Cost-effectiveness of facility-based, stand-alone and mobile-based voluntary counseling and testing for HIV in Addis Ababa, Ethiopia

Background: Globally, there is a consensus to end the HIV/AIDS epidemic by 2030, and one of the strategies to achieve this target is that 90% of people living with HIV should know their HIV status. Even if there is strong evidence of clients’ preference for testing in the community, HIV voluntary counseling and testing (VCT) continue to be undertaken predominantly in health facilities. Hence, empirical cost-effectiveness evidence about different HIV counseling and testing models is essential to inform whether such community-based testing are justifiable compared with additional resources required. Therefore, the purpose of this study was to compare the cost-effectiveness of facility-based, stand-alone and mobile-based HIV voluntary counseling and testing methods in Addis Ababa, Ethiopia. Methods: Annual economic costs of counseling and testing methods were collected from the providers’ perspective from July 2016 to June 2017. Ingredients based bottom-up costing approach was applied. The effectiveness of the interventions was measured in terms of the number of HIV seropositive clients identified. Decision tree modeling was built using TreeAge Pro 2018 software, and one-way and probabilistic sensitivity analyses were conducted by varying HIV positivity rate, costs, and probabilities. Results: The cost of test per client for facility-based, stand-alone and mobile-based VCT was USD 5.06, USD 6.55 and USD 3.35, respectively. The unit costs of test per HIV seropositive client for the corresponding models were USD 158.82, USD 150.97 and USD 135.82, respectively. Of the three models, stand-alone-based VCT was extendedly dominated. Mobile-based VCT costs, an additional cost of USD 239 for every HIV positive client identified when compared to facility-based VCT. Conclusion: Using a mobile-based VCT approach costs less than both the facility-based and stand-alone approaches, in terms of both unit cost per tested individual and unit cost per HIV seropositive cases identified. The stand-alone VCT approach was not cost-effective compared to facility-based and mobile-based VCT. The incremental cost-effectiveness ratio for mobile-based VCT compared with facility-based VCT was USD 239 per HIV positive case.publishedVersio

Contextualization of cost-efectiveness 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$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.publishedVersio

Economic evaluation of Health Extension Program packages in Ethiopia

Background Ethiopia launched the Health Extension Program (HEP) in 2004, aimed at ensuring equitable community-level healthcare services through Health Extension Workers. Despite the program’s being a flagship initiative, there is limited evidence on whether investment in the program represents good value for money. This study assessed the cost and cost-effectiveness of HEP interventions to inform policy decisions for resource allocation and priority setting in Ethiopia. Methods Twenty-one health care interventions were selected under the hygiene and sanitation, family health services, and disease prevention and control sub-domains. The ingredient bottom-up and top-down costing method was employed. Cost and cost-effectiveness were assessed from the provider perspective. Health outcomes were measured using life years gained (LYG). Incremental cost per LYG in relation to the gross domestic product (GDP) per capita of Ethiopia (US$852.80) was used to ascertain the cost-effectiveness. All costs were collected in Ethiopian birr and converted to United States dollars (US$) using the average exchange rate for 2018 (US$1 = 27.67 birr). Both costs and health outcomes were discounted by 3 Result The average unit cost of providing selected hygiene and sanitation, family health, and disease prevention and control services with the HEP was US$0.70, US$4.90, and US$7.40, respectively. The major cost driver was drugs and supplies, accounting for 53% and 68%, respectively, of the total cost. The average annual cost of delivering all the selected interventions was US$9,897. All interventions fall within 1 times GDP per capita per LYG, indicating that they are very cost-effective (ranges: US$22–$295 per LYG). Overall, the HEP is cost-effective by investing US$77.40 for every LYG. Conclusion The unit cost estimates of HEP interventions are crucial for priority-setting, resource mobilization, and program planning. This study found that the program is very cost-effective in delivering community health services.publishedVersio

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Cost-effectiveness of treating multidrug-resistant tuberculosis in treatment initiative centers and treatment follow-up centers in Ethiopia

Background: In Ethiopia, MDR-TB has become a significant public health threat; therefore, the Ministry of Health introduced two treatment approaches for MDR-TB cases: treatment initiative center (TIC) and treatment follow-up center (TFC). TIC is where patients usually are diagnosed and start the treatment. At TFC, we follow MDR-TB patients until they completed the treatment. However, there is no evidence about the cost-effectiveness of the approaches. Therefore, this study aimed to analyze the cost-effectiveness of MDR-TB treatment in TIC and TFC. Methods: In this study, we employed a full economic evaluation from a providers' perspective. We followed a hypothetical cohort of individuals from the age of 15 for a lifetime using a Markov model with five mutually exclusive health states. We used both primary and secondary data sources for the study. Ingredient-based costing approach was used. The costs include healthcare provider costs (recurrent and capital cost) and patient-side costs (direct and indirect). We use a human capital approach to estimate the indirect cost. The cost estimates were reported in the 2017 United States Dollar (US$), and effectiveness was measured using disability-adjusted life-years (DALYs) averted. Both costs and health benefits were discounted using a 3% discount rate. Both average and incremental cost-effectiveness ratios (ICER) were reported calculated. One-way and probabilistic sensitivity analyses were reported to determine the robustness of the estimates. Results: The cost per HIV negative patient successfully treated for MDR-TB was USD 8,416 at TIC and USD 6,657 at TFC. The average cost-effectiveness ratio per DALY averted at TFC was USD 671 and USD 1,417 per DALY averted at TIC. The incremental cost-effectiveness ratio (ICER) of MDR-TB treatment at TIC was USD 1,641 per DALYs averted. Conclusion: This study indicates that the treatment of MDR-TB at both TIC and TFC are cost-effective interventions compared with the willingness to pay threshold of three-times the GDP per capita in Ethiopia

Climate change impact on hydro-climatic variables of Ribb watershed, Tana sub-basin, Ethiopia

Abstract In Ethiopia, the Ribb River is one of the tributaries of the Lake Tana sub-basin. Temperature, precipitation, and streamflow would all be affected by climate change in the Ribb watershed. As a result of the disruption of regular hydrological processes, these climate changes have an impact on water resources. The goal of this study was to look into the effects of climate change on the Ribb watershed’s hydro-climatic characteristics. The forecasted climatic data for rainfall and temperature (minimum and maximum) came from the CORDEX (Coordinated Regional Climate Downscaling Experiments) Africa database. Climate change consequences were investigated using RCP 4.5 emission scenarios for the 2021–2060 time range, compared to the 1985–2005 baselines. The observed precipitation and temperature data were used to adjust for bias. The simulation of stream flow was carried out using the semi-distributed and physically based soil and water assessment tool (SWAT). From 1997 to 2003, the model was calibrated, and from 2004 to 2007, it was validated. To determine the trend of the climate variables, trend test analyses were performed on the various time series data. In all of the experiments conducted, the trend test revealed that historical and forecast precipitation recording stations showed statistically negligible trends for all critical values. At a level of 0.05, the historical and prospective maximum and minimum temperature data revealed increasing patterns. In general, the results demonstrated that meteorological conditions cause the flow to decrease over the season. As a result, climate change will have an impact on the Ribb watersheds water resources

Cost-effectiveness of facility-based, stand-alone and mobile-based voluntary counseling and testing for HIV in Addis Ababa, Ethiopia

Background: Globally, there is a consensus to end the HIV/AIDS epidemic by 2030, and one of the strategies to achieve this target is that 90% of people living with HIV should know their HIV status. Even if there is strong evidence of clients’ preference for testing in the community, HIV voluntary counseling and testing (VCT) continue to be undertaken predominantly in health facilities. Hence, empirical cost-effectiveness evidence about different HIV counseling and testing models is essential to inform whether such community-based testing are justifiable compared with additional resources required. Therefore, the purpose of this study was to compare the cost-effectiveness of facility-based, stand-alone and mobile-based HIV voluntary counseling and testing methods in Addis Ababa, Ethiopia. Methods: Annual economic costs of counseling and testing methods were collected from the providers’ perspective from July 2016 to June 2017. Ingredients based bottom-up costing approach was applied. The effectiveness of the interventions was measured in terms of the number of HIV seropositive clients identified. Decision tree modeling was built using TreeAge Pro 2018 software, and one-way and probabilistic sensitivity analyses were conducted by varying HIV positivity rate, costs, and probabilities. Results: The cost of test per client for facility-based, stand-alone and mobile-based VCT was USD 5.06, USD 6.55 and USD 3.35, respectively. The unit costs of test per HIV seropositive client for the corresponding models were USD 158.82, USD 150.97 and USD 135.82, respectively. Of the three models, stand-alone-based VCT was extendedly dominated. Mobile-based VCT costs, an additional cost of USD 239 for every HIV positive client identified when compared to facility-based VCT. Conclusion: Using a mobile-based VCT approach costs less than both the facility-based and stand-alone approaches, in terms of both unit cost per tested individual and unit cost per HIV seropositive cases identified. The stand-alone VCT approach was not cost-effective compared to facility-based and mobile-based VCT. The incremental cost-effectiveness ratio for mobile-based VCT compared with facility-based VCT was USD 239 per HIV positive case

Contextualization of cost-efectiveness 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$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-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.publishedVersio

Economic evaluation of Health Extension Program packages in Ethiopia

Background Ethiopia launched the Health Extension Program (HEP) in 2004, aimed at ensuring equitable community-level healthcare services through Health Extension Workers. Despite the program’s being a flagship initiative, there is limited evidence on whether investment in the program represents good value for money. This study assessed the cost and cost-effectiveness of HEP interventions to inform policy decisions for resource allocation and priority setting in Ethiopia. Methods Twenty-one health care interventions were selected under the hygiene and sanitation, family health services, and disease prevention and control sub-domains. The ingredient bottom-up and top-down costing method was employed. Cost and cost-effectiveness were assessed from the provider perspective. Health outcomes were measured using life years gained (LYG). Incremental cost per LYG in relation to the gross domestic product (GDP) per capita of Ethiopia (US$852.80) was used to ascertain the cost-effectiveness. All costs were collected in Ethiopian birr and converted to United States dollars (US$) using the average exchange rate for 2018 (US$1 = 27.67 birr). Both costs and health outcomes were discounted by 3 Result The average unit cost of providing selected hygiene and sanitation, family health, and disease prevention and control services with the HEP was US$0.70, US$4.90, and US$7.40, respectively. The major cost driver was drugs and supplies, accounting for 53% and 68%, respectively, of the total cost. The average annual cost of delivering all the selected interventions was US$9,897. All interventions fall within 1 times GDP per capita per LYG, indicating that they are very cost-effective (ranges: US$22–$295 per LYG). Overall, the HEP is cost-effective by investing US$77.40 for every LYG. Conclusion The unit cost estimates of HEP interventions are crucial for priority-setting, resource mobilization, and program planning. This study found that the program is very cost-effective in delivering community health services