Willingness to pay for Social Health Insurance and associated factors among Public Civil Servants in Ethiopia: A systematic review and meta-analysis.

BACKGROUND: The provision of equitable and accessible healthcare is one of the goals of universal health coverage. However, due to high out-of-pocket payments, people in the world lack sufficient health services, especially in developing countries. Thus, many low and middle-income countries introduced different prepayment mechanisms to reduce large out-of-pocket payments and overcome financial barriers to accessing health care. Though many studies were conducted on willingness to pay for social health insurance in Ethiopia, there is no aggregated data at the national level. Therefore, this systematic review and meta-analysis aimed to estimate the pooled magnitude of willingness to pay for social health insurance and its associated factors among public servants in Ethiopia. METHOD: Studies conducted before June 1, 2022, were retrieved from electronic databases (PubMed/Medline, Science Direct, African Journals Online, Google Scholar, and Web of Science) as well as from Universities' digital repositories. Data were extracted using a data extraction format prepared in Microsoft Excel and the analysis was performed using STATA 16 statistical software. The quality of the included studies was assessed using the Newcastle-Ottawa Scale for cross-sectional studies. To evaluate publication bias, a funnel plot, and Egger's regression test were utilized. The study's heterogeneity was determined using Cochrane Q test statistics and the I2 test. To determine the pooled effect size, odds ratio, and 95% confidence intervals across studies, the DerSimonian and Laird random-effects model was used. Subgroup analysis was conducted by region, sample size, and publication year. The influence of a single study on the whole estimate was determined via sensitivity analysis. RESULT: To estimate the pooled magnitude of willingness to pay for the Social Health insurance scheme in Ethiopia, twenty articles with a total of 8744 participants were included in the review. The pooled magnitude of willingness to pay for Social Health Insurance in Ethiopia was 49.62% (95% CI: 36.41-62.82). Monthly salary (OR = 6.52; 95% CI:3.67,11.58), having the degree and above educational status (OR = 5.52; 95%CI:4.42,7.17), large family size(OR = 3.69; 95% CI:1.10,12.36), having the difficulty of paying the bill(OR = 3.24; 95%CI: 1.51, 6.96), good quality of services(OR = 4.20; 95%CI:1.97, 8.95), having favourable attitude (OR = 5.28; 95%CI:1.45, 19.18) and awareness of social health insurance scheme (OR = 3.09;95% CI:2.12,4.48) were statistically associated with willingness to pay for Social health insurance scheme. CONCLUSIONS: In this review, the magnitude of willingness to pay for Social Health insurance was low among public Civil servants in Ethiopia. Willingness to pay for Social Health Insurance was significantly associated with monthly salary, educational status, family size, the difficulty of paying medical bills, quality of healthcare services, awareness, and attitude towards the Social Health Insurance program. Hence, it's recommended to conduct awareness creation through on-the-job training about Social Health Insurance benefit packages and principles to improve the willingness to pay among public servants.

Burden of lower respiratory infections and associated risk factors across regions in Ethiopia: a subnational analysis of the Global Burden of Diseases 2019 study.

OBJECTIVE: This analysis is to present the burden and trends of morbidity and mortality due to lower respiratory infections (LRIs), their contributing risk factors, and the disparity across administrative regions and cities from 1990 to 2019. DESIGN: This analysis used Global Burden of Disease 2019 framework to estimate morbidity and mortality outcomes of LRI and its contributing risk factors. The Global Burden of Disease study uses all available data sources and Cause of Death Ensemble model to estimate deaths from LRI and a meta-regression disease modelling technique to estimate LRI non-fatal outcomes with 95% uncertainty intervals (UI). STUDY SETTING: The study includes nine region states and two chartered cities of Ethiopia. OUTCOME MEASURES: We calculated incidence, death and years of life lost (YLLs) due to LRIs and contributing risk factors using all accessible data sources. We calculated 95% UIs for the point estimates. RESULTS: In 2019, LRIs incidence, death and YLLs among all age groups were 8313.7 (95% UI 7757.6-8918), 59.4 (95% UI 49.8-71.4) and 2404.5 (95% UI 2059.4-2833.3) per 100 000 people, respectively. From 1990, the corresponding decline rates were 39%, 61% and 76%, respectively. Children under the age of 5 years account for 20% of episodes, 42% of mortalities and 70% of the YLL of the total burden of LRIs in 2019. The mortality rate was significantly higher in predominantly pastoralist regions-Benishangul-Gumuz 101.8 (95% UI 84.0-121.7) and Afar 103.7 (95% UI 86.6-122.6). The Somali region showed the least decline in mortality rates. More than three-fourths of under-5 child deaths due to LRIs were attributed to malnutrition. Household air pollution from solid fuel attributed to nearly half of the risk factors for all age mortalities due to LRIs in the country. CONCLUSION: In Ethiopia, LRIs have reduced significantly across the regions over the years (except in elders), however, are still the third-leading cause of mortality, disproportionately affecting children younger than 5 years old and predominantly pastoralist regions. Interventions need to consider leading risk factors, targeted age groups and pastoralist and cross-border communities.

Assessment of hospitalisation costs and their determinants among Covid-19 patients in South Central Ethiopia.

BACKGROUND: The coronavirus disease 2019 (Covid-19) pandemic is a global public health problem. The Covid-19 pandemic has had a substantial impact on the economy of developing countries, including Ethiopia.This study aimed to determine the hospitalisation costs of Covid-19 and the factors associated with the high cost of hospitalisation in South Central Ethiopia. METHODS: A retrospective cost analysis of Covid-19 patients hospitalised between July 2020 and July 2021 at Bokoji Hospital Covid-19 Treatment Centre was conducted using both the micro-costing and top-down approaches from the health system perspective. This analysis used cost data obtained from administrative reports, the financial reports of the treatment centre, procurement invoices and the Covid-19 standard treatment guidelines. The Student's t-test, Mann-Whitney U test or Kruskal-Wallis test was employed to test the difference between sociodemographic and clinical factors when appropriate.To identify the determinants of cost drivers in the study population, a generalised linear model with gamma distribution and log link with a stepwise algorithm were used. RESULTS: A total of 692 Covid-19 patients were included in the costing analysis. In this study, the mean cost of Covid-19-infected patients with no symptoms was US$1,073.86, with mild symptoms US$1,100.74, with moderate symptoms US$1,394.74 and in severe-critically ill condition US$1,708.05.The overall mean cost was US$1,382.50(95% CI: 1,360.60-1,404.40) per treated episode.The highest mean cost was observed for personnel, accounting for 64.0% of the overall cost. Older age, pre-existing diseases, advanced disease severity at admission, admission to the intensive care unit, prolonged stay on treatment and intranasal oxygen support were strongly associated with higher costs. CONCLUSIONS: This study found that the clinical management of Covid-19 patients incurred significant expenses to the health system. Factors such as older age, disease severity, presence of comorbidities, use of inhalation oxygen therapy and prolonged hospital stay were associated with higher hospitalisation costs.Therefore, the government should give priority to the elderly and those with comorbidities in the provision of vaccination to reduce the financial burden on health facilities and health systems in terms of resource utilisation.

The role of universal health coverage and global health security nexus and interplay on SARS-CoV-2 infection and case-fatality rates in Africa : a structural equation modeling approach.

BACKGROUND: The Coronavirus Disease (COVID-19) caused by SARS-CoV-2 infections remains a significant health challenge worldwide. There is paucity of evidence on the influence of the universal health coverage (UHC) and global health security (GHS) nexus on SARS-CoV-2 infection risk and outcomes. This study aimed to investigate the effects of UHC and GHS nexus and interplay on SARS-CoV-2 infection rate and case-fatality rates (CFR) in Africa. METHODS: The study employed descriptive methods to analyze the data drawn from multiple sources as well used structural equation modeling (SEM) with maximum likelihood estimation to model and assess the relationships between independent and dependent variables by performing path analysis. RESULTS: In Africa, 100% and 18% of the effects of GHS on SARS-CoV-2 infection and RT-PCR CFR, respectively were direct. Increased SARS-CoV-2 CFR was associated with median age of the national population (ß = -0.1244, [95% CI: -0.24, -0.01], P = 0.031 ); COVID-19 infection rate (ß = -0.370, [95% CI: -0.66, -0.08], P = 0.012 ); and prevalence of obesity among adults aged 18 + years (ß = 0.128, [95% CI: 0.06,0.20], P = 0.0001) were statistically significant. SARS-CoV-2 infection rates were strongly linked to median age of the national population (ß = 0.118, [95% CI: 0.02,0.22 ], P = 0.024); population density per square kilometer, (ß = -0.003, [95% CI: -0.0058, -0.00059], P = 0.016 ) and UHC for service coverage index (ß = 0.089, [95% CI: 0.04,0.14, P = 0.001 ) in which their relationship was statistically significant. CONCLUSIONS: The study shade a light that UHC for service coverage, and median age of the national population, population density have significant effect on COVID-19 infection rate while COVID-19 infection rate, median age of the national population and prevalence of obesity among adults aged 18 + years were associated with COVID-19 case-fatality rate. Both, UHC and GHS do not emerge to protect against COVID-19-related case fatality rate.

Institutionalizing health technology assessment in Ethiopia: seizing the window of opportunity.

Ethiopia's commitment to achieving universal health coverage (UHC) requires an efficient and equitable health priority-setting practice. The Ministry of Health aims to institutionalize health technology assessment (HTA) to support evidence-based decision making. This commentary highlights key considerations for successful formulation, adoption, and implementation of HTA policies and practices in Ethiopia, based on a review of international evidence and published normative principles and guidelines. Stakeholder engagement, transparent policymaking, sustainable financing, workforce education, and political economy analysis and power dynamics are critical factors that need to be considered when developing a national HTA roadmap and implementation strategy. To ensure ownership and sustainability of HTA, effective stakeholder engagement and transparency are crucial. Regulatory embedding and sustainable financing ensure legitimacy and continuity of HTA production, and workforce education and training are essential for conducting and interpreting HTA. Political economy analysis helps identify opportunities and constraints for effective HTA implementation. By addressing these considerations, Ethiopia can establish a well-designed HTA system to inform evidence-based and equitable resource allocation toward achieving UHC and improving health outcomes.

Cervical cancer screening utilization and associated factors among women attending antenatal care at Asella Referral and Teaching Hospital, Arsi zone, South Central Ethiopia.

BACKGROUND: Cervical cancer is a major public health problem affecting women worldwide. It is the second cause of mortality among women in Ethiopia. Early Cervical cancer screening has a tremendous impact on reducing morbidity and mortality related to cervical cancer infection. Therefore, this study aimed to assess cervical cancer screening utilization and associated factors among women attending Antenatal Care at Asella referral and teaching hospital, Arsi Zone, south-central Ethiopia. METHOD: This study employed a facility-based cross-sectional study among 457 Antenatal Care mothers from December 2020 to February 2021. Data collection was performed using interviewer-administered structured questionnaires. Data were entered into EpiInfo Version 7 and transferred to SPSS V.21 for analysis. A logistic regression model was used to determine the factors associated with cervical cancer screening utilization and an adjusted odds ratio with a 95% confidence interval at p-value < 0.05 was computed to determine the level of statistical significance. RESULT: The magnitude of cervical cancer screening utilization was found to be 7.2%(95% CI: 5.2, 10.6). Educational status of secondary and above (AOR = 2.92; 95%CI = 1.078-7.94), getting screened for any reproductive healthcare services(AOR = 4.95; 95%CI = 2.24-10.94), having multiple sexual partners(AOR = 4.55; 95%CI = 1.83-11.35), and satisfactory knowledge of cervical cancer screening(AOR = 3.89; 95%CI = 1.74-8.56) were significantly associated factors with cervical cancer screening utilization. CONCLUSION: Utilization of cervical cancer screening was low among women attending Antenatal care at Asella Referral and Teaching hospital, Southcentral Ethiopia. Educational status, history of multiple sexual partners, getting screened for any reproductive healthcare services, and knowledge of cervical cancer screening were significant factors associated with the utilization of cervical cancer screening. Hence, to improve the utilization of Cervical cancer screening, there should be the implementation of programmed health education and awareness creation on the benefits of screening as well as the promotion of reproductive healthcare services at health facilities.

Country readiness and prerequisites for successful design and transition to implementation of essential packages of health services: experience from six countries.

This paper reviews the experience of six low-income and lower middle-income countries in setting their own essential packages of health services (EPHS), with the purpose of identifying the key requirements for the successful design and transition to implementation of the packages in the context of accelerating progress towards universal health coverage (UHC). The analysis is based on input from three meetings of a knowledge network established by the Disease Control Priorities 3 Country Translation Project and working groups, supplemented by a survey of participating countries.All countries endorsed the Sustainable Development Goals target 3.8 on UHC for achievement by 2030. The assessment of country experiences found that health system strengthening and mobilising and sustaining health financing are major challenges. EPHS implementation is more likely when health system gaps are addressed and when there are realistic and sustainable financing prospects. However, health system assessments were inadequate and the government planning and finance sectors were not consistently engaged in setting the EPHS in most of the countries studied. There was also a need for greater engagement with community and civil society representatives, academia and the private sector in package design. Leadership and reinforcement of technical and managerial capacity are critical in the transition from EPHS design to sustained implementation, as are strong human resources and country ownership of the process. Political commitment beyond the health sector is key, particularly commitment from parliamentarians and policymakers in the planning and finance sectors. National ownership, institutionalisation of technical and managerial capacity and reinforcing human resources are critical for success.The review concludes that four prerequisites are crucial for a successful EPHS: (1) sustained high-level commitment, (2) sustainable financing, (3) health system readiness, and (4) institutionalisation.

Decision-making processes for essential packages of health services: experience from six countries.

Many countries around the world strive for universal health coverage, and an essential packages of health services (EPHS) is a central policy instrument for countries to achieve this. It defines the coverage of services that are made available, as well as the proportion of the costs that are covered from different financial schemes and who can receive these services. This paper reports on the development of an analytical framework on the decision-making process of EPHS revision, and the review of practices of six countries (Afghanistan, Ethiopia, Pakistan, Somalia, Sudan and Zanzibar-Tanzania).The analytical framework distinguishes the practical organisation, fairness and institutionalisation of decision-making processes. The review shows that countries: (1) largely follow a similar practical stepwise process but differ in their implementation of some steps, such as the choice of decision criteria; (2) promote fairness in their EPHS process by involving a range of stakeholders, which in the case of Zanzibar included patients and community members; (3) are transparent in terms of at least some of the steps of their decision-making process and (4) in terms of institutionalisation, express a high degree of political will for ongoing EPHS revision with almost all countries having a designated governing institute for EPHS revision.We advise countries to organise meaningful stakeholder involvement and foster the transparency of the decision-making process, as these are key to fairness in decision-making. We also recommend countries to take steps towards the institutionalisation of their EPHS revision process.

Impact of good governance, economic growth and universal health coverage on COVID-19 infection and case fatality rates in Africa.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has disrupted lives across all countries and communities. It significantly reduced the global economic output and dealt health systems across the world a serious blow. There is growing evidence showing the progression of the COVID-19 pandemic and the impact it has on health systems, which should help to draw lessons for further consolidating and realizing universal health coverage (UHC) in all countries, complemented by more substantial government commitment and good governance, and continued full implementation of crucial policies and plans to avert COVID-19 and similar pandemic threats in the future. Therefore, the objective of the study was to assess the impact of good governance, economic growth and UHC on the COVID-19 infection rate and case fatality rate (CFR) among African countries. METHODS: We employed an analytical ecological study design to assess the association between COVID-19 CFR and infection rate as dependent variables, and governance, economic development and UHC as independent variables. We extracted data from publicly available databases (i.e., Worldometer, Worldwide Governance Indicators, Our World in Data and WHO Global Health Observatory Repository). We employed a multivariable linear regression model to examine the association between the dependent variables and the set of explanatory variables. STATA version 14 software was used for data analysis. RESULTS: All 54 African countries were covered by this study. The median observed COVID-19 CFR and infection rate were 1.65% and 233.46%, respectively. Results of multiple regression analysis for predicting COVID-19 infection rate indicated that COVID-19 government response stringency index (ß = 0.038; 95% CI 0.001, 0.076; P = 0.046), per capita gross domestic product (GDP) (ß = 0.514; 95% CI 0.158, 0.87; P = 0.006) and infectious disease components of UHC (ß = 0.025; 95% CI 0.005, 0.045; P = 0.016) were associated with COVID-19 infection rates, while noncommunicable disease components of UHC (ß = -0.064; 95% CI -0.114; -0.015; P = 0.012), prevalence of obesity among adults (ß = 0.112; 95% CI 0.044; 0.18; P = 0.002) and per capita GDP (ß = -0.918; 95% CI -1.583; -0.254; P = 0.008) were associated with COVID-19 CFR. CONCLUSIONS: The findings indicate that good governance practices, favourable economic indicators and UHC have a bearing on COVID-19 infection rate and CFR. Effective health system response through a primary healthcare approach and progressively taking measures to grow their economy and increase funding to the health sector to mitigate the risk of similar future pandemics would require African countries to move towards UHC, improve governance practices and ensure economic growth in order to reduce the impact of pandemics on populations.

Health-Related Quality of Life and Associated Factors Among Covid-19 Survivors. Experience from Ethiopian Treatment Centers.

Background: The pandemic of the novel coronavirus (Covid-19), which is extremely stressful and has an adverse effect on people's health-related quality of life (HRQoL), poses a serious threat to global public health. As a result, this study evaluated the health-related quality of life and associated factors among Covid-19 patients who were discharged from Ethiopian treatment centers. Methods: We conducted a multi-center, cross-sectional study among 493 Covid-19 survivors who had been discharged from treatment centers between 1st January 2020, and 20th October 2021. We collected respondents' data using validated Amharic version EuroQol 5-dimensional-5 levels (EQ-5D-5L) questionnaire along with medical records of the patients. Differences in HRQOL scores between patient subgroups were tested by Mann-Whitney U or Kruskal-Wallis test, and the multivariable betaMix regression was used to investigate factors associated with HRQOL scores. Results: The EQ-5D and VAS median score for Covid-19 survivors was 0.940 (IQR: 0.783-0.966) and 87 (IQR: 70-91) respectively. Overall, married individuals, old-aged, individuals who had low educational status, high monthly income, comorbidities, admitted to the Intensive care Unit, received intranasal oxygen care, and prolonged hospitalization had lower utility scores and EQ-VAS scores compared to their counterparts. In multivariate betaMix regression, respondents' health status at admission, old age, chronic obstructive pulmonary disease, asthma, and hospital length of stay were significantly associated with the lower EQ-5D-Index value and EQ-VAS score. Conclusion: We found that Covid-19 infection had a persisting impact on the physical and psychosocial health of Covid-19 survivors. Age, having asthma and chronic obstructive pulmonary disease, having a worsening health state upon admission, and a prolonged hospital length of stay were significantly associated with the lower EQ-5D and EQ-VAS score. Therefore, the cost-effective psychological treatment such as cognitive behaviour therapy should be encouraged after hospitalization to improve the post-Covid-19 depression and fatigue.

Is Ethiopian community-based health insurance affordable? Willingness to pay analysis among households in South Central, Ethiopia.

BACKGROUND: Community-based Health Insurance (CBHI) is a voluntary prepayment mechanism that guarantees the provision of basic healthcare services without financial barriers to underserved segments of the population in developing countries. The Government of Ethiopia launched the CBHI program to protect the community from high out-of-pocket health expenditure and improve health service utilization a decade ago. However, to improve the quality of healthcare services delivery in health facilities and cover the changing costs of healthcare, the government should revise the contribution of the CBHI scheme. Therefore, we determined the willingness to pay for a CBHI scheme and associated factors among rural households of Lemu and Bilbilo district, South Central Ethiopia. METHODS: We conducted a community-based cross-sectional study design to assess willingness to pay for the CBHI scheme and its associated factors among households in Lemu and Bilbilo districts, South Central Ethiopia. We used a double bounded contingent valuation method to elicit households' willingness to pay for the CBHI scheme. Data were coded, cleaned, entered into Statistical Package for Social Science (SPSS) version 25, and exported to STATA 16 for analysis. A logistic regression analysis was conducted to determine the presence of statistically significant associations between the willingness to pay for the CBHI scheme and independent variables at a p-value <0.05 and Adjusted odds ratio (AOR) values with 95% CI. Finally, we checked the fitness of the model using Hosmer and Lemeshow's goodness-of-fit test. RESULTS: Of the 476 study participants, 82.9% (95% CI: 79.2%, 86.01%) were willing to pay for the CBHI scheme and only 62% of them can afford the average amount of 358.32ETB ($7.68) per household per annum. Primary education (AOR = 3.17; 95% CI: 1.74-5.80), secondary and above education (AOR = 4.13; 95% CI: 1.86-9.18), large family size (AOR = 2.75; 95% CI: 1.26-5.97), monthly income of 500-1000ETB (AOR = 3.75; 95% CI: 1.97-7.13) and distance to public health facilities (AOR = 2.14, 95% CI: 1.04-4.39 were significantly associated with willingness to pay for the CBHI scheme. CONCLUSION: In this study, around 83% of respondents were willing to pay for the CBHI and meet the government expectation for 2020. The study also revealed that educational status, family size, monthly income, and distance from the health facilities were significant factors associated with WTP for the CBHI scheme. In addition, we found that a large number of the respondents couldn't afford the average amount of money that the participants were willing to pay for the CBHI scheme. So, the government should consider the economic status of the communities while revising the CBHI scheme premium not to miss those who cannot afford the contribution.

Changes in life expectancy and disease burden in Norway, 1990-2019: an analysis of the Global Burden of Disease Study 2019.

BACKGROUND: Geographical differences in health outcomes are reported in many countries. Norway has led an active policy aiming for regional balance since the 1970s. Using data from the Global Burden of Disease Study (GBD) 2019, we examined regional differences in development and current state of health across Norwegian counties. METHODS: Data for life expectancy, healthy life expectancy (HALE), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) in Norway and its 11 counties from 1990 to 2019 were extracted from GBD 2019. County-specific contributors to changes in life expectancy were compared. Inequality in disease burden was examined by use of the Gini coefficient. FINDINGS: Life expectancy and HALE improved in all Norwegian counties from 1990 to 2019. Improvements in life expectancy and HALE were greatest in the two counties with the lowest values in 1990: Oslo, in which life expectancy and HALE increased from 71·9 years (95% uncertainty interval 71·4-72·4) and 63·0 years (60·5-65·4) in 1990 to 81·3 years (80·0-82·7) and 70·6 years (67·4-73·6) in 2019, respectively; and Troms og Finnmark, in which life expectancy and HALE increased from 71·9 years (71·5-72·4) and 63·5 years (60·9-65·6) in 1990 to 80·3 years (79·4-81·2) and 70·0 years (66·8-72·2) in 2019, respectively. Increased life expectancy was mainly due to reductions in cardiovascular disease, neoplasms, and respiratory infections. No significant differences between the national YLD or DALY rates and the corresponding age-standardised rates were reported in any of the counties in 2019; however, Troms og Finnmark had a higher age-standardised YLL rate than the national rate (8394 per 100 000 [95% UI 7801-8944] vs 7536 per 100 000 [7391-7691]). Low inequality between counties was shown for life expectancy, HALE, all level-1 causes of DALYs, and exposure to level-1 risk factors. INTERPRETATION: Over the past 30 years, Norway has reduced inequality in disease burden between counties. However, inequalities still exist at a within-county level and along other sociodemographic gradients. Because of insufficient Norwegian primary data, there remains substantial uncertainty associated with regional estimates for non-fatal disease burden and exposure to risk factors. FUNDING: Bill & Melinda Gates Foundation, Research Council of Norway, and Norwegian Institute of Public Health.

Cost-analysis of COVID-19 sample collection, diagnosis, and contact tracing in low resource setting: The case of Addis Ababa, Ethiopia.

BACKGROUND: Ethiopia has been responding to the COVID-19 pandemic through a combination of interventions, including non-pharmaceutical interventions, quarantine, testing, isolation, contact tracing, and clinical management. Estimating the resources consumed for COVID-19 prevention and control could inform efficient decision-making for epidemic/pandemic-prone diseases in the future. This study aims to estimate the unit cost of COVID-19 sample collection, laboratory diagnosis, and contact tracing in Addis Ababa, Ethiopia. METHODS: Primary and secondary data were collected to estimate the costs of COVID-19 sample collection, diagnosis, and contact tracing. A healthcare system perspective was used. We used a combination of micro-costing (bottom-up) and top-down approaches to estimate resources consumed and the unit costs of the interventions. We used available cost and outcome data between May and December 2020. The costs were classified into capital and recurrent inputs to estimate unit and total costs. We identified the cost drivers of the interventions. We reported the cost for the following outcome measures: (1) cost per sample collected, (2) cost per laboratory diagnosis, (3) cost per sample collected and laboratory diagnosis, (4) cost per contact traced, and (5) cost per COVID-19 positive test identified. We conducted one-way sensitivity analysis by varying the input parameters. All costs were reported in US dollars (USD). RESULTS: The unit cost per sample collected was USD 1.33. The unit cost of tracing a contact of an index case was USD 0.66. The unit cost of COVID-19 diagnosis, excluding the cost for sample collection was USD 3.91. The unit cost of sample collection per COVID-19 positive individual was USD 11.63. The unit cost for COVID-19 positive test through contact tracing was USD 54.00. The unit cost COVID-19 DNA PCR diagnosis for identifying COVID-19 positive individuals, excluding the sample collection and transport cost, was USD 37.70. The cost per COVID-19 positive case identified was USD 49.33 including both sample collection and laboratory diagnosis costs. Among the cost drivers, personnel cost (salary and food cost) takes the highest share for all interventions, ranging from 51-76% of the total cost. CONCLUSION: The costs of sample collection, diagnosis, and contact tracing for COVID-19 were high given the low per capita health expenditure in Ethiopia and other low-income settings. Since the personnel cost accounts for the highest cost, decision-makers should focus on minimizing this cost when faced with pandemic-prone diseases by strengthening the health system and using digital platforms. The findings of this study can help decision-makers prioritize and allocate resources for effective public health emergency response.

Survival analysis of COVID-19 patients in Ethiopia: A hospital-based study.

BACKGROUND: COVID-19 is a global public health problem causing high mortality worldwide. This study aimed to assess time to death and predictors of mortality among patients hospitalized for COVID-19 in the Arsi zone treatment center. METHOD: We performed a retrospective observational cohort study using medical records of laboratory-confirmed COVID-19 cases hospitalized at Bokoji Hospital COVID-19 treatment center from 1st July 2020 to 5th March 2021. We extracted data on the patients' sociodemographic and clinical characteristics from medical records of hospitalized patients retrospectively. We carried out Kaplan Meier and Cox regression analysis to estimate survival probability and investigate predictors of COVID-19 death 5% level of significance. The Adjusted Hazard Ratio (aHR) with 95% Confidence Interval (CI) was estimated and interpreted for predictors of time to death in the final cox model. RESULT: A total of 422 COVID-19 patients treated were analyzed, of these more than one tenth (11.14%) deaths, with a mortality rate of 6.35 cases per 1000 person-days. The majority (87.2%) of deaths occurred within the first 14 days of admission, with a median time-to-death of nine (IQR: 8-12) days. We found patients that age between 31 and 45 years (aHR = 2.55; 95% CI: (1.03, 6.34), older than 46 years (aHR = 2.59 (1.27, 5.30), chronic obstructive pulmonary disease (aHR = 4.60, 95%CI: (2.37, 8.91), Chronic kidney disease (aHR = 5.58, 95%CI: (1.70, 18.37), HIV/AIDS (aHR = 3.66, 95%CI: (1.20, 11.10), admission to the Intensive care unit(aHR = 7.44, 95%CI: (1.82, 30.42), and being on intranasal oxygen care (aHR = 6.27, 95%CI: (2.75, 4.30) were independent risk factors increasing risk of death from COVID-19 disease than their counterparts. CONCLUSION: The risk of dying due to COVID-19 disease was higher among patients with HIV/AIDS, chronic obstructive pulmonary disease, and chronic kidney diseases. We also found that older people, those admitted to ICU, and patients who received intranasal oxygen care had a higher risk of dying due to COVID-19 disease. Therefore, close monitoring hospitalized patients that are old aged and those with comorbidities after hospitalization is crucial within the first ten days of admission.

Evaluation of health-related quality of life of Covid-19 patients: a hospital-based study in South Central Ethiopia.

BACKGROUND: Covid-19 causes a wide range of symptoms in patients, ranging from mild manifestations to severe disease and death. This study assessed the health-related quality of life (HRQOL) and associated factors of Covid-19 patients using primary data from confirmed cases in South Central Ethiopia. METHODS: We employed a facility-based, cross-sectional study design and conducted the study at the Bokoji Hospital Covid-19 treatment centre. A structured questionnaire and the EQ-5D-3L scale were used to collect the data for analysis. The HRQOL results measured by the EQ-5D-3L tool were converted to a health state utility (HSU) using the Zimbabwe tariff. The average health utility index and HSU-visual analogue scale across diverse sociodemographic and clinical characteristics were compared using the Mann-Whitney U test or Kruskal-Wallis test. We employed a multiple linear regression to examine factors associated with HSU values simultaneously. The data were analysed using STATA version 15. RESULTS: The overall mean HSU score from the EQ-5D was 0.688 (SD: 0.285), and the median was 0.787 (IQR 0.596, 0.833). The mean HSU from the visual analogue scale score was 0.69 (SD: 0.129), with a median of 0.70 (IQR 0.60, 0.80). Those who received dexamethasone and intranasal oxygen supplement, those with comorbidity, those older than 55 years and those with a hospital stay of more than 15 days had significantly lower HSU scores than their counterparts (p < .001). CONCLUSION: Covid-19 substantially impaired the HRQOL of patients in Ethiopia, especially among elderly patients and those with comorbidity. Therefore, clinical follow-up and psychological treatment should be encouraged for these groups. Moreover, the health utility values from this study can be used to evaluate quality adjusted life years for future cost-effectiveness analyses of prevention and treatment interventions against Covid-19.

Equity in public health spending in Ethiopia: a benefit incidence analysis.

Inequality in access and utilization of health services because of socioeconomic status is unfair, and it should be monitored and corrected with appropriate remedial action. Therefore, this study aimed to estimate the distribution of benefits from public spending on health care across socioeconomic groups in Ethiopia using a benefit incidence analysis. We employed health service utilization data from the Living Standard Measurement Survey, recurrent government expenditure data from the Ministry of Finance and health services delivery data from the Ministry of Health's Health Management Information System. We calculated unit subsidy as the ratio of recurrent government health expenditure on a particular service type to the corresponding number of health services visits. The concentration index (CI) was applied to measure inequality in health care utilization and the distribution of the subsidy across socioeconomic groups. We conducted a disaggregated analysis comparing health delivery levels and service types. Furthermore, we used decomposition analysis to measure the percentage contribution of various factors to the overall inequalities. We found that 61% of recurrent government spending on health goes to health centres (HCs), and 74% was spent on outpatient services. Besides, we found a slightly pro-poor public spending on health, with a CI of -0.039, yet the picture was more nuanced when disaggregated by health delivery levels and service types. The subsidy at the hospital level and for inpatient services benefited the wealthier quintiles most. However, at the HC level and for outpatient services, the subsidies were slightly pro-poor. Therefore, an effort is needed in making inpatient and hospital services more equitable by improving the health service utilization of those in the lower quintiles and those in rural areas. Besides, policymakers in Ethiopia should use this evidence to monitor inequity in government spending on health, thereby improving government resources allocation to target the disadvantaged better.

Costs and cost-effectiveness of Gene Xpert compared to smear microscopy for the diagnosis of pulmonary tuberculosis using real-world data from Arsi zone, Ethiopia.

BACKGROUND: Early diagnosis and treatment are one of the key strategies of tuberculosis control globally, and there are strong efforts in detecting and treating tuberculosis cases in Ethiopia. Smear microscopy examination has been a routine diagnostic test for pulmonary tuberculosis diagnosis in resource-constrained settings for decades. Recently, many countries, including Ethiopia, are scaling up the use of Gene Xpert without the evaluation of the cost and cost-effectiveness implications of this strategy. Therefore, this study evaluated the cost and cost-effectiveness of Gene Xpert (MTB/RIF) and smear microscopy tests to diagnosis tuberculosis patients in Ethiopia. METHODS: We compared the costs and cost-effectiveness of tuberculosis diagnosis using smear microscopy and Gene Xpert among 1332 patients per intervention in the Arsi zone. We applied combinations of top-down and bottom-up costing approaches. The costs were estimated from the health providers' perspective within one year (2017-2018). We employed "cases detected" as an effectiveness measure, and the incremental cost-effectiveness ratio was calculated by dividing the changes in cost and change in effectiveness. All costs and incremental cost-effectiveness ratio were reported in 2018 US$. RESULTS: The unit cost per test for Gene Xpert was $12.9 whereas it is $3.1 for AFB smear microscopy testing. The cost per TB case detected was $77.9 for Gene Xpert while it was $55.8 for the smear microscopy method. The cartridge kit cost accounted for 42% of the overall Gene Xpert's costs and the cost of the reagents and consumables accounted for 41.3% ($1.3) of the unit cost for the smear microscopy method. The ICER for the Gene Xpert strategy was $20.0 per tuberculosis case detected. CONCLUSION: Using Gene Xpert as a routine test instead of standard care (smear microscopy) can be potentially cost-effective. In the cost scenario analysis, the price of the cartridge, the number of tests performed per day, and the life span of the capital equipment were the drivers of the unit cost of the Gene Xpert method. Therefore, Gene Xpert can be a part of the routine TB diagnostic testing strategy in Ethiopia.

Contextualization of cost-effectiveness evidence from literature for 382 health interventions for the Ethiopian essential health services package revision.

BACKGROUND: Cost-effectiveness of interventions was a criterion decided to guide priority setting in the latest revision of Ethiopia's essential health services package (EHSP) in 2019. However, conducting an economic evaluation study for a broad set of health interventions simultaneously is challenging in terms of cost, timeliness, input data demanded, and analytic competency. Therefore, this study aimed to synthesize and contextualize cost-effectiveness evidence for the Ethiopian EHSP interventions from the literature. METHODS: The evidence synthesis was conducted in five key steps: search, screen, evaluate, extract, and contextualize. We searched MEDLINE and EMBASE research databases for peer-reviewed published articles to identify average cost-effectiveness ratios (ACERs). Only studies reporting cost per disability-adjusted life year (DALY), quality-adjusted life year (QALY), or life years gained (LYG) were included. All the articles were evaluated using the Drummond checklist for quality, and those with a score of at least 7 out of 10 were included. Information on cost, effectiveness, and ACER was extracted. All the ACERs were converted into 2019 US dollars using appropriate exchange rates and the GDP deflator. RESULTS: In this study, we synthesized ACERs for 382 interventions from seven major program areas, ranging from US$3 per DALY averted (for the provision of hepatitis B vaccination at birth) to US$242,880 per DALY averted (for late-stage liver cancer treatment). Overall, 56% of the interventions have an ACER of less than US$1000 per DALY, and 80% of the interventions have an ACER of less than US$10,000 per DALY. CONCLUSION: We conclude that it is possible to identify relevant economic evaluations using evidence from the literature, even if transferability remains a challenge. The present study identified several cost-effective candidate interventions that could, if scaled up, substantially reduce Ethiopia's disease burden.

Cost-Effectiveness of Saxagliptin Compared With Glibenclamide as a Second-Line Therapy Added to Metformin for Type 2 Diabetes Mellitus in Ethiopia.

Background. Metformin is a widely accepted first-line pharmacotherapy for patients with type 2 diabetes mellitus (T2DM). Treatment of T2DM with glibenclamide, saxagliptin, or one of the other second-line treatment agents is recommended when the first-line treatment (metformin) cannot control the disease. However, there is little evidence on the additional cost and cost-effectiveness of adding second-line drugs. Therefore, this study aimed to estimate the cost-effectiveness of saxagliptin and glibenclamide as second-line therapies added to metformin compared with metformin only in T2DM in Ethiopia. Methods. This cost-effectiveness study was conducted in Ethiopia using a mix of primary data on cost and best available data from the literature on the effectiveness. We measured the interventions' cost from the providers' perspective in 2019 US dollars. We developed a Markov model for T2DM disease progression with five health states using TreeAge Pro 2020 software. Disability-adjusted life year (DALY) was the health outcome used in this study, and we calculated the incremental cost-effectiveness ratio (ICER) per DALY averted. Furthermore, one-way and probabilistic sensitivity analysis were performed. Results. The annual unit cost per patient was US$70 for metformin, US$75 for metformin + glibenclamide, and US$309 for metformin + saxagliptin. The ICER for saxagliptin + metformin was US$2259 per DALY averted. The ICER results were sensitive to various changes in cost, effectiveness, and transition probabilities. The ICER was driven primarily by the higher cost of saxagliptin relative to glibenclamide. Conclusion. Our study revealed that saxagliptin is not a cost-effective second-line therapy in patients with T2DM inadequately controlled by metformin monotherapy based on a gross domestic product per capita per DALY averted willingness-to-pay threshold in Ethiopia (US$953).

Validity and reliability of the Amharic version of the Schwartz Center Compassionate Care Scale.

BACKGROUND: Compassionate care is the sensitivity shown by health care providers to understand another person's suffering and a willingness to help and to promote the well being of that person. Although monitoring of compassionate care is key to ensuring patient-centered care, there is no validated tool in the Ethiopian context that can be applied to measure compassionate care. Therefore, this study aimed to assess the structural validity and reliability of the 12-item Schwartz Center Compassionate Care Scale® (SCCCS) in the Ethiopian context. METHODS: The structural validity and reliability of the 12-item Schwartz Center Compassionate Care Scale® were investigated in a sample of 423 oncology patients in the adult Oncology department of Tikur Anbessa Specialized Hospital in Addis Ababa, Ethiopia. The internal consistency of the instrument was examined based on Cronbach's alpha coefficient, and the structural validity was evaluated by subjecting the items of the instrument to factor analysis. Statistical analysis was made using SPSS version 23.0. RESULTS: We have found that the Schwartz Center Compassionate Care scale is a two-factor structure (recognizing suffering and acting to relieve suffering). The scale has high overall scale reliability, which was 0.88, and subscale reliability of 0.84 for both recognizing suffering and acting to relieve suffering factors. CONCLUSIONS: The Schwartz Center Compassionate Care Scale has high internal consistency and acceptable structural validity value. The tool can be used to measure compassionate care practice in the Ethiopian context.