Evaluation of non-continuous temperature monitoring practices for vaccine storage units: A Monte Carlo simulation study

Abstract

Objectives: Evaluate different non-continuous temperature monitoring practices for detection of out-of-range temperatures (above or below the recommended temperature range of 2-8°C for refrigeration units), which are called excursions, within vaccine storage units.

Methods: Simulations based on temperature data collected by 243 digital data loggers operated in vaccine storage units at health care providers who participated in a CDC-sponsored continuous temperature monitoring pilot project, from 2012 to 2015. In the primary analysis, we evaluate: (1) twice-daily current temperature readings without minimum and maximum readings (min/max), (2) twice-daily current temperature readings with once-daily min/max, and (3) twice-daily current temperature readings with twice-daily min/max.

Results: Recording current temperature twice-daily without min/max resulted in the detection of 4.8-6.4% of the total number of temperature excursions. When min/max readings were introduced, the percentage of detected temperature excursions increased to 27.8-96.6% with once-daily min/max and to 34.8-96.7% with twice-daily min/max.

Conclusions: Including min/max readings improves the ability of a temperature monitoring practice to detect temperature excursions. No combination of the non-continuous temperature monitoring practices were able to consistently detect all simulated temperature excursions.

Keywords: cold-chain; simulation; storage units; vaccines.

Figure 1.. Illustrative example of temperature excursions with evidence of a corrective action^a in household-grade combination refrigeration vaccine storage unit

^a.In this illustrative example, the corrective action takes place around 22 hours, several hours after the first temperature excursion that would be detected by continuous temperature monitoring. In an ideal scenario, if staff are present and available to address the excursion, the corrective action would occur as soon as the first temperature excursion is detected.

Figure 2.. Duration and temperatures associated with excursions from household-grade combination refrigeration units with a grey box indicating the normal range for temperatures

Note(s): Each point in the figure represents the duration (x-axis) and the most extreme temperature (y-axis) of a temperature excursion from the DDL Pilot Project data. As an example, points just above the area labeled the normal temperature range constitute relatively long excursions that had a maximum temperature that was only slightly warmer than the recommended temperature range. By comparison, points in the bottom left region constitute relatively brief temperature excursions with a low minimum temperature recorded.

Figure 3.. Portion of detected excursions verses total excursion time in a sensitivity analyses, with each panel representing different temperature monitoring practices and 500 simulation iterations

Note(s): Each point in the figure represents the outcome of a single iteration of the simulation model. For example, a point in the bottom left of panel a, represents a simulation iteration that experienced relatively few temperature excursions, and a relatively small portion of these excursions that was detected by once daily current temperature readings. For a comparison, consider a point in the top left of panel (d). A point in this region represents a simulation iteration that experienced a relatively small number of temperature excursions but the majority of which were detected by the twice daily min/max temperature readings.