Knowledge, Attitude, and Prevention Practices Toward Coronavirus Disease 2019 in Ethiopia: A Systematic Review and Meta-Analysis

Background

Coronavirus disease is a major global public health problem. The contagious disease caused by a newly discovered coronavirus, coronavirus disease 2019 (COVID-19), was declared a pandemic following the outbreak of cases of respiratory illness during 2019. Although studies assessed COVID-19 knowledge, attitude, and practice in Ethiopia the findings were highly variable and inconsistent.

Objectives

This study assessed the pooled status of knowledge, attitude, and prevention practices regarding COVID-19 in Ethiopia.

Methods

International and national electronic databases, including PubMed/MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Google Scholar, Science Direct, and Google, were systematically searched. All observational studies on COVID-19 knowledge, attitude, and prevention practices in Ethiopia were included. We assessed heterogeneity among the included studies using the Cochrane Q test statistics and I² test. Lastly, a random-effects meta-analysis model was fitted to estimate the pooled proportion of knowledge, attitude, and prevention practices toward COVID-19 in Ethiopia.

Results

Our search identified 206 studies, 13 of which were included in the final analysis. Adequate knowledge, good attitude, and good prevention practice toward COVID-19 in Ethiopia were observed in 70.25% (95% CI, 61.82%–78.02%), 69.08% (95% CI, 55.42%–81.24%), and 41.62% (95% CI, 27.77%–56.17%) of total participants across studies, respectively.

Conclusions

The results of this study revealed low proportions of adequate knowledge, attitudes, and preventive practices toward COVID-19 in Ethiopia. The lowest pooled proportion was observed in the Amhara region. These findings indicate the need to revise plans and policies to improve the knowledge, attitudes, and prevention practices of people toward COVID-19 in Ethiopia, especially in the Amhara region. (Curr Ther Res Clin Exp. 2021; 82:XXX–XXX) © 2021 Elsevier HS Journals, Inc.

Bayesian model with application to a study of dental caries

BACKGROUND

Dental caries are a significant public health problem. It is a disease with multifactorial causes. In Sub-Sahara Africa, Ethiopia is one of the countries with a high record of dental caries. This study was to determine the risk factors affecting dental caries using both Bayesian and classical approaches.

METHODS

The study design was a retrospective cohort study in the period of March 2009 to March 2013 dental caries patients Hawassa Haik Poly Higher Clinic. The Bayesian logistic regression procedure was adapted to make inference about the parameters of a logistic regression model. The purpose of this method was generating the posterior distribution of the unknown parameters given both the data and some prior density for the unknown parameters.

RESULTS

From this study the prevalence of natural dental caries was 87% and non-natural dental caries were 13%. The age group of 18-25 was higher prevalence of dental caries than the other age groups. From Bayesian logistic regression, we found out that rural patients, do not clean their teeth, patients from SNNPR and age group 18-25 are statistically significant. The finding from the Bayesian statistics approach is getting popular in data analysis than classical statistics because the technique is more robust and precise.

CONCLUSIONS

Bayesian approach was found to be better than classical method as the value of the standard errors in Bayesian approaches is smaller than that of classical logistic regression. The Bayesian credible interval is smaller than the length of the confidence interval for all significant risk factors. Age, sex, place of residence, region and habit of cleaning teeth was found to have a significant effect on dental caries patients.