Wolfram Data Repository

Immediate Computable Access to Curated Contributed Data

UK Occupation Estimates: Exposure to Generic Disease and Physical Proximity

Source Notebook

An estimate of exposure to disease (generally) and physical proximity for UK occupations based on US analysis of these factors, using 2019 data

Details

While working practices and conditions may be slightly different in the US for similar occupations, these estimates offer valuable insight into occupations that involve working in close proximity with others and those that are regularly exposed to diseases. This is a useful indication of which roles may be more likely to come into contact with people with COVID-19, based on what these roles normally entail.

Examples

Basic Examples

Explore the data:

In[1]:=
ResourceData[ ResourceObject[ "UK Occupation Estimates: Exposure to Generic Disease and Physical \ Proximity"]][[1]]
Out[1]=

(The BAME group includes: Mixed/Multiple ethnic groups; Indian; Pakistani; Bangladeshi; Chinese; any other Asian background; Black/African/Caribbean/Black British)

Visualizations

Plot generic disease exposure risk versus physical proximity :

In[2]:=
BubbleChart[ Tooltip[{#1, #2, #3}, #4] & @@@ Select[{#ProximityToOthers, #ExposureToDisease, #TotalInEmployment, \ #OccupationTitle} & /@ ResourceData[ ResourceObject[ "UK Occupation Estimates: Exposure to Generic Disease and \ Physical Proximity"]], FreeQ[#, _Missing] &], ChartElementFunction -> "NoiseBubble", FrameLabel -> {"physical proximity", "exposure risk"}]
Out[2]=

Plot generic disease exposure risk versus median hourly pay :

In[3]:=
BubbleChart[ Tooltip[{#1, #2, #3}, #4] & @@@ Select[{#MedianHourlyPay, #ExposureToDisease, #TotalInEmployment, \ #OccupationTitle} & /@ ResourceData[ ResourceObject[ "UK Occupation Estimates: Exposure to Generic Disease and \ Physical Proximity"]], FreeQ[#, _Missing] &], ChartElementFunction -> "NoiseBubble", FrameLabel -> {"median hourly pay", "exposure risk"}]
Out[3]=

Analysis

Show occupation metrics after ranking by exposure risk to disease:

In[4]:=
ReverseSort[{#ExposureToDisease, \ #PercentageOfTheWorkforceThatAreFemale, \ #PercentageOfTheWorkforceThatAreAged55AndOlder, \ #PercentageOfTheWorkforceThatAreBAME, #MedianHourlyPay, \ #TotalInEmployment, #OccupationTitle} & /@ ResourceData[ ResourceObject[ "UK Occupation Estimates: Exposure to Generic Disease and Physical \ Proximity"]]]
Out[4]=

Wolfram Research, "UK Occupation Estimates: Exposure to Generic Disease and Physical Proximity" from the Wolfram Data Repository (2020)  

Data Resource History

  • Date Created:

Source Metadata

  • Citation:
    • Office for National Statistics
    • https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/whichoccupationshavethehighestpotentialexposuretothecoronaviruscovid19/2020-05-11

Data Downloads

Publisher Information

  • Prepared for the Wolfram Data Repository By: Wolfram|Alpha Content Team
  • Publisher of Record: Wolfram Research