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Risk Perception Towards COVID-19 and Its Associated Factors Among Waiters in Selected Towns of Southwest Ethiopia

Authors Asefa A, Qanche Q, Hailemariam S, Dhuguma T, Nigussie T

Received 12 August 2020

Accepted for publication 21 October 2020

Published 13 November 2020 Volume 2020:13 Pages 2601—2610


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Professor Marco Carotenuto

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Adane Asefa,1 Qaro Qanche,1 Shewangizaw Hailemariam,2 Tadesse Dhuguma,3 Tadesse Nigussie1

1Department of Public Health, College of Health Science, Mizan-Tepi University, Mizan Aman, Ethiopia; 2Department of Midwifery, College of Health Science, Mizan-Tepi University, Mizan Aman, Ethiopia; 3Department of Medical Laboratory, College of Health Science, Mizan-Tepi University, Mizan Aman, Ethiopia

Correspondence: Adane Asefa
Department of Public Health, College of Health Science, Mizan -Tepi University, Mizan-Aman, Ethiopia
Email [email protected]

Background: Waiters working in hotels, pensions, restaurants, and cafeteria are more susceptible to COVID-19 and easily transmit the virus to others because they interact with almost all individuals who enter those establishments. However, information regarding their risk perception is scarce; hence, this study aimed to assess risk perception regarding COVID-19 and its associated factors among waiters working in the selected towns of southwest Ethiopia.
Methods: A cross-sectional study was conducted from June 1 to 15, 2020. The interview-administered structured questionnaire was used to collect data. Data were entered into Epi data manager version 4.0.2 and exported to SPSS version 24 for analysis. Multiple linear regression analysis was done to identify factors associated with risk perception. A p-value of less than 0.05 was used as a level of significance.
Results: A total of 416 waiters were interviewed, with a 98.6% response rate. The mean age of respondents was 27.26 (SD=8.35) years. More than half (53.4%) agreed that COVID-19 causes more deaths than other respiratory diseases. Regarding overall risk perception, two hundred twenty-two (53.4%) participants had high-risk perceptions concerning COVID-19. Risk perception was associated with age (β= 0.10; 95% CI: 0.02, 0.18), knowledge of COVID-19 (β=0.50, 95% CI: 0.23, 0.76) and preventive behaviors (β=0.62; 95% CI: 0.33, 0.90).
Conclusion: A higher level of risk perception was found regarding the COVID-19. Proper risk communication to promote protective behaviors is very essential since waiters are more at risk to be infected with COVID-19 and their infection with the virus has important public health implications.

Keywords: risk perception, COVID-19, coronavirus, waiters


Coronavirus disease-2019 (COVID-19) is a newly emerged disease caused by a highly infectious novel coronavirus that primarily affects the respiratory system. The first case was reported in the Hubei province of China on 29th December 2019.1 The disease has been recognized as a global public health emergency by the World Health Organization (WHO) on 11 March 2020, after cases had started to be seen outside China in less than two months.2 On 13 March 2020, the Ethiopia Federal Ministry of Health was confirmed the first case of COVID-19 in Addis Ababa.3 According to a recent study, the virus spreads between individuals through respiratory droplets, direct contact with an infected individual, or indirect contact with surfaces or objects that have been contaminated with respiratory secretions.4

The impacts of the pandemic are multidimensional; health, social, psychological, political, and economic.5 Hotels, pensions, restaurants, and cafeterias are more susceptible to contagion because they are visited by many people who interact among themselves and with employees.6 In addition, the transmissibility of COVID-19 virus from asymptomatic and symptomatic patients could lead to a higher probability of work-related transmission, as people with mild or no symptoms could continue to work or travel.7 Thus, waiters are more susceptible to contagion, and can easily spread the infection to gusts and to communities where they live. Therefore, they should strictly comply with the basic protective behaviors against the pandemic.4

In the absence of effective vaccination or treatment, active case finding and isolation, quarantine, travel restrictions, frequent hand washing, wearing of face masks, respiratory hygiene, avoiding public gatherings, and social distancing are the measures of choice.8 However, the effectiveness of such measures fundamentally depends on the public willingness to cooperate, which in turn is influenced by public risk perception regarding the pandemic.9–12

Different health education and psychological models indicate that risk perception is a key driver of behaviors.12–15 People who perceive greater risk are more likely to implement protective behaviors, and this influences the probability of infection.16–18 Thus, sound empirical data on how laypersons perceive the risks of newly emerged COVID-19 is essential to devise proper risk communication strategies. Moreover, though waiters are more at risk of contracting the infection,15 information regarding their risk perception is scarce. Previous studies mainly focused on the general population.19–24 However, waiters working in different food and drinking establishments are more vulnerable to contract COVID-19 than the public because of the nature of their work. Thus, they may have different risk perceptions on the disease, and the engagements in preventive behaviors may also not be similar to the public. Hence, data regarding population are important to devise proper risk communication approaches. Therefore, this study aimed to assess risk perception concerning COVID-19 and its associated factors among waiters in selected towns of Bench-Sheko, Sheka, and West-Omo zones, southwest Ethiopia.

Materials and Methods

Study Area and Period

This study was conducted among waiters working in hotels, pensions, restaurants and cafeterias found in Mizan-Aman, Tepi and Jemu towns from June 01 to 15/2020. The towns are located in Southern Nations, Nationalities, and People Regional State in the southwest part of Ethiopia. Mizan-Aman is the capital town of the Bench-Sheko zone and is located at 561 km from Addis Ababa. Jemu is the capital town of the West-Omo zone and is located 625km from Addis Ababa. Tepi is the capital town of Sheka zone and is found at 585 km from Addis Ababa. These towns were selected for the study because they are inhabited by a larger number of people, and there are high social mobilities because they are located in cash crops (coffee) producing areas, which make a conducive condition for the spread of COVID-19 virus.

Study Design

Cross-sectional study design was employed.


All waiters working in hotels, pensions, restaurants, and cafeterias found in selected towns were a source population, while randomly selected waiters working in hotels, pensions, restaurants and cafeterias found in the selected towns were the study population. Waiters who were on duty in the selected institutions at the time of data collection were included in the study. All hotels, pensions, restaurants, and cafeterias in the specified towns that were licensed by the towns’ trade and tourism offices were selected for the study.

Sample Size Determination and Sampling Procedure

The sample size was calculated using a single population proportion formula based on the assumptions of a 95% confidence level, 5% margin of error, and 50% of proportion of high-risk perception. A prevalence of 50% was taken because there was no similar study done in Ethiopia previously. After adding a 10% contingency for non-response, the final sample size became 422 waiters. Regarding the sampling procedure, based on the total number of establishments in each town, the sample size was proportionally allocated to the towns. Then, simple random sampling was employed to select 422 establishments. Finally, one waiter from each selected establishment was randomly recruited using the lottery method for the interview.

Data Collection Tool and Procedure

A structured questionnaire was developed from related studies.12,18–20 The questionnaire has five parts: socio-demographic characteristics, knowledge of COVID-19, preventive behaviors, risk perception, and self-efficacy to practice COVID-19 prevention measures. The questionnaire was prepared in English and translated to the local language “Amharic” and back to English to ensure consistency. The tool was pretested on 10% of the sample size in a town that was not selected for the actual study and modified accordingly. The reliability (internal consistency) of the questionnaire was calculated based on data from the pretest.

The data were collected through face-to-face interviews. We chose face-to-face interview technique than online or telephone surveys due to most waiters in study areas had no access to the internet or telephone. The data collectors used appropriate personal protective equipment (PPE) during data collection to prevent the transmission of COVID-19 virus to data collectors and study participants during the interview. Data were collected by health professionals (BSc) who had experience of data collection under supervision.


Knowledge of COVID-19 (etiology, mode of transmission, symptoms, and prevention methods) was measured using 15 items. The questions were answered on yes, no or I do not know responses. During analysis, the correct answer was coded with “1” and the incorrect, or I do not know coded with “0”. Then sum score was calculated (range 0–15) and categorized. Participants who answered ≤60% of the knowledge questions correctly were considered as having poor knowledge; whereas, those who mentioned 61–75% and >75% of the questions correctly were classified as having fair and good knowledge, respectively.

Risk perception regarding COVID-19 was measured using 12 items which answered on five Likert scales: strongly disagree (1), disagree (2), neutral (3), agree (4), and strongly agree (5). The respondents rated their levels of agreement with different statements. Six items were used to measure the perceived susceptibility dimension of risk perception and the left six items used to measure the perceived severity dimension. The items were stated in a way higher value indicates higher risk perception. The cumulative risk perception score (range 12–60) was computed.25 Based on the mean score, the risk perception categorized as high if scored above mean, and low if scored mean or below. The internal consistency of the items was evaluated on data from pretest, and Cronbach’s alphas for perceived susceptibility was 0.717; whereas, it was 0.684 for perceived severity dimension. Respondents’ level of concern regarding COVID-19 was compared with different diseases that are common in the study areas. The respondents rate their level of concern if they contracted those diseases on five scale items: not at all serious (1), not serious (2), not serious-slight serious (3), serious (4), and very serious (5). The Cronbach’s alpha for these items was 0.685.

The practice of COVID-19 prevention methods was measured using 10 questions. The respondents rated how often they were following the preventive methods that recommended by WHO on five scales: none (1), rarely (2), sometimes (3), frequently (4), and always (5). Finally, the cumulative practice score was computed (range 10–50). The Cronbach’s alpha for practice items was 0.703.

Perceived self-efficacy to practice prevention measures was measured using 4 items which responded on five scales: certainly not (1), probably not (2), perhaps not – perhaps yes (3), probably yes (4), and most certainly (5). The items were stated in a way that the higher value indicates more perceived self-efficacy to practice the measures. The sum and mean scores were computed. Based on the finding of the pretest, the items were internally consistent (Cronbach’s alpha= 0.764).

Data Quality Control

To assure the quality of the data, training was given for data collectors and supervisors on the data collection tool, how to approach the interviewees, details of interview techniques, the need for respecting the right of participants, and how to maintain confidentiality. Also, a pretest was conducted and necessary corrections were made accordingly. The data collection process was closely overseen by trained supervisors. Finally, the data entry was carefully done using Epi-data manager software to minimize errors.

Data Processing and Analysis

The data were entered into Epi data manager version 4.0.2 and exported to SPSS version 24 statistical packages for analysis. Descriptive statistics were done for different variables as supposed necessary. Linear regression analysis was done to identify factors associated with risk perception by treating the cumulative score of risk perception as a continuous variable. The variables were selected using bivariate analysis and dropped from further inclusion in the multivariate model if their p-values were greater than 0.25. Finally, the multivariable linear regression model was fitted using a backward stepwise elimination method, and variables with a p-value less than 0.05 in the final model were considered as significant predictors of risk perception regarding COVID-19. Unstandardized β with 95% CI was used to measure the amount by which dependent variable changes if we change independent variable by one unit keeping other independent variables constant. Multicollinearity was checked using the variance inflation factor (VIF) and found to be within a tolerable range for all variables included in the model.


Socio-Demographic Characteristics

A total of 416 respondents participated in the study, with a response rate of 98.6%. The mean age of study participants was 27.26 (SD=8.35) years. Of the total respondents,350 (84.1%) were single marital status, and 183 (44%) and 154 (37%) had attended primary and secondary or above education, respectively. Three hundred thirty (79.3%) study participants were living with one or more persons in the house (Table 1).

Table 1 Sociodemographic Characteristics of Study Participants, Southwest Ethiopia, 2020

Knowledge of COVID-19

All respondents had heard about new coronavirus/COVID-19 disease. Of the 416 respondents, 84.4% correctly answered the cause of the pandemic. A significant proportion of participants knew the mode of spread of the virus: inhalation of droplets from infected people (78.8%), direct contact with infected people (84.4%), contaminated animals (72.8%), and contaminated object/surfaces (60.6%). The mean of the sum score of knowledge items was 10.32 (SD=2.37) with minimum and maximum scores of 3 and 15, respectively (Table 2). Regarding overall knowledge status, out of 416 respondents, 30.8% had poor knowledge, while the rest 27.6% 41.6 had fair and good knowledge concerning COVID 19, respectively.

Table 2 Knowledge of COVID-19 Among Waiters Working Food and Drinking Establishments Southwest Ethiopia, 2020. (n=416)

Risk Perception Regarding COVID-19

More than half (53.4%) of the study participants agreed that COVID-19 causes more deaths than other respiratory diseases. About two-thirds (66.6%) respondents agreed that people stigmatize them if they get sick due to coronavirus. About one-fourth (25.5%) of waiters strongly agreed that their work exposes them more to COVID-19 more. The mean cumulative score of risk perception was 40.7 (SD=6.65) (Table 3). Two hundred twenty-two (53.4%) participants had high-risk perceptions concerning COVID-19. The highest proportion of respondents was very seriously concerned if they contracted COVID-19 than other diseases (Figure 1).

Table 3 Risk Perception Toward COVID-19 Diseases Among Waiters in Southwest Ethiopia 2020 (n=416)

Figure 1 Level concern about seriousness COVID-19 in comparison with different diseases, 2020. (n=416).

Preventive Behaviors

About, 36.3% and 22.1% of respondents reported that they were maintaining social distancing frequently, and always, respectively. Very few respondents were wearing facemask at work or outside the home always (6.0%), and frequently (11.5%). Out of the total respondents, 45.4% did not wear a glove at all; while, 17.3% wear rarely, 26.4% wear sometimes, 6.7% wear frequently and 4.1% wear always (Table 4).

Table 4 Practice COVID-19 Prevention Methods Among Waiters in Southwest Ethiopia, 2020 (n=416)

Perceived Self-Efficacy to Implement COVID-19 Prevention Measures

Out of the 416 respondents, only 20.9% were almost certain that they can wash their hands with water and soap or with sanitizers. About 6.0% of the respondents reported they certainly did not manage to use facemasks. The mean of the cumulative score of self-efficacy items was 13.40 (Table 5).

Table 5 Self-Efficacy to Practice COVID-19 Prevention Methods Among Waiters in Southwest Ethiopia, 2020 (n=416)

Factors Associated with Risk Perception Towards COVID-19

In the final multivariable linear regression model, the age of respondents, preventive behaviors, and knowledge of COVID-19 were significantly associated with risk perception regarding COVID-19 (p-value <0.05). As the age increase by one year, the risk perception score will increase by 0.10 if the effects of other variables keep constant (β= 0.10; 95% CI: 0.02, 0.18). For a unit increase in the knowledge score, the risk perception score will increase by half if the effects of other factors keep constant (β =0.50: 95%; CI:0.23,0.76). Furthermore, if the score of practicing of COVID-19 prevention measures increased by one unit, the risk perception will increase by 0 0.62 keeping other factors constant (β=0 0.62; 95% CI: 0.33, 0.90) (Table 6).

Table 6 Factors Associated with Risk Perception Towards COVID-19 Disease Among Waiter in Southwest Ethiopia, 2020


Risk perception is central to many health behaviors.13,26 Its role in shaping protective health behaviors could be positive, negative or none.14 This study intended to assess risk perception toward COVID-19 and its associated factors among waiters working in food and drinking establishments in selected towns of southwest Ethiopia. It was recognized that a significant proportion of study participants perceived that COVID-19 virus causes more deaths than other respiratory diseases. Likewise, another study done in Iran showed that the majority of people thought that COVID-19 disease was very severe.27 The highest proportion of respondents was very seriously concerned if they contracted COVID-19. This finding agrees with a study done in Wuhan, China.19 In addition, most waiters perceived that their work exposes them more to the virus than other persons.

The study showed that a very small proportion of study participants were following the recommended protective behaviors. For instance, only 6% and 4.1% of the respondents were wearing facemask and gloves always at work, respectively. These findings are lower compared to a study done in Iran.27 This variation could be due to difference in study populations, awareness, availability of protective equipment, and effect of the pandemic across study settings. Also, the low facemask use in our study could be due to the controversies on the importance of facemask to prevent the transmission of the virus during the earlier phase of the pandemic.

The study also showed that the higher the perceived risk regarding COVID-19, the more likely practicing protective behaviors. This finding is consistent with other studies.11,12,14,23 This implies proper risk communication that addresses susceptibility to the virus and the severity of the disease could enhance protective behaviors such as frequent hand washing, wearing of face mask, avoiding public gatherings, and social distancing.

The higher the age, the more perceived risk towards COVID-19. The risk of death from the COVID-19 virus is higher among older people.28 As a result, older people might have higher perceived severity of the COVID-19 pandemic. On the other hand, during the earlier phase of the pandemic, it was wrongly perceived older people infected with the virus more than youngers. This might also give rise to the perception that older people are highly susceptibility to the virus.

The knowledge about COVID-19 is also positively associated with perceived risk regarding COVID-19. A similar finding was also reported by previous studies.20,29 This could be due to individuals who had high-perceived risk might follow the media frequently or read about the pandemic more often. Likewise, people’s knowledge of the spread of the virus and case fatality might affect the risk perception regarding the pandemic. However, due to the cross-sectional nature of this study, we cannot confirm the exact temporal relationship between knowledge and risk perception.


Due to the cross-sectional nature of this study, we cannot assess how risk perceptions change over time. Furthermore, the temporal relationship between the outcome and predictor variables cannot be established. Also, there might be the risk of social desirability bias since individual behaviors have public health implications and the data were collected through self-report.


A higher level of risk perception was found regarding the COVID-19 among waiters working in food and drinking establishments in southwest Ethiopia. The risk perception was positively associated with age, knowledge, and preventive behaviors. Proper risk communication to promote protective behaviors is very essential since waiters are more at risk to be infected with COVID-19 and their infection with the virus has public health implications. The findings from the current study provided the evidence for health policy on the risk perception, and its association with preventive behaviors among waiters during the early stage of the COVID-19 pandemic.

Data Sharing Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Ethical Approval and Consent to Participate

This study was conducted per the Declaration of Helsinki. Ethical clearance was obtained from the Institutional Review Board (IRB) of Mizan-Tepi University. The participants have informed the purpose of the study and gave written consent before the interview. Participation in the study was completely voluntary, and the right to withdraw from the interview was also secured. Confidentiality of the information was ensured throughout the study.


We would like to express our heartfelt gratitude to Mizan-Tepi University for supporting this research project. We also extend our thanks to our data collectors and study participants for their magnificent contributions to this work.


There is no funding to report.


The authors declare that they have no competing interests.


1. Vandeweerd V, Van Der VD. COVID-19 overview of information available to support the development of medical countermeasures and interventions against COVID-19. 2020;1–120.

2. Hauck G, Gelles K, Bravo V. Coronavirus updates_ how COVID-19 unfolded in the US. 2020.

3. WHO. First Case of Covid-19 Confirmed in Ethiopia WHO Regional Office for Africa; 2020

4. WHO. Operational Considerations for COVID-19 Management in the Accommodation Sector. 2020.

5. FMoH. National Comprehensive COVID19 Management Handbook. 2020.

6. Multnomah County Health Department. COVID19 Cleaning & Sanitizing Guidelines for Restaurants & Food Service. 2020.

7. Lan FY, Wei CF, Hsu YT, Christiani DC, Kales SN. Work-related COVID-19 transmission in six Asian countries/areas: a follow-up study. PLoS One. 2020;15(5):1–11doi:10.1371/journal.pone.0233588

8. World Health Organization. Q&A on coronaviruses (COVID-19). 2020. Available from: Accessed October 23, 2020.

9. Ibuka Y, Chapman GB, Meyers LA, et al. The dynamics of risk perceptions and precautionary behavior in response to 2009 (H1N1) pandemic influenza. BMC Infect Dis.2010;10(1):296. doi:10.1186/1471-2334-10-296

10. Brug J, Aro AR, Richardus JH. Risk perceptions and behaviour: towards pandemic control of emerging infectious diseases. Int J Behav Med. 2009;16(1):3–6. doi:10.1007/s12529-008-9000-x

11. Carter SE, O’Reilly M, Walden V, Frith-Powell J, Umar Kargbo A, Niederberger E. Barriers and enablers to treatment-seeking behavior and causes of high-risk practices in ebola: a case study from Sierra Leone. J Health Commun. 2017;22(sup1):31–38. doi:10.1080/10810730.2016.1222034

12. Glanz K, Rimer BK, Viswanath K. Health Behavior and Health Eduction: Theory, Research and Practice.4th edition. San Francisco, USA: Jossey-Bass.2002;1–552.

13. Brewer NT, Weinstein ND, Cuite CL, Herrington JE. Risk perceptions and their relation to risk behavior. Ann Behav Med. 2004;27(2):125–130.

14. Brewer NT, Chapman GB, Gibbons FX, Gerrard M, McCaul KD, Weinstein ND. Meta-analysis of the relationship between risk perception and health behavior: the example of vaccination. Health Psychol. 2007;26(2):136–145doi:10.1037/0278-6133.26.2.136

15. Dionne G, Fluet C, Desjardins D. Predicted risk perception and risk-taking behavior: the case of impaired driving. J Risk Uncertain. 2007;35(3):237–264.

16. Massaro E, Bagnoli F. Epidemic spreading and risk perception in multiplex networks: a self-organized percolation method. Phys Rev. 2014;90(5):1–8.

17. Herrera-Diestra JL, Meyers LA, Yang Y. Local risk perception enhances epidemic control. PLoS One. 2019;14(12):1–15. doi:10.1371/journal.pone.0225576

18. Leppin A, Aro AR. Risk perceptions related to SARS and avian influenza: theoretical foundations of current empirical research. Int J Behav Med. 2009;16(1):7–29. doi:10.1007/s12529-008-9002-8

19. Zhong Y, Liu W, Lee T, Zhao H, Ji J. Risk perception, knowledge, information sources and emotional states among COVID-19 patients in Wuhan, China. Nurs Outlook. 2020:1–9. doi:10.1016/j.outlook.2020.08.005

20. Dryhurst S, Schneider CR, Kerr J, et al. Risk perceptions of COVID-19 around the world. J Risk Res. 2020;1466–4461. doi:10.1080/13669877.2020.1758193

21. Luu T, Huynh D. The COVID-19 risk perception: a survey on socioeconomics and media attention. Econ Bull. 2020;40(1):758–764.

22. Ding Y, Du X, Li Q, et al. Risk perception of coronavirus disease 2019 (COVID-19) and its related factors among college students in China during quarantine. PLoS One. 2020:15(8); e0237626. doi:10.1371/journal.pone.0237626

23. Ying E, Chan Y, Huang Z, et al. Sociodemographic predictors of health risk perception, attitude and behavior practices associated with health-emergency disaster risk management for biological hazards: the case of covid-19 pandemic in Hong Kong, SAR China. Int J Environ Res Public Heal. 2020;17:3869. doi:10.3390/ijerph17113869

24. Luu T, Huynh D. Data for understanding the risk perception of COVID-19 from vietnamese sample. Data Br. 2020;30:105530. doi:10.1016/j.dib.2020.105530

25. Wol K, Larsen S, Øgaard T. How to define and measure risk perceptions. Ann Tour Res. 2019;79:102759. doi:10.1016/j.annals.2019.102759

26. Abdulkareem SA, Augustijn EW, Filatova T, Musial K, Mustafa YT. Risk perception and behavioral change during epidemics: comparing models of individual and collective learning. PLoS One. 2020;15(1):1–22.

27. Honarvar B, Lankarani KB, Kharmandar A, Shaygani F. Knowledge, attitudes, risk perceptions, and practices of adults toward COVID-19: a population and field-based study from Iran. Int J Public Health. 2020;65(6):731–739. doi:10.1007/s00038-020-01406-2

28. Ioannidis JPA, Axfors C, Contopoulos-Ioannidis DG. Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicenters. Environ Res. 2020;188:109890. doi:10.1016/j.envres.2020.109890

29. Saqlain M, Munir MM, Ur Rehman S, et al. Knowledge, attitude and practice among healthcare professionals regarding COVID-19: a cross-sectional survey from Pakistan. J Hosp Infect. 2020;105(3):419–423. doi:10.1016/j.jhin.2020.05.007

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