Visual impairment has a profound impact on loss of economy and productivity, which can impair health-related quality of life. Objective: The purpose of this study was to determine productivity loss and its predictive factors among adults with visual impairment in Addis Ababa tertiary eye care centers, Ethiopia. Methods: An institution-based cross-sectional study was conducted between February and July 30, 2021. A total of 425 samples were retrieved using systematic random sampling. Data collection included socio-demographic information, employment status, job absenteeism, presenteeism and reduced work participation. Analysis was done by SPSS version 23, and binary logistic regression was employed for statistical analysis. P-values less than 0.05 were used to state significant associations between dependent and outcome variables. Results: A total of 416 study participants were involved in the study, with a response rate of 97.88%. The mean age was 48±14.3 years. The total productivity loss was $775,325.51, with a median of $358.02. Maximum productivity loss was contributed by reduced workforce participation, which was about $746,337.45, with a median of $1,432.10. Regarding predictor factors, gender, monthly income, degree and duration of visual impairment and support of family to get job were statistically associated with high productivity loss. Conclusion:In general, the current study revealed that there is a profound annual loss of productivity due to visual impairment. The predictor factors for higher productivity loss were gender, monthly income, degree of visual impairment, duration of visual impairment and presence of support from family to get job or achieve better performance on job activities. Rehabilitation for visually impaired adults is recommended to enhance their quality of life by increasing their workplace participation to the maximum potential.

Introduction: Worldwide, including in Ethiopia, there is an increased risk of coronavirus disease 2019 (COVID-19) disease severity and mortality. This study aimed to assess the survival status and predictors of mortality among COVID-19 patients admitted to the intensive care unit. Methods: This study included 508 COVID-19 patients retrospectively who were under follow-up. The work has been reported in line with the STROCSS (strengthening the reporting of cohort, cross-sectional and case–control studies in surgery) criteria. The data were collected through a systematic sampling from patients’ charts. Kaplan–Meier survival curves and logrank test, and Cox’s regression analyses were conducted to check the difference among categories of covariates and to identify predictors of mortality, respectively. Results: All patient charts were reviewed and the information was recorded. The average age (mean+SD) of these patients was 62.1+13.6 years. Among study participants, 422 deaths occurred and the mortality rate was 64.1 per 1000 person-days. The median survival time was 13 days [interquartile range (IQR): 10–18]. The significant predictors for this survival were: Age>45 years [adjusted hazard ratio (AHR)=4.34, 95% CI: 2.46–7.86], Diabetes mellitus (AHR=1.37, 95% CI: 1.05–1.77), Hypertension (AHR=1.39, 95% CI: 1.09–1.79), Renal disease (AHR=1.86, 95% CI: 1.01–3.43), Hypotension (AHR=1.71, 95% CI: 1.28–2.27), Electrolyte treatment (AHR=0.78, 95% CI: 0.63–0.97). Conclusion: The median survival of COVID-19 patients after their admission was 13 days, and predictors for this time were advanced age, preexisting comorbidities (like diabetes mellitus, hypertension, and renal disease), hypotension, and electrolyte therapy.