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© Grossman et al. 2021. Published under the Creative Commons Attribution-NonCommercial licence 3.0 Australia (CC BY-
NC 3.0 AU). Journal website: www.australianpopulationstudies.org 

Visualising the COVID-19 related 
disruptions to long-distance 
population mobility in Australia 

Irina Grossman*  The University of Melbourne 

Tom Wilson  The University of Melbourne 

Jonathan Garber  The University of Melbourne 

Jeromey Temple  The University of Melbourne 

 

*Corresponding author. Email: irina.grossman@unimelb.edu.au. Address: Melbourne School of 

Population and Global Health, The University of Melbourne, Melbourne, Vic 3010, Australia. 

Paper received 6 March 2021; accepted 26 March 2021; published 31 May 2021 

 

Introduction 

The public health response to mitigate the spread of COVID-19 in Australia involved an entry ban 

limiting entrance to Australia to its citizens and residents, a travel ban preventing Australians from 

leaving the country, and a series of state border closures limiting travel within the country (Grattan 

Institute 2020). The aims of this paper are to document the extent of the downturn in domestic and 

international air mobility in Australia that was associated with COVID-19. We use aviation statistics as 

a proxy for long-distance human mobility. Several papers have already been written on COVID-19 

impacted mobility using flight data (e.g., Iacus et al. 2020; Garcia-Gasulla et al. 2020; Lau et al. 2020; 

Suzumura et al. 2020). Our contribution focuses on the Australian context, providing a summary 

visual representation of the huge changes in both domestic and international mobility trends which 

have occurred recently.  

Data and methods 

The Australian Government’s Bureau of Infrastructure and Transport Research Economics (BITRE) 

provides publicly available monthly publications documenting domestic and international aviation 

activity (https://www.bitre.gov.au/statistics/aviation). The international data was sourced from the 

‘Table 5 Scheduled International Traffic by City Pairs’ dataset found in the ‘Table_5’ sheets in the 

January 2019 – December 2020 Excel workbooks, published as part of the International Airline 

Activity—Monthly Publications (BITRE 2021a). The domestic data was sourced from the ‘Australian 

Domestic Airlines, Traffic-On-Board-By-Stage Passengers, Top Competitive Routes’ dataset found in 

the ‘Summary’ sheets in the January 2019 –December 2020 Excel workbooks published as part of the 

Australian Domestic Aviation Activity Monthly Publications (BITRE 2021b). 

MATLAB 2020b was used to aggregate monthly data into time series datasets for total domestic and 

international passenger numbers. Additionally, time series data was assembled for travel between 

Australian capital cities. RStudio 1.3.1056 was used together with the Circlize package (Gu et al. 

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http://www.australianpopulationstudies.org/
mailto:irina.grossman@unimelb.edu.au
https://www.bitre.gov.au/statistics/aviation


102 Grossman et al.  Australian Population Studies 5 (1) 2021 

 

2014) to illustrate the geographical connections and numbers of passengers moving between 

Australian capital cities. We created these for the months of December 2019, April 2020, August 

2020, and December 2020. Microsoft Excel 2016 was used to create a line chart representing 

changes in domestic and international travel for the 2019 – 2020 period. 

 

Figure 1: Australian international and domestic air passengers, by month, 2019 and 2020 

Source: International data was sourced from the passenger numbers provided through the ‘Table_5’ sheets in the excel 
workbooks (BITRE 2021a). Domestic data was sourced from the ‘REVENUE PASSENGERS’ column in the ‘Summary’ sheets of 
the excel workbooks (BITRE 2021b). 

Note: Passenger numbers include both inbound and outbound flights for international flights. 

 

Key features 

The line chart in Figure 1 shows that international and domestic travel both decreased dramatically 

in the first few months of 2020. In April 2020, international and domestic passenger numbers were at 

just 2.0% and 2.8% of their April 2019 numbers, respectively. This corresponds with the closure of 

the Australian border, the international travel ban, and state border closures (Grattan Institute 

2020). International travel remained flat through till the end of 2020. Recovery in Australian aviation 

activity has been led by domestic travel. Domestic travel experienced a local maxima in July before 

decreasing again slightly, which was expected given the state border closures associated with the 

second wave of COVID-19 in Victoria (Grattan Institute 2020). Since September there has been a 

gradual increase in travel, and this rate increased significantly in December of 2020, corresponding 

with the opening of state borders (Grattan Institute 2020) following the successful suppression of the 

second wave in Victoria. By December 2020 domestic passenger numbers had recovered to 41% of 

the December 2019 numbers.  

  

0

1

2

3

4

5

6

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Millions of 
passengers
per month

2019 domestic

2019 international

2020 domestic

2020 international



Australian Population Studies 5 (1) 2021  Grossman et al. 103 

 

 

Figure 2: Circular charts comparing Inter-Capital City travel in selected months of 2019 and 2020. 

Source: Inter-capital city passenger numbers were sourced from the ‘REVENUE PASSENGERS’ column in the ‘Summary’ 

sheets of the excel workbooks (BITRE 2021b). 

Notes: The width of the links indicates the number of passengers travelling between two cities. These links are not 

directional. Each unit on the axes of the circular charts represents 100,000 passengers. Total inter-capital city passenger 

numbers, and inter-capital passenger numbers as a percentage of total domestic passenger numbers, are also presented. 



104 Grossman et al.  Australian Population Studies 5 (1) 2021 

 

The circular charts in Figure 2 provide more detail on changes in domestic travel in 2020 by depicting 

passenger flows between capital cities. The December 2019 circular chart depicts standard pre-

COVID-19 passenger flows, when inter-capital city travel comprised 57% of total domestic passenger 

numbers. The April and August 2020 circular charts show how Australia became disconnected, with 

few passengers moving between the capital cities. The December 2020 circular chart displays the 

recovery in domestic air travel with the reforming of key inter-capital city links, particularly those 

between Melbourne, Sydney, and Brisbane. 

Ethics approval 

Ethics approval for this project was granted by the Melbourne School of Population and Global 

Health (MSPGH) Human Ethics Advisory Group (HEAG), ID 2056902.1. 

Acknowledgements 

The authors gratefully acknowledge funding support from the Melbourne School of Population and 

Global Health for COVID-19 research. 

References 

BITRE (2021a) International Airline Activity—Monthly Publications.  

https://www.bitre.gov.au/publications/ongoing/international_airline_activity-

monthly_publications. Accessed on 23 February 2021. 

BITRE (2021b) Australian Domestic Aviation Activity Monthly Publications. 

https://www.bitre.gov.au/publications/ongoing/domestic_airline_activity-monthly_publications. 

Accessed on 23 February 2021. 

Garcia-Gasulla D, Napagao S A, Li I, Maruyama H, et al. (2020) Global Data Science Project for COVID-19 

Summary Report. https://arxiv.org/abs/2006.05573. Accessed on 14 September 2020. 

Grattan Institute (2020) Grattan: coronavirus announcements tracker. 

https://docs.google.com/spreadsheets/d/1ZqnCmSueVD26Xrw1hMszi5Q_aQwsZJe78Y5HCLwXQ

64/edit#gid=0. Accessed on 26 February 2021. 

Gu Z, Gu L, Eils R, Schlesner M, & Brors B (2014) circlize implements and enhances circular visualization in 

R. Bioinformatics 30(19): 2811-2812. https://doi.org/10.1093/bioinformatics/btu393.  

Iacus S M, Natale F, Santamaria C, Spyratos S, & Vespe M (2020) Estimating and projecting air passenger 

traffic during the COVID-19 coronavirus outbreak and its socio-economic impact. Safety Science 

129: 104791. https://doi.org/10.1016/j.ssci.2020.104791.  

Lau H, Khosrawipour V, Pior Kocbach P, Mikolajczyk A, Ichii H, Zacharski M, Bania J, & Khosrawipour T 

(2020) The association between international and domestic air traffic and the coronavirus 

(COVID-19) outbreak. Journal of Microbiology, Immunology and Infection 53(3): 467-472. 

https://doi.org/10.1016/j.jmii.2020.03.026.2020.  

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impact of COVID-19 on flight networks. https://arxiv.org/abs/2006.02950. Accessed on 14 

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https://www.bitre.gov.au/publications/ongoing/international_airline_activity-monthly_publications
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