Volume 21, Number 2—February 2015
Research
Refining Historical Limits Method to Improve Disease Cluster Detection, New York City, New York, USA
Table 4
Explanation | No. signals produced by HLMoriginal | No. signals produced by HLMrefined |
---|---|---|
Attributable to an uncorrected bias toward signaling | ||
Neighborhood disease count threshold too low | 47† | 0 |
Pending cases in current period | 21 | 0 |
Increasing trends in baseline period | 3 | 0 |
Total signals attributable to an uncorrected bias toward signaling |
71 |
0 |
Attributable to the correction of a bias against signaling | ||
Confirmatory proportion higher in current period than in baseline period | 9 | 0 |
Accounted for data accrual lags | 0 | 17 |
Deleted outliers in baseline period | 0 | 2 |
Adjusted for decreasing trends in baseline period | 0 | 1 |
Total signals attributable to the correction of a bias against signaling |
9 |
20 |
Not attributable to any known systematic bias |
54 |
54 |
Total signals | 134 | 74 |
*HLM, historical limits method; HLMoriginal, method as originally applied in NYC prior to May 20, 2013; HLMrefined, refined method applied starting May 20, 2013.
†These were excluded from the calculation of type I and type II error rates.
1Current affiliation: RTI International, Research Triangle Park, North Carolina, USA.
2Current affiliation: Colorado Department of Public Health and Environment, Denver, Colorado, USA.
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Page updated: January 20, 2015
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