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Adherence to COVID-19 preventive measures and associated factors in Ethiopia: A systematic review and meta-analysis

  • Gdiom Gebreheat ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    gdiom7@gmail.com, gdiom.abady@napier.ac.uk

    Affiliations Department of Nursing, Adigrat University, Adigrat, Ethiopia, School of Health and Social Care, Edinburgh Napier University, Edinburgh, United Kingdom

  • Ruth Paterson,

    Roles Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation School of Health and Social Care, Edinburgh Napier University, Edinburgh, United Kingdom

  • Henok Mulugeta,

    Roles Data curation, Methodology, Validation, Writing – review & editing

    Affiliation Department of Nursing, Debre Markos University, Debre Markos, Ethiopia

  • Hirut Teame

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Public Health, Adigrat University, Adigrat, Ethiopia

Abstract

Background

Reluctance to the COVID-19 preventive measures have been repeatedly reported in Ethiopia although compliance with these actions is the key step to minimize the pandemic’s burden. Hence, this systematic review and meta-analysis aims to address the gap in the literature by determining the pooled magnitude of adherence to COVID-19 preventive measures and identifying its associated factors in Ethiopia.

Materials and methods

The electronic databases used to search articles were PubMed/MEDLINE, CINAHL, Web of Science, ScienceDirect, Research4Life and other sources of grey literature including Google Scholar and World Health Organization (WHO) database portals for low- and middle-income countries. Full English-language articles published between 2019 and 2022 were eligible for the review and meta-analysis. Relevant data extracted and descriptive summaries of the studies presented in tabular form. The methodological quality of articles assessed using the Joanna Briggs Institute (JBI) quality assessment tool. The pooled magnitude of adherence determined by applying a random-effects model at a 95% CI.

Results

Of 1029 records identified, 15 articles were included in the systematic review and 11 were selected for meta-analysis. The pooled estimate of adherence to COVID-19 preventive measures in Ethiopia was 41.15% (95% CI:32.16–50.14%). Furthermore, perceived COVID-19 disease severity (AOR:1.77, 95% CI: (1.40–2.25)), attitude (AOR:1.85, 95% CI: (1.36–2.53)) and knowledge (AOR:2.51, 95% CI: (1.67–3.78)) to COVID-19 preventive measures showed significant association with adherence to COVID-19 preventive measures.

Conclusion

The magnitude of adherence to COVID-19 preventive measures in Ethiopia appeared to be low. Therefore, the government of Ethiopia and other stakeholders should mobilize resources to improve the adherence level of the community to the COVID-19 preventive measures and decrease public fatigue.

Introduction

The current pandemic, COVID-19 disease, is a highly contagious viral infection caused by novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Person-to-person spread is the main means of transmission, when any infected person sneeze or cough respiratory droplets of the virus, and these droplets enter the lungs of a nearby person via inhalation. Besides, environmental contamination is another way to spread the virus, resulting in an unprecedented threat to global health and well-being. Patients infected from SARS-CoV-2 infection often presented with dry cough, fever, sputum production and shortness of breath and upper airway congestion [1,2].

The WHO has recommended multiple COVID-19 prevention and control measures including proper hand washing, physical distancing, covering mouth and nose when coughing and sneezing, avoiding touching face and staying at home [3]. Several countries have implemented the WHO recommendations to prevent and control COVID-19 infection [4]. The earlier announcement of lockdown and the stricter the adherence was believed to lead to fewer infected total cases and deaths. Hence, it was expected to accelerate the containment of the virus and lessen the consequences of the mitigating measures [5]. Unfortunately, globally, as of 1 August, 2022, there were more than 577 million confirmed cases of COVID-19, including 6.4 million deaths, reported to WHO [6].

In Ethiopia, following the confirmation of the first case of COVID-19 in March 2020, the Ethiopian ministry of health and public health institute have taken several initiatives to decrease the burden of COVID-19 [7]. Among these, hand hygiene, facemask and social distancing were the primary three preventive measures that the government communicated to the community through various media platforms [8]. Furthermore, measures were imposed to close schools, restrict major gatherings and movements of people, and even lockdown. Despite this, the preventive measures were being ignored by the community and leaders at different level [9].

Poor adherence towards COVID-19 mitigation measures has continued as an escalating problem in Ethiopia [10]. According to the study conducted among Hossana residents, nearly half of them had poor adherence to the COVID-19 preventive measures [11]. Likewise, in a recent study in the capital of Ethiopia, Addis Ababa, nearly 40% of the community has shown poor implementation of COVID-19 preventive measures [12]. Surprisingly, in a study of Oromia region of Ethiopia, the overall adherence level of the community to the recommended safety measures of COVID-19 was 8.3% [13], which seems far lower than the other studies. The main barriers to effective implementation of public health measures were resistance to change, lack of community engagement, negligence, insufficient training for front line workers, poor law enforcement, poor supportive supervision, and lack of continuous community awareness creation [14].

However, there is no pooled evidence on the magnitude of adherence to COVID-19 preventive measures and its associated factors in Ethiopia. Thus, this meta-analysis aims to estimate the magnitude of adherence to COVID-19 preventive measures and its associated factors. More importantly, the systematic review and meta-analysis results will help decision-makers to plan and implement effective action against the COVID-19 pandemic.

Materials and methods

Search strategies

Research articles were accessed through electronic web-based database searches and reference list reviews using the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) checklist guidelines [15]. Literature that reported adherence status to COVID-19 preventive measures and/or its associated factors in Ethiopia were searched from both main electronic databases and grey literature sources. The electronic databases used to search articles were PubMed/MEDLINE, ScienceDirect, Web of Science, CINAHL, Research4Life and other World Health Organization (WHO) database portals for low- and middle-income countries. In addition, the researchers found related articles through a desk review of the doctoral dissertations available at Ethiopian university libraries and institutional repositories, and from reviewing the reference lists of related articles. Electronic database searches were conducted from July 20, 2022, to July 23, 2022. The main terms used during electronic database search were: (“Adherence” OR “Compliance” OR “Associated factors” OR “Determinants” OR “Predictors”) AND (“COVID-19 prevention measures” OR “COVID-19 preventive measures”) AND (Ethiopia). Please see S1 Table for a detail article searching process, terms used in each database and search results.

Inclusion and exclusion criteria

All English-language, full-text, original research articles conducted in Ethiopia from January1, 2019 to July 23, 2022 and published in peer-reviewed journals or filed as completed dissertations were considered for inclusion. Moreover, the article should measure the adherence level and/or associated factors of COVID-19 preventive measures in Ethiopia. However, case series, opinion papers and reports were excluded.

Studies screening and selection process

All electronic search results were transferred into Mendeley reference manager software version 1. 19.8. Next, we organized all these articles into a single folder for duplicate citation removal and further management of articles. After removing duplicate citations with the software, two authors (GG, RP) independently screened the articles, based on preset eligibility criteria. The article screening process had three sequential stages, title, abstract and full-text screening. Through title screening, studies entitled with terms directly/indirectly measure the adherence level and/or associated factors of COVID-19 preventive measures in Ethiopia, were selected for abstract screening. And, in abstract screening, articles were read their abstract if they could measure either of the review and meta-analysis outcomes. Consequently, full-text screenings were carried out with four independent authors. The final decision whether to include an article were reached on the consensus of all the authors. The screening and selection of articles were guided according to the PRISMA guideline (Fig 1).

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Fig 1. A PRISMA flow chart that shows the process of article selection.

https://doi.org/10.1371/journal.pone.0275320.g001

Critical appraisal of studies

Quality of studies was critically evaluated for the validity of results. The methodological quality of the papers was assessed using the JBI quality assessment checklists for cross-sectional analytical studies [16]. This JBI critical appraisal checklist has eight elements, which mainly addresses the methodological area of each article. It focused on the appropriateness of the statistical analysis, objective, inclusion criteria, study population and setting, exposure and outcomes measurement, and management of confounding factors. The evaluation and decision of each article was finalized on the consensus of all authors. Accordingly, articles with positive answers (yes) for more than 50% of the eight-elemental checklist (i.e., yes for five or more) were included in this systematic review and meta-analysis (S2 Table).

Data extraction

After all authors agreed on the articles to be included in the review and meta-analysis, we set an extraction template in the Microsoft Excel sheet. The study description in Table 1 was formulated to summarize the study design, study setting, sample size, aim, key finding (magnitude of adherence to COVID-19 preventive measures), and secondary outcome (associated factors with Adherence to COVID-19 preventive measures). Data extraction was carried out by two authors (GD and RP) and double checked by the other authors. The extracted numerical data were documented and stored in a Microsoft Excel separate sheet (S3 Table).

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Table 1. Characteristics and main findings of the articles included in the systematic review and meta-analysis.

https://doi.org/10.1371/journal.pone.0275320.t001

Outcome of interest

The primary outcome of interest was the pooled magnitude of adherence to COVID-19 preventive measures in Ethiopia. The magnitude of adherence was measured as the number of adhering study subjects divided by the total sample size multiplied by 100. Secondly, we have also pooled the odds ratio of each factor to see if there was a statistical association with adherence to COVID-19 preventive measures in Ethiopia.

Data analysis

The raw data in the Microsoft Excel spreadsheet template was transferred to STATA version 16 software for analysis. A pooled magnitude of adherence to COVID-19 preventive measures in Ethiopia was estimated at a 95% confidence interval (CI). Furtherly, we conducted a regional subgroup analysis. Also, a pooled odds ratio of different variables was calculated using a RevMan version 5.4.1 to check if there was an association between independent variables and the dependent variable (adherence to COVID-19 preventive measures). The heterogeneity of study outcomes was assessed using the I2 statistic [17]. Accordingly, studies with high heterogeneity were estimated using a random-effects model, and fixed effect model was run in variables showed low heterogeneity (<50%). Parallelly, a publication bias was checked using a funnel plot asymmetry and Egger’s and Begg-Mazumdar Rank correlation tests [18]. Eventually, the statistical analysis and the results were double-checked by all authors.

Results

Identification and description of studies

A total of 1029 citations were collected through electronic database search and other sources (Fig 1). Of these, we excluded 359 items due to duplication. From the remained 670 collections, 578 items were excluded through title screening, while 70 were excluded after the abstract screening. Next, 22 full articles were reviewed according to the predefined eligibility criteria. Eventually, 15 articles were found fully eligible for systematic review, of which 11 articles were included in meta-analysis. All of them were conducted using a cross-sectional study design [10,11,13,1930]. Nearly half (n = 7) of these studies were conducted in Amhara region [10,19,24,2729,31], four articles in SNNP (Southern Nations, Nationalities, and Peoples’) region [11,20,21,25], three in Oromia region [13,22,23] and the remained one study was conducted in Addis Ababa [30]. The maximum sample size recorded was 2751 subjects [13], while the minimum was 324 [19]. Furthermore, majority of the studies had more than 95% response rate (Table 1).

Quality appraisal of the review

The JBI quality assessment tools were used to evaluate the methodological quality of the articles, based on the consensus of the two evaluators (RP, GD). We included studies with clear eligibility criteria for inclusion in the sample, a detailed description of the context, a reliable and valid measure of exposure, and adequate statistical analysis. Both authors agreed that articles with ≥ 50% of the total score to be included in the systematic review and meta-analysis. As a result, 15 studies were of high methodological quality for the primary outcome of interest [10,11,13,1930] (S2 Table).

Publication bias

Publication bias was evidenced on both the funnel plots of precision asymmetry and the Egger’s test of the intercept. We run a trim and fill analysis in the random-effects model [32]. The magnitude estimates did not differ significantly between the initial and, trim and fill models (Figs 2 and 3).

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Fig 2. Funnel plot with pseudo 95% confidence interval limits.

https://doi.org/10.1371/journal.pone.0275320.g002

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Fig 3. Filled funnel plot with pseudo 95% confidence interval.

https://doi.org/10.1371/journal.pone.0275320.g003

Adherence to COVID-19 preventive and control measures

Fifteen articles [10,11,13,1930] discussed the participants’ level of adherence to COVID-19 preventive measures in Ethiopia. Of these, four articles [19,20,29,30] discussed the adherence level of participants to each preventive measures separately while the remained 11 articles [10,11,13,2128] estimated the overall compliance or adherence level. In two articles, the compliance percentage to hand hygiene was 22.3 [19] and 97.1 [30]. W. Hailu, et al. reported that 55.4% of the participants had poor compliance with social distancing measures [29]. In another article, 35.4% of respondents reported to be adherence with regular mask wearing [20]. Furthermore, 11 articles [10,11,13,2128] were included to estimate the pooled magnitude of adherence to COVID-19 preventive measures in Ethiopia. The magnitude of adherence to COVID- 19 preventive measures in Ethiopia was ranged from 8.3% in Oromia [13] to 56.1% in Amhara [26]. Hence, the I2 statistic for heterogeneity has shown significant differences between the studies (I2 = 99%, p<0.05). Therefore, we have decided to fit DerSimonian and Laird random-effects model to estimate the pooled magnitude of adherence to COVID-19 preventive measures. Our decision was based on the theoretical assumptions that the heterogeneity (difference between the studies) might be because of the settings and socio-economic contexts [33,34]. The model also shows the weight of each study as per its sample size and effect size [35]. Accordingly, highest weight was reported in Silesh et al, 9.72% [26] while the lowest weight was recorded in a study conducted by Abeya et al., 7.96% [13] (Fig 4). The pooled estimate of adherence to COVID-19 preventive measures in Ethiopia was 41.15% (95% CI:32.16–50.14%) (Fig 4).

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Fig 4. Forest plot studies assessing the magnitude of adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g004

Also, the sub-group analysis of study setting showed that the pooled magnitude of adherence to COVID-19 measures in Amhara, SNNP and Oromia regions of Ethiopia was, 48.8% (95% CI:42.59–55.12%), 40.22% (95% CI:16.46–63.97%) and 27.35% (95% CI:2.24–52.46%), respectively (Fig 5).

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Fig 5. Forest plot of studies assessing region-based magnitude of adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g005

Factors associated with adherence to COVID-19 preventive measures in Ethiopia

Twelve articles have discussed about the associated factors of adherence to COVID-19 preventive measures in Ethiopia [10,11,13,19,20,2326,2830]. Of these, 8 articles were included in our meta-analysis to identify the associated factors of adherence to COVID-19 preventive measures in Ethiopia [10,11,13,2326,28]. Sex [10,11,2325,30], age [11,24,25,29], perceived COVID-19 severity [10,11,19,20,24,25], attitude [10,11,13,2526] and knowledge [10,11,13,23,25,26,28] to COVID-19 preventive measures were found to have a statistically significant association with adherence to COVID-19 preventive measures (Figs 610).

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Fig 6. Association between sex and adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g006

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Fig 7. Association between age and adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g007

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Fig 8. Association between knowledge and adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g008

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Fig 9. Association between attitude and adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g009

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Fig 10. Association between perceived disease severity and adherence to COVID-19 preventive measures in Ethiopia.

https://doi.org/10.1371/journal.pone.0275320.g010

Sex.

In this meta-analysis, the sex of the study participants was found to be a statistically significant factor in the adherence level of COVID-19 preventive measures. Male participants were 36% less likely to adhere to COVID-19 preventive measures than female participants (AOR:0.64, 95% CI: (0.54–0.78)). The heterogeneity between these studies was low (Fig 6).

Age.

Also, age was another factor that had a statistically significant correlation with the adherence status of study participants to COVID-19 preventive measures in Ethiopia. People who were younger than 40 years old had 1.6 odds of adherence to COVID-19 preventive measures (AOR:1.6, 95% CI: (1.04–2.46)) (Fig 7).

Knowledge of COVID-19 preventive measures.

The present meta-analysis also found that people’s knowledge about COVID-19 preventive measures significantly associated with their adherence status to the COVID-19 preventive measures. Those who had good knowledge about COVID-19 were 2.51 more likely to adhere to COVID-19 preventive measures than those who had poor knowledge, (AOR:2.51, 95% CI: (1.67–3.78)) (Fig 8).

Attitude towards COVID-19 preventive measures.

People who had a favourable attitude towards COVID-19 preventive measures were 1.85 times more likely to adhere to the preventive measures, (AOR:1.85, 95% CI: (1.36–2.53)) (Fig 9).

Perceived severity of COVID-19 disease.

Perceived COVID-19 severity was also another significant variable that correlated with the peoples’ adherence status to the COVID-19 preventive measures in Ethiopia. People who had perceived the severity of COVID-19 infection were 1.77 times more likely to adhere to the COVID-19 preventive measures than those who had not this perception (AOR:1.77, 95% CI: (1.40–2.25)) (Fig 10).

Discussion

This systemic review and meta-analysis attempted to estimate the pooled magnitude of adherence to COVID-19 preventive measures and its associated factors in Ethiopia. We found 41.15% of the people were adhered to the COVID-19 preventive measures in Ethiopia. This is consistent with a previous review in the country where the pooled level of health professional’ practice, towards WHO COVID-19 management and personal protection recommendations, estimated to be 40.3% [36]. This low level of adherence to COVID-19 preventive measures could be related with public fatigue, ignorance, misinformation, personal or social norms and perceived behavior control [3740].

Another aim of this study was to identify the associated factors of adherence to COVID-19 preventive measures. Accordingly, sex, age, perceived COVID-19 severity, attitude, and knowledge of COVID-19 preventive measures were found to have a statistically significant association with the adherence to COVID-19 preventive measures.

Regarding sex, male participants were 36% less likely to adhere to COVID-19 preventive measures than female participants (AOR:0.64, 95% CI: (0.54–0.78)). This finding is consistent with previous studies conducted in Canada, China, Brazil, Uganda and Somalia, where male participants had had lower compliance with the COVID-19 preventive measures [4145]. In the context of Ethiopia, men are the one often who runs the outdoor day-to-day activities that may lead to break the COVID-19 preventive measures.

People who were younger than 40 years old had 1.6 odds of adherence to COVID-19 preventive measures (AOR:1.6, 95% CI: (1.04–2.46)). We believe that Ethiopia has a higher educated adult population than it had before decades. Therefore, related with the recent digital technology advancements, the young generation might have better awareness and adherence to COVID-19 preventive measures than the old population. Conversely, studies from Brazil and Switzerland indicated that young adults are non-compliant [41,46]. This controversy might be because of the socio-demographic differences of study participants between Ethiopia and, Brazil and Switzerland.

In our meta-analysis, those who had good knowledge about COVID-19 preventive measures were 2.51 more likely to adhere to COVID-19 preventive measures than those who had poor knowledge, (AOR:2.51, 95% CI: (1.67–3.78)). This finding is complementary to that of the Democratic Republic of the Congo [47]. In connection, knowledge of restrictions can also predict positive attitudes towards restrictions and increase perceived ability to adhere to the mitigating measures as well [48]. Therefore, in this review, people who had a favourable attitude towards COVID-19 preventive measures had had 1.85 times more likely to adhere to the preventive measures (AOR:1.85, 95% CI: (1.36–2.53)). In line with this, a study from Iran established the positive relationship between positive attitude towards the effectiveness of preventive measures and adherence to them [49]. Therefore, the participants’ awareness and attitude could have an impact on their level of compliance to the rules and regulation of COVID-19 preventive measures.

Our finding also revealed that people who perceived the severity of COVID-19 had 1.77 odds of adherence to the COVID-19 preventive measures, (AOR:1.77, 95% CI: (1.40–2.25)). In previous studies, perceived susceptibility to COVID-19 infection and perceived severity of health-related consequences were linked to engagement in disease-preventive behaviors. Consequently, there is a possibility of a positive relationship between perceived severity and adherence [5053]. Also, according to previous Health Belief Model (HBM)-based studies, people’s perception of the seriousness of having COVID-19 infection can dictate them to comply with recommended preventive measures [5457].

Limitations

Our systematic review and meta-analysis had some limitations. First, all included studies were cross-sectional by design. Instead, it would have been more impactful if studies with variety of design had been included in the review. Secondly, the presence of heterogeneity between studies may not be supportive to draw inclusive inference about the general population.

Conclusion

This systematic review and meta-analysis found that the level of adherence to COVID-19 preventive measures in Ethiopia was low, below 50%. Furthermore, sex, age, perceived COVID-19 severity, attitude and knowledge to COVID-19 preventive measures were found to have a statistically significant association with adherence to COVID-19 preventive measures. Therefore, the government of Ethiopia and other stakeholders should mobilize resources to improve the adherence level of the community to the COVID-19 preventive measures and decrease public fatigue.

Supporting information

S3 Appendix. RevMan dataset for factors associated with adherence to COVID-19 preventive measures.

https://doi.org/10.1371/journal.pone.0275320.s006

(RM5)

Acknowledgments

We thank Adigrat University and Edinburgh Napier University for allowing us to access their databases.

References

  1. 1. Tsang HF, Chan LWC, Cho WCS, Yu ACS, Yim AKY, Chan AKC, et al. An update on COVID-19 pandemic: the epidemiology, pathogenesis, prevention and treatment strategies. Expert Rev Anti Infect Ther [Internet]. 2021;19(7):877–88. Available from: pmid:33306423
  2. 2. Jin Yuefei and Yang Haiyan and Ji Wangquan and Wu Weidong and Chen Shuaiyin and Zhang Weiguo et al. Intuition on virology, epidemiology, pathogenesis, and control of COVID-19. Nov Res Microbiol J. 2020;4(5):955–67.
  3. 3. Coronavirus [Internet]. [cited 2021 Jul 11]. https://www.who.int/health-topics/coronavirus#tab=tab_2.
  4. 4. Stephen O, Ilesanmi OS, Bello AE, Afolabi AA. COVID-19 pandemic response fatigue in Africa: causes, consequences, and counter-measures. Pan Afr Med J [Internet]. 2020 [cited 2021 Jul 13];37(1). Available from: https://www.panafrican-med-journal.com/content/series/37/1/37/fullJournal. https://www.panafrican-med-journal.com//content/series/1/.
  5. 5. Amer F, Hammoud S, Farran B, Boncz I, Endrei ora. Assessment of Countries’ Preparedness and Lockdown Effectiveness in Fighting COVID-19. 2020.
  6. 6. WHO Coronavirus (COVID-19) Dashboard | WHO Coronavirus (COVID-19) Dashboard With Vaccination Data [Internet]. [cited 2021 Jul 11]. https://covid19.who.int/.
  7. 7. Ethiopian health care facility COVID-19 Preparedness and response protocol.
  8. 8. Baye K. COVID-19 prevention measures in Ethiopia: Current realities and prospects.
  9. 9. Shewamene Z, Shiferie F, Girma E, Wubishet BL, Kiros M, Abraha A, et al. Ethiopia: Experts’ Perspective on the Need of Effective Health Communication Strategies. Ethiop J Heal Sci [Internet]. 2021 [cited 2021 Jul 11];31(1):201. Available from:
  10. 10. Azene ZN, Merid MW, Muluneh AG, Geberu DM, Kassa GM, Yenit MK, et al. Correction: Adherence towards COVID-19 mitigation measures and its associated factors among Gondar City residents: A community-based cross-sectional study in Northwest Ethiopia. Vol. 16, PloS one. 2021. p. e0256954. pmid:34437652
  11. 11. Temesgen T, Abute L. Adherence towards COVID-19 prevention measures and associated factors in Hossana town, South Ethiopia, 2021. Int J Clin Pract [Internet]. 2021 Dec 15;75(12):e14530–e14530. Available from: https://login.ezproxy.napier.ac.uk/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=c8h&AN=151420400&site=ehost-live. pmid:34128577
  12. 12. Desalegn IdZ, Deyessa N, Teka B, Shiferaw W, Hailemariam D, Addissie A, et al. COVID-19 and the public response: Knowledge, attitude and practice of the public in mitigating the pandemic in Addis Ababa, Ethiopia. 2021 [cited 2021 Jul 11]; Available from: pmid:33411766
  13. 13. Abeya SG, Barkesa SB, Sadi CG, Gemeda DD, Muleta FY, Tolera AF, et al. Adherence to COVID-19 preventive measures and associated factors in Oromia regional state of Ethiopia. PLoS One. 2021 Oct;16(10):e0257373. pmid:34669723
  14. 14. Sidamo NB, Hussen S, Shibiru T, Girma M, Shegaze M, Mersha A, et al. Exploring Barriers to Effective Implementation of Public Health Measures for Prevention and Control of COVID-19 Pandemic in Gamo Zone of Southern Ethiopia: Using a Modified Tanahashi Model. Risk Manag Healthc Policy [Internet]. 2021 Mar 19 [cited 2021 Jul 11];14(12):1219. Available from: https://www.dovepress.com/exploring-barriers-to-effective-implementation-of-public-health-measur-peer-reviewed-fulltext-article-RMHP.
  15. 15. Moher D, Liberati A, Tetzlaff J, Altman D. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med [Internet]. 2009 Jul [cited 2021 Jul 14];6(7):1–6. Available from: https://pubmed.ncbi.nlm.nih.gov/19621072/.
  16. 16. Velissaris D, Karamouzos V, Pierrakos C, Koniari I, Apostolopoulou C, Karanikolas M. The Joanna Briggs Institute Critical Appraisal Tools for Use in JBI Systematic Reviews Checklist for Analytical Cross Sectional Studies. North Adelaide, Aust Joanna Briggs Inst [Internet]. 2017 [cited 2020 Oct 22]; Available from:
  17. 17. Huedo-Medina T. B., Sánchez-Meca J., Marín-Martínez F., & Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I2 index? Psychol Methods. 2006 Oct;11(2):193–206. pmid:16784338
  18. 18. Rendina-Gobioff G. Detecting publication bias in random effects meta-analysis: An empirical comparison of statistical methods. 2006 [cited 2021 Jul 14]; https://scholarcommons.usf.edu/etd/2671/.
  19. 19. Keleb A, Ademas A, Lingerew M, Sisay T, Berihun G, Adane M. Prevention Practice of COVID-19 Using Personal Protective Equipment and Hand Hygiene Among Healthcare Workers in Public Hospitals of South Wollo Zone, Ethiopia. Front public Heal. 2021;9:782705. pmid:34926394
  20. 20. Zewude B, Melese B, Habtegiorgis T, Tadele M, Solomon W. Compliance With Protective Behavioral Recommendations in the Outbreak of COVID-19 Among People Working in the Urban-Based Informal Economy in Southern Ethiopia. Front PUBLIC Heal. 2021 Aug;9. pmid:34422754
  21. 21. Kayrite QQ, Hailu AA, Tola TN, Adula TD, Lambyo SH. Compliance with COVID-19 Preventive and Control Measures among Food and Drink Establishments in Bench-Sheko and West-Omo Zones, Ethiopia, 2020. Int J Gen Med. 2020;13:1147. pmid:33235488
  22. 22. Etafa W, Gadisa G, Jabessa S, Takele T. Healthcare workers’ compliance and its potential determinants to prevent COVID-19 in public hospitals in Western Ethiopia. BMC Infect Dis [Internet]. 2021 [cited 2021 Jun 24];21(1). Available from: pmid:34011263
  23. 23. Zenbaba D, Sahiledengle B, Takele A, Tekalegn Y, Yassin A, Tura B, et al. Compliance towards infection prevention measures among health professionals in public hospitals, southeast Ethiopia: a cross-sectional study with implications of COVID-19 prevention. Trop Med Health. 2021;49(1):1–11.
  24. 24. Shewasinad Yehualashet S, Asefa KK, Mekonnen AG, Gemeda BN, Shiferaw WS, Aynalem YA, et al. Predictors of adherence to COVID-19 prevention measure among communities in North Shoa Zone, Ethiopia based on health belief model: A cross-sectional study. PLoS One. 2021 Jan;16(1):e0246006. pmid:33481962
  25. 25. Bante A, Mersha A, Tesfaye A, Tsegaye B, Shibiru S, Ayele G, et al. Adherence with COVID-19 Preventive Measures and Associated Factors Among Residents of Dirashe District, Southern Ethiopia. Patient Prefer Adherence. 2021;15:237–49. pmid:33568900
  26. 26. Silesh M, Demisse TL, Taye BT, Desta K, Kitaw TM, Mekuria AD, et al. Compliance with COVID-19 Preventive Measures and Associated Factors Among Women Attending Antenatal Care at Public Health Facilities of Debre Berhan Town, Ethiopia. Risk Manag Healthc Policy. 2021;14:4561–9. pmid:34795541
  27. 27. Kebede AA, Taye BT, Wondie KY, Tiguh AE, Eriku GA, Mihret MS. COVID-19 preventive practices during intrapartum care- adherence and barriers in Ethiopia; a multicenter cross- sectional study. PLoS One. 2021;16(11):e0260270. pmid:34793560
  28. 28. Temesgan WZ, Aklil MB, Yacob HS, Mekonnen ET, Tegegne ED, Tesfa EB, et al. Adherence to COVID-19 preventive practice and associated factors among pregnant women in Gondar city, northwest Ethiopia, 2021: Community-based cross-sectional study. PLoS One. 2022;17(3). pmid:35235581
  29. 29. Hailu W, Derseh L, Hunegnaw MT, Tesfaye T, Angaw DA. Compliance, Barriers, and Facilitators to Social Distancing Measures for Prevention of Coronavirus Disease 2019 in Northwest Ethiopia, 2020. Curr Ther Res. 2021;94:100632. pmid:33967298
  30. 30. Asnakew Z, Asrese K, Andualem M. Community Risk Perception and Compliance with Preventive Measures for COVID-19 Pandemic in Ethiopia. Risk Manag Healthc Policy. 2020;13:2887–97. pmid:33335434
  31. 31. Taye BT, Amogne FK, Demisse TL, Zerihun MS, Kitaw TM, Tiguh AE, et al. Coronavirus disease 2019 vaccine acceptance and perceived barriers among university students in northeast Ethiopia: A cross-sectional study. Clin Epidemiol Glob Heal [Internet]. 2021;12:100848. Available from: https://www.sciencedirect.com/science/article/pii/S2213398421001561. pmid:34395948
  32. 32. Basic MT-IRJ of A and, 2013 undefined. Study of publication bias in meta-analysis using trim and fill method. irjabs.com [Internet]. 2013 [cited 2021 Jul 14];4(1):31–6. Available from: https://irjabs.com/files_site/paperlist/r_607_130116132831.pdf.
  33. 33. Kelley G, Kelley K. Statistical models for meta-analysis: A brief tutorial. World J Methodol [Internet]. 2012 [cited 2021 Jul 14];2(4):27. Available from: https://pubmed.ncbi.nlm.nih.gov/25237614/
  34. 34. Jackson D, Bowden J, and RB-J of SP, 2010 undefined. How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts? Elsevier [Internet]. [cited 2021 Jul 14]; Available from: https://www.sciencedirect.com/science/article/pii/S0378375809003073.
  35. 35. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Br Med J. 2003 Sep 6;327(7414):557–60. pmid:12958120
  36. 36. Lake EA, Demissie BW, Gebeyehu NA, Wassie AY, Gelaw KA, Azeze GA. Knowledge, attitude and practice towards COVID-19 among health professionals in Ethiopia: A systematic review and meta-analysis. PLoS One [Internet]. 2021;16(2 February 2021):1–16. Available from: pmid:33606744
  37. 37. Akalu Y, Ayelign B, Molla MD. Knowledge, attitude and practice towards covid-19 among chronic disease patients at addis zemen hospital, Northwest Ethiopia. Infect Drug Resist. 2020;13:1949–60. pmid:32612371
  38. 38. Nwagbara UI, Osual EC, Chireshe R, Bolarinwa OA, Saeed BQ, Khuzwayo N, et al. Knowledge, attitude, perception, and preventative practices towards COVID-19 in sub-Saharan Africa: A scoping review. PLoS One [Internet]. 2021;16(4 April):1–20. Available from: pmid:33872330
  39. 39. Shanka MS, Gebremariam Kotecho M, Kotecho MG. Combining rationality with morality—integrating theory of planned behavior with norm activation theory to explain compliance with COVID-19 prevention guidelines. Psychol Heal & Med. 2021 Jun;105(2):1–11. pmid:34193002
  40. 40. Indrayathi PA, Januraga PP, Pradnyani PE, Gesesew HA, Ward PR. Perceived Social Norms as Determinants of Adherence to Public Health Measures Related to COVID-19 in Bali, Indonesia. Front PUBLIC Heal. 2021 Apr;9:1–8. pmid:33996723
  41. 41. Villela EF de M, López RVM, Sato APS, de Oliveira FM, Waldman EA, Van den Bergh R, et al. COVID-19 outbreak in Brazil: adherence to national preventive measures and impact on people’s lives, an online survey. BMC Public Health [Internet]. 2021 Dec 1 [cited 2021 Jul 13];21(1). Available from: https://pubmed.ncbi.nlm.nih.gov/33461508/.
  42. 42. Ahmed MAM, Nelson J, Fodjo S, Gele AA, Farah AA, Osman S, et al. COVID-19 in Somalia: Adherence to Preventive Measures and Evolution of the Disease Burden. [cited 2021 Jul 12]; www.mdpi.com/journal/pathogens.
  43. 43. Chui A, Tang Y, Enid , Kwong W-Y, Chen Liangying, Lai W, et al. Associations between demographic characteristics, perceived threat, perceived stress, coping responses and adherence to COVID-19 prevention measures among Chinese healthcare students. J Adv Nurs. 2021;00:1–13.
  44. 44. Amodan BO, Bulage L, Katana E, Ario AR, Siewe Fodjo JN, Colebunders R, et al. Level and Determinants of Adherence to COVID-19 Preventive Measures in the First Stage of the Outbreak in Uganda. [cited 2021 Jul 12]; https://www.icpcovid.com.
  45. 45. Yang XY, Gong RN, Sassine S, Morsa M, Tchogna AS, Drouin O, et al. Risk Perception of COVID-19 Infection and Adherence to Preventive Measures among Adolescents and Young Adults. [cited 2021 Jul 12]; www.mdpi.com/journal/children.
  46. 46. Nivette A, Ribeaud D, Murray A, Steinhoff A, Bechtiger L, Hepp U, et al. Non-compliance with COVID-19-related public health measures among young adults in Switzerland: Insights from a longitudinal cohort study. Soc Sci Med [Internet]. 2021 Jan 1 [cited 2021 Jul 13];268. Available from: https://pubmed.ncbi.nlm.nih.gov/32980677/
  47. 47. Nzaji MK, Mwamba GN, Miema JM, Kilolo E, Umba N, Kangulu IB, et al. Predictors of Non-Adherence to Public Health Instructions During the COVID-19 Pandemic in the Democratic Republic of the Congo. 2020 [cited 2021 Jul 12]; Available from: pmid:33116566
  48. 48. Sturman D, Auton J, Thacker J. Knowledge of social distancing measures and adherence to restrictions during the COVID-19 pandemic. Health Promot J Austr [Internet]. 2021 Apr 1 [cited 2021 Jul 13];32(2):344–51. Available from: https://pubmed.ncbi.nlm.nih.gov/33249695/
  49. 49. Kamran A, Isazadehfar K, Heydari H, Azgomi RND, Naeim M. Risk perception and adherence to preventive behaviours related to the COVID-19 pandemic: a community-based study applying the health belief model. BJPsych Open [Internet]. 2021 Jul 13 [cited 2021 Jul 13];7(4):e133. Available from: https://www.cambridge.org/core/journals/bjpsych-open/article/risk-perception-and-adherence-to-preventive-behaviours-related-to-the-covid19-pandemic-a-communitybased-study-applying-the-health-belief-model/A81D4843A6B6BD18C24337756625D306. pmid:34253277
  50. 50. Brooks SK, Greenberg N, Wessely S, Rubin GJ. Factors affecting healthcare workers’ compliance with social and behavioural infection control measures during emerging infectious disease outbreaks: Rapid evidence review. BMJ Open. 2021;11(8):1–8. pmid:34400459
  51. 51. Tadesse T, Alemu T, Amogne G, Endazenaw G, Mamo E. Predictors of Coronavirus Disease 2019 (COVID-19) Prevention Practices Using Health Belief Model Among Employees in Addis Ababa, Ethiopia, 2020. Infect Drug Resist [Internet]. 2020 [cited 2021 Jul 13];13:3751–61. Available from: https://pubmed.ncbi.nlm.nih.gov/33122922/. pmid:33122922
  52. 52. Rayani M, Rayani S, Najafi-Sharjabad F. COVID-19-related knowledge, risk perception, information seeking, and adherence to preventive behaviors among undergraduate students, southern Iran. Environ Sci Pollut Res Int [Internet]. 2021 Jun 20 [cited 2021 Jul 13]; Available from: https://pubmed.ncbi.nlm.nih.gov/34148194/.
  53. 53. Adriaan J, Van Loenhout F, Vanderplanken K, Scheen B, Van Den Broucke S, Aujoulat I. Determinants of adherence to COVID-19 measures among the Belgian population: an application of the protection motivation theory. [cited 2021 Jul 12]; Available from: pmid:33980316
  54. 54. Shitu K, Adugna A, Kassie A, Handebo S. Application of Health Belief Model for the assessment of COVID-19 preventive behavior and its determinants among students: A structural equation modeling analysis. PLoS One [Internet]. 2022 Mar 1 [cited 2022 Jul 28];17(3):e0263568. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263568. pmid:35312697
  55. 55. Kim S, Kim S. Analysis of the Impact of Health Beliefs and Resource Factors on Preventive Behaviors against the COVID-19 Pandemic. [cited 2022 Jul 28]; www.mdpi.com/journal/ijerph
  56. 56. Park S, Oh S. Factors associated with preventive behaviors for COVID-19 among adolescents in South Korea. 2021 [cited 2022 Jul 28]; Available from: pmid:34301442
  57. 57. Ismael OY, Li Y, Sha Z, Wu Q, Wei L, Jiao M, et al. Assessing knowledge and self-report intention from COVID-19 symptoms based on the Health Belief Model among international students in Heilongjiang, China: a cross-sectional study. BMJ Open [Internet]. 2022 [cited 2022 Jul 28];12:50867. Available from: pmid:35017238