Literature DB >> 32428031

Work-related COVID-19 transmission in six Asian countries/areas: A follow-up study.

Fan-Yun Lan1,2, Chih-Fu Wei1, Yu-Tien Hsu3, David C Christiani1, Stefanos N Kales1,4.   

Abstract

OBJECTIVE: There is limited evidence of work-related transmission in the emerging coronaviral pandemic. We aimed to identify high-risk occupations for early coronavirus disease 2019 (COVID-19) local transmission.
METHODS: In this observational study, we extracted confirmed COVID-19 cases from governmental investigation reports in Hong Kong, Japan, Singapore, Taiwan, Thailand, and Vietnam. We followed each country/area for 40 days after its first locally transmitted case, and excluded all imported cases. We defined a possible work-related case as a worker with evidence of close contact with another confirmed case due to work, or an unknown contact history but likely to be infected in the working environment (e.g. an airport taxi driver). We calculated the case number for each occupation, and illustrated the temporal distribution of all possible work-related cases and healthcare worker (HCW) cases. The temporal distribution was further defined as early outbreak (the earliest 10 days of the following period) and late outbreak (11th to 40th days of the following period).
RESULTS: We identified 103 possible work-related cases (14.9%) among a total of 690 local transmissions. The five occupation groups with the most cases were healthcare workers (HCWs) (22%), drivers and transport workers (18%), services and sales workers (18%), cleaning and domestic workers (9%) and public safety workers (7%). Possible work-related transmission played a substantial role in early outbreak (47.7% of early cases). Occupations at risk varied from early outbreak (predominantly services and sales workers, drivers, construction laborers, and religious professionals) to late outbreak (predominantly HCWs, drivers, cleaning and domestic workers, police officers, and religious professionals).
CONCLUSIONS: Work-related transmission is considerable in early COVID-19 outbreaks, and the elevated risk of infection was not limited to HCW. Implementing preventive/surveillance strategies for high-risk working populations is warranted.

Entities:  

Mesh:

Year:  2020        PMID: 32428031      PMCID: PMC7237000          DOI: 10.1371/journal.pone.0233588

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Coronavirus disease 2019 (COVID-19) was declared by the World Health Organization (WHO) as a pandemic on March 11, 2020 and its local transmission has been reported in many countries [1]. The transmission pathways and the related risk factors are of vital interest in efforts to control the outbreak [2-4]. Work-related transmission is a crucial contributor to infectious disease outbreaks. The characteristics of SARS-CoV-2 virus and its transmission patterns could lead to high transmission rates among workers. For example, cases of COVID-19 largely present with mild or no symptoms [5]. Also, some studies have found similar transmissibility from asymptomatic and symptomatic patients [6-8]. These characteristics could lead to a higher probability of work-related transmission as people with mild symptoms could continue to work, travel or otherwise conduct business and spread the disease to others during work or commuting. Furthermore, the infected workers can subsequently transmit the virus to other people in their households and communities. Therefore, it is contingent to better understand the epidemiology of work-related transmission of COVID-19 to implement evidence-based prevention and protection strategies in workplaces. Most of the studies to date focus on occupational exposure among healthcare workers (HCWs). Work-related transmission among HCWs constituted a large proportion in previous coronavirus outbreaks. HCWs comprised 37–63% of suspected severe acute respiratory syndrome (SARS) cases in highly affected Asian countries, and around 43.5% of Middle East respiratory syndrome (MERS) cases [9-11]. There was high prevalence of infection among HCWs despite the introduction of precautions against nosocomial transmission [12,13]. In contrast, there is limited discussion on the work-related risks among workers such as taxi drivers, tour guides, cleaners and janitors, and civil servants, who have frequent contact with the public in their daily routines or have workplaces with higher risks of virus exposure [14]. In this study, we aimed to identify the occupations at higher risk of COVID-19 transmission, and to explore the temporal distribution of work-related cases among local transmission.

Materials and methods

Study population selection

We extracted and included all locally transmitted COVID-19 confirmed cases from the publicized government investigation reports from six Asian countries/areas, including Hong Kong [15], Japan [16], Singapore [17], Taiwan [18], Thailand [19], and Vietnam [20]. These countries/areas were selected since they shared some common temporo-spatial characteristics. First, they are proximal to Mainland China, where the first outbreak of COVID-19 was reported. Second, the first cases of these countries/areas were imported cases from Mainland China in mid-January. Third, the first locally transmitted cases in these countries/areas were identified around late January to early February. We followed each country/area for forty days since the report of the first locally transmitted case and excluded the imported cases. The study population selection process is presented in Fig 1.
Fig 1

Study population selection process.

Categorization of work-related cases

The investigation reports of the six countries/areas mostly included case information such as age, sex, and brief contact/medical history. An example is: “The new case was a 35 year-old female health care worker, and had close contacts with the X confirmed case [19].” There were also sections indicating infection clusters: “Four of the confirmed cases (Cases W, X, Y and Z) are linked to the XXX construction site [17].” Occupational history was not always available. In most cases, if the contact history was obvious such as family cluster, the report would likely lack an occupational description. Based on the available information, each case report was reviewed by two occupational physicians and categorized for work-relatedness. Subsequently, the possible work-related cases were grouped into two categories based on whether the transmission source was known: Category 1: had clear close contact with a confirmed case due to work, such as a registered nurse having a history of directly caring for a patient who is an index confirmed case; and Category 2: unknown transmission source; no apparent contact history but likely to be infected in the working environment, such as an airport taxi driver without clear contact history to any confirmed case. The cases with occupations and contact histories were coded according to the International Standard Classification of Occupations, 2008 (ISCO-08) [21]. We defined health professionals, medical doctors, and nursing professionals as healthcare workers (HCWs) regarding the high risk of infection due to the work. We further grouped the occupations into drivers and transport workers, services and sales workers, cleaning and domestic workers, public safety workers, religious workers, construction workers, and other groups according to the jobs similarity. All differences between the occupation physicians were reviewed by the third investigator, who is a physician-epidemiologist to reach a consensus.

Statistical analysis

Descriptive analysis was performed to compare the trends of daily reported cases in the locally transmitted cases, work-related cases, and HCW groups. For each country/area, we calculated the intervals between the first reported locally transmitted case and the first reported work-related case, as well as the interval between the first reported locally transmitted case and the first reported HCW case. We also summarized the number of cases for each occupation across country/area and stratified the cases into early and late transmission periods. We defined early transmission period as the first 10 days from when the first locally transmitted case was reported, and late transmission period as the 11th to 40th day of the study period. We enlisted the most common occupations in each period and compared the distribution of occupations in order to examine the temporal difference. We performed Chi-squared tests or Fisher exact tests to compare the proportions of work-related cases and HCW cases among all local transmissions between early and late transmission periods. We also conducted sensitivity analysis comparing the results between the six countries/areas and five countries/areas excluding Japan. We excluded Japan due to its different case reporting system from other countries/areas. Unlike other countries/areas that have central reporting systems providing cases’ occupation and other contact history in a standardized form, Japan’s reporting system is prefecture-based, where each prefecture reports separately, without consistent occupational coding. For example, some prefectures reported a case as a taxi driver; while some prefectures only reported a driver, without specifying the type of vehicle he/she drove [16,22,23]. Differences in reporting mechanisms and case information across prefectures could potentially bias the results. The descriptive analysis was performed by R software (version 3.6.2). The figures were plotted by Microsoft® EXCEL™.

Results

We identified 2,002 officially confirmed COVID-19 cases within the designated 40-day interval among the six countries/areas. We excluded 1,312 imported cases and included 690 locally transmitted cases in the final analysis. The cases included in this study were reported between January 23, 2020 and March 14, 2020 (S1 Table). 103 possible work-related cases were included for analysis (including 37 cases from Category 1 and 66 from Category 2), accounting for 15% of local transmissions. Among the possible work-related cases, 22% were HCW. In addition to HCWs, we identified other occupations that were at higher risk of work-related transmission. The high-risk occupations included car, taxi and van drivers (N = 15), shop salesperson (N = 7), domestic housekeepers (N = 7), religious professionals (N = 6), construction laborers (N = 5), tour guides (N = 5), and so on. In terms of occupation grouping, the groups with the most cases were HCWs, drivers and transport workers, services and sales workers, cleaning and domestic workers, and public safety workers. (Table 1)
Table 1

Possible work-related COVID-19 cases categorized by occupation.

Occupation groupN (%)Occupation (ISCO-08)N (%)
Health professional (Healthcare workers)23 (22)Other health professionals10 (10)
Nursing professionals10 (10)
Medical doctors3 (3)
Drivers and Transport workers19 (18)Car, taxi and van drivers15 (15)
Locomotive engine drivers and related workers2 (2)
Bus and tram drivers2 (2)
Services and sales workers19 (18)Shop salespersons7 (7)
Travel attendants, conductors and guides5 (5)
Receptionists3 (3)
Waiter or bartenders2 (2)
Cooks1 (1)
Personal care workers in health services1 (1)
Cleaning and domestic workers9 (9)Domestic housekeepers7 (7)
Domestic cleaners and helpers2 (2)
Public safety workers7 (7)Police officers3 (3)
Fire fighter2 (2)
Security guards2 (2)
Religious workers6 (6)Religious professionals6 (6)
Construction workers5 (5)Construction laborers5 (5)
Other groups15 (15)Unspecifieda15 (15)
Summary103 (100)

ISCO-08: International Standard Classification of Occupations, 2008

aMainly from workplace clusters without detailed occupational description of each case

ISCO-08: International Standard Classification of Occupations, 2008 aMainly from workplace clusters without detailed occupational description of each case There were 31 incident confirmed cases during early transmission period, while there were 72 incident cases occurring in late transmission period. The most common occupations during early transmission were shop salesperson (N = 6), car, taxi and van drivers (N = 5), construction laborer (N = 4), religious professionals (N = 3), tour guides (N = 3), and receptionist (N = 3). Meanwhile, most common occupations during late transmission were health professionals (N = 23), car, taxi and van drivers (N = 10), domestic housekeepers (N = 6), police officers (N = 3), and religious professionals (N = 3) (Table 2).
Table 2

Occupation distribution of possible work-related COVID-19 cases in early and late transmission.

Occupation (ISCO-08)Early transmission period, N = 31Late transmission period, N = 72P-valuea
Count, N (%)Count, N (%)
Health professionals0 (0)23 (32)<0.001
Shop salespersons6 (19)1 (1)0.003
Car, taxi and van drivers5 (16)10 (14)0.767
Domestic housekeepers1 (3)6 (8)0.672
Construction laborers4 (13)1 (1)0.028
Religious professionals3 (10)3 (4)0.362
Police officers0 (0)3 (4)0.552
Travel attendants, conductors and guides3 (10)2 (3)0.159
Receptionists3 (10)0 (0)0.025

ISCO-08: International Standard Classification of Occupations, 2008

aP-values were calculated with Fisher exact test.

ISCO-08: International Standard Classification of Occupations, 2008 aP-values were calculated with Fisher exact test. Notably, there were different composition of high-risk occupations across transmission periods. Car, taxi and van driver and religious professionals were the most common occupations in both early and late transmission periods. Retail salespersons and tour guides were predominant in the early transmission period, while HCWs, domestic housekeepers, and police officers were the leading high-risk occupations in the late transmission period. Furthermore, while the proportion of work-related transmission decreased for shop salespersons, construction laborers and receptionists, there was a discernable increase in proportion of HCWs in the late period (P <0.001, Table 2) Fig 2A illustrates new daily confirmed local transmission, possible work-related transmission, and HCW cases over time in the six countries/areas. While the number of daily confirmed local transmission increased, the number of work-related cases reported in each day remained relatively steady throughout the follow-up period. We found 48% of locally transmitted cases in the early transmission period were due to possible work-related transmission, compared to 11% in the late transmission period (Chi-squared statistic = 61.84, P <0.0001).
Fig 2

New daily confirmed COVID-19 cases within 40-day follow-up periods across countries/areas.

(A) New daily confirmed Covid-19 cases within 40-day follow-up periods among the six countries/areas. (B) New daily confirmed Covid-19 cases within 40-day follow-up periods among the five countries/areas excluding Japan. HCW: Healthcare worker.

New daily confirmed COVID-19 cases within 40-day follow-up periods across countries/areas.

(A) New daily confirmed Covid-19 cases within 40-day follow-up periods among the six countries/areas. (B) New daily confirmed Covid-19 cases within 40-day follow-up periods among the five countries/areas excluding Japan. HCW: Healthcare worker. In further sensitivity analysis excluding Japan because of its different case reporting system, the daily confirmed local transmissions became relatively constant (Fig 2B). After excluding Japan, possible work-related cases comprised 44% of the locally transmitted cases in the early period, while only 18% in the late period (Chi-squared statistic = 18.8, P-value<0.0001). HCW comprised 22% of the possible work-related cases. In the sensitivity analysis excluding Japan, the proportion of HCWs decreased to 7%. Moreover, we found the occurrence of COVID-19 transmission among the HCW was relatively late compared to the non-HCW population. Fig 2A and Fig 2B showed a two-week lag of the first HCW case after the local COVID-19 outbreak (median lag: 15 days, IQR 13–20 days). The median time lag from the report of the first possible work-related case to the first HCW case was 13.5 days (IQR: 12.3–14.5 days) among the study population. In further sensitivity analysis excluding Japan, the median lags were 14 days (range: 10–32 days) and 13 days (range: 10–14 days), respectively. Furthermore, nearly all the HCWs (95%) had clear and traceable contact history with a confirmed case (Category 1); while only 43.2% of the non-HCW cases could trace back the infection source (P-value<0.001).

Discussion

In this study, we identified several high-risk occupations for COVID-19 infection that are rarely discussed [24]. These high-risk occupations comprised almost a half of local transmission during the early period of outbreak. In terms of the occupational risks of COVID-19 infection among the HCW, we found a median of two-week lag of HCW case after local transmission outbreaks. Moreover, non-HCW comprised the majority of the possible work-related cases and most of the cases were not able to trace back the infection sources. Our results indicate the importance of work-related transmission in the local COVID-19 outbreak. One novel finding of this study is that the early transmissions were highly related to some occupations beyond healthcare settings, including taxi driver, salesperson, tour guide, and housekeeper and cleaner. Taxi drivers, salespersons and tour guides are at higher risk because of frequent contact with travelers. In fact, one of the earliest locally transmitted cases in Taiwan was a taxi driver who took a passenger returning from mainland China. This case led to a family cluster of COVID-19 with four more locally transmitted cases [18]. Another example was an infected worker involved in a reported cluster leading to three more local cases within a household in Singapore [4]. On the other hand, housekeepers and cleaners are more likely to be exposed to contaminated surfaces than direct contact with COVID-19 patients [25]. In this study, the proportion of HCWs among locally transmitted cases was smaller than non-HCWs in the included countries/areas, 3% versus 12% respectively. The first cases HCWs appeared much later than the first non-HCW cases in all the study countries. The lower rate of HCW and the occurrence time lags among HCWs likely reflects improved triage, screening and isolation of COVID-19 patients in the healthcare setting, as well as better personal protective equipment (PPE) and hygiene among HCWs once knowledge and experience with outbreaks increase [26-28]. Health professionals are more equipped with infection control knowledge and concepts, are more aware of self-hygiene and more informed regarding new outbreaks compared to non-HCWs [29]. This study raises the importance of protecting high-risk non-HCWs for several reasons. First, the work-related risks of respiratory infection, including COVID-19 infection, among the occupations are often neglected, and the workers are less likely to have PPEs or proper infection control in their workplaces. Second, it is much challenging to trace back the infection source of the non-HCW cases compared to the HCW cases, indicating the urging need of precautions for the high-risk population. Third, many of these occupations are impossible to work remotely and the workers may not benefit from the measures of worker-protection, such as government-imposed shutdown or work-from-home order. Fourth, many of the high-risk workers are in relatively lower socioeconomic status (SES), which is a risk factor of having COVID-19 infection and worse disease outcomes [30]. People from the lower ends of the society are more susceptible to infectious outbreaks due to poorer living and working conditions [31,32]. They are more likely to have chronic health conditions which could lead to more severe consequences after being infected [33]. Protecting the high-risk workers could provide an opportunity to prevent the spread of the disease and to mitigate the deepening of health disparities. The substantial contribution of non-HCW to the COVID-19 locally transmitted cases emphasizes the importance of implementing effective infection control in the non-healthcare workplaces to protect the workers in this pandemic [34]. Early delivery of infection control knowledge and health concepts to workers, as well as providing adequate PPE are crucial in protecting workers and the whole society. Our study has some strengths. First, the data were extracted from the investigation reports published by the government of six countries/areas, which should be valid [35,36], and pooling of multi-county sources prevented the results from being skewed by single-country experience. Regarding the different case reporting system in Japan, we did further sensitivity analysis using the data from other five countries/areas and found similar temporal distribution patterns, which strengthened our conclusions. Second, every eligible case was reviewed by two occupational physicians and a physician epidemiologist with agreements on work-relatedness after thorough inspection of case reports. Moreover, we followed each country/area for 40 days, which allowed us to obtain comparable data for pooled analysis and illustrate trends of transmission in early stages of COVID-19 outbreak. Nonetheless, there are limitations of this study. First, there were discrepancies in reporting and investigation across the countries/areas. Cases without reported occupational history could potentially lead to underestimation in the analysis. Second, the report date of a case could be different to the date of getting infected and having symptoms. However, the information bias should be non-differential as the official reports were not different between whether a case was work-related or not. Third, the criteria of deciding whom to be tested varied between countries/areas, especially during early outbreaks when testing capacities were limited. Therefore, high risk populations, including high risk occupations, might tend to be tested. However, we believe the bias was non-differential, as health authorities should not decide whom to be tested differently based on whether the suspected case was a worker or not. In fact, most of the early cases were tested because of the symptoms or obvious contact histories, instead of occupations [37]. Finally, we excluded all imported cases in the analysis. Travelers, however, could actually be business travelers, or other workers in travel-related industries, such as flight attendants, tour managers, and so on. Although workers of these occupations do have frequent contact with the public and have higher probability to be infected, our results could not demonstrate their risks and thus further studies on business travelers are warranted. In conclusion, our study demonstrates that occupational infections are considerable in early COVID-19 local transmission. Second, several specific professional groups were at higher risk during early domestic outbreaks. We urge authorities to implement preventive strategies for each of these high-risk working populations.

Information of the 103 possible work-related COVID-19 cases during the study period.

(DOCX) Click here for additional data file. 27 Apr 2020 PONE-D-20-09603 Work-related Covid-19 transmission PLOS ONE Dear Dr. Kales, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please respond on a point-by-point basis to the reviewer comments and revise the manuscript accordingly. We would appreciate receiving your revised manuscript by Jun 11 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. 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(Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: In this manuscript, the authors calculated the case number for each occupation, and illustrated the temporal distribution of all possible work-related cases and healthcare worker (HCW) cases by extracting confirmed COVID-19 cases from governmental investigation reports in six countries/areas. The results indicate the importance of work-related transmission in the local COVID-19 outbreak. They further found that the proportion of HCWs among locally transmitted cases was smaller than non-HCWs in the included countries/areas, emphasizing the importance of implementing effective infection control in the non-healthcare workplaces to protect the workers in this pandemic. This study provides a new insight in understanding the epidemiology of work-related transmission of COVID-19 and implement evidence-based prevention and protection strategies in workplaces. One concern from me is if there should be some difference among these countries and what should be the reasons? Reviewer #2: The objective of this study was to describe the occupations among early COVID-19 cases arising from local transmission in five Asian countries for cases where occupational was thought to contribute to disease transmission, based on governmental reports. The investigators look at two time period, first week after introduction and the next month. Infections among healthcare workers appeared in the second period, and there were suggestions of some other changes in the distribution but interpretation is limited by the small sample size. It is important to understand what occupations put individuals at risk of COVID-19 to inform the need for intervention at the individual level and the society level. Specific comments: 1. It would be helpful to know more about the data, including extraction of occupation and the judgement of occupationally-related disease transmission. For example, how frequently was occupation information missing? What types of occupations were identified that were judged not related to disease transmission? How was occupation recorded in the governmental reports, and did this vary among countries? What is the confidence in the role of occupation when an infection source could not be identified? 2. The sensitivity analysis with Japan is not well justified. Why was it thought that variation data recording practices among prefectures in Japan was greater among the four other coutnries? What was the evidence of this? The sensitivity results suggest that adding Japan wasn't a big impact on the results. 3. The results section text is very repetitive. 4. Figure 2 is difficult to read in black and white, or for people with color vision problems. Suggest using different line textures or thicknesses to enhance readability. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step. 29 Apr 2020 Journal Requirements: 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf Response: Thank you. We have revised the format/file names according to PLOS ONE’s requirements throughout the paper. 2. Please consider modifying your title to ensure that it is specific, descriptive, concise, and comprehensible to readers outside the field (for example by specifying the nature of the study, and the names of the countries analysed ). When making changes please ensure that you amend the title on the online submission form (via Edit Submission) and the title in the manuscript so that they are identical. Response: Thank you. The paper title has been modified to “Work-related COVID-19 transmission in six Asian countries/areas: a follow-up study”, and the change has been made throughout the submission. 3. In your Methods section, please detail the data sources used. Response: Thank you. The data sources have been added as references, as follows. We extracted and included all locally transmitted COVID-19 confirmed cases from the publicized government investigation reports from six Asian countries/areas, including Hong Kong [15], Japan [16], Singapore [17], Taiwan [18], Thailand [19], and Vietnam [20]. 15. Centre for Health Protection [Internet]. Media Room: Press Releases; c2020 [cited 2020 April 28]. Available from: https://www.chp.gov.hk/en/media/116/index.html 16. Ministry of Health, Labour and Welfare [Internet]. 報道発表資料; c2020 [cited 2020 April 28]. Available from: https://www.mhlw.go.jp/stf/houdou/index.html 17. Singapore Ministry of Health [Internet]. Past Updates on COVID-19 Local Situation; c2020 [cited 2020 April 28]. Available from: https://www.moh.gov.sg/covid-19/past-updates 18. Taiwan Centers for Disease Control [Internet]; c2020 [cited 2020 April 28]. Available from: https://www.cdc.gov.tw/En 19. Department of Disease Control [Internet]; Corona Virus Disease (COVID-19): Press Release; c2020 [cited 2020 April 28]. Available from: https://ddc.moph.go.th/viralpneumonia/eng/news.php 20. Ministry of Health [Internet]; c2020 [cited 2020 April 28]. Available from: https://ncov.moh.gov.vn 4. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ Response: Thank you. Dr Kales’ (the corresponding author) account has been linked to his ORCID iD. 5. Please include a caption for figures 1 and 2. Response: Thank you. The captions of Fig 1 and Fig 2 have been embedded in the manuscript body. 6. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information Response: Thank you. The caption of S1 Table has been included at the end of the manuscript (after References). The in-text citation has also been updated to match accordingly. Reviewer #1: In this manuscript, the authors calculated the case number for each occupation, and illustrated the temporal distribution of all possible work-related cases and healthcare worker (HCW) cases by extracting confirmed COVID-19 cases from governmental investigation reports in six countries/areas. The results indicate the importance of work-related transmission in the local COVID-19 outbreak. They further found that the proportion of HCWs among locally transmitted cases was smaller than non-HCWs in the included countries/areas, emphasizing the importance of implementing effective infection control in the non-healthcare workplaces to protect the workers in this pandemic. This study provides a new insight in understanding the epidemiology of work-related transmission of COVID-19 and implement evidence-based prevention and protection strategies in workplaces. One concern from me is if there should be some difference among these countries and what should be the reasons? Response: Thank you. Different countries do have different disease investigation and reporting policies, probably due to various political systems, historical factors, religious reasons, and so on. In the revised discussion, we addressed the limitation that there were discrepancies in reporting and investigation across the countries/areas. This is also the reason we excluded Japan as a sensitivity analysis, because unlike other countries/areas that have central reporting systems, Japan reports cases from each prefecture separately. Reviewer #2: The objective of this study was to describe the occupations among early COVID-19 cases arising from local transmission in five Asian countries for cases where occupational was thought to contribute to disease transmission, based on governmental reports. The investigators look at two time period, first week after introduction and the next month. Infections among healthcare workers appeared in the second period, and there were suggestions of some other changes in the distribution but interpretation is limited by the small sample size. It is important to understand what occupations put individuals at risk of COVID-19 to inform the need for intervention at the individual level and the society level. Specific comments: 1. It would be helpful to know more about the data, including extraction of occupation and the judgment of occupationally-related disease transmission. For example, how frequently was occupation information missing? What types of occupations were identified that were judged not related to disease transmission? How was occupation recorded in the governmental reports, and did this vary among countries? What is the confidence in the role of occupation when an infection source could not be identified? Response: Thank you for your comments. Please find the point-by-point responses below. 1) We have added more detailed descriptions of the government reports, as follows. The investigation reports of the six countries/areas mostly included case information such as age, sex, and brief contact/medical history. An example is: “The new case was a 35 year-old female health care worker, and had close contacts with the Xth confirmed case [19].” There were also sections indicating infection clusters: “Four of the confirmed cases (Cases W, X, Y and Z) are linked to the XXX construction site [17].” Occupational history was not always available. In most cases, if the contact history was obvious such as family cluster, the report would likely lack an occupational description. Based on the available information, each case report was reviewed by two occupational physicians and categorized for work-relatedness. 2) Most cases judged not related to work were because of obvious non-occupational contact history or a lack of occupational history. Therefore, we did not determine particular types of occupations that were not related to disease transmission. 3) Different countries do have different disease investigation and reporting policies. Occupational history was not generally reported for each case. However, for the reports with available and adequate occupation information, we were able to determine the possible work-relatedness. We addressed this issue in the discussion as a limitation that cases without reported occupational history could potentially lead to underestimation in the analysis. 4) We were more confident in determining the work-relatedness if a case had close contact with a confirmed case due to work, or Category 1, such as a registered nurse having a history of directly caring for a patient who is an index confirmed case. As to Category 2, unknown transmission source; no apparent contact history but likely to be infected in the working environment, such as an airport taxi driver without clear contact history to any confirmed case, we had less confidence in work-relatedness but judged such cases to be probable (or more likely than not) work-related. 2. The sensitivity analysis with Japan is not well justified. Why was it thought that variation data recording practices among prefectures in Japan was greater among the four other countries? What was the evidence of this? The sensitivity results suggest that adding Japan wasn't a big impact on the results. Response: Thank you for your comments. We have revised the following sentences and added references accordingly as follows. Unlike other countries/areas that have central reporting systems providing cases’ occupation and other contact history in a standardized form, Japan’s reporting system is prefecture-based, where each prefecture reports separately, without consistent occupational coding. For example, some prefectures reported a case as a taxi driver; while some prefectures only reported a driver, without specifying the type of vehicle he/she drove [16,22,23]. Differences in reporting mechanisms and case information across prefectures could potentially bias the results. 16. Ministry of Health, Labour and Welfare [Internet]. 報道発表資料; c2020 [cited 2020 April 28]. Available from: https://www.mhlw.go.jp/stf/houdou/index.html 22. Ministry of Health, Labour and Welfare [Internet]. 新型コロナウイルス感染症患者の発生について(第 2 報); c2020 [cited 2020 April 28]. Available from: https://www.mhlw.go.jp/content/10906000/000598149.pdf?fbclid=IwAR0SZCxLB4VruarnnbNNcsfyGG-Bb96y_KXFBIX3UR4t7B_BzhlbIA4_6Gk 23. Ministry of Health, Labour and Welfare [Internet]. 新型コロナウイルス感染症患者の発生について(県内8・9・10例目); c2020 [cited 2020 April 28]. Available from: https://www.mhlw.go.jp/content/10906000/000609268.pdf?fbclid=IwAR1bImIVvBWmrftmd0X0cCrmmg6HJdnD2F8UsXm3c9j-jtAEO3Hs8y0nYGA Therefore, the exclusion of Japan is because of the concerns of potential misclassification. The most substantial impact after excluding Japan was the proportion of non-HCWs among work-related cases raised from 78% to 93% (shown in the revised Results). 3. The results section text is very repetitive. Response: Thank you for your comments. We have streamlined the text of Results by incorporating sensitivity analysis results into the main results, as follow. HCW comprised 22% of the possible work-related cases. In the sensitivity analysis excluding Japan, the proportion of HCWs decreased to 7%. Moreover, we found the occurrence of COVID-19 transmission among the HCW was relatively late compared to the non-HCW population. Fig 2A and Fig 2B showed a two-week lag of the first HCW case after the local COVID-19 outbreak (median lag: 15 days, IQR 13-20 days). The median time lag from the report of the first possible work-related case to the first HCW case was 13.5 days (IQR: 12.3-14.5 days) among the study population. In further sensitivity analysis excluding Japan, the median lags were 14 days (range: 10-32 days) and 13 days (range: 10-14 days), respectively. 4. Figure 2 is difficult to read in black and white, or for people with color vision problems. Suggest using different line textures or thicknesses to enhance readability. Response: Thank you for your comments. We have revised the figures. Submitted filename: Response to Reviewers.docx Click here for additional data file. 11 May 2020 Work-related COVID-19 transmission in six Asian countries/areas: a follow-up study PONE-D-20-09603R1 Dear Dr. Kales, We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements. Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication. Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. With kind regards, Jeffrey Shaman Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: (No Response) Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: (No Response) Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: (No Response) Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: (No Response) Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) Reviewer #2: The authors have addressed the comments from this reviewer, and the manuscript is improved. The figures look better. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No 12 May 2020 PONE-D-20-09603R1 Work-related COVID-19 transmission in six Asian countries/areas: a follow-up study Dear Dr. Kales: I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. For any other questions or concerns, please email plosone@plos.org. Thank you for submitting your work to PLOS ONE. With kind regards, PLOS ONE Editorial Office Staff on behalf of Prof. Jeffrey Shaman Academic Editor PLOS ONE
  25 in total

1.  Transmission dynamics and control of severe acute respiratory syndrome.

Authors:  Marc Lipsitch; Ted Cohen; Ben Cooper; James M Robins; Stefan Ma; Lyn James; Gowri Gopalakrishna; Suok Kai Chew; Chorh Chuan Tan; Matthew H Samore; David Fisman; Megan Murray
Journal:  Science       Date:  2003-05-23       Impact factor: 47.728

2.  Occupational health disparities: a state public health-based approach.

Authors:  Martha Stanbury; Kenneth D Rosenman
Journal:  Am J Ind Med       Date:  2013-12-30       Impact factor: 2.214

3.  Trends in Health Care-Associated Infection Prevention Practices in US Veterans Affairs Hospitals From 2005 to 2017.

Authors:  Valerie M Vaughn; Sanjay Saint; M Todd Greene; David Ratz; Karen E Fowler; Payal K Patel; Sarah L Krein
Journal:  JAMA Netw Open       Date:  2020-02-05

4.  Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 - United States, January-February 2020.

Authors:  Rachel M Burke; Claire M Midgley; Alissa Dratch; Marty Fenstersheib; Thomas Haupt; Michelle Holshue; Isaac Ghinai; M Claire Jarashow; Jennifer Lo; Tristan D McPherson; Sara Rudman; Sarah Scott; Aron J Hall; Alicia M Fry; Melissa A Rolfes
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-03-06       Impact factor: 17.586

5.  Journey of a Thai Taxi Driver and Novel Coronavirus.

Authors:  Wannarat A Pongpirul; Krit Pongpirul; Anuttra C Ratnarathon; Wisit Prasithsirikul
Journal:  N Engl J Med       Date:  2020-02-12       Impact factor: 91.245

6.  Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study.

Authors:  Gerardo Chowell; Fatima Abdirizak; Sunmi Lee; Jonggul Lee; Eunok Jung; Hiroshi Nishiura; Cécile Viboud
Journal:  BMC Med       Date:  2015-09-03       Impact factor: 8.775

7.  Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures.

Authors:  Rachael Pung; Calvin J Chiew; Barnaby E Young; Sarah Chin; Mark I-C Chen; Hannah E Clapham; Alex R Cook; Sebastian Maurer-Stroh; Matthias P H S Toh; Cuiqin Poh; Mabel Low; Joshua Lum; Valerie T J Koh; Tze M Mak; Lin Cui; Raymond V T P Lin; Derrick Heng; Yee-Sin Leo; David C Lye; Vernon J M Lee
Journal:  Lancet       Date:  2020-03-17       Impact factor: 79.321

8.  Coronavirus outbreak: the role of companies in preparedness and responses.

Authors:  Marc Fadel; Jérôme Salomon; Alexis Descatha
Journal:  Lancet Public Health       Date:  2020-02-28

9.  Effectiveness of precautions against droplets and contact in prevention of nosocomial transmission of severe acute respiratory syndrome (SARS).

Authors:  W H Seto; D Tsang; R W H Yung; T Y Ching; T K Ng; M Ho; L M Ho; J S M Peiris
Journal:  Lancet       Date:  2003-05-03       Impact factor: 79.321

10.  Control measures for severe acute respiratory syndrome (SARS) in Taiwan.

Authors:  Shiing-Jer Twu; Tzay-Jinn Chen; Chien-Jen Chen; Sonja J Olsen; Long-Teng Lee; Tamara Fisk; Kwo-Hsiung Hsu; Shan-Chwen Chang; Kow-Tong Chen; I-Hsin Chiang; Yi-Chun Wu; Jiunn-Shyan Wu; Scott F Dowell
Journal:  Emerg Infect Dis       Date:  2003-06       Impact factor: 6.883

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  74 in total

1.  Working in a bubble: How can businesses reopen while limiting the risk of COVID-19 outbreaks?

Authors:  Jeffrey Shaw; Troy Day; Nadia Malik; Nancy Barber; Hayley Wickenheiser; David N Fisman; Isaac Bogoch; John I Brownstein; Tyler Williamson
Journal:  CMAJ       Date:  2020-09-30       Impact factor: 8.262

2.  Chinese Livery Drivers' Perspectives on Adapting a Community Health Worker Intervention to Facilitate Lung Cancer Screening.

Authors:  Jennifer Leng; Florence Lui; Francesca Gany
Journal:  J Health Care Poor Underserved       Date:  2022

3.  COVID-19 infection across workplace settings in Qatar: a comparison of COVID-19 positivity rates of screened workers from March 1st until July 31st, 2020.

Authors:  Mohamed Ghaith Al-Kuwari; Asma Ali Al-Nuaimi; Jazeel Abdulmajeed; Sandy Semaan; Hamad Eid Al-Romaihi; Mujeeb Chettiyam Kandy; Selvakumar Swamy
Journal:  J Occup Med Toxicol       Date:  2021-06-17       Impact factor: 2.646

Review 4.  COVID-19 false dichotomies and a comprehensive review of the evidence regarding public health, COVID-19 symptomatology, SARS-CoV-2 transmission, mask wearing, and reinfection.

Authors:  Kevin Escandón; Angela L Rasmussen; Isaac I Bogoch; Eleanor J Murray; Karina Escandón; Saskia V Popescu; Jason Kindrachuk
Journal:  BMC Infect Dis       Date:  2021-07-27       Impact factor: 3.090

5.  Health Care Access Among Essential Critical Infrastructure Workers, 31 States, 2017-2018.

Authors:  Winifred L Boal; Jia Li; Sharon R Silver
Journal:  Public Health Rep       Date:  2021-03-09       Impact factor: 2.792

Review 6.  COVID-19: the importance of physical therapy in the recovery of workers' health.

Authors:  Luís Eduardo Santos Paz; Bruno José da Silva Bezerra; Taciane Machado de Melo Pereira; Welma Emidio da Silva
Journal:  Rev Bras Med Trab       Date:  2021-04-30

Review 7.  What is the risk of acquiring SARS-CoV-2 from the use of public toilets?

Authors:  Stephanie J Dancer; Yuguo Li; Alwyn Hart; Julian W Tang; Davey L Jones
Journal:  Sci Total Environ       Date:  2021-06-11       Impact factor: 7.963

8.  Comparison between RT-qPCR for SARS-CoV-2 and expanded triage in sputum of symptomatic and asymptomatic COVID-19 subjects in Ecuador.

Authors:  Ariel Torres; Martha Fors; Tamaris Rivero; Karina Pantoja; Santiago Ballaz
Journal:  BMC Infect Dis       Date:  2021-06-12       Impact factor: 3.090

9.  Seroprevalence of SARS-CoV-2 Antibodies in Symptomatic Individuals Is Higher than in Persons Who Are at Increased Risk Exposure: The Results of the Single-Center, Prospective, Cross-Sectional Study.

Authors:  Alexandr Zurochka; Maria Dobrinina; Vladimir Zurochka; Desheng Hu; Alexandr Solovyev; Liana Ryabova; Igor Kritsky; Roman Ibragimov; Alexey Sarapultsev
Journal:  Vaccines (Basel)       Date:  2021-06-09

Review 10.  Original Hosts, Clinical Features, Transmission Routes, and Vaccine Development for Coronavirus Disease (COVID-19).

Authors:  Ting Wu; Shuntong Kang; Wenyao Peng; Chenzhe Zuo; Yuhao Zhu; Liangyu Pan; Keyun Fu; Yaxian You; Xinyuan Yang; Xuan Luo; Liping Jiang; Meichun Deng
Journal:  Front Med (Lausanne)       Date:  2021-07-06
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