Examining out of pocket payments for maternal health in rural Ethiopia: Paradox of free health care un-affordability

Background: One of the components of reproductive health is maternal care. Maternal health care is supposed to be provided free of charge for public health concerns thus women have the right to get services related to maternal care free of charge at government health care facilities. But there is low utilization of the services. Only 12% of women receive ANC and only 6% get assistance of skilled health worker during delivery in Ethiopia. There are different factors for the low utilization of services. Un-affordability of services is cited as the first main reason contributing to the low utilization.Objectives: To examine the magnitude of out of pocket expenditure for maternal health series in rural Ethiopia.Methods: This study was conducted within ten randomly selected kebeles of the Butajira DSS from October 2007 to May 2008 using a cross-sectional survey design and a source population of households that expend out-of-pocket on RH services during the period of 12 months prior to the study.Results: In the study, nearly three fifth of the studied families paid out of pocket expenditures exceeding 20% of their monthly household expenditure for maternal health care seeking. Excluding expenditures for food, about 61% of them paid more than 40% of their non-food expenditure on maternal health care. Households in the lower wealth quintiles are paying greater proportion of their income (49%) than those in the highest wealth quintile who paid 19% of their income. In addition to the direct expenditures made at point of service, the indirect expenditures of reaching to the services are also found to be substantial. These indirect expenditures share 32% of ANC, 31% of obstetric care, and 44% of abortion services. Thus even if direct expenditures at point of service in public providers are assumed to be negligible, women are obliged to go to expensive private providers to reduce the indirect costs of care seeking such as waiting time. Regarding coping mechanism to respond to expenditure, households usually borrow from relatives and friends and 4.4% of the households resorted to distress sale of their assets.Conclusions: This study identified the presence of price elasticity among the poor that suggests out-of-pocket expenditure has a regressive distributional impact and poor and very poor people were expending more. On top of this, all expenses were covered from regular income which leads to catastrophic household economic crises.Recommendations: Health care providers should be evenly distributed, easily accessible and work on awareness creation on the advantages of early care seeking and preventive care. On the other hand, health care financing should also be based on the principle of cost sharing and move into prepayment schemes or insurance

Genetic Identification of Separase Regulators in Caenorhabditis elegans

Separase is a highly conserved protease required for chromosome segregation. Although observations that separase also regulates membrane trafficking events have been made, it is still not clear how separase achieves this function. Here, we present an extensive ENU mutagenesis suppressor screen aimed at identifying suppressors of sep-1(e2406), a temperature-sensitive maternal effect embryonic lethal separase mutant that primarily attenuates membrane trafficking rather than chromosome segregation. We screened nearly a million haploid genomes and isolated 68 suppressed lines. We identified 14 independent intragenic sep-1(e2406) suppressed lines. These intragenic alleles map to seven SEP-1 residues within the N-terminus, compensating for the original mutation within the poorly conserved N-terminal domain. Interestingly, 47 of the suppressed lines have novel mutations throughout the entire coding region of the pph-5 phosphatase, indicating that this is an important regulator of separase. We also found that a mutation near the MEEVD motif of HSP-90, which binds and activates PPH-5, also rescues sep-1(e2406) mutants. Finally, we identified six potentially novel suppressor lines that fall into five complementation groups. These new alleles provide the opportunity to more exhaustively investigate the regulation and function of separase

Elucidating Drivers for Variations in the Explosive Human Immunodeficiency Virus Epidemic among People Who Inject Drugs in Pakistan

BACKGROUND: Pakistan’s explosive human immunodeficiency virus (HIV) epidemic among people who inject drugs (PWID) varies widely across cities. We evaluated possible drivers for these variations. METHODS: Multivariable regression analyses were undertaken using data from 5 national surveys among PWID (n = 18 467; 2005–2017) to determine risk factors associated with variations in city-level HIV prevalence. A dynamic HIV model was used to estimate the population-attributable fraction (PAF; proportion of HIV infections prevented over 10 years when that risk factor is removed) of these risk factors to HIV transmission and impact on HIV incidence of reducing their prevalence. RESULTS: Regression analyses suggested that city-level HIV prevalence is strongly associated with the prevalence of using professional injectors at last injection, heroin use in last month, and injecting ≥4 times per day. Through calibrating a model to these associations, we estimate that the 10-year PAFs of using professional injectors, heroin use, and frequent injecting are 45.3% (95% uncertainty interval [UI], 4.3%–79.7%), 45.9% (95% UI, 8.1%–78.4%), and 22.2% (95% UI, 2.0%–58.4%), respectively. Reducing to lowest city-level prevalences of using professional injectors (2.8%; median 89.9% reduction), heroin use (0.9%; median 91.2% reduction), and frequent injecting (0.1%; median 91.8% reduction) in 2020 reduces overall HIV incidence by 52.7% (95% UI, 6.1%–82.0%), 53.0% (95% UI, 11.3%–80.2%), and 28.1% (95% UI, 2.7%–66.6%), respectively, over 10 years. CONCLUSIONS: Interventions should focus on these risk factors to control Pakistan’s explosive HIV epidemic among PWID, including a concomitant expansion of high-coverage needle/syringe provision, opioid substitution therapy, and antiretroviral therapy

Assessment of predictive models for chlorophyll-a concentration of a tropical lake

<p>Abstract</p> <p>Background</p> <p>This study assesses four predictive ecological models; Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.</p> <p>Results</p> <p>Same data set was used for models development and the data was divided into two sets; training and testing to avoid biasness in results. FL and RANN models were developed using parameters selected through sensitivity analysis. The selected variables were water temperature, pH, dissolved oxygen, ammonia nitrogen, nitrate nitrogen and Secchi depth. Dissolved oxygen, selected through stepwise procedure, was used to develop the MLR model. HEA model used parameters selected using genetic algorithm (GA). The selected parameters were pH, Secchi depth, dissolved oxygen and nitrate nitrogen. RMSE, r, and AUC values for MLR model were (4.60, 0.5, and 0.76), FL model were (4.49, 0.6, and 0.84), RANN model were (4.28, 0.7, and 0.79) and HEA model were (4.27, 0.7, and 0.82) respectively. Performance inconsistencies between four models in terms of performance criteria in this study resulted from the methodology used in measuring the performance. RMSE is based on the level of error of prediction whereas AUC is based on binary classification task.</p> <p>Conclusions</p> <p>Overall, HEA produced the best performance in terms of RMSE, r, and AUC values. This was followed by FL, RANN, and MLR.</p

Genome-wide scans identify known and novel regions associated with prolificacy and reproduction traits in a sub-Saharan African indigenous sheep (Ovis aries)

Maximizing the number of offspring born per female is a key functionality trait in commercial- and/or subsistence-oriented livestock enterprises. Although the number of offspring born is closely associated with female fertility and reproductive success, the genetic control of these traits remains poorly understood in sub-Saharan Africa livestock. Using selection signature analysis performed on Ovine HD BeadChip data from the prolific Bonga sheep in Ethiopia, 41 candidate regions under selection were identified. The analysis revealed one strong selection signature on a candidate region on chromosome X spanning BMP15, suggesting this to be the primary candidate prolificacy gene in the breed. The analysis also identified several candidate regions spanning genes not reported before in prolific sheep but underlying fertility and reproduction in other species. The genes associated with female reproduction traits included SPOCK1 (age at first oestrus), GPR173 (mediator of ovarian cyclicity), HB-EGF (signalling early pregnancy success) and SMARCAL1 and HMGN3a (regulate gene expression during embryogenesis). The genes involved in male reproduction were FOXJ1 (sperm function and successful fertilization) and NME5 (spermatogenesis). We also observed genes such as PKD2L2, MAGED1 and KDM3B, which have been associated with diverse fertility traits in both sexes of other species. The results confirm the complexity of the genetic mechanisms underlying reproduction while suggesting that prolificacy in the Bonga sheep, and possibly African indigenous sheep is partly under the control of BMP15 while other genes that enhance male and female fertility are essential for reproductive fitness

Bioactive Compounds in Fermented Foods and Management of Depression and Anxiety.

Fermented foods are considered functional foods because they may contribute additional health benefits beyond basic nutrition. Fermented functional foods act biologically in the gastrointestinal tract and can help replenish the gut microbiome, reducing intestinal permeability, which can support the restoration of normal mental health in disordered individuals. Fermentation is a biochemical process in which microorganisms are intentionally added to foods or naturally occur in foods. Due to the fermentation process, fermented foods contain three main functional components that may be present in varying amounts: functional microorganisms (probiotics), prebiotics, and biogenics (bioactive components). In particular, fermented foods may exert beneficial health effects through bioactive compounds, which are small molecules that result from chemical changes during the fermentation process. Accordingly, bioactive compounds in fermented foods may have the potential to manage depression and anxiety by altering the underlying pathways involved in the causes of these disorders

Digital Twin models in industrial operations: State-of-the-art and future research directions

A Digital Twin is a virtual representation of a physical product, asset, process, system, or service that allows us to understand, predict, and optimise their performance for better business outcomes. Recently, the use of Digital Twin in industrial operations has attracted the attention of many scholars and industrial sectors. Despite this, there is still a need to identify its value in industrial operations mainly in production, predictive maintenance, and after-sales services. Similarly, the implementation of a Digital Twin still faces many challenges. In response, a systematic literature review and analysis of 41 papers published between 2016 and 11 July 2020 have been carried out to examine recently published works in the field. Future research directions in the area are also highlighted. The result reveals that, regardless of the challenges, the role of Digital Twin in the advancement of industrial operations, especially production and predictive maintenance is highly significant. However, its role in after-sales services remains limited. Insights are offered for research scholars, companies, and practitioners to understand the current state-of-the-art and challenges, and to indicate future research possibilities in the field