Prediction of gastrointestinal disease with over-the-counter diarrheal remedy sales records in the San Francisco Bay Area.
Prediction of gastrointestinal disease with over-the-counter diarrheal remedy sales records in the San Francisco Bay Area.
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DOI：
10.1186/1472-6947-10-39
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发表时间：
2010-07-20
影响因子：
3.5
通讯作者：
Weintraub JM
中科院分区：
文献类型：
--
作者：
Kirian ML;Weintraub JM
水务公司继续有兴趣实施综合症监测，以加强对水传播疾病暴发的发现。作者评估了来自全国零售数据监测的非处方腹泻药物的销售能力，以预测旧金山湾区的地方性和流行性胃肠疾病。时间序列模型适合于每周腹泻药物销售和腹泻病例数。计算预白化残差序列之间的相互关系。腹泻药销售模型残差根据每周爆发的次数和与爆发相关的病例进行回归。腹泻药销售模型被用来自动预测一周前的销售情况。计算了观察到的腹泻药物销售超过95%预测置信区间所产生的信号在预测每周暴发时的敏感性和特异性。未发现每周腹泻药物销售与腹泻病例数、爆发数或爆发相关病例数之间存在显著相关性。与随机选择的信号相比，用腹泻药物销售模型预测产生的信号与爆发周的吻合度更可靠。这项工作不支持通过全国零售数据监测来实施胃肠道疾病综合征监测。
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.
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DOI：
10.1331/1544-3191.46.5.574.lam
发表时间：
2006-09-01
影响因子：
2.1
作者：
Lam, Annie;Bradley, George
通讯作者：
Bradley, George
DOI：
10.1111/j.1532-5415.1997.tb04501.x
发表时间：
1997-02-01
影响因子：
6.3
作者：
Stoehr, GP;Ganguli, M;Belle, S
通讯作者：
Belle, S
DOI：
10.1111/j.1532-5415.1998.tb04538.x
发表时间：
1998-10-01
影响因子：
6.3
作者：
Espino, DV;Lichtenstein, LJ;Markides, KS
通讯作者：
Markides, KS
DOI：
10.1007/bf03405234
发表时间：
2006-11-01
影响因子：
4.3
作者：
Frosst, Gillian O.;Majowicz, Shannon E.;Edge, Victoria L.
通讯作者：
Edge, Victoria L.
影响因子：
2.2
作者：
HANSSENS, DM
通讯作者：
HANSSENS, DM