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Fig 1.

The testing ecosystem.

Schematic representation of the SARS-CoV-2 testing system, including 1) a variety of community and facility sites collecting samples for testing, which are transported to 2) a centralized SARS-CoV-2 testing laboratory, which completes the test and 3) delivers results back to the individual through multiple platforms. Information systems link the different sectors.

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Fig 2.

Sample collection and testing process.

Steps performed at sample collection sites are shown in blue, sample accessioning in green, and laboratory steps in yellow.

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Fig 3.

Laboratory process steps.

(Top left) Samples racked and scanned; note the many different sizes and shapes. (Top right) Tubes are uncapped and deswabbed manually then placed on the deck of the Hamilton STARlet for transfer to deep-well plates. (Bottom left) Deep-well plates stacked in front of a Hamilton STAR for RNA extraction. (Bottom right) qPCR in progress and completed.

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Fig 4.

Number of samples arriving for testing at UMPA/MG weekly (line) and daily (bars) during a six-week period in November and December 2020.

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Fig 5.

Time to return results at UMPA/MG during a six-week period in November and December 2020.

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Table 1.

Baseline parameters.

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Fig 6.

Example of validation results.

The model reproduces the empirical data from six weeks of varying demand and two hypothetical higher-demand scenarios.

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Fig 7.

KPIs for the baseline scenario that represents current UMPA/MG operations.

(a) Tests conducted per week. (b) Average turnaround time from collection to result. (c) Percent utilization of resources at each process step (e.g., technicians or robots).

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Fig 8.

Changes in capacity resulting from various process modifications.

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Table 2.

Capacity and bottlenecks with various process modifications.

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Table 2 Expand

Fig 9.

Average turnaround time for demand scenarios with one-day spikes compared to evenly spread demand, for Scenario 1.

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Table 3.

Minimum resources required to meet target levels of demand (8-hour shifts).

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