How will COVID-19 affect future UK passenger numbers ? By First O fficer A BALPA dam C memb rehaner Clark, here are lots of questions surrounding UK passenger numbers, and how things will look in the future. Can we predict how much they will be affected? When will they recover? And what kind of demand for air travel will we have in the near future? Since commercial aviations inception, the world has not seen a global pandemic like COVID-19. Fleets have never been grounded for this long, so its difficult to find accurate comparisons. But we can look at other variables to get a value to compare namely GDP (Gross Domestic Product). First, when we look at both annual passenger numbers (data from the World Bank) and annual real UK GDP (data from the Office for National Statistics) since 1970, we see there is a similar pattern of positive growth (see Figure 1). Passenger count Passenger count and GDP data 150,000,000 100,000,000 50,000,000 1970 1980 1990 2000 2010 2020 1970 1980 1990 2000 2010 2020 GDP (m) 2,000,000 1,000,000 0 Year Fig 1: Passenger count and GDP data Polynomial regression of GDP vs passenger numbers (2009-2019) UK air passengers (count) 170,000,000 160,000,000 150,000,000 140,000,000 130,000,000 120,000,000 110,000,000 100,000,000 1,750,000 1800,000 1,850,000 1,900,000 1,950,000 2,000,000 2,050,000 2,100,000 Nominal GDP (m) Fig 2: GDP v passenger numbers The question is: do they correlate? We can see from the graph (Figure 2) that they are, in fact, closely correlated when using polynomial regression (R^2 = 0.99). We have subset the data to the latest decade to more accurately represent both the current generation of aircraft and culture of air travel. Lets sense-check this: would passenger numbers follow an exponential growth against GDP? Greater GDP means better economies of scale, and more efficient aircraft would reduce ticket prices. Increased GDP is found with greater globalisation and trade, which could also be correlated with more travel. So yes, it does make sense. If we have a prediction for GDP, we can use the above regression to also predict the corresponding passenger numbers. The next step is to predict the future real GDP. For this we can use the forecast GDP growth data in per cent, both pre-COVID-19 (data from Office for Budget Responsibility) and postCOVID-19 (data from UK Government). A bit of mathematical processing leads us to be able to plot the predicted passenger figures for 2020 to 2023 (see Figure 3). As we can see, the GDP-dependent figures take a sharp dip, but become positive from an immediate bounce in 2021 and return to the base level in 2022. This analysis doesnt include the lockdown factor, where people are forced to reduce their travel. It also doesnt include any changing culture to air travel, like using Skype or Zoom to replace business meetings. Thus, the predicted dip here is to about 90%, when we know that most airlines are running at 1% and Ryanair has only suggested a return to 80% in September. UK air passengers (count) 190,000,000 Actual passengers Predicted average pre-COVID-19 180,000,000 Predicted post-COVID-19 170,000,000 160,000,000 150,000,000 140,000,000 130,000,000 120,000,000 2012 2014 2016 2018 2020 2022 Fig 3: Predicted passenger numbers for 2020 to 2023 This is where we diverge from quantitative analysis to speculation. We can suggest (arbitrarily) that the lockdown could ground fleets for four months in 2020 and then again for two months in 2021. This artificial depression of the data would emulate the unknown quantity of the lockdown affect. The result is shown in Figure 4 and is markedly lower for 2020 and 2021. Predicted average pre-COVID-19 Predicted post-COVID-19 including lockdown Predicted passenger numbers 1.8 1.7 1.6 1.5 1.4 1.3 1.2 2019 2020 2021 2022 2023 Fig 4: Predicted passenger numbers with artificial depression of data Predicted capacity estimates pre-COVID-19 v post-COVID-19 100 Load factor (%) 80 60 40 20 0 2020 2021 2022 2023 Fig 5: Capacity: percentage of forecast demand We can then plot this data as an estimated UK-wide load factor percentage in terms of what we had planned for in 2020. Most airlines will have purchased aircraft, pilots and crew according to the 2020 forecast. Figure 5 shows what kind of percentage of forecast demand the airlines would be working to. So, we can expect about 50% of capacity in 2020; and most forecasters are predicting similar. In 2021 we can see recovery but still an under-served market. This makes sense because of the loss of jobs, depressed GDP and customer caution about travel. It also estimates smaller, repeat waves as the country adopts a new normal. But in 2022, we should start to return to figures we were estimating in 2020. Then, from 2023 onwards, we should be back to pre-COVID-19 growth. To sum up: a depression in 2020, slow recovery in 2021, return to normal in 2022 and growth in 2023. COVID-19 T h e after-e ffects