key: cord-0965338-ncy7o64c
authors: Verbeeck, J.; Vanersmissen, L.; Peeters, J.; Klamer, S.; Hancart, S.; Lernout, T.; Dewatripont, M.; Godderis, L.; Molenberghs, G.
title: Confirmed COVID-19 cases per economic activity during Autumn wave in Belgium
date: 2021-06-02
journal: nan
DOI: 10.1101/2021.05.31.21256946
sha: 2a47882e96b059db169dc96488a36affb1caf95e
doc_id: 965338
cord_uid: ncy7o64c

Objective: To assess the COVID19 incidence per economic activity during the Autumn wave 2020 in Belgium. Methods: The 14-day incidence of confirmed COVID19 cases per NACEBEL code is described in the periods immediately preceding the Belgian more strict measures of October 19, 2020, and is evaluated longitudinally by a GaussianGaussian modelling twostage approach. Additionally, the number of high risk contacts in working segments and regions is described. Results: The peak of COVID19 14day incidence in most NACEBEL sectors is reached in the period October 20 November 2, 2020 and was considerably higher than average in human health activities, residential care activities, fitness facilities, human resource provision, hairdressing and other beauty treatment and some public service activities. Human health activities, residential care activities, food and beverage service activities, hotels, arts, food retail activities, and human resources provision have high pre-lockdown incidences. The frequency of index cases that report more than two high risk contacts is increasing over time in all sectors. Conclusion: Despite the restrictive protocols present in many sectors before the Autumn wave, employees in activities where close contact with others is high, show increased risk of COVID19 infection. Especially sports activities are among the highest risk activities. Finally, the increasing amount of high risk contacts by COVID19 confirmed cases is compatible with the decreasing motivation over time to adhere to the measures.

Since the SARS-CoV-2 virus was identified in Wuhan (Hubei, China) in December 2019, the virus spread globally, causing the largest pandemic in a century. Managing this pandemic was a challenge for many countries.

Soon it was clear that the virus was airborne and spread through close human contact. In Italy it was estimated that, up to May 2020, COVID-19 was probably contracted at work in 30% of cases at working age. [2] Many countries implemented interventions to limit physical contact in private life and at work. As little was known on the role of various actors and activities on the spread of SARS-CoV-2 at the beginning of the first wave, a general lockdown to manage spread and prevent health care system collapse was introduced by many governments. Despite adequately controlling viral spread, a full lockdown leads in time to serious economic and well-being issues; hence, more targeted tools are necessary, such as the restriction and re-opening of economic activities. Therefore, it is essential to gather knowledge on the dynamics of the virus and the risk of contracting COVID-19 in different economic activities.

Economic activities where social distancing is challenging, have been related to clusters of COVID-19 cases. In Japan, 61 clusters of COVID-19 were tracked to health care (30%) and other care (16%) facilities, cultural activities (11%), gyms (8%), ceremonies (3%) and transport (2%). [3] COVID-19 outbreaks have been documented in economic activities of Manufacturing, Agriculture/Forestry/Fishing/Hunting, and Transportation/Warehousing in the US [4] and Canada, [5] while several sources report COVID-19 outbreaks in poultry, meat and food processing companies [6] and residential care facilities. [7, 8] Employees in bars and restaurants have been shown to have increased COVID-19 risk [1, 9] or were involved in clusters of COVID-19 [10] . This was confirmed by a study of the European Centre for Disease Control (ECDC) that examined the number of clusters per sector during the first wave in 15 European countries and the United Kingdom. [11] In Norway, the odds of COVID-19 was 1.1-3 times higher during the first wave in nurses, doctors, dentists, physiotherapists, bus, tram, and taxi drivers relative to the general population at working age. [1] During the second wave, however, the odds did not increase for some contact professions suggesting that taking appropriate measures at work can contain the spread of the virus at the workplace.

Despite the observed association between activities and COVID-19, it does not provide information on the effect of opening or closing sectors on the spread of SARS-CoV-2. In some US states, closing and re-opening of bars, restaurant and schools and wearing masks were found to have a significant effect on the spread of the virus, hospitalisations and deaths. [12, 13] A study combining mobility data with confirmed COVID-19 cases examined the effect of re-opening single economic activities on viral spread [14] : restaurants, gyms, hotels, cafes, and religious organizations were identified to produce the largest increase in infections when re-opened under pre-pandemic conditions. Therefore, many policy makers have decided to allow re-opening of these locations only with reduced visitors and visitor time to control SARS-CoV-2 spread. To our knowledge, only one study investigated different opening strategies. In selected municipalities in Norway, bartenders and waiters had similar rates of COVID-19 in areas with full and partial bans on serving. [9] In Belgium, a general, national strict lockdown was installed on 18 March 2020, closing schools and suspending all cultural, leisure, and non-essential activities. [15] These extreme measures proved successful in decreasing the daily new infections and COVID-19 hospitalisations to a level where the government felt confident to gradually . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint alleviate the lockdown measures. While most activities could resume over Summer 2020 with strict protocols, including restrictions on capacity, dwelling time, and social contacts, in September 2020 these restrictions were relaxed despite indication of increased circulation of SARS-CoV-2. [15] Since October 2020, progressively more restrictive measures were implemented to contain the second COVID-19 wave, ultimately leading to a closure of bars and restaurants on 19 October, and further tightening on 2 November (closure of social and some economic activities; no school closure nor movement restriction). [15] Arguably due to the consistency of measures and restrictions on end of year festivities, Belgium managed to avoid further flare-ups until March 2021. [16] .

By linking COVID-19 confirmed cases of employees with the NACE-BEL code [17] of the main economic activity of their employer, the COVID-19 incidence is examined over Autumn and Winter 2020. A cross-sectional analysis of the COVID-19 14-day incidence immediately prior to 19 October 2020 is contrasted with a longitudinal analysis of the incidence over the entire Autumn, to examine the effectiveness of the soft lockdown. Finally, contact tracing of confirmed COVID-19 cases gives insights into the high-risk contacts in specific work segments and regions.

The Belgian institute for health, Sciensano registers daily all confirmed COVID-19 cases, [18] and forwards them to the National Social Security Office (NSSO), who in turns links these to the Dimona database of active employees. The Dimona database covers most of the employees (∼ 4.5 million), such as employees in private and public sectors, interim employment and student job, but includes neither self-employed nor foreign workers that are not subjected to the Belgian social security scheme.

The data are aggregated at NSSO to weekly incidences (number of cases per 100,000) by NACE-BEL code.

NACE-BEL classifies workplaces into 21 main economic sectors (level 1) and then further into ever finer subcategories (levels 2 -5), with 943 subcategories at level 5. [17] Although some companies may be active in more than one sector, only the main NACE-BEL code is assigned. This limitation is particularly important for education, because a majority of schools provide both primary and secondary education, while all employees are categorized as secondary school personnel.

As the code is given at company level, no distinction is made between activity within the company (e.g., administrative work in metal industry). No information is available on exact employment location (omitting information on telework or temporary unemployment).

Finally, the actual source of infection, particularly workplace or elsewhere, is unavailable. Hence, the data are useful to compare the incidence evolution with overall trends in the working population and in the general population.

Data on workplace high-risk contacts of confirmed COVID 19 cases are available from the IDEWE contact tracing database. IDEWE is one of the largest occupational health services in Belgium and responsible for the well-being of approximately 800,000 employees from 33,000 companies or institutions, covering more than 20% of Belgian workers. IDEWE is active in all economic sectors, with a predominance in healthcare. More than 20% . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint of all employees, under medical surveillance of IDEWE, are working in the healthcare sector.

Since 29 October 2020, the COVID-Contact Tracing application, developed by IDEWE for its employers, registers in a standardized manner information on COVID-19 incidences and on high-and low-risk contacts of index cases. Most of the index cases are employees, but also seasonal workers, interns, pupils and external people working at companies' and institutions' premises that tested positive are contacted. Contact tracing of high-and low-risk contacts, defined according to Sciensano guidelines [19] , within the company is performed.

Measures are taken for within-company high-risk contacts (testing, 7 or 10 days quarantine). Contacts exterior to the company are identified and followed-up through the regular contact tracing. Employers are grouped by customer segment in one of 9 regional offices, named after the city where they are located. Most Belgian provinces have one regional office, except Antwerp that is served by the regions Antwerpen, Mechelen, and Turnhout; and Namur that serves all of Wallonia. IDEWE distinguishes between ten customer segments based on NACE codes, but an exact link with the NSSO codes is not fully possible. Some larger IDEWE companies have organized contact tracing via their internal prevention service, which is not included in this analysis, potentially leading to underestimation of index cases. For some segments this underestimation might be more important.

The NSSO weekly incidences from 8 September 2020 to 25 January 2021 are mapped to 14-day incidences by joining two consecutive weeks. Adjacent 14-day incidences share an overlapping week. Details on the calculation of the 95% confidence interval for the incidence is available in online supplementary annex A.

For the 5 NACE-BEL levels, the highest incidences in the two 14-day periods before the measures of 19

October 2020 (29 September-12 Oct 2020; 6-19 October 2020) are presented, together with the 14-day incidence over all work sectors (∼ 4.5 million individuals) and in the general population (∼ 11.5 million individuals).

The longitudinal profile of the 14-day incidences is modelled by fitting so-called Gaussian-Gaussian functions, in a two-step approach (online supplementary annex B).

Precision in small NACE-BEL sectors is low. Hence, for levels 1, 2, and 3, only sectors with a minimum of 10,000 employees are analyzed, for levels 4 and 5, the minimum is 3000 and 1500, respectively.

For the index cases that were reported via IDEWE tracing between 29 October 2020 and 18 February 2021, the mean number of high-risk contacts and the four-weekly percentage of index cases with two or more high-risk contacts are described per work segment and per region. Under-reporting may arise because the tracing application reports zero high-risk contacts for an index case by default, which might be incorrect for an index that is non-contactable or refuses to respond. Over-reporting might occur in the education segment. The contact tracing for schools is performed by Student Guidance Centres (SGC), who forward the contract tracing of pupils to IDEWE if employees might be involved as high-or low-risk contact. The SGC tracing is centre dependent and often only index cases with high-risk contacts are forwarded to IDEWE.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint

Pre-peak period At NACE-BEL level 1, among sectors with a minimum of 10,000 employees, Arts, entertainment and Recreat Accommodation and food service activities; Human health and social work activities; Public administration defence, compulsory social security; and Education show a 14-day incidence above the NACE-BEL averag both periods before 19 October 2020 (Figure 1 and online Supplementary Table 1 ). CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint From levels 3 -5 it follows that within the Arts, entertainment and Recreation sector, mainly Sports activities have high incidence before 19 October 2020 (Figure 1 and online Supplementary Tables 2 and 3 ). Within sports, high incidences come from activities of sport clubs (especially football clubs,), fitness activities, and other sport activities (Figure 1 and online Supplementary Table 4 and 5). As the human health and social work sector is subject to frequent close contacts, it is no surprise that its incidence is among the highest among the lower level sectors (Figure 1 and online Supplementary data). The sports activity sector has higher incidence still. Also, education organized by the regional authorities (sector 85311) has a higher incidence than the care sector, unlike general education (sector 85319) and other levels of education (sector 854, 855) ( Figure 1 and online Supplementary data).

The Accommodation and food service incidence is comparable to that of health and care, and is similar between hotels, restaurants, and bars between 29 September-12 October, while hotels are doing slightly better All NACE-BEL sectors with their corresponding 14-day incidence and confidence interval can be found in the online Supplementary file. Various rankings or aggregates of sectors can be easily constructed from this file.

The pre-peak period can further be studied via the longitudinal profile, which is represented by the pre-peak plateau parameter ߜ ௦ ଵ in the Gaussian-Gaussian model. Although the plateau parameter at level 1 indicates no significant differences in incidences before the peak, the incidences in Sports activities, more specifically Activities of sport clubs and Residential care for elderly and disabled are significantly elevated (Figure 2 ). At level 4, additionally Child-day care, Organisation of conventions and trade shows, and some Wholesale and retail trade sectors have an increased incidence before the peak (Figure 2 ).

Both the cross-sectional and longitudinal analyses show that for the majority of sectors the Autumn wave reaches the incidence peak in the period of 20 October-2 November 2020 ( Figure 3 and online Supplementary file).

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint

The longitudinal analysis shows that the peak is significantly higher for Human health and social work activitie both for the Human health activities, and the Residential care activities (Figures 2 and 3) . Within Human hea activities, both Hospitals and General medical practice have a higher incidence, while for Residential care activities, most sectors show an extreme peak (sectors 872, 873, 879). At level 4, additionally Fitness centre activities, non-medical contact professions, General administration, Federal and local police, Pharmacies, an Other human resource provision have a significantly elevated peak incidence (Figure 2 ). Figure 2 : Forest plots of characteristics of the longitudinal profile of selected sectors. The plateau before after the peak are related to the 14-day incidence. The height of the peak is the 14-day incidence at the high moment in the curve and the half-width of the peak is the number of weeks it takes for the curve to reduce 14-day incidence by a half.

In the longitudinal analyses two parameters inform us about the incidences after the peak. The plateau after t peak, , captures the incidence to which the sector decreased, while the half-width, , quantifies t ities, ealth re and re and ighest ce the r the s the . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint time in weeks for the incidences to decrease.

Human health and social work activities, both for the Human health activities, and the Residential care activities, have a significantly higher post-peak incidence level, while the latter sector also has a larger half-width ( Figures   2 and 3) . Within Human health activities, Hospitals have a higher post-peak incidence, while for the Residential care activities, most sectors show both an increased incidence after the peak (sector 871, 872, 873), and a longer half-width (sector 871, 873). At Level4, Activities of sports clubs, and Other human resource provision (sector 7830) had a significantly elevated post-peak incidence (Figure 2 ). For most sectors the post-peak plateau is higher than the pre-peak one (Figure 4) . The number of index cases for the segments 'construction', 'emergency services' and 'agriculture' and for the region 'Namur' was very low during some time periods, leading to imprecise estimates.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint

We studied the 14-day incidence of COVID-19 per economic activity in Belgium, cross-sectionally, during uptick of the Autumn wave and longitudinally during the entire wave. Measures prior 19 October 2020 [15] described in online supplementary annex C. With the September protocols in place, incidence was increased in: sports activities; hotels, bars restaurants; arts; public transport; certain types of stores; child day-care; public law enforcement; and educa during the build-up of the Autumn wave. In many of these sectors, incidence exceeded that of naturally high r sectors such as human health activities and residential care activities. Sports activities, strongly driven is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. football club activities, had the highest incidence at almost all levels before 19 October 2020.

An relevant metric is a sector's peak incidence. Apart from human health activities and residential care activities, also other human resource provision, fitness facilities, hairdressing and beauty treatment and some public services are high-peak activities. Before the peak, again human health activities, residential care activities, but also sports activities had a significantly elevated incidence.

Economic activities with increased incidence are mostly sectors with the professional need for close proximity to other people. Based on the risk inflation factor suggested by Jobs At Risk Index (JARI) [21] , in occupations that bring employees into close contact with others and/or with infections, such as in health care activities, residential care, prison and undertakers, a higher COVID-19 incidence is expected. However, in Belgium sectors that are labelled by JARI as occupations with only close proximity and no regular contact with disease (education, law enforcement, fitness, beauty, retail, musicians/actors, restaurants and bars, and transport) have an equally high or further elevated incidence. Since index cases in the health care segment report relative low amount of high-risk contacts, this suggests that health care employees are effective in avoiding high-risk contacts and/or health care infection protective protocols are efficient. The restrictive rules before the second wave may have been insufficient for the close proximity occupations. Arguably, employees' behaviour in these sectors could be more risky (on the work floor and/or beyond), as evidences by increased reporting of high-risk contacts by Public transport for example. Additionally, restrictive protocols may be sufficient during periods of low-level virus circulation but progressively less with increasing incidence.

Our results contrast with the findings of no increased incidence in sports activities of the SafeActive survey on self-reported COVID-19 in a sample of fitness and exercise facilities [22] and that of no difference in incidence in a sample of occupations in a UK survey [23] . Our findings agree with the analysis of mobility data, identifying gyms, bars and restaurants as a high-risk location of infection, [14] and the reports of clusters of COVID-19 and outbreaks [1, 3, 4, 5, 6, 7, 8, 9, 10] . Various high-incidence sectors are mentioned as potential location of infection by index patients during contact tracing. Places mentioned most as activity or event visited two weeks before infection are restaurants and bars, sports activities, public activities, wellness and hairdressers and fitness facilities (Flemish contact tracing). While no formal proof for the place of infection, the increased incidence in these sectors is striking.

On 19 October 2020 more stringent measures were issued in Belgium to control the emerging Autumn COVID-19 wave [15] (online supplementary Annex D). On 2 November 2020, non-essential shops, non-medical contact professions, bars, and restaurants professions were closed. Hotels remained open. The effect is these measures is seen in the timing of peak incidence, which for most sectors is in the 2-week period past 19 October 2020, for the general population, sectors with restricted activity, and sectors that remained active, such as human health activities, residential care activities, and essential shops. Despite their forefront position [24] employees in the food industry seem adequately protected and well informed on protective measures in Belgium, as incidences in food retail decreased to the all-sector average after the peak; the number of high-risk contacts reported by Accommodation & food trade and industry is low.

The effect of the measures is also seen in width and height of post-peak incidence. Unsurprisingly, the peak . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint this version posted June 2, 2021. ; https://doi.org/10.1101/2021.05.31.21256946 doi: medRxiv preprint width is significantly broader for human health activities and residential care activities. For most activities, postpeak incidence is higher than pre-peak, reflecting controlled but increased SARS-CoV-2 circulation. Human health activities, residential care activities, activities of sports clubs and other human resource provision have a significantly higher post-peak incidence. Although incidence in sports activities is largely influenced by virtually unrestricted activities of professional football clubs, also fitness facilities, other sports activities, and activities of leagues and sports federations have an increased peak and/or pre-lockdown incidence.

The success of the measures to curb the second wave notwithstanding, the increasing number of index cases over time reporting 2 or more high-risk contacts potentially demonstrates the decreasing motivation to adhere to these measures. Evidently, increasing high-risk behaviour by a part of the general population may result in delays towards relieving non-pharmaceutical interventions by the decision makers.

Further insights on the COVID-19 incidence per economic activity should be gained from including information on self-employed workers.

The data analyzed here includes all confirmed COVID-19 cases among employees, interim employment, and job students, across all economic activities; it is thus more complete than information based on a random sample on a restricted set of occupations or a self-completed survey in a sample. [23] Besides the cross-sectional description of incidences, several aspects of the COVID-19 wave are compared via a longitudinal Gaussian-Gaussian model.

The absence of information on COVID-19 incidence in self-employed workers is a limitation. As the proportion of self-employed workers per NACE-BEL sector is variable, this might have variable impact. The data depends on the COVID-19 testing strategy, which has changed on 20 October 2020. To safeguard testing laboratory capacity, testing of asymptomatic individuals following a high-risk contact was suspended until 23 November 2020. However, this likely impacts most sectors equally. NACE-BEL codes are assigned only to the main activity of a company and no inference can be made regarding the location of infection (workplace or elsewhere) nor the location of employment (work, telework, temporarily unemployed). The results, however, do reflect the behaviour and potential risk of spreading COVID-19 by employees in a sector.

Despite the limitations of the data, our results give clear insights in the incidence and the effect of restrictive protocols on COVID-19 incidence per NACE-BEL sector. These insights offer guidance to policy makers on which economic activity to restrict or relieve to control the COVID-19 pandemic and keep the work floor as safe as possible.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 

Not applicable.

Occupational risk of COVID-19 in the 1st vs 2nd wave of infection

Occupational factors in the COVID-19 pandemic in Italy: compensation claims applications support establishing an occupational surveillance system

Clusters of coronavirus disease in communities

Racial and ethnic disparities among COVID-19 cases in 15 workplace outbreaks by industry sector-Utah

COVID-19 workplace outbreaks by industry sector and their associated household transmission

Meat plants-a new front line in the covid-19 pandemic

Mortality associated with COVID-19 outbreaks in care homes: early international evidence, 2020. LTCcovid.org, International Long-Term Care Policy Network

Why, in almost all countries, was residential care for older people so badly affected by COVID-19?

COVID-19 among bartenders and waiters before and after pub lockdown

Clusters of coronavirus disease (COVID-19) in pubs, bars and nightclubs in Bangkok

European Centre for Disease Prevention and Control. COVID-19 clusters and outbreaks in occupational settings in the EU/EEA and the UK

Strong impact of closing schools, closing bars and wearing masks during the COVID-19 pandemic: results from a simple and revealing analysis. medRxiv

Association of state-issued mask mandates and allowing on premises restaurant dining with county-level COVID-19 case and death growth rates -United States

Mobility network models of COVID-19 explain inequities and inform reopening

The Belgian government. Coronavirus COVID-19

European Centre for Disease Prevention and Control. COVID-19 country overviews

Covid-19

Coronavirus covid-19: Classification of contacts

Models for discrete longitudinal data

The Jobs at Risk Index (JARI)

An independent assessment of COVID 19 cases reported in fitness clubs and leisure facilities across Europe: a THiNK Active report

Coronavirus (COVID-19) Infection Survey: characteristics of people testing positive for COVID-19 in England

Food system workers are the unexpected but under protected COVID heroes