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Community’s perceived high risk of coronavirus infections during early phase of epidemics are significantly influenced by socio-demographic background, in Gondar City, Northwest Ethiopia: A cross-sectional -study

Author

Listed:
  • Gebisa Guyasa Kabito
  • Mekuriaw Alemayehu
  • Tesfaye Hambisa Mekonnen
  • Sintayehu Daba Wami
  • Jember Azanaw
  • Tsegaye Adane
  • Zelalem Nigussie Azene
  • Mehari Woldemariam Merid
  • Atalay Goshu Muluneh
  • Demiss Mulatu Geberu
  • Getahun Molla Kassa
  • Melaku Kindie Yenit
  • Sewbesew Yitayih Tilahun
  • Kassahun Alemu Gelaye
  • Habtamu Sewunet Mekonnen
  • Abere Woretaw Azagew
  • Chalachew Adugna Wubneh
  • Getaneh Mulualem Belay
  • Nega Tezera Assimamaw
  • Chilot Desta Agegnehu
  • Telake Azale
  • Animut Tagele Tamiru
  • Bayew Kelkay Rade
  • Eden Bishaw Taye
  • Asefa Adimasu Taddese
  • Zewudu Andualem
  • Henok Dagne
  • Kiros Terefe Gashaye

Abstract

Background: Epidemiological studies during the early phase of the coronavirus (COVID-19) pandemics reported different level of people’s risk perception in different countries. There is a paucity of data on perceived high risk of COVID-19 and associated factors in Ethiopia. We sought to assess the prevalence of community’s perceived high risk about COVID-19 infections and associated factors among Gondar town community. Methods: A cross-sectional study was carried out from April 20 to 27, 2020 in Gondar town community, Northwest Ethiopia. Multistage cluster sampling technique was used to recruit 635 participants. Structured and pre-tested questionnaire was used to collect the data. Descriptive statistics, bivariate and multivariable binary logistic regression were used to summarize the results. Results: A total of 623 participants were considered in the analysis with a response rate of 98.1%. The prevalence of coronavirus high risk perceptions of the respondents was found to be 23.11% (95% CI; 19.80%–26.43%). Age above 45 years (AOR = 1.41, 95%CI; 1.19–2.66), college and above educational level (AOR = 0.28, 95%CI; 0.21–0.98), and poor knowledge towards COVID-19 virus (AOR = 1.57, 95%CI; 1.09–2.23) were significantly associated with perceived high risk about COVID-19. Conclusions: The prevalence of perceived high risk of COVID-19 was found to be low. Factors such as age, educational status, and knowledge about COVID-19 virus were found to be independent predictors of perceived high risk towards COVID-19. Government and non-government organizations should use formal and informal means of educating the community.

Suggested Citation

  • Gebisa Guyasa Kabito & Mekuriaw Alemayehu & Tesfaye Hambisa Mekonnen & Sintayehu Daba Wami & Jember Azanaw & Tsegaye Adane & Zelalem Nigussie Azene & Mehari Woldemariam Merid & Atalay Goshu Muluneh & , 2020. "Community’s perceived high risk of coronavirus infections during early phase of epidemics are significantly influenced by socio-demographic background, in Gondar City, Northwest Ethiopia: A cross-sect," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-12, November.
    • Handle: RePEc:plo:pone00:0242654
    DOI: 10.1371/journal.pone.0242654
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    References listed on IDEAS

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    1. Smith, Richard D., 2006. "Responding to global infectious disease outbreaks: Lessons from SARS on the role of risk perception, communication and management," Social Science & Medicine, Elsevier, vol. 63(12), pages 3113-3123, December.
    2. Behnam Honarvar & Kamran B. Lankarani & Ali Kharmandar & Fatemeh Shaygani & Mohammadhassan Zahedroozgar & Mohammad Reza Rahmanian Haghighi & Sulmaz Ghahramani & Hossein Honarvar & Mohammad Mehdi Darya, 2020. "Knowledge, attitudes, risk perceptions, and practices of adults toward COVID-19: a population and field-based study from Iran," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 65(6), pages 731-739, July.
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    Cited by:

    1. Sabrina Cipolletta & Gabriela Rios Andreghetti & Giovanna Mioni, 2022. "Risk Perception towards COVID-19: A Systematic Review and Qualitative Synthesis," IJERPH, MDPI, vol. 19(8), pages 1-25, April.
    2. Li, Tingting & Guo, Youming, 2022. "Optimal control and cost-effectiveness analysis of a new COVID-19 model for Omicron strain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    3. Hassan Hosseinzadeh & Zubair Ahmed Ratan & Kamrun Nahar & Ann Dadich & Abdullah Al-Mamun & Searat Ali & Marzieh Niknami & Iksheta Verma & Joseph Edwards & Mahmmoud Shnaigat & Md Abdul Malak & Md Musta, 2023. "Telemedicine Use and the Perceived Risk of COVID-19: Patient Experience," IJERPH, MDPI, vol. 20(4), pages 1-19, February.

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