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Editorial
. 2020 Oct;75(10):1278-1283.
doi: 10.1111/anae.15144. Epub 2020 Jun 15.

Demand-capacity modelling and COVID-19 disease: identifying themes for future NHS planning

J J Pandit  1
Affiliations
Editorial

Demand-capacity modelling and COVID-19 disease: identifying themes for future NHS planning

J J Pandit. Anaesthesia. 2020 Oct.
No abstract available

Keywords: COVID-19; efficiency; health services research; modelling.

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Figures

Figure Figure 1
Figure Figure 1
Demand (which can be measured variously; horizontal black line) is constant over time so optimal capacity (red line 1) is easy to estimate. For varying demands shown, although mean demand is identical to the horizontal black line, the optimal capacities required to meet all the demand all the time increase (from dotted red line 2 to solid red line 3) as variation increases. However, this results in wasted capacity when demand falls to less than the peak. [Colour figure can be viewed at wileyonlinelibrary.com]
Figure Figure 2
Figure Figure 2
Demand on NHS services vs. time (arbitrary scales) estimated using logistic map equation (see Appendix 1). (a) Baseline fluctuations in demand similar to sinusoidal variations in Fig. 1. (b) Demand created by viral population with an r value in logistic map equation just 2.8% higher. (c) A further increase in r value of just 2.8%. Note that the mean demand is little affected but there is a dramatic increase in variation, and in panel (c), unpredictability of that variation. These do not represent actual, accurate modelling of NHS demand, but plots on arbitrary scales to illustrate the nature of the relationships.
See this image and copyright information in PMC

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