COVID has skewed census data on commuting. Here’s how city planners can make the most of it
Melanie Davern, RMIT University; Alain Both, RMIT University; Jago Dodson, RMIT Universityand Tiebei (Terry) Li, RMIT University
Australian cities are slowly recovering from the COVID pandemic. Travel across cities is almost back to pre-pandemic levels. Google Mobility only shows a 14% drop in commuting to work in Victoria and 12% in New South Wales as a whole compared to pre-COVID results.
However, the COVID disruption will impact transportation planning for years to come. The 2021 census – when people were asked how they got to work – coincided with the COVID shutdowns in our two largest cities. The distortion of commuting patterns at this time creates problems for anyone who wants to use this data.
Data on where people work, how they get to work, and how far they travel is a powerful tool for transportation planners and decision makers. Transport has a critical influence on the liveability of cities, health, sustainability and quality of life.
So what can we do about this COVID-skewed transportation data? In this article, we offer some ideas for ensuring that census results remain useful for urban planning.
Why are census responses important?
The Australian Bureau of Statistics has conducted the census and collected data on transport methods and place of work every five years since 1976. In 2016, it enhanced this data to include distance traveled to work and method of displacement.
That year, 9.2 million commuters traveled an average distance of 16.5 km to get to work. Of these people, 79% used a private vehicle, 14% took public transport and 5.2% cycled or walked. Another 500,000 people worked from home and 1 million employed people were not working on Census Day.
The level of detail provided by the census is not available with other methods. This is why commuting questions are so important.
But many of us were in lockdown in 2021
On census night, Australia’s two largest cities, Melbourne and Sydney, were in lockdown, as were major regional cities in Victoria, New South Wales and Queensland (and the lockdown in Brisbane had only taken end only two days before). People were asked, “How did the person get to work on Tuesday, August 10, 2021?”
Planners and researchers expect unusual results due to the closures. We don’t know if people registered their workplace as if the lockdown wasn’t in place, or treated their home as their workplace. While a higher than expected number of “worked at home” responses may signal the latter, we cannot know for sure.
The 2021 census data will not provide a reliable record of “normal” commuting patterns, nor an accurate record of commuting changes over time. It’s not even clear if work attendance and commuting patterns will ever return to their pre-COVID state.
What can we do with census data?
So the big question is how can policymakers usefully work with data to correct the distortion of COVID lockdowns? We offer the following suggestions.
Look at cities that weren’t on lockdown
One option is to use the broad transport schemes of Australia’s less closed regions, such as Adelaide or Perth. We can use their results and changes in transportation mode over time to help estimate results in other cities.
Link to previous census results
Another option would be to look at previous census results on commuting for cities and try to match or predict what would have been expected in 2021 for different modes of transport and distances. An advantage of this model is that the previous results are available at the local neighborhood level and incorporate local influences of transport types and distances.
Another idea would be to look at the occupations people list on their census forms, and then match the types of occupations to the modes of transportation used in the previous census results.
Correspondence with household travel survey data
Transport departments collect travel data at the household level in a number of cities, including Sydney and Melbourne, to understand how far people travel and the modes of transport they use. These surveys could be used to model regional differences in commuting patterns based on more up-to-date commuting results than older census data.
Investigate other travel datasets
The use of big data has come a long way since 2016. Today we have a number of other public and private travel datasets that could be used. These include Google Mobility results, traffic light counts, road sensors, and Myki/Opal/go map travel data.
These datasets could be linked or modeled with census results to get a better estimate of results in closed areas.
Quarterly and annual COVID surveys could also help understand how transportation has changed throughout the pandemic.
Evaluate against other government data
Data matching is another area the Australian Bureau of Statistics has been working on for years. One example is the Multi-Agency Data Integration Project, which was designed to help better understand census data. The Australian Tax Office holds employment and work-related vehicle claims which could also be useful in identifying modes of transport and travel requests by area.
Strict privacy rules apply to this data, but government agencies working together could lead to better travel data for cities affected by lockdowns in 2021.
All of these options have strengths and weaknesses. None are as good as the full set of census data unaffected by lockdowns. However, they are worth considering when the 2021 commute results are released on October 12.
Transport planners and researchers are resourceful. They will likely find ways to correct the above issues to assess and understand transport patterns in Australian cities. Now is the time to discuss and exchange ideas on these questions and the unusual census results to ensure that transport planning is based on solid and up-to-date data.
Melanie Davern, Associate Professor, Director of the Australian Urban Observatory, Center for Urban Research, RMIT University; Alan Both, Senior Researcher, Center for Urban Research, RMIT University; Jago Dodson, Professor of Urban Policy and Director of the Center for Urban Research, RMIT Universityand Tiebei (Terry) Li, Senior Fellow, School of Global, Urban and Social Studies, RMIT University
This article is republished from The Conversation under a Creative Commons license. Read the original article.