Evidence map›Paper›PMID 20646311›Full record

ArticleBMC medical informatics and decision making2010

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

Michelle L Kirian, June M Weintraub

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Drug sales data for gastrointestinal infections surveillance: a systematic review up to 2025.Archives of public health = Archives belges de sante publique · 2026
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Michelle L KirianDepartment of Public Health, City and County of San Francisco, San Francisco, California 94102, USA. michelle.kirian@sfdph.org
June M Weintraub

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWater 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.

methodsTime 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.

resultsNo 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.

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

Indexed as

Disease OutbreaksNonprescription DrugsAdultCaliciviridae InfectionsCommerceDiarrheaForecastingGastrointestinal DiseasesHumansModels, EconomicNorovirusPopulation SurveillanceSan FranciscoNonprescription Drugs

Identifiers

PMID20646311
PMCPMC2920250

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.