Occupation classification and COVID19

In the previous post we looked at the relationship between industry of employment and COVID19. In this article we will look at whether there is also socio-geographic differences in the distribution of worker occupations between Local Government Areas (‘LGAs’). To the extent that there is a relationship between occupational distribution and levels of COVID19, we can identify occupation types that may require significant attention.

To this end, we looked at the percentage of employed persons working in a given occupation, against the number of cumulative COVID19 cases (per 100K of population) at the peak of the second wave¹, by LGA.

The percentage of the community employed as ‘Machine Operators and Drivers’ was positively correlated with COVID19 levels (0.4). Moreso than for any other industry.

The percentage of the community employed as Community and Personal Service Workers was also positively correlated with COVID19 levels (0.3 - statistically significant at the 10% level).

Table 1 Correlation of Occupation and COVID19 cases (per 100K population) on 2 August

It can be seen in Figure 1a, below, that Drivers are over-represented in the far Western LGAs of Melton, Wyndham, Brimbank and Hume. These are also the areas which saw rapid rates of COVID19 increase in July (see Figure 1b).

Figure 1a Persons employed as drivers (%) and COVID19 cases (per 100K population) by LGA

Download Occupation LGA data as csv

Figure 1b Persons Employed in Transport (%) and COVID cases (actual) over time, by LGA

Data sources: Time series from COVID19data; Industry data from ABS 2016 Census

Machine Operators and Drivers

This occupational grouping includes all automobile, rail, tram and bus drivers as well as delivery drivers. Storepersons and forklift drivers are also included in this classification.

As increasing numbers of Australians turn to online shopping for a range of daily needs in order to reduce their risk of COVID19 exposure, these risks are deferred to logistics workers. In many cases major operations such as Coles and Woolworths have had to recruit hastily in order to meet intense consumer demand for ‘socially-distanced shopping.’ Whether sufficient consideration has been given to safely inducting and protecting these workers warrants further investigation.

Community and Personal Service Workers

The percentage of the community employed as Community and Personal Service Workers was also positively correlated with COVID19 levels across LGAs. This is an expansive group that covers a range of health, caring, hospitality and safety work.

This occupation includes many health workers on the front lines. That is, ambulance workers, paramedics, as well as nursing support and disability support workers. It does not include doctors and nurses, who are placed in the ‘Professional’ occupational category (it must be emphasised that this does not mean doctors and nurses do not face the same level of elevated risk as non-Professional health care workers, merely that individuals in these roles are less concentrated in terms of LGA of residence).

This occupational grouping also includes other types of caring work such as child care and aged care.

Notably, it also includes hotel workers and security guards.

‘Community and Personal Service Workers’ and ‘Machine Operators and Drivers’ share a number of characteristics:

• They are public facing roles;
  
• These roles cannot be done from home; and
  
• The individuals in these groupings are not in management, nor are they considered ‘high skilled’ (‘Management’ and ‘Professionals’ constitute separate occupational categories).

Managers

On the flip side of things, the occupation category that is negatively correlated with COVID19 is ‘Managers.’ This grouping covers individuals who work as managers across almost all areas from HR to finance to retail. It also includes Members of Parliament and School Principals.

Of note, these are workers whose roles can, for the most part, be done from home, have limited contact with the public and exercise significant control over their level of contact with other staff members.

Conclusion

Socio-geographic analysis of Melbourne’s second wave suggests that how we work is closely connected to how COVID19 is transmitted.

Optimising COVID19-safe practices for workers in occupations that are most at risk, must be put front and centre in the fight against COVID19. It can be seen that a feature of many ‘at risk’ occupations is a relatively low level of autonomy over workplace safety measures. Concerns that are raised by workers on the ground must be taken seriously, as safety failures can result in widespread infection in the communities in which they reside.

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