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4 months ago by Debbie Lloyd

The Jobs Most at Risk from CoronaVirus

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HR Grapevine looks at the cccupations that expose workers to coronavirus the most. At Prime Minister Boris Johnson’s orders, many UK employees have temporarily moved to remote working arrangements to relieve pressure on the NHS and prevent the virus from spreading further.

However, there are jobs that either can’t be done remotely or require people to continue going into their place of work.

Given that coronavirus is spread due to close human contact, such as via breath and touching surfaces, those workers that are in close contact with others, or who are regularly exposed to infection and disease, are at a greater risk of contracting COVID-19.

Occupations that expose workers to coronavirus the most

With that in mind, a recently published interactive chart has collated data showcasing the occupations that expose workers to coronavirus the most.

According to data published on autonomy.work, nursing was identified as an occupation that involves high physical proximity (94) and a high exposure to infection and disease (95), so workers in this occupation could be at a greater risk of contracting COVID-19.

Medical practitioners, dental nurses and practioners, hospital porters and paramedics also shared equally high levels of physical proximity and exposure to infection and disease because of the nature of the job.

Waiters and waitresses received a score of 80 for physical proximity to others while their exposure to disease was relatively low at 20. Chefs, catering and bar managers, taxi drivers and chauffeurs also demonstrated high levels of physical proximity but low exposure to disease.

Further down the rankings, financial managers and directors received a score of just over 50 for physical proximity to others, with a low score of circa five for exposure to disease.

Vehicle technicians, mechanics, printers, IT engineers and business development managers also received far higher scores for physical proximity to others, as opposed to exposure to disease.

On the other end of the scale, farmers received a relatively low score for both physical proximity to others and exposure to disease, with graphic designers, fork-lift truck drivers, economists and statisticians receiving lower scores too.

In the interactive charts published on autonomy.work’s website, the site plotted 273 different UK-based occupations according to the numbers employed in each, the level of physical proximity that each job requires, and the potential exposure to disease or infections that each job entails.

The study stated that each blue dot represents an occupation; the larger the dot, the more people employed in that occupation. On the firm’s website, hovering on each blue dot will provide a plethora of information including the gender split in this occupation and median pay.

Each job has a score that ranks it for both physical proximity and exposure to infection and disease.

The data has also been unpicked into different graphs to highlight different data including employment and exposure to diseases and infections, employment and physical proximity to others and employment and overall Risk Infection Factor (RIF).

The methodology

Autonomy.work explained that the study was conducted in a similar fashion to that which The New York Times recently published though, this study, focussed on the UK context.

They used the O*NET database which holds details on thousands of US occupations. They provided a score for exposure to disease by asking ‘how often does this job require exposure to disease/ infections’. Answers varied from every day, once a week, once a year, once a month and never.

For the physical proximity measure, they asked ‘to what extent does this job require the worker to perform job tasks in physical proximity to other people'. Answers ranged from ‘very close’ to ‘slightly close’ and rarely working with other people.

The researchers matched the US occupations in the O*NET data to the ONS Standard Occupational Classification system to find out what these metrics mean for UK-based jobs.

ONS data was then used to find out the gender split and median pay of those working in each occupation.

Source: HR Grapevine