Efficiency of TB service provision in the public and private health sectors in Ethiopia.

BACKGROUND: The Ethiopian Government has identified efficiency of TB services as a key priority in planning and budgeting. Understanding the magnitude and sources of inefficiencies is key to ensuring value for money and improved service provision, and a requirement from donors to justify resource needs. This study identifies the cost of providing a wide range of TB services in public and private facilities in Ethiopia.METHODS: Financial and economic unit costs were estimated from a health provider´s perspective, and collected retrospectively in 26 health facilities using both top-down (TD) and bottom-up (BU) costing approaches for each TB service output. Capacity inefficiency was assessed by investigating the variation between TD and BU unit costs where the factor was 2.0 or more.RESULTS: Overall, TD unit costs were two times higher than BU unit costs. There was some variation across facility ownership and level of care. Unit costs in urban facilities were on average 3.8 times higher than in rural facilities.CONCLUSION: We identified some substantial inefficiencies in staff, consumable and capital inputs. Addressing these inefficiencies and rearranging the TB service delivery modality would be important in ensuring the achievement of the country´s End TB strategy

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

Road traffic accident risk indicators among traumatized patients visiting emergency outpatient clinics in public hospitals in Addis Ababa, Ethiopia

This study sought to assess the magnitude and factors associated with road traffic accidents among traumatized patients attending at emergency outpatient departments of public hospitals in Addis Ababa. Facility-based cross-sectional study design was employed on 381 samples. All traumatized patients who attend at emergency department of public hospitals in Addis Ababa city was population of the study. Systematic random sampling technique were employed to select study unites. The data was entered and cleaned by Epi-info version 7 and analyzed using SPSS for windows version 23.0 and presented using tables and figures. A total of 373 samples were collected in the study and the most of samples were in the 30–40 years of age range. The magnitude of the road traffic accident was 57.1%. Most of the study participant (64.83%) were male and the maximum age was 79 with a mean of age is (+/- 34 years) responders. Road traffic accident is more prevalence among the most productive and economically active age group. Being Females are 0.48 times higher protective for RTA than Males. Occupation (driver) 5.3 times higher risk to road traffic accident than students, weather condition(cloudy) 0.4 times protective than sunny for RTA and driving at a day time 2.1 times higher risk for RTA than at night. Improve the traffic system and community-based awareness creation could decrease the incident of car accident

Evaluation of patient safety culture among community pharmacists in Ethiopia: A cross-sectional study.

OBJECTIVE:The study was aimed to explore patient safety culture of community pharmacists working in Dessie and Gondar towns, Northern Ethiopia. METHODS:A cross-sectional study was conducted from 1st to 31st March 2018. In this cross-sectional survey, the Pharmacy Survey on Patient Safety Culture (PSOPSC), developed by the Agency for Healthcare Research and Quality (AHRQ), was used to collect data. PSOPSC is a self-administered questionnaire. The questionnaire was distributed among staffs who work in community pharmacies of Dessie and Gondar towns. All staffs available on data collection period in the pharmacy were included. The Statistical Package for Social Science (SPSS) software version 25 was used to enter and analyze the data. RESULTS:A total of 120 participants were approached and completed the questionnaire. Results from the study showed that high positive response rate was demonstrated in the domains of "Teamwork" (90.2%) followed by physical space and environment (83.1%). On the other hand, the result also identified that there is an enormous problem related to mistake communication (44.8%) and work pressure (45%). In addition, significant difference of percent positive responses were obtained across towns and staff working hours. CONCLUSIONS:The patient safety culture of community pharmacists is appreciable especially with respect to their teamwork. Besides, urgent attention should be given to areas of weakness, mainly in the domain of "mistake communication" and "staffing and work pressure"

Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families

Histone deacetylases (HDACs) are an important class of drug targets for the treatment of cancers, neurodegenerative diseases, and other types of diseases. Virtual screening (VS) has become fairly effective approaches for drug discovery of novel and highly selective histone deacetylase inhibitors (HDACIs). To facilitate the process, we constructed maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using our recently published methods that were originally developed for building unbiased benchmarking sets for ligand-based virtual screening (LBVS). The MUBD-HDACs cover all four classes including Class III (Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors and 24 609 unbiased decoys. Its ligand sets have been validated extensively as chemically diverse, while the decoy sets were shown to be property-matching with ligands and maximal unbiased in terms of “artificial enrichment” and “analogue bias”. We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs are unique in that they can be applied unbiasedly to both LBVS and SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore, to detect the “2D bias” and “LBVS favorable” effect within the benchmarking sets. In summary, MUBD-HDACs are the only comprehensive and maximal-unbiased benchmark data sets for HDACs (including Sirtuins) that are available so far. MUBD-HDACs are freely available at http://www.xswlab.org/

Magnitude of Multidrug Resistance among Bacterial Isolates from Surgical Site Infections in Two National Referral Hospitals in Asmara, Eritrea

Background. The World Health Organization has emphasized the importance of understanding the epidemiology of MDR organisms from a local standpoint. Here, we report on a spectrum of bacteria associated with surgical site infections in two referral hospitals in Eritrea and the associated antibiotic susceptibility patterns. Methods. This survey was conducted between February and May 2017. A total of 83 patients receiving treatment for various surgical conditions were included. Swabs from infected surgical sites were collected using Levine technique and processed using standard microbiological procedures. In vitro antimicrobial susceptibility testing was performed on Mueller–Hinton Agar by the Kirby-Bauer disk diffusion method following Clinical and Laboratory Standards Institute guidelines. The data were analyzed using SPSS version 20. Results. A total of 116 isolates were recovered from 83 patients. In total, 67 (58%) and 49 (42%) of the isolates were Gram-positive and Gram-negative bacteria, respectively. The most common isolates included Citrobacter spp., Klebsiella spp., Escherichia coli, Proteus spp., Pseudomonas aeruginosa, Salmonella spp., Enterobacter spp., and Acinetobacter spp. In contrast, Staphylococcus aureus, CONS, and Streptococcus viridians were the predominant Gram-positive isolates. All the Staphylococcus aureus isolates were resistant to penicillin. MRSA phenotype was observed in 70% of the isolates. Vancomycin, clindamycin, and erythromycin resistance were observed in 60%, 25%, and 25% of the isolates, respectively. Furthermore, a high proportion (91%) of the Gram-negative bacteria were resistant to ampicillin and 100% of the Pseudomonas aeruginosa and Escherichia coli isolates were resistant to >5 of the tested antibiotics. The two Acinetobacter isolates were resistant to >7 antimicrobial agents. We also noted that 4 (60%) of the Klebsiella isolates were resistant to >5 antimicrobial agents. Possible pan-drug-resistant (PDR) strains were also isolated. Conclusion. Due to the high frequency of MDR isolates reported in this study, the development and implementation of suitable infection control policies and guidelines is imperative

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

BackgroundRegular, 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.MethodsThe 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.FindingsThe 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.InterpretationLong-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