An innovative index for assessing vulnerability of employees of different occupations from the COVID-19 pandemic in Iran.

The vulnerability of employees of different occupations from the Coronavirus disease 2019 (COVID-19) pandemic in Iran was assessed using an innovative index. The vulnerability index was developed in five steps as follows: (1) determining the principles and components of employees' susceptibility and resilience, (2) weighting the principles and components, (3) converting the levels of components to the sub-index values, (4) introducing the aggregation functions, and (5) characterizing the vulnerability index values in five categories as very high (80-100), high (65-79), medium (50-64), low (30-49), and very low (0-29). The average values of susceptibility, resilience, and vulnerability index of the employees were determined to be 35.2 ± 15.0, 73.9 ± 17.0, and 32.9 ± 12.7, respectively. The average resilience of the employees was more desirable than their average susceptibility. The distribution of the employees into the vulnerability index categories was 46.3% for very low, 41.9% for low, 3.6% for medium, and 8.2% for high. The worst cases of susceptibility and resilience principles were exposure to contaminated surfaces (59.1 ± 22.8) and top management commitment (66.6 ± 23.1). The elderly staff (especially over 50 years old), employees with low education levels, and employees in private and self-employment sectors were significantly more vulnerable (p value < 0.01) from the COVID-19 pandemic. The principles with significant incremental effects on the vulnerability index (p value < 0.05) were respectively top management commitment (+1.78), exposure to COVID-19 patients at work (+1.36), exposure to contaminated surfaces (+0.82), installing clear shields and wearing PPE (+0.59), observance of social distancing (+0.48), and just culture (+0.22). An especial plan to support the more vulnerable employees with an emphasis on the principles with the most incremental effects on the vulnerability index can efficiently control the inequality between the employees as well as occupational transmission of the COVID-19 in Iran.

Introduction

Coronavirus disease 2019 (COVID-19) as an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan Province, China, and has spread rapidly all around the world. Rapid transmission, severe symptoms and the lack of definitive drugs have caused many countries to face serious problems in dealing with the infectious disease (Haines et al., 2020; Qiu et al., 2020; Wyper et al., 2020). According to the main routes of transmission of COVID-19 (respiratory droplets and saliva and contact with infected people and surfaces), the most important ways to prevent this disease are social distancing, quarantine, isolation, contact tracing, other personal and respiratory hygiene measures (frequent hand washing with soap and water or hand sanitizer, avoid touching of the face (eyes, nose and mouth), covering the face with tissue or bent elbow during coughing and sneezing, use of personal protective equipment), and environmental health measures (disinfection of objects and surfaces) (Cheung et al., 2020; Spinazzè et al., 2020; Wyper et al., 2020). The recent studies indicated that in addition to public health conditions and observance of the protective measure, a number of environmental factors such as air pollution, meteorological parameters, and environmental conditions of viral infectivity could play an important role in transmission dynamics of the COVID-19; therefore, a proactive environmental strategy should be considered to cope with future pandemics or epidemics (Coccia, 2020a,b).

An important part of the adverse outcomes of COVID-19 are imposed to the employees of different occupations as increasing the infection risk and decreasing income and job security. The healthcare workers are at the frontline of dealing with COVID-19, facing them with the significantly elevated risk of catching the disease. The health risks to the frontline key workers are not limited to the infection risk, but the harsh working conditions increase the risk of psychological injuries. During the early stages of the COVID-19 pandemic, mandatory closures of high-risk occupations with different severities and lengths were implemented in many countries, including China, Italy, Spain, the United States, Canada, the United Kingdom, and Iran to intensify the observance of social distancing. The temporary job closures during the COVID-19 peak could fell the risk of transmitting the disease for employees and people, but on the other hand might threaten job security and employees' income as well.‌ The adverse effects of the COVID-19 pandemic on occupations and workers’ health and income are not limited to the mandatory closure period, as the working conditions of many occupations have changed fundamentally during the pandemic. Although the overall outcome of the COVID-19 pandemic is considered to be undesirable for the employees, the situation may increase the revenue and employment capacity of a few businesses, such as online shops. The effect of the prevalence of COVID-19 on employees of different occupations depends on a number of factors such as exposure to COVID-19 patients, age, observance of social distancing, personal and respiratory hygiene, food hygiene, installing protective shields, and use of personal protective equipment (PPE) (Berger et al., 2020; DeCaprio et al., 2020; González-Olmo et al., 2020; Kikuchi et al., 2020; Sim, 2020; Spinazzè et al., 2020; Williamson et al., 2020; World Health Organization, 2020).

The vulnerability of employees of different occupations from the COVID-19 pandemic is a function of the susceptibility (exposure to the hazards and undesirable conditions) and resilience (ability to withstand the disruptions) and can be considered in terms of the disease risk, the effect on income, and job security. Simultaneous inclusion of all the aspects in a vulnerability index can provide a comprehensive understanding of the impact of the pandemic on employees and can help to identify the most vulnerable occupations and relevant corrective strategies for directing support packages of government and responsible organizations (Adams and Walls, 2020; DeCaprio et al., 2020; González-Olmo et al., 2020; Kikuchi et al., 2020; McMichael et al., 2020; Ng et al., 2020; Patel et al., 2020; Tan et al., 2020; Wyper et al., 2020). Despite the importance and applications of vulnerability assessment results, so far, no comprehensive index has been provided to assess the vulnerability of employees from the COVID-19 pandemic and the need for supporting employees during the COVID-19 pandemic is mainly focused on the infection risk and health-care personnel and other adverse aspects of the COVID-19 pandemic and workforces have received less attention (Adams and Walls, 2020; Gan et al., 2020; Mohammadi et al., 2020; Ng et al., 2020; Sim, 2020; Tan et al., 2020; World Health Organization, 2020).

The objective of this study was to develop the vulnerability index of employees of different occupations from the COVID-19 pandemic and apply the index to assess the vulnerability of employees in Iran. For this purpose, the principles and components of susceptibility and resilience of employees were determined and weighted by an expert panel. Then, by collecting data from employees of different occupations, the vulnerability of employees from the COVID-19 pandemic were estimated, and finally, the most vulnerable employees and most effective interventions were introduced.

Materials and methods

Study area and sampling

This study was conducted in Iran at the national level. Iran with a population over 83,000,000 is the world's eighteenth largest country (covered an area of 1,648,195 km2) and located in the southwest of Asia. The first case of COVID-19 in Iran was reported on February 19, 2020. The COVID-19 pandemic has caused a deep impact on the daily routine, habits, and working program of people and health-care system in the country. To assess the vulnerability of employees from the COVID-19 pandemic, a vulnerability assessment tool was developed based on the susceptibility and resilience determinants. The vulnerability assessment questionnaire was entered into an internet website and its link was broadcasted through online sources including email, websites and social networking services. The sampling was performed from all the employees over 15 years old across the country. The cross-sectional survey was conducted all over the country in one-month (from August 16, 2020 to September 16, 2020). The responding rate of the questionnaire was 39%, so that the questionnaire website was opened 3451 times and the number of participants in this survey was 1343.

The study protocol and procedures were confirmed by Ethics Committee of School of Public Health and Safety, Shahid Beheshti University of Medical Sciences. The participation in this study was based on informed consent. In the first page of the questionnaire website, the research objective was explained and the website visitors who confirmed their willingness to participate voluntarily were directed to complete the questionnaire.

Construction of the vulnerability index

Vulnerability is defined as the degree of inability of a community or an individual to predict, confront, resist and recover from the event of failure or a crisis situation such as the COVID-19 pandemic. The vulnerability is considered to be a function of susceptibility and resilience. Susceptibility concerns the characteristics and factors operating in a community or an individual that allow a hazard to cause an incidence of adverse events (catching COVID-19). Resilience is the ability to adapt, withstand, and handle the hazard caused by a crisis situation or the event of failure (Acharya and Porwal, 2020; Coulombe et al., 2020; Godri Pollitt et al., 2020; Mills et al., 2020; Vicente-Herrero et al., 2020; Wisner and Adams, 2002). In this study, a panel of 15 experts from the different fields of health sciences, including Environmental Health (six experts), Occupational Health (four experts), Health Education and Promotion (two experts), Health Care Services Management (two experts), Health, Safety, and Environment Management (one expert) was established to determine principles and components of susceptibility and resilience of employees, weight them, and develop the vulnerability index of employees from the COVID-19 pandemic.

The initial list of principles and components of employees' susceptibility and resilience in the COVID-19 pandemic was prepared by reviewing the literature and brain storming. A number of 12 principles (75% of the initial list) and 34 components (79% of the initial list) of employees' susceptibility and resilience were extracted from the literature (Acharya and Porwal, 2020; Coggon et al., 2020; Jackson et al., 2020; Kikuchi et al., 2020; Mills et al., 2020; Morton, 2020; Santos et al., 2020; Team and Manderson, 2020; Tran et al., 2020; Vicente-Herrero et al., 2020). The initial list was completed by receiving the opinions of the expert panel. The inclusion of the components in the final index was determined based on necessity using the content validity ratio (CVR) and relevancy and clarity by the content validity index (CVI). The response for necessity had three choices to be “not necessary”, “useful but not essential”, and “essential”. The quality of components in terms of relevancy and clarity was characterized by four choices as (1) poor, (2) fair, (3) good, and (4) excellent. The CVR and CVI were calculated by the following equations (Shrotryia and Dhanda, 2019; Zamanzadeh et al., 2015): where N is the total number of responses (15 responses), n is the number of “essential” responses, and n and n are the numbers of “excellent” and “good” responses, respectively. Based on the total number of responses, the minimum values of CVR and CVI for inclusion of each component were respectively 0.49 and 0.79. The final principles and components of susceptibility and resilience of employees are given in Table 1, Table 2 . Due to the disproportionate contribution of the principles and components to the vulnerability of employees from the COVID-19 pandemic, the principles and components were weighted using the analytic hierarchy process (AHP) by pairwise comparison (Rezaei, 2015; Triantaphyllou, 2000). The weights of the principles and components of susceptibility and resilience of employees are provided in Table 1, Table 2. In order to apply the output of the susceptibility and resilience components to a quantitative vulnerability index, the response levels of components were converted to the sub-index values from 0 to 100 in a manner that zero represents the best condition for the susceptibility components and worst case for the resilience components and 100 reflects the reverse of the zero description.

Table 1

Susceptibility components for vulnerability assessment of employees of different occupations from the COVID-19 pandemic in Iran.

Section	Principle	Weight (Wi)	Component	Choices	Weight (wk)
Risk of infection	Exposure to COVID-19 patients at work	0.216	Dealing with COVID-19 patients at work	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, (5) No exposure, and (6) Do not know	0.437
			Work at home	(1) Not work at home, (2) One day a week, (3) Two days a week, (4) Three days a week, and (5) Total workweek	0.294
			Providing sick leave to complete recovery for employees impacted by COVID-19	(1) No and (2) Yes	0.115
			Number of clients per day	(1) 50 persons and higher, (2) 20–49 persons, (3) 10–19 persons, (4) 5–9 persons, and (5) Lower than 5 persons	0.073
			Having business travel during COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.066
			Diagnostic screening and testing for COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.015
	Risk for severe illness from COVID-19	0.116	Risk for severe Illness from COVID-19	(1) high risk groups (cardiovascular disease, diabetes, cancer, respiratory disease, kidney failure, hypertension, obesity, pregnancy, old age (higher than 50 years old)) and (2) low risk groups	1.000
	Observance of social distancing	0.109	Distance from clients	(1) Lower than 1.0 m, (2) 1.0–1.5 m, (3) 1.5–2.0 m, (4) Higher than 2.0 m	0.500
			Method of travel to work	(1) Bus, minibus, or metro, (2) Employment-related transportation services, (3) Taxi, (4) Internet taxi, (5) Private car, bicycle, or motorcycle,(6) Walking, (7) Work at home, (8) Other cases	0.500
	Compliance with hand and respiratory hygiene	0.092	Observance of hand hygiene	Based on habits of handwashing at key times ((a) After blowing your nose, coughing, or sneezing, (b) After caring for someone at home who have COVID-19 symptoms, (c) After physical contact with other people, (d) Before eating food, (e) After using the toilet, (f) Before, during, and after preparing food, (g) After touching contaminated surfaces, and (h) After touching an animal)): (1) Very bad, (2) Bad, (3) Moderate, (4) Good, and (5) Excellent.	0.500
			Covering coughs and sneezes with a tissue or bent elbow	(1) No, (2) Seldom, (3) Sometimes, (4) Often, and (5) Always	0.500
	Installing clear shields and wearing personal protective equipment	0.075	Wearing a face mask	(1) Do not wear, (2) Lower than 2 h, (3) 2–3 h, (4) 4–6 h, and (5) Continuous	0.414
			Installing clear shields	(1) No and (2) Yes	0.280
			Wearing a face shield	(1) Do not wear, (2) Lower than 2 h, (3) 2–3 h, (4) 4–6 h, and (5) Continuous	0.216
			Wearing gloves	(1) Do not wear, (2) Lower than 2 h, (3) 2–3 h, (4) 4–6 h, and (5) Continuous	0.045
			Wearing a gown or overall	(1) Do not wear, (2) Lower than 2 h, (3) 2–3 h, (4) 4–6 h, and (5) Continuous	0.045
	Exposure to contaminated surfaces	0.044	Contact with high-touch surfaces and objects	(1) Very high, (2) High, (3) Moderate, (4) Low, and (5) Very low	0.500
			Disinfecting high-touch surfaces and objects	(1) No, (2) Seldom, (3) Sometimes, (4) Often, and (5) Always	0.500
	Ventilation status	0.015	Location of workplace	(1) Indoor and (2) Outdoor	0.500
			Ventilation rate	(1) Very low, (2) Low, (3) Suitable, and (4) Do not know	0.500
	Observing food hygiene	0.007	Observing food hygiene	(1) No, (2) Yes, to some extent, (3) Yes, exactly, and (4) Do not know	1.000
Effect on income	Effect on income of employees	0.044	Effect on income of employees	(1) Higher than 50% decrease, (2) 20–49% decrease, (3) Lower than 20% decrease, (4) No effect, (5) Lower than 20% increase, (6) 20–49% increase, and (7) Higher than 50% increase	1.000
	Effect on income of COVID-19 patients	0.001	Effect on income of COVID-19 patients	(1) Higher than 50% decrease, (2) 20–49% decrease, (3) Lower than 20% decrease, and (4) No effect	1.000
Losing job	Losing job during COVID-19 pandemic	0.275	Probability of losing job during COVID-19 pandemic	(1) High, (2) Low, and (3) Not probable	1.000
	Losing job due to catching COVID-19	0.006	Probability of losing job due to catching COVID-19	(1) High, (2) Low, and (3) Not probable	1.000

Table 2

Resilience components for vulnerability assessment of employees of different occupations from the COVID-19 pandemic in Iran.

Principle	Weight (Wj)	Component	Choices	Weight (wl)
Top management commitment	0.495	Prioritizing employee health over profits and work productivity	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.304
		Motivating employees to control the stress caused by COVID-19	(1) Very high, (2) High, (3) Moderate, (4) Low, and (5) Very low	0.232
		Providing handwashing facilities with soap and water	(1) Adequate, (2) Inadequate, and (3) No	0.109
		Providing hand sanitizer for employees	(1) Adequate, (2) Inadequate, and (3) No	0.109
		Providing tissue paper for employees	(1) Adequate, (2) Inadequate, and (3) No	0.109
		Providing face mask for employees	(1) Adequate, (2) Inadequate, and (3) No	0.036
		Providing face shield for employees	(1) Adequate, (2) Inadequate, and (3) No	0.036
		Providing gloves for employees	(1) Adequate, (2) Inadequate, and (3) No	0.036
		Prevention of holding face-to-face meetings and gatherings	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.027
Awareness and risk perception	0.278	Paying attention to educations on prevention of COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.333
		Awareness regarding spread and prevention of COVID-19	(1) Good, (2) Moderate, and (3) Weak	0.333
		Knowledge about the correct usage of face mask	(1) Good, (2) Moderate, and (3) Weak	0.333
Learning culture	0.113	Discussing about risk and prevention of COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.500
		Providing instructions and posters to prevent the spread of COVID-19	(1) Adequate, (2) Inadequate, and (3) No	0.500
Just culture	0.113	Training and warning employees who do not follow health protocols of COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.333
		Informing the superiors about catching COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.333
		Considering comments and suggestions of employees in prevention protocol of COVID-19	(1) Always, (2) Often, (3) Sometimes, (4) Seldom, and (5) No	0.333

By summarizing the opinions of the expert panel, the integration functions for calculation of the susceptibility, resilience, and vulnerability index of employees in the COVID-19 pandemic were defined as follows: where S is the value of susceptibility, S is the value of susceptibility principle i, W is the weight of the susceptibility principle i, R is the value of resilience, R is the value of resilience principle j, W is the weight of the resilience principle j, s is the value of susceptibility component k, w is the weight of the susceptibility component k, r is the value of resilience component l, w is the weight of the resilience component l, V is the value of vulnerability, VI is the value of vulnerability index, V is the lowest value of vulnerability to be −100 and V is the highest value of vulnerability to be 200. The values of the VI, R, S, S , R , s , and r range from 0 to 100 in a manner that 0 indicates best condition of the vulnerability index and susceptibility parameters and the worst case of the resilience parameters and 100 reversely reflects the worst situation of the vulnerability index and susceptibility parameters and the best case of the resilience parameters. In order to qualitatively describe the susceptibility, resilience, and vulnerability index of employees in different occupations, the expert panel provided a system for classifying the vulnerability index levels. The susceptibility, resilience, and vulnerability index values were classified into the five categories as very high (80–100), high (65–79), medium (50–64), low (30–49), and very low (0–29).

Data analysis

The susceptibility, resilience, and vulnerability of employees of different occupations in the COVID-19 pandemic at the national level were assessed using the above-mentioned equations. The effects of age, sex, marital status, occupation group, level of education, working years, employment status, and workplace status in terms of ownership on vulnerability of employees from the COVID-19 pandemic was analyzed by n-way analysis of variance (ANOVA) using Statistical Package for Social Science (SPSS) for Windows version 19 software.

Result and discussion

The demographic and occupational characteristics of the participants are given in Table 3 . The average (±standard deviation: SD) age and working years of participants were 36.4 ± 9.8 y and 11.7 ± 9.0 y, respectively. The gender distribution of the participants was 46.2% women versus 53.8% men. The average age and gender distribution of the participants were different from those of the workforce in the country (to be 39.4 ± 12.0 y and 18% women versus 82% men) (Abtahi et al., 2018). The education levels of the participants were 5.0% lower than diploma (lower than 12 y of education), 12.8% diploma, 6.8% associate's degree, 43.8% bachelor's degree, 24.7% master's degree, and 7.0% doctorate degree or higher. The distribution of the participants in the occupation groups was as follows: 31.9% for health-care services, 20.5% for administrative and service activities, 14.5% for manufacturing and construction, 13.6% for education and research, 5.9% for wholesale and retail trade and repair of goods, 4.3% for food supply chain, 2.8% for beauty and cosmetic services, 2.2% for transportation, 1.9% for electronic and digital services, 1.7% for cultural and recreational services, and 0.6% for travel and tourism. The majority of the participants were working in the public sector (43.0%) and the lowest share of the participants were self-employed (15.3%). The ownership status of the workplaces was as follows: 53.4% public property, 22.4% private property, 17.1% rented property, and 7.1% no property.

Table 3

Vulnerability assessment of the employees from the COVID-19 pandemic in Iran by demographic and occupational characteristics of the participants.

Characteristic	Category	Frequency (%)	Susceptibility value (mean ± SD)	Resilience value (mean ± SD)	Vulnerability index (mean ± SD)	p value
Sex	Female	46.2	32.8 ± 14.2	74.3 ± 15.9	31.0 ± 11.6	0.039a
	Male	53.8	37.3 ± 15.4	73.6 ± 17.9	34.6 ± 13.3
Age group	15 to 19 y	1.6	29.2 ± 16.1	72.1 ± 18.5	28.9 ± 13.1	0.000b
	20 to 24 y	10.7	33.9 ± 16.0	73.8 ± 16.1	32.0 ± 13.3
	25 to 29 y	16.6	36.3 ± 14.7	74.7 ± 16.3	33.6 ± 12.7
	30 to 34 y	18.0	36.1 ± 15.5	74.8 ± 18.0	33.4 ± 13.4
	35 to 39 y	19.5	35.0 ± 15.5	73.2 ± 17.4	32.9 ± 13.0
	40 to 44 y	14.2	34.2 ± 14.1	73.1 ± 17.8	32.4 ± 12.1
	45 to 49 y	9.4	31.3 ± 13.9	73.2 ± 15.4	30.2 ± 11.6
	50 to 54 y	6.4	40.5 ± 12.7	75.3 ± 17.4	36.5 ± 9.9
	55 to 59 y	2.4	39.1 ± 13.2	73.1 ± 14.4	36.0 ± 11.1
	60 to 64 y	0.9	37.0 ± 11.5	73.5 ± 18.6	34.4 ± 11.8
	65 to 69 y	0.3	41.5 ± 23.1	64.5 ± 24.6	40.0 ± 21.6
Marital status	Married	66.1	35.2 ± 14.8	74.7 ± 16.9	32.8 ± 12.5	0.011a
	Single	33.9	35.2 ± 15.3	72.3 ± 17.2	33.3 ± 17.2
Type of community	City/town	92.8	35.2 ± 15.0	73.8 ± 17.1	32.9 ± 12.7	0.925
	Village	7.2	35.8 ± 14.2	74.5 ± 16.9	33.2 ± 12.1
Education level	Lower than diploma	5.0	43.0 ± 16.8	72.8 ± 19.9	39.0 ± 13.1	0.009b
	Diploma	12.8	38.5 ± 15.9	73.8 ± 19.0	35.5 ± 14.1
	Associate's degree	6.8	37.2 ± 15.7	75.2 ± 16.7	34.1 ± 13.0
	Bachelor's degree	43.8	35.2 ± 14.0	74.4 ± 16.3	32.8 ± 11.9
	Master's degree	24.7	32.9 ± 14.8	73.3 ± 17.4	31.4 ± 12.5
	Doctorate degree	7.0	30.2 ± 14.4	72.9 ± 14.9	29.4 ± 12.2
Occupation group	Health-care services	31.9	33.8 ± 13.1	77.3 ± 14.4	31.0 ± 11.0	0.107
	Administrative and service activities	20.5	32.8 ± 14.1	71.4 ± 17.3	31.8 ± 12.2
	Manufacturing and construction	14.5	39.8 ± 14.9	71.3 ± 19.4	37.0 ± 12.9
	Education and research	13.6	30.5 ± 15.2	71.1 ± 16.9	30.1 ± 12.8
	Wholesale and retail trade and repair of goods	5.9	40.0 ± 17.0	79.7 ± 16.6	35.0 ± 14.3
	Food supply chain	4.3	38.0 ± 14.1	74.2 ± 17.4	35.0 ± 10.9
	Beauty and cosmetic services	2.8	42.3 ± 16.1	80.9 ± 16.2	36.5 ± 13.3
	Transportation	2.2	44.5 ± 18.1	57.1 ± 15.7	44.1 ± 15.5
	Electronic and digital services	1.9	36.1 ± 18.6	70.5 ± 18.2	34.5 ± 15.8
	Cultural and recreational services	1.7	39.2 ± 17.9	80.3 ± 13.4	34.3 ± 14.7
	Travel and tourism	0.6	42.2 ± 15.2	65.2 ± 16.5	40.4 ± 13.4
Working years	0 to 4 y	32.7	35.4 ± 15.7	74.0 ± 16.6	33.1 ± 13.4	0.832
	5 to 9 y	18.0	36.0 ± 15.0	74.2 ± 17.3	33.5 ± 12.7
	10 to 14 y	16.3	34.3 ± 15.0	73.6 ± 18.3	32.4 ± 12.6
	15 to 19 y	13.5	34.4 ± 14.0	73.0 ± 17.6	32.5 ± 12.3
	20 to 24 y	10.1	36.0 ± 15.4	73.7 ± 16.4	33.6 ± 12.4
	25 to 29 y	5.7	34.2 ± 12.9	77.2 ± 14.3	31.3 ± 10.9
	30 + y	3.7	36.1 ± 13.4	71.6 ± 17.5	34.2 ± 10.6
Workplace ownership	Public property	53.4	31.0 ± 12.7	73.7 ± 15.8	29.8 ± 10.9	0.000b
	Private property	22.4	38.1 ± 15.8	74.6 ± 17.8	34.9 ± 13.4
	Rented property	17.1	42.2 ± 15.5	75.0 ± 18.5	37.9 ± 13.3
	No property	7.1	41.1 ± 16.4	70.3 ± 19.4	38.3 ± 14.0
Employment sector	Self-employment	15.3	39.2 ± 16.2	76.8 ± 19.3	35.2 ± 13.7	0.000b
	Public	43.0	29.4 ± 11.9	73.2 ± 16.2	28.7 ± 10.4
	Private	25.9	41.3 ± 16.3	73.9 ± 17.1	37.5 ± 13.9
	Joint public-private	15.9	37.3 ± 13.3	73.0 ± 16.7	34.8 ± 11.7
Total		100	35.2 ± 15.0	73.9 ± 17.0	32.9 ± 12.7	–

Significant effect with a p value < 0.05.

Significant effect with a p value < 0.01.

The employees’ perception about an increase in the risk of catching COVID-19 at work and disruption of work procedures during the COVID-19 pandemic is illustrated in Fig. 1 . As can be seen in Fig. 1, over 55% of the participants reflected that the presence at work increased the risk of catching COVID-19 to high or very high levels. The corresponding value for the disruption of work procedures during the COVID-19 pandemic was as high as over 53%. Fig. 2 presents the current situations of the susceptibility and resilience components of the employees in the COVID-19 pandemic. The five best conditions of susceptibility factors (out of 25 factors) were related to providing sick leave to COVID-19 patients (88.1% for provided), risk for severe illness from COVID-19 (73.1% for low risk), losing job due to catching COVID-19 (68.9% for not probable), wearing a face mask (64.5% for continuous), and covering coughs and sneezes with a tissue or bent elbow (63.5% for always), and the five worst cases were determined to be location of workplace (85.3% for indoor), installing clear shields (84.0% for not installing), wok at home (65.4% for not work at home), distance from clients (64.7% for lower than 1.5 m), and effect on income of employees (51.5% for a decrease in income of employees).

Fig. 1

The employees' perception about an increase in the risk of catching COVID-19 at work (A) and disruption of work procedures during the COVID-19 pandemic (B).

Fig. 2

Frequency distribution of vulnerability components of employees of different occupations from the COVID-19 pandemic in Iran: (A) susceptibility components and (B) resilience components (green: The best condition, red: The worst case, gray: Do not know, full description of the choices is presented in Table 1). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

One of the effective measures to control the spread of the COVID-19 is providing sick leave to the patients. According to Fig. 2, the percentage of not providing sick leave to the COVID-19 patients was determined to be 11.9%, occurring mostly in the private employment sector and small businesses. Compensation of sick leave expenses for gig economy and small business employees by the government can increase the equitability and inclusion of the control measure (Berger et al., 2020). A study by Baert et al. (2020) indicated that teleworking, in addition to lowering the risk of catching COVID-19, mainly caused some other positive attitudes for employees such as lower risk of fatigue and increased productivity. On the other hand, teleworking may decrease promotion opportunities for employees and weaken the relationships and constructive competitions at work. In order to achieve desirable output and productivity, the requirements of teleworking such as telecommunication infrastructures, surveillance system and training should also be provided.

The current situation of the resilience components was better than that of the susceptibility factors; so that eight resilience components (out of 17 components) exhibited the best condition frequencies higher than 50% to be knowledge about the correct usage of face mask (86.8%), providing handwashing facilities (83.3%), awareness regarding spread and prevention of COVID-19 (81.5%), paying attention to educations on prevention of COVID-19 (71.7%), providing hand sanitizer for employees (60.0%), informing the superiors about catching COVID-19 (56.7%), providing tissue paper for employees (54.5%), and providing instructions to prevent the spread of COVID-19 (54.4%). In contrast, only two resilience components of providing face shields and gloves for employees had the worst-case frequencies higher than 50% to be 78.8% and 56.0%, respectively.

It should be noted that the necessity of providing and wearing PPE depends on probability of exposure to COVID-19 patients, so that the employees who always or often expose to COVID-19 patients should wear all the above-mentioned PPE (face mask, face shield, gloves, and gown or overall) and for the other ones only wearing a face mask was considered to be necessary. The difference between employees regarding the necessity of wearing PPE was reflected in the estimation of susceptibility, resilience, and vulnerability index of employees in the COVID-19 pandemic.

Table 3 provides the susceptibility, resilience, and vulnerability index of employees of different occupations in the COVID-19 by sex, age group, marital status, type of community, education level, occupation group, working years, workplace ownership, and employment sector. The average values of susceptibility, resilience, and vulnerability index of all the participants were determined to be 35.2 ± 15.0, 73.9 ± 17.0, and 32.9 ± 12.7 that fell into the low, high, and low categories, respectively. The average resilience of the participants was more desirable than their average susceptibility. Fig. 3 displays the box plot diagrams of the susceptibility and resilience principles of employees of different occupations from the COVID-19 pandemic in Iran. The variations of susceptibility principles were much more than those of resilience principles. The best average values of the susceptibility and resilience principles were related to ventilation status (22.8 ± 32.9) and awareness and risk perception (91.7 ± 14.1), respectively. Also, the worst cases of susceptibility and resilience principles were exposure to contaminated surfaces (59.1 ± 22.8) and top management commitment (66.6 ± 23.1), respectively. According to the results, there was no correlation between the susceptibility and resilience of the employees. Fig. 4 shows the distribution of employees of different occupations in Iran into the susceptibility, resilience, and vulnerability index categories. As can be seen in Fig. 4, the distribution of the participants into the vulnerability index categories was 46.3% for very low, 41.9% for low, 3.6% for medium, and 8.2% for high. The designation of the participants by the vulnerability index was to an extent different from that by the susceptibility value due to the inclusion of the resilience factors.

Fig. 3

Box plot diagrams of the vulnerability principles of employees of different occupations from the COVID-19 pandemic in Iran: (A) susceptibility principles and (B) resilience principles.

Fig. 4

Distribution of employees of different occupations in Iran into the categories of susceptibility (A), resilience (B), and vulnerability indices (C) (from August 16, 2020 to September 16, 2020).

Based on the statistical analysis, the demographic and occupation characteristics of the participants with a significant effect on the vulnerability index value were sex (p value < 0.04), age group (p value < 0.001), marital status (p value < 0.02), education level (p value < 0.01), workplace ownership (p value < 0.001), and employment sector (p value < 0.001). Contrary to expectations, the occupation group did not exhibit statistically significant effect on the vulnerability index. The single participants were characterized more vulnerable from the COVID-19 pandemic. As indicated in Table 3, the vulnerability of women employees from the COVID-19 (31.0 ± 11.6) was lower than that of men employees (34.6 ± 13.3). The lower vulnerability of women was mostly due to less susceptibility in a manner that the susceptibility values of women and men were respectively 32.8 ± 14.2 and 37.3 ± 15.4, whereas the corresponding values for resilience were very close to each other (74.3 ± 15.9 and 73.6 ± 17.9, respectively). Despite the results obtained in this study, Wenham et al. (2020) and Kikuchi et al. (2020) expressed a concern about higher impacts of the COVID-19 pandemic on women. Among the age groups, the highest average vulnerability index was observed in the age group 65–69 y to be 40.0 ± 21.6, partly due to the highest risk for severe illness from COVID-19 and lowest resilience value. According to Table 3, the average value of the vulnerability index constantly fell by increasing education level from 39.0 ± 13.1 for lower than diploma to 29.4 ± 12.2 for doctorate degree. Similarly, Kikuchi et al. (2020) reported that the employees with low education levels were more vulnerable than those with high education levels.

In terms of workplace ownership, the employees with no property and rented workplaces were assessed to be more vulnerable. Among the employment sectors, the average values of the vulnerability index of the employees in the private and self-employment sectors were considerably higher than those values in the public and joint public-private sectors. These results indicated that the public sectors provided more reliable supports for employees to cope with the COVID-19 pandemic. Inequality in vulnerability of workers from the COVID-19 crisis was also reported by Kikuchi et al. (2020). Ahmed et al. (2020) explained that inequality could exacerbate the spread of COVID-19. Our finding revealed that there was an inequality in the vulnerability of employees from the COVID-19 pandemic in Iran. An especial plan for provision of governmental support to the more vulnerable employees such as elderly staff, employees with low education levels, and employees in private and self-employment sectors can control the inequality between the employees as well as transmission of the COVID-19 (Ahmed et al., 2020; Burdorf et al., 2020; Kikuchi et al., 2020; Koh, 2020; Patel et al., 2020).

Due to relatively low number of samples, it was not possible to estimate the spatial distribution of the vulnerability index and the results were only reported at the national level. For developing the vulnerability index, we considered the individual and workplace aspects, whereas recent studies suggested that a number of other factors including environmental, epidemiological, socioeconomic, housing, and health system domains can also affect the potential risk and vulnerability from COVID-19 at community, regional, and national levels (Acharya and Porwal, 2020; Coccia, 2020a, b, c, d). Coccia (2020a) introduced an index (Index c) to quantify environmental risk of exposure to COVID-19 using four factors of air pollution, wind speed, density of population, and respiratory disorders of people. The results revealed a strong positive correlation between Index c value and the number of confirmed cases of the COVID-19 in Italy at the community level. Acharya and Porwal (2020) developed a vulnerability index for describing the risk of the COVID-19 pandemic in India based of 15 indicators in 5 domains to be epidemiological, demographic, housing and hygiene, socioeconomic, and health system. Based on the vulnerability index, the more vulnerable districts in India were identified and prioritized for resource allocation and better responses to the COVID-19 pandemic. Therefore, in order to characterize the vulnerability of employees from the COVID-19 pandemic by community, regional, and national levels, application of the vulnerability index proposed in this study along with the above-mentioned ones can provide more precise and reliable description. As the other limitation of our study, the psychological factors were not included in the proposed vulnerability index. Several previous studies reported that employees of different sectors including healthcare professionals, police, and hospitality workers experienced stress and serious psychological problems during the COVID-19 pandemic. The most prevalent causes of the employees’ psychological problems during the COVID-19 pandemic were introduced to be harsh working conditions, long working hours, fear of catching the infection, economic instability, fear of job loss, and uncertainty (Bozdağ and Ergün, 2020; Coulombe et al., 2020; Luceño-Moreno et al., 2020; Sönmez et al., 2020; Stogner et al., 2020; Tan et al., 2020).

The effect of removing each input principle on the average value of the vulnerability index of employees of different occupations from the COVID-19 pandemic in Iran is illustrated in Fig. 5 . The effect of removing input principles on the average value of the vulnerability index ranged −1.78 to +1.72. The principles with a significant positive effect including, awareness and risk perception (+1.72), losing job during COVID-19 pandemic (+1.38), compliance with hand and respiratory hygiene (+0.86), risk for severe illness from COVID-19 (+0.82), ventilation status (+0.15), and effect on income of employees (+0.10) had better condition than the total input principles and their inclusion fell the average values of vulnerability index. In contrast, the principles with a significant negative effect as well as worse condition than the total input principles were determined to be top management commitment (−1.78), exposure to COVID-19 patients at work (−1.36), exposure to contaminated surfaces (−0.82), installing clear shields and wearing PPE (−0.59), observance of social distancing (−0.48), and just culture (−0.22). The principles with a significant negative effect could be considered as the more challenging aspects of the work environment in coping with COVID-19; therefore, these principles should be taken into more consideration in the occupational health plan during the COVID-19 pandemic. All the vulnerability indices developed by removal of each input principle were significantly correlated to the main index (R 2 > 0.91, p value < 0.002); this result indicated that none of the input principles exhibited a very strong effect on the vulnerability index value and the index could reflect the contribution of all the input principles to the vulnerability of employees from COVID-19 pandemic (Abtahi et al., 2015, 2016).

Fig. 5

Effect of removing each input principle on the average value of the vulnerability index of employees of different occupations from the COVID-19 pandemic in Iran (* shows significant effect with a p value < 0.05 and ** indicates significant effect with a p value < 0.01).

Conclusion

The vulnerability of about one-tenth of the employees from the COVID-19 pandemic was estimated to be high. The vulnerability of the employees from the COVID-19 pandemic was significantly different by sex, marital status, age, education level, workplace ownership, and employment sector (p value < 0.05). The principles of top management commitment, exposure to COVID-19 patients at work, exposure to contaminated surfaces, installing clear shields and wearing PPE, observance of social distancing significantly increased the vulnerability of the employees (p value < 0.05). The elderly staff (especially over 50 years old), employees with low education levels, and employees in private and self-employment sectors as more vulnerable employees and the principles with the most incremental effects on the vulnerability were introduced as the high priority targets of resource allocation and implementation of mitigation measures for efficient control of the inequality between the employees as well as the occupational spread of COVID-19 in Iran. The application of the proposed vulnerability index considering the individual and workplace factors along with the other ones reflecting the other affecting factors such as environmental, epidemiological, socioeconomic, etc. can provide more precise and reliable description of the vulnerability of employees from the COVID-19 pandemic.

Authorship contribution statement

All authors contributed to preparation of the final manuscript and discussed the results. RS and MA designed the study and drafted the manuscript. RG, MJ, and MHV designed the analysis of the collected data. AK, SD, and SJ contributed to the interpretation of the results and performed the statistical analyses. AB, MK, and PR collected the data and performed the calculation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.