Scope

This page outlines that parts of the journal article which we will attempt to reproduce.

Within scope

Figure 2

Figure 2. “Patient state over time by unit. The patient population progresses through infection over three months (with 80% infected). The bold line shows the median results of 30 trials, and the fainter lines show the minimum and maximum from the 30 trials.” Allen et al. (2020)

Figure 3

Figure 3. “Progression of patient population through COVID infection, assuming 80% become infected over three months, with 15% mortality. The figure also shows the number of patients not allocated to a dialysis session at any time. The bold line shows the median results of 30 trials, and the fainter lines show the minimum and maximum from the 30 trials.” Allen et al. (2020)

Figure 4

Figure 4. “Patient displacement. The number of patients displaced from their current unit (left panel) and the additional travel time to the unit of care (right panel) for displaced patients. These results do not include those receiving inpatient care. The patient population progresses through infection over three months (with 80% infected). The bold line shows the median results of 30 trials, and the fainter lines show the minimum and maximum from the 30 trials.” Allen et al. (2020)

Outside scope

Table 1

Outside scope as it is a table of model parameters rather than outputs.

Table 1. “Baseline model parameters.” Allen et al. (2020)

Figure 1

Outside scope as it is a flow chart representing the model pathways.

Figure 1. “Schematic representation of patient pathway.” Allen et al. (2020)

Figure 5

Outside scope as it is a result of the Monte Carlo model.

Figure 5. “One-way ambulance transport time distributions (1000 model runs). Results compare population COVID-positive and ambulance seating capacity (e.g. 2 = 2 seats.) Figures do not include ambulance clean-down/turnaround time.” Allen et al. (2020)

Figure 6

Outside scope as it is a result of the Monte Carlo model.

Figure 6. “Two-way ambulance transport time distributions (1000 model runs). Results compare population COVID-positive and ambulance seating capacity (e.g. 2 = 2 seats.) Figures do not include ambulance clean-down/turnaround time.” Allen et al. (2020)

References

Allen, Michael, Amir Bhanji, Jonas Willemsen, Steven Dudfield, Stuart Logan, and Thomas Monks. 2020. “A Simulation Modelling Toolkit for Organising Outpatient Dialysis Services During the COVID-19 Pandemic.” PLOS ONE 15 (8): e0237628. https://doi.org/10.1371/journal.pone.0237628.