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Comprehensive Analysis of C1 Algorithm: Sensitivity, Specificity, and Surveillance Metrics

This document provides an in-depth overview of the C1 algorithm used in monitoring and evaluating clinical data. It details the methods for calculating sensitivity and specificity across multiple thresholds, the process for iterating over CDC iterations and days, and the techniques for obtaining baseline data. The current test period configuration, alarm generation over surveillance periods, and ROC curve generation for the C1 algorithm are discussed. This resource is essential for practitioners looking to enhance their data analysis and surveillance capabilities using the C1 framework.

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Comprehensive Analysis of C1 Algorithm: Sensitivity, Specificity, and Surveillance Metrics

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  1. CDCIterationRangeConfig SurveillancePeriodConfig DatasetConfigC1 Legend: Tag - to save space the word “Tag” omitted Tag - tag containing range or vector of aggregated values ObtainTrueOBData _forC1Algorithm Tag Tag - iterated variable drawn from iteration range Tag Tag - step results aggregated into final output TrueOBDataC1 IterationOverThresholdsConfig EvaluateC1_SensitivitySpecificity_multipleThresholds MonitorData_withC1 ThresholdC1 CDCIterationRangeConfig MonitorDataC1_IterateOverCDCIterations CDCIteration SurveillancePeriodConfig MonitorDataC1_IterateOverDays CurrentTestPeriodC1 DatasetConfigC1 BaselineDataConfigC1 ReplicateData _TrueOB ComputeBaselineSD_C1 GetCurrentTestValue_C1 Get7DaysBaselineData_C1 ComputeBaselineMean_C1 TrueOBDataCOPYC1 ThresholdC1 PartialSumInitConfigC1 EvaluateTestValue _ControlLimit ComputePartial- Sum_forC1 AlarmValueC1 (single) AlarmsOverSurveillPeriodC1 (short vector) AlarmsOverAllCDCIterationsC1 (long vector) ComputeSensi- tivity_ofC1 ComputeSpeci- ficity_ofC1 SensitivityC1 (single) SpecificityC1 (single) SensitivitiesC1 (vector) SpecificitiesC1 (vector) GenerateROC_ forC1Algorithm ROCplotConfigC1 ROCforC1

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