology; Health aspects; Humans; Models, Economic; Nonprescription Drugs - economics; Norovirus; Population Surveillance - methods; San Francisco - epidemiology
• ISSN: 1472-6947; 1472-6947
• DOI: 10.1186/1472-6947-10-39

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. 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. 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. This work does not support the implementation of syndromic surveillance for gastrointestinal disease with data available though the National Retail Data Monitor.