Article Text

Original research
COVID-19 outbreak rates and infection attack rates associated with the workplace: a descriptive epidemiological study
  1. Yiqun Chen1,
  2. Timothy Aldridge1,
  3. Claire Ferraro2,
  4. Fu-Meng Khaw3
  1. 1Science Division, Health and Safety Executive, Buxton, UK
  2. 2Public Health England South West, Public Health England, Bristol, UK
  3. 3Health Protection and Screening Services, Public Health Wales, Cardiff, UK
  1. Correspondence to Dr Yiqun Chen; yiqun.chen{at}


Objectives A large number of COVID-19 outbreaks/clusters have been reported in a variety of workplace settings since the start of the pandemic but the rate of outbreak occurrence in the workplace has not previously been assessed. The objectives of this paper are to identify the geographical areas and industrial sectors with a high rate of outbreaks of COVID-19 and to compare infection attack rates by enterprise size and sector in England.

Methods Public Health England (PHE) HPZone data on COVID-19 outbreaks in workplaces, between 18 May and 12 October 2020, were analysed. The workplace outbreak rates by region and sector were calculated, using National Population Database (NPD) with the total number of workplaces as the denominator. The infection attack rates were calculated by enterprise size and sector using PHE Situations of Interest data with the number of test-confirmed COVID-19 cases in a workplace outbreak as the numerator and using NPD data with the number employed in that workplace as the denominator.

Results The highest attack rate was for outbreaks in close contact services (median 16.5%), followed by outbreaks in restaurants and catering (median 10.2%), and in manufacturers and packers of non-food products (median 6.7%). The overall outbreak rate was 66 per 100 000 workplaces. Of the nine English regions, the North West had the highest workplace outbreak rate (155 per 100 000 workplaces). Of the industrial sectors, manufacturers and packers of food had the highest outbreak rate (1672 per 100 000), which was consistent across seven of the regions. In addition, high outbreak rates in warehouses were observed in the East Midlands and the North West.

Conclusions Early identification of geographical regions and industrial sectors with higher rates of COVID-19 workplace outbreaks can inform interventions to limit transmission of SARS-CoV-2.

  • epidemiology
  • COVID-19
  • public health
  • occupational & industrial medicine

Data availability statement

Data may be obtained from a third party and are not publicly available. All data relevant to the study are included in the article or uploaded as supplementary information. The data used to support the findings of the study are included in the references within this paper. No additional data available.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Strengths and limitations of this study

  • This study has described in detail the relevant data sets used for the calculation of COVID-19 outbreak rates and infection attack rates in the workplace, in England, by industrial sector and geographical region.

  • The same methodological approach can be applied to the calculation of outbreak rates and attack rates in other countries and for other types of settings to support pandemic response.

  • The number of outbreaks included in the analysis was obtained from the public health outbreak management information system, which could be affected by national-level and local-level operational changes and limit the ability to measure regional variations.

  • The COVID-19 outbreaks included in the analysis could be biased towards large and more impactful outbreaks and therefore could underestimate the true outbreak rates.

  • The working population would be overestimated in some workplace settings with reduced number of employees working during the pandemic, but underestimated in other workplace settings with many seasonal workers, agency workers and subcontractors less likely to be accounted for, which could cause imprecisions in the attack rate calculation.


SARS-CoV-2 is a highly transmissible novel virus that has caused the ‘coronavirus disease 2019’ (COVID-19) pandemic.1 On 30 January 2020, the WHO declared COVID-19 as a public health emergency of international concern and later declared a pandemic on 11 March 2020.2 COVID-19 is a highly contagious disease and can spread rapidly without effective control measures. Due to the heterogeneity characteristics of the SARS-CoV-2 transmission, COVID-19 cases are appearing in clusters in different settings.3 4

In October 2020, Public Health England (PHE) reported 503 COVID-19 outbreaks/clusters in workplace settings in the previous 4 weeks. This is compared with 720 in care homes, 853 in education settings and 89 in hospital settings.5 A survey conducted by the European Centre for Disease Prevention and Control reported a total of 1377 COVID-19 clusters in workplace settings across 13 EU/EEA (European Union/European Economic Area) countries and the UK between March and July 2020. Most clusters were reported in long-term care (591 clusters) and hospital (241 clusters) settings, followed by food packing and processing (153 clusters), non-food manufacturing (77 clusters) and office settings (65 clusters).6 However, the total number of settings and the number of people exposed within these settings (ie, the denominator data) could vary significantly. Without the denominator information to calculate the rate of outbreaks, it is difficult to know which types of settings are more likely to experience an outbreak.

This study aims to analyse the occurrence of COVID-19 outbreaks in workplace settings in England to understand which industrial sectors are more likely to experience an outbreak and to estimate the potential extent of the transmission in these workplace outbreaks. These will guide further research and control measures. However, the design of this study would not allow the investigation of factors potentially contributing to the outbreaks. A separate study is underway to address this.7

This study is part of the UK National Core Study on Transmission and Environment.8 The Health and Safety Executive (HSE) and PHE worked collaboratively and, with the appropriate data sharing agreements in place, linked the relevant data sets to calculate the outbreak rates for different workplace settings and the infection attack rates among workers working in these outbreak settings.


PHE data on COVID-19 outbreaks in the workplace, between 18 May and 12 October 2020, were analysed. The workplace settings here are defined using the categories in PHE’s surveillance system. They include non-residential settings that are not schools or hospitals, as outbreaks in these settings are recorded and analysed separately.9

A COVID-19 cluster is defined as two or more test-confirmed cases of COVID-19 among individuals associated with a setting (ie, a workplace) with onset dates within 14 days, where information about exposure between the confirmed cases is not available or is absent. A COVID-19 outbreak is a COVID-19 cluster where direct exposure between at least two of the test-confirmed cases can be identified or information on an alternative source of infection outside the setting is absent for the initial identified cases.10

Data from three sources, namely PHE HPZone data set, PHE Situations of Interest (SOI) data set and the HSE National Population Database (NPD), were used to calculate (1) outbreak rates by geographical area (regional and upper tier local authority (UTLA)) and industrial sector; and (2) attack rates of individual workplace outbreaks by enterprise size (small, 1–49 employees; medium, 50–249 employees; and large, 250 employees or more) and industrial sector. These three data sources are described in more detail in the following section.

HPZone data set

HPZone is a national web-based system for communicable disease control in England and is PHE’s case management system.11 It has direct import of laboratory data, receiving statutory infectious disease notifications and collecting contextual data of management of infectious disease cases and outbreaks, and other non-infectious environmental threats. During the COVID-19 pandemic, HPZone provides summary-level information about the COVID-19 situations (ie, outbreaks/clusters) that local health protection teams (HPTs) are responding to. HPTs receive information about suspected or confirmed cases of COVID-19 directly from workplaces or through ‘coincidence reports’ from NHS Test and Trace, where two or more individuals report in the same workplace. Test-confirmed cases are linked to HPZone through the Second Generation Surveillance System, which is the national laboratory reporting system used in England to capture routine laboratory data, including data on infectious diseases. The HPZone data are verified by epidemiologists from the PHE National Surveillance Cell if a situation is a confirmed outbreak or a cluster of COVID-19. This is done at a snapshot in time on a weekly basis for the previous week’s new situations. Outbreaks evolve over time. If the information about these outbreaks is not updated, for example to capture the increased number of confirmed cases as the outbreak develops, the data could underestimate the true size of the outbreak or clusters as more data become available over time about these outbreaks.

SOI data set

The SOI data set is a subset of outbreaks from the HPZone data set that are deemed to be more complex to manage and includes updates on the number of test-confirmed COVID-19 cases as the outbreaks evolve over time. At the time of the data analysis, there was no formal definition of a situation of interest. It is used operationally to share understanding of significant outbreaks due to their scale, impact and complexity. An SOI outbreak will be updated regularly until transmission is controlled and as such provides a dynamic tool to track the total number of confirmed cases for the outbreak.

National Population Database

The NPD includes geographically referenced estimates of the Great Britain (GB) population in geographical information system layers.12 The NPD groups the GB population into five themes: residential, sensitive (eg, schools, care homes, hospitals and prisons), transport, workplaces and leisure. The workplace layer provides information on individual workplaces including the number of employees, industry type (using Standard Industrial Classification (SIC)) and a spatial reference (address and postcode). The workplace information is extracted from the Office for National Statistics (ONS) Inter-Departmental Business Register13 at the enterprise level, with the data used in this analysis extracted in May 2019. This extract included information for two million UK businesses.

Outbreak rates and attack rates

Outbreak rate=the number of outbreaks in workplace settings/100 000 workplaces

Outbreak rate is defined as the proportion of workplace settings with COVID-19 outbreaks, expressed as the number of outbreaks per 100 000 workplaces. The numerator is the number of confirmed workplace outbreaks identified from HPZone. The denominator is the total number of workplaces identified from the NPD.

Attack rate=the number of test-confirmed COVID-19 cases in a workplace outbreak setting/100 employed in that setting

An attack rate measures the proportion of persons in an identified population who become infected during an outbreak.14 It indicates the potential extent of the transmission in an outbreak. It is defined here as the proportion of workers in a workplace that become cases of COVID-19 by the end of the outbreak, expressed as a percentage. The numerator is the number of test-confirmed COVID-19 cases in a workplace outbreak obtained from the SOI data set. The denominator is the number employed in that workplace obtained from the NPD.

The lists of outbreaks/clusters in the HPZone data set and the SOI data set are categorised into primary, secondary and tertiary contexts. Workplace is one of the primary contexts, for which the secondary contexts (categories) and the tertiary contexts (subcategories) are listed in table 1. All secondary contexts were included as sectors and were mapped against the SIC before matching them to the denominator data set.

Table 1

Public Health England classification of workplace settings, July 2020

Outbreak sites from the SOI records were linked to workplaces in the NPD through their postcode and business name. Unmatched SOI records were not included in the attack rate analysis. Furthermore, if the number of cases exceeded the number employed, the sites were excluded from the analysis. This may be due to underestimation of employment in the NPD for some workplace settings, such as crop production and warehouses where there is a reliance on temporary agency worker. Geographical coordinates were added to HPZone and SOI data from the ONS Postcode Directory15 using the postcode of the outbreak settings. The statistical software R was used for the analysis and record linkages; Microsoft Excel was used for data preparation and creating the charts. ArcGIS was used to create maps.

Patient and public involvement

Patients and the public were not involved in the design or conduct of the study.


In total, 1317 confirmed workplace outbreaks were identified from HPZone, of which 1305 could be mapped to NPD by postcode. In addition, 390 outbreaks were identified from the SOI data set, of which 285 could be linked directly to records in the NPD workplaces to add SIC and employment information. A further 21 outbreaks from the SOI data set, where no case numbers were recorded or where the number of cases exceeded the number employed, were removed. This leaves 264 SOI records of outbreaks, including a total 2649 confirmed COVID-19 cases, for the attack rate calculation. See online supplemental figure S1 on the geographical distribution of the outbreaks.

Outbreak rates by geographical area (region, UTLA)

Of the nine regions in England, the North West had the highest number of outbreaks, affecting 351 workplaces, as well as the highest rate of outbreaks (155 per 100 000 workplaces) (table 2). Of the 151 UTLAs, the largest numbers of workplace outbreaks were mainly observed in northern English towns and cities, with the highest outbreak rates registered in Blackburn with Darwen (387 per 100 000), Sandwell (351 per 100 000), Liverpool (349 per 100 000), Rochdale (277 per 100 000), Manchester (275 per 100 000) and Bradford (254 per 100 000).

Table 2

Number and rate of COVID-19 workplace outbreaks by English region, May–October 2020

Outbreak rates by sector

In comparison with other sectors, retailers had the highest number of outbreaks, affecting 219 workplaces, followed by manufacturers and packers of non-food products (195) and offices (193). However, after applying the denominator data, the highest outbreak rate was in manufacturers and packers of food (1672 per 100 000), based on 117 outbreaks out of 6998 workplaces. This was much higher than the outbreak rates for the remaining sectors, with warehouses and manufacturers and packers of non-food products the next highest at 385 per 100 000 workplaces and 308 per 100 000 workplaces, respectively (table 3).

Table 3

Number and rate of workplace outbreaks by sector in England, May–October 2020

Outbreak rates by region and sector

High outbreak rates in manufacturers and packers of food were observed consistently across seven regions, namely the West Midlands (3555 per 100 000 workplaces), Yorkshire and the Humber (3132 per 100 000 workplaces), North West (2926 per 100 000 workplaces), East Midlands (2031 per 100 000 workplace), East of England (1664 per 100 000), North East (1282 per 100 000 workplaces) and South West (638 per 100 000 workplaces) (table 4). In addition, high rates of outbreaks were observed in warehouse settings in the East Midlands and the North West, with an outbreak rate of 1524 per 100 000 workplaces and 793 per 100 000 workplaces, respectively (table 4). See online supplemental table S1 for more information on the outbreak rate for each combination of region and sector.

Table 4

Top 10 outbreak rates by English region and sector combined, May–October 2020

Attack rates by enterprise size

A minority (29%) of the outbreaks recorded in SOI were in small enterprises (<50 employees), but the proportion of small enterprises was higher for close contact services (83%) and restaurants and caterers (56%). The overall median attack rate was 3.4% for outbreaks in all enterprises. The median attack rate was 1.1% for outbreaks in large enterprises (250 employees or more), 4.3% in medium-sized enterprises (50–249 employees) and 17.8% in small enterprises (1–49 employees). The attack rates increased as the number employed at a workplace decreased.

Attack rates by sector

Outbreaks in close contact services had the largest attack rate (median 16.5%), which was based on 22 test-confirmed cases at 6 outbreak sites (table 5). The attack rates were also high for outbreaks in restaurants and caterers (median 10.3%), based on 49 test-confirmed cases at 14 sites; and in manufacturers and packers of non-food products (median 6.7%), which was based on 270 cases at 29 sites. Most of the outbreaks (162 of 264 outbreaks) had an attack rate less than 6%. However, in a small number of outbreaks (57 of 264), the attack rate was over 15% (see online supplemental figure S2).

Table 5

Median attack rates of workplace outbreaks by sector in England, May–October 2020


Our study has used the number of confirmed COVID-19 outbreaks recorded in PHE information system and combined them with relevant denominator data held by HSE to calculate outbreak rates and attack rates by sector and geographical area. A relatively large number of outbreaks were observed in some workplace settings, including retail, manufacturers and packers of non-food products and offices. After applying the denominator data of the total number of the relevant settings, manufacturers and packers of food had the highest outbreak rates and this was consistent across seven English regions. Manufacturers and packers of food are part of the national infrastructure and these workplaces were kept open throughout the pandemic even during the national lockdown. Outbreaks of COVID-19 in manufacturers and packers of food have been frequently reported in the literature and in the media in many countries.16 However, only a few studies have investigated the potential transmission risk factors in this type of workplace settings.17 High rates of outbreaks were found in sectors where production demands are high and workers cannot work from home. It will be important to continue to monitor outbreak rates by industrial sector as the country is moving out of the pandemic and more sectors are increasing their work capacity.

Our study has also used data from the public health COVID-19 outbreak management records to calculate infection attack rates. This allows comparison of the potential extent of transmission between outbreaks in different workplace settings. Close contact services and restaurants/caterers had the highest attack rates, which were mostly associated with outbreaks in small enterprises. Manufacturers and packers of non-food products also had relatively large attack rates but were mostly associated with outbreaks in medium and large enterprises. However, it is worth noting that the SOI data are skewed towards large and more impactful outbreaks. Furthermore, more detailed analysis of attack rates is limited by low numbers of outbreaks in certain industrial sectors, such as primary producers which include fruit and vegetable growers, animal and animal products.

Our analysis carried some limitations. The potential underidentification of outbreaks in small enterprises (<50 employees) in the numerator coupled with the vast number of small enterprises in the denominator may greatly underestimate the outbreak rates. This could particularly impact on small business-dominated sectors, such as close contact services and restaurants/caterers, where estimated outbreak rates were relatively low, but attack rates were relatively high.

The number of outbreaks reported to HPZone could be affected by national-level and local-level operational changes. For example, as case load increased in September and October 2020, some HPTs transferred the management of some outbreaks/clusters to local authorities. As a result, HPZone no longer represents a comprehensive list of COVID-19 outbreaks/clusters in England. This will affect the ability to measure the changes of outbreak occurrence or outbreak rate over time, as well as the ability to measure regional variations, but it remains valuable to conduct sector comparisons.

SOI outbreak data are a subset of the HPZone outbreaks/clusters. Data entry was through a separate mechanism. The proportion of HPZone outbreaks/clusters in the workplace being reported as SOI decreased over time, especially from September 2020 onwards as HPTs were under pressure to respond to an increasing number of outbreaks. However, it is unclear if these decreases are biased towards certain sectors. It remains valuable to assess the attack rates of individual outbreaks across different sectors.

NPD workplace information also has some limitations in providing reliable working population data as the denominator, which will cause imprecisions in the attack rate calculation. In our study, NPD data represent the distribution of the GB population prepandemic; the number of employees in some workplace settings will be reduced during the pandemic due to social distancing measures. This may cause underestimation of the attack rates due to overestimation of the denominator. The level of underestimation varies by sector, with some sectors completely closed and others kept operating in full capacity throughout the pandemic. However, the impact of this limitation may attenuate as society gradually opens.

In addition, the NPD workplace information may not capture the number of employees in the transient workforce or working in irregular patterns, for example, seasonal workers in the agriculture sector. Employees in some other workplaces, such as in distribution centres, transportation of goods between depots, and in construction, will be accounted for, but their non-fixed working locations will not be well represented by a single geographical reference (eg, postcode of the company address). Similarly, agency staff and subcontractors are unlikely to be accounted for at the location where they carry out their work activities. This may cause overestimation of the attack rate due to the underestimation of the denominator.

Early identification of COVID-19 outbreaks/clusters and visualisation of their geographical distribution can provide a rapid assessment of where the SARS-CoV-2 transmission is occurring. A large number of COVID-19 outbreaks/clusters have been reported, both in scientific literature and in the media, in a wide range of mostly indoor settings across the world.3 18 Most of the COVID-19 clusters will be in residential settings, particularly in households, due to the increased risk of transmission caused by close and frequent contact.19 However, a household cluster will not result in a large outbreak without the virus spreading beyond the household setting. Some of these individuals in households could also travel to other settings including the workplaces. Transmission is a continuous risk. It is difficult to establish where transmission really occurred. Community transmission will also occur through social gathering, particularly gathering outdoors, shopping in supermarkets or using public transport. However, it is difficult to identify outbreaks/clusters from the large number of transient populations in these settings without a rigorous surveillance system for widespread testing and detailed contact tracing. This may underestimate the relative importance of the potential transmission in these less well-defined settings or population.

Since our study, the approach of using the suitable denominator data to calculate outbreak rates has been adopted by the UK Joint Biosecurity Centre and will be embedded in their regular national surveillance analysis and reporting on workplace outbreaks and outbreaks rates. Although this study was only able to analyse the workplace outbreak data in England, the same approach can be applied to the calculation of outbreak rates and attack rates in other countries in the UK, Europe and USA, where the relevant available data sources can be explored. The same approach can also be applied to the calculation for other types of settings, such as care homes, hospitals, schools and prisons. These will potentially guide interventions to target high-risk areas and to limit the spread of the virus.

This study was not able to assess the potential changes in COVID-19 outbreak rates and attack rates over time due to, in part, the limited time period of data and the inconsistency in recording outbreaks/clusters in the HPZone and SOI data sets. Further consideration will be to analyse the more enhanced outbreak/cluster data collected over time from NHS Test and Trace to identify past and emerging trends.

Evidence shows that there could be marked heterogeneity in the characteristics of SARS-CoV-2 transmission,4 with the majority (~80%) of the secondary transmission caused by a very small proportion of SARS-CoV-2-infected persons, and outbreaks of COVID-19 distributed unevenly in certain settings and geographical locations.20 Our study has found increased rates of outbreak in certain industrial sectors and geographical regions, and a large variation of the size of the attack rates. The variation of the rates may be impacted by the type of work activities, the size of the enterprises, the transmission risk and the intervention strategies to limit the transmission in these sectors. The risk of transmission will also be associated with the behavioural and social factors of the individuals, the environment and the control measures that influence transmission dynamics of the virus in certain settings.3

The current study has investigated the patterns and rates of COVID-19 outbreaks in England. Further studies, as part of the National Core Study programme, will investigate and identify the characteristics of the outbreak settings that could increase risk of transmission. A comprehensive epidemiological field study has been designed and commissioned to collect data from live COVID-19 outbreaks in workplace settings to better understand the transmission risk factors and transmission routes.8

Data availability statement

Data may be obtained from a third party and are not publicly available. All data relevant to the study are included in the article or uploaded as supplementary information. The data used to support the findings of the study are included in the references within this paper. No additional data available.

Ethics statements

Patient consent for publication


We would like to thank Gillian Frost for her advice on the statistical analysis.


Supplementary materials


  • Contributors Conceptualisation: YC, TA and F-MK. Methodology, TA, YC and CF. Validation: YC, TA, CF and F-MK. Formal analysis: TA. Investigation: YC, TA and CF. Data curation: TA and CF. Writing - original draft preparation: YC, TA and CF. Writing - review and editing: YC, TA, CF and F-MK. Visualisation: TA. Supervision: YC and F-MK. Project administration: F-MK and YC. Funding acquisition: UK COVID-19 National Core Studies Consortium. Guarantor: YC.

  • Funding This work is supported by funding from the PROTECT COVID-19 National Core Study on Transmission and Environment, managed by the Health and Safety Executive on behalf of the HM Government.

  • Disclaimer The opinions and assertions contained herein are private views of the authors and do not necessarily reflect those of the Health and Safety Executive or Public Health England.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.