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Accurate weather forecast information has the potential to improve water resources management, energy, and agriculture. This study evaluates the accuracy of medium-range (1–15 d) precipitation forecasts from the Global Forecast System (GFS) over watersheds of eight major dams (Selingue Dam, Markala Dam, Goronyo Dam, Bakolori Dam, Kainji Dam, Jebba Dam, Dadin Kowa Dam, and Lagdo Dam) in the Niger river basin using NASA's Integrated Multi-satellitE Retrievals (IMERG) Final Run merged satellite gauge rainfall observations. The results indicate that the accuracy of GFS forecast varies depending on climatic regime, lead time, accumulation timescale, and spatial scale. The GFS forecast has large overestimation bias in the Guinea region of the basin (wet climatic regime), moderate overestimation bias in the Savannah region (moderately wet climatic regime), but has no bias in the Sahel region (dry climate). Averaging the forecasts at coarser spatial scales leads to increased forecast accuracy. For daily rainfall forecasts, the performance of GFS is very low for almost all watersheds, except for Markala and Kainji dams, both of which have much larger watershed areas compared to the other watersheds. Averaging the forecasts at longer timescales also leads to increased forecast accuracy. The GFS forecasts, at 15 d accumulation timescale, have better performance but tend to overestimate high rain rates. Additionally, the performance assessment of two other satellite products was conducted using IMERG Final estimates as reference. The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) merged satellite gauge product has similar rainfall characteristics to IMERG Final, indicating the robustness of IMERG Final. The IMERG Early Run satellite-only rainfall product is biased in the dry Sahel region; however, in the wet Guinea and Savannah regions, IMERG Early Run outperforms GFS in terms of bias.

Understanding extreme precipitation is very important for Ethiopia, which is heavily dependent on low-productivity rainfed agriculture but lacks structural and non-structural water regulating and storage mechanisms. There has been an increasing concern about whether there is an increasing trend in extreme precipitation as the climate changes. Existing analysis of this region has been descriptive, without taking advantage of the advances in extreme value modeling. After reviewing the statistical methodology on extremes, this paper presents an analysis based on the generalized extreme value modeling with daily time series of precipitation records at Debre Markos in the Northwestern Highlands of Ethiopia. We found no strong evidence to reject the null hypothesis that there is no increasing trend in extreme precipitation at this location.

High resolution satellite-based rainfall estimates (SREs) have enormous potential for use in hydrological applications, particularly in the developing world as an alternative to conventional rain gauges which are typically sparse. In this study, three SREs have been evaluated against collocated rain gauge measurements in Ethiopia across six river basins that represent different rainfall regimes and topography. The comparison is made using five-year (2003–2007) averages, and results are stratified by river basin, elevation and season. The SREs considered are: the Climate Prediction Center morphing method (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Neural Networks (PERSIANN) and the real-time version of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT. Overall, the microwave-based products TMPA 3B42RT and CMORPH outperform the infrared-based product PERSIANN: PERSIANN tends to underestimate rainfall by 43 %, while CMORPH tends to underestimate by 11 % and TMPA 3B42RT tends to overestimate by 5 %. The bias in the satellite rainfall estimates depends on the rainfall regime, and, in some regimes, the elevation. In the northwest region, which is characterized mainly by highland topography, a humid climate and a strong Intertropical Convergence Zone (ITCZ) effect, elevation has a strong influence on the accuracy of the SREs: TMPA 3B42RT and CMORPH tend to overestimate at low elevations but give reasonably accurate results at high elevations, whereas PERSIANN gives reasonably accurate values at low elevations but underestimates at high elevations. In the southeast region, which is characterized mainly by lowland topography, a semi-arid climate and southerly winds, elevation does not have a significant influence on the accuracy of the SREs, and all the SREs underestimate rainfall across almost all elevations.

The objective is to assess the suitability of commonly used high-resolution satellite rainfall products (CMORPH, TMPA 3B42RT, TMPA 3B42 and PERSIANN) as input to the semi-distributed hydrological model SWAT for daily streamflow simulation in two watersheds (Koga at 299 km2 and Gilgel Abay at 1656 km2) of the Ethiopian highlands. First, the model is calibrated for each watershed with respect to each rainfall product input for the period 2003–2004. Then daily streamflow simulations for the validation period 2006–2007 are made from SWAT using rainfall input from each source and corresponding model parameters; comparison of the simulations to the observed streamflow at the outlet of each watershed forms the basis for the conclusions of this study. Results reveal that the utility of satellite rainfall products as input to SWAT for daily streamflow simulation strongly depends on the product type. The 3B42RT and CMORPH simulations show consistent and modest skills in their simulations but underestimate the large flood peaks, while the 3B42 and PERSIANN simulations have inconsistent performance with poor or no skills. Not only are the microwave-based algorithms (3B42RT, CMORPH) better than the infrared-based algorithm (PERSIANN), but the infrared-based algorithm PERSIANN also has poor or no skills for streamflow simulations. The satellite-only product (3B42RT) performs much better than the satellite-gauge product (3B42), indicating that the algorithm used to incorporate rain gauge information with the goal of improving the accuracy of the satellite rainfall products is actually making the products worse, pointing to problems in the algorithm. The effect of watershed area on the suitability of satellite rainfall products for streamflow simulation also depends on the rainfall product. Increasing the watershed area from 299 km2 to 1656 km2 improves the simulations obtained from the 3B42RT and CMORPH (i.e. products that are more reliable and consistent) rainfall inputs while it deteriorates the simulations obtained from the 3B42 and PERSIANN (i.e. products that are unstable and inconsistent) rainfall inputs.

In the present study, spatial and temporal patterns of rain event properties are analysed. These event properties are rain event depth, event duration, mean event rain rate, peak rain rate and the time span between two consecutive rain events which is referred to as inter-event time (IET). In addition, we assessed how rain event properties change when the period over which rainfall data is aggregated changes from 1 to 6 min and when the minimum inter-event time (MIT) changes from 30 min to 8 h. Rainfall data is obtained from a field campaign in two wet seasons of June–August (JJA) of 2007 and 2008 in Gilgel Abbay watershed that is situated at the source basin of the Upper Blue Nile River in Ethiopia. The rainfall data was automatically recorded at eight stations. The results revealed that rain event depth is more related to peak rain rate than to event duration. At the start and towards the end of the wet season, the rain events have larger depth with longer duration and longer IET than those in mid-season. Event rain rate and IET are strongly related to terrain elevation. Sekela which is on a mountain area has the shortest IET while Bahir Dar which is at the south shore of Lake Tana has the longest IET. The period over which rainfall data is aggregated significantly affected the values of rain event properties that are estimated using relatively small value (30 min) of MIT but its effect diminished when the MIT is increased to 8 h. It is shown that increasing the value of MIT has the largest effect on rain event properties of mountain stations that are characterised by high rainfall intermittency.

Routine information on regional evapotranspiration (ET) and dryness index is essential for agricultural water management, drought monitoring, and studies of water cycle and climate. However, this information is not currently available for the East Africa highlands. The main purpose of this study is to develop (1) a new methodology that produces spatially gridded daily ET estimates on a (near) real-time basis exclusively from satellite data, and (2) a new dryness index that depends only on satellite data and weather forecast data. The methodology that calculates daily actual ET involves combining data from two sensors (MODIS and SEVIRI) onboard two kinds of platforms (Terra – polar orbit satellite and MSG – geostationary orbit satellite). The methodology is applied to the East African highlands, and results are compared to eddy covariance measurements at one site. Results show that the methodology produces ET estimates that accurately reproduce the daily fluctuation in ET but tends to underestimate ET on the average. It is concluded that the synergistic use of the polar-orbiting MODIS data and the geostationary-orbiting SEVIRI data has potential to produce reliable daily ET, but further research is needed to improve the accuracy of the results. This study also proposes an operational new dryness index that can be calculated from the satellite-based daily actual ET estimates and daily reference ET estimates based on SEVIRI data and weather forecast air temperature. Comparison of this index against ground measurements of daily actual ET at one site indicates that the new dryness index can be used for drought monitoring.

By providing continuous high-resolution simulations of soil moisture fields, distributed hydrologic models could be powerful tools to advance the scientific community's understanding of the space-time variability and scaling characteristics of soil moisture fields. However, in order to use the soil moisture simulations from hydrologic models with confidence, it is important to understand whether the models are able to represent in a reliable way the processes regulating soil moisture variability. In this study, a comparison of the scaling characteristics of spatial soil moisture fields derived from a set of microwave radiometer observations from the Southern Great Plains 1997 experiment and corresponding simulations using the distributed hydrologic model GEOtop is performed through the use of generalized variograms. Microwave observations and model simulations are in agreement with respect to suggesting the existence of a scale-invariance property in the variograms of spatial soil moisture fields, and indicating that the scaling characteristics vary with changes in the spatial average soil water content. However, observations and simulations give contradictory results regarding the relationship between the scaling parameters (i.e. spatial organization) and average soil water content. The drying process increased the spatial correlation of the microwave observations at both short and long separation distances while increasing the rate of decay of correlation with distance. The effect of drying on the spatial correlation of the model simulations was more complex, depending on the storm and the simulation examined, but for the largest storm in the simulation most similar to the observations, drying increased the long-range correlation but decreased the short-range. This is an indication that model simulations, while reproducing correctly the total streamflow at the outlet of the watershed, may not accurately reproduce the runoff production mechanisms. Consideration of the scaling characteristics of spatial soil moisture fields can therefore serve as a more intensive means for validating distributed hydrologic models, compared to the traditional approach of only comparing the streamflow hydrographs.

Abstract: Seasonal snow water equivalent (SWE) accumulation in California’s Sierra Nevada is primarily governed by a few orographically enhanced snowstorms. However, as air temperatures gradually rise, resulting in a shift from snow to rain, the governing processes determining SWE accumulation versus ablation become ambiguous. Using a network of 28 snow pillow measurements to represent an elevational and latitudinal gradient across the Sierra Nevada, we identify distributions of critical temperatures and corresponding storm and snowpack properties that describe how SWE accumulation varies across the range at an hourly timescale for water years 2010 through 2019. We also describe antecedent and prevailing conditions governing whether SWE accumulates or ablates during warm storms. Results show that atmospheric moisture regulates a temperature dependence of SWE accumulation. Conditions balancing precipitable water and snow formation requirements produce the most seasonal SWE, which was observed in the (low-elevation) northern and (middle-elevation) central Sierra Nevada. The high southern Sierra Nevada conservatively accumulates SWE with colder, drier air, resulting in less midwinter ablation. These differences explain a tendency for deep, low-density snowpacks to accumulate rather than ablate SWE during warm storms (having median temperatures exceeding 1.0°C), reflecting counteracting liquid storage and internal energy deficits. The storm events themselves in these cases are brief with modest moisture supplies or are otherwise followed immediately by ablation.

Background: Effective infection prevention and control (IPC) was central to keeping healthcare workers (HCWs) safe during the COVID-19 pandemic. However, as the pandemic continued, the maintenance of high-quality IPC practices waned, placing HCWs at increased risk of infection. A COVID-19 Safety Officer (SO) program was piloted by the United States Agency for International Development (USAID)-funded Reaching Impact, Saturation and Epidemic Control (RISE) project across two health facilities in Ethiopia, which trained clinical and non-clinical HCWs on IPC protocols to promote safe practices in patient care areas. We sought to evaluate the implementation and effectiveness of the SO program in improving IPC practices within the clinical setting., Methods: This is a post-implementation evaluation of the SO program, implemented in two hospitals in Ethiopia between May 2022 and December 2022. Participants completed a 4-day course on COVID-19 epidemiology, IPC, safety communication, and learning theory as a part of the Training of Trainers component ( n = 23), and were posted in clinical wards to provide staff training and support to maintain IPC protocols. The program was evaluated at 6 months using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Effectiveness was measured using direct observation of IPC practices across intervention sites. Implementation outcomes were measured using surveys and qualitative interviews to capture training cascade, knowledge, comfort, acceptability, and maintenance., Results: Participants were able to cascade training to an additional 167 clinical (67.6%) and 80 non-clinical (32.3%) staff across both sites. Direct observation of clinical staff at 6 months showed that 95% (59/62) wore at least a surgical mask with patients and were compliant with masking and/or distancing protocol. Clinical interviews revealed that SOs contributed to increased perceived comfort with screening and isolation procedures and environmental cleaning procedures., Conclusion: The SO training program was widely adopted, and effective in improving the implementation and comfort of maintaining IPC practices in clinical settings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Woldeamanuel, Thumba, Gabul, Ahmed, Mekonnen, Tarekegn, Nhanala, Kent, Ashengo, Wu, Dagoye, Curless, Fisseha, Ayalew, Gebremichael and Hansoti.)

Non-communicable diseases (NCDs) are a leading health and development challenge worldwide. Since 2015, WHO and the United Nations Development Programme have provided support to governments to develop national NCD investment cases to describe the socioeconomic dimensions of NCDs. To assess the impact of the investment cases, semistructured interviews and a structured process for gathering written feedback were conducted between July and October 2022 with key informants in 13 countries who had developed a national NCD investment case between 2015 and 2020. Investment cases describe: (1) the social and economic costs of NCDs, including their distribution and projections over time; (2) priority areas for scaled up action; (3) the cost and returns from investing in WHO-recommended measures to prevent and manage NCDs; and (4) the political dimensions of NCD responses. While no country had implemented all the recommendations set out in their investment case reports, actions and policy changes attributable to the investment cases were identified, across (1) governance; (2) financing; and (3) health service access and delivery. The pathways of these changes included: (1) stronger collaboration across government ministries and partners; (2) advocacy for NCD prevention and control; (3) grounding efforts in nationally owned data and evidence; (4) developing mutually embraced 'language' across health and finance; and (5) elevating the priority accorded to NCDs, by framing action as an investment rather than a cost. The assessment also identified barriers to progress on the investment case implementation, including the influence of some private sector entities on sectors other than health, the impact of the COVID-19 pandemic, and changes in senior political and technical government officials. The results suggest that national NCD investment cases can significantly contribute to catalysing the prevention and control of NCDs through strengthening governance, financing, and health service access and delivery., Competing Interests: Competing interests: None declared., (© World Health Organization 2024. Licensee BMJ.)

Preparedness to endure extreme situations such as natural disasters or military conflicts is not commonplace in healthcare training programs. Moreover, multidisciplinary teams in health services rarely (if ever) include experts in security. However, when emergency situations occur, prevailing healthcare demands do not cease to exist, and unexpected demands often surge due to the shortage of other services and supplies or as a consequence of the emergency condition itself.With services in 45 countries, AIDS Healthcare Foundation (AHF) has operated in several conflict zones, facing broad and challenging security demands. Since 2017 AHF has implemented the Global Department of Safety and Security (GDSS), a dedicated intelligence and safety program that had a key role in the security monitoring, preparedness, and defense responses, assisting staff members and clients during recent conflicts.In this manuscript, we describe the experience of AHF's GDSS in three recent military conflicts in Ethiopia, Myanmar, and Ukraine, and provide insights into steps that can be taken to assure staff safety and support the mission of caring for patients throughout catastrophic events., (© 2024. The Author(s).)

Background: Cutaneous leishmaniasis (CL) is a growing public health threat in Ethiopia. Leishmania aethiopica is the predominant causative organism. Affected individuals develop chronic skin lesions on exposed parts of the body, mostly on the face, which are disfiguring and cause scarring. The effects of CL on the health-related quality of life (HRQoL) of affected individuals has not been assessed in Ethiopia., Objective: To assess HRQoL in adults with active CL at ALERT Hospital, Addis Ababa, Ethiopia., Methods: A cross-sectional study was done using the Amharic version of the Dermatology Life Quality Index (DLQI). Trained health staff administered the DLQI., Results: Three hundred and two adults with active CL participated and all of them exhibited a reduced HRQoL. The median DLQI score was 10 (IQR 8). Almost half of the participants reported very poor HRQoL, 36.4% and 11.3% fell within the very large and extremely large effect categories respectively. DLQI scores were higher (median 18) in patients diagnosed with diffuse cutaneous leishmaniasis (DCL) compared to those with localized cutaneous leishmaniasis (LCL). The DLQI domain of 'work and school' was the most affected, scoring 73.3% and 66.6% of total possible score for female and male respectively, followed by that of 'symptom and feeling' (at 50.0% and 56.6% for female and male respectively). Men were more affected than women in the domains of 'leisure' (P = 0.002) and 'personal relationships' (P = 0.001). In the multivariate ordinal logistic regression site of lesion, clinical phenotype and age of participant remained associated with significantly poor HRQoL., Conclusion: The HRQoL impairment associated with CL is significant. Thus, patient-reported outcome measure should be used to assess the efficacy of treatments along with clinical outcome measures., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Doni et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The under-five mortality rate is a reliable indicator of a country's general level of development and the wellbeing of its children. Life expectancy is a good indicator of a population's standard of living., Objectives: To identify Socio-demographic and Environmental determinants of under-five child mortality in Ethiopia., Methods: A national representative cross sectional study and a quantitative study were conducted among 5753 households selected based on 2019 Mini-Ethiopian Demographic and Health Survey (EDHS-2019) data. The analysis was done using STATA version 14 statistical software. Bivariate and multivariate analyses were used. To assess the determinants of under-five child mortality in multivariate analysis, p values less than 0.05 were considered statistically significant, and odds ratios with 95% CI (confidence interval) were used., Results: A total of 5,753 children were included in the study. Sex of the head of the household being female (AOR = 2:350, 95% CI: 1.310, 4.215), the U5CM for being their mother were currently married (AOR = 2:094, 95% CI: 1.076, 4.072), The odds of U5CM was less by 80% (AOR = 1.797, 95% CI: 1.159-2.782) with the number of under-five children at the household born 2-4th order as compared to those children born on the first order. For the mothers visit anti natal care four and above visit (AOR = 1:803, 95% CI: 1.032, 3.149), for the way of delivery (AOR = 0:478, 95% CI: 0.233, 0.982)., Conclusion: Multivariate logistic analysis reflected that way of delivery, mothers had being currently marred, sex of the head of the household and number of antenatal care visit were found to be significant predictors of under-five child mortality. So, government policy, nongovernmental organizations, and all concerned bodies should be focused on the major determinants of under-five child mortality and put in a lot more effort to reduce under-five child mortality., (© 2023. The Author(s).)

Mountain snowpacks are transitioning to experience less snowfall and more rainfall as the climate warms, creating more persistent low- to no-snow conditions. This precipitation shift also invites more high-impact rain-on-snow (ROS) events, which have historically yielded many of the largest and most damaging floods in the western United States. One such sequence of events preceded the evacuation of 188,000 residents below the already-damaged Oroville Dam spillway in February 2017 in California's Sierra Nevada. Prior studies have suggested that snowmelt during ROS dramatically amplified reservoir inflows. However, we present evidence that snowmelt may have played a smaller role than previously documented (augmenting terrestrial water inputs by 21%). A series of hydrologic model experiments and subdaily snow, soil, streamflow, and hydrometeorological measurements demonstrate that direct, "passive" routing of rainfall through snow, and increasingly efficient runoff driven by gradually wetter soils can alternatively explain the extreme runoff totals. Our analysis reveals a crucial link between frequent winter storms and a basin's hydrologic response-emphasizing the role of soil moisture "memory" of within-season storms in priming impactful flood responses. Given the breadth in plausible ROS flood mechanisms, this case study underscores a need for more detailed measurements of soil moisture along with in-storm changes to snowpack structure, extent, energy balance, and precipitation phase to address ROS knowledge gaps associated with current observational limits. Sharpening our conceptual understanding of basin-scale ROS better equips water managers moving forward to appropriately classify threat levels, which are projected to increase throughout the mid-21st century., (© The Author(s) 2022. Published by Oxford University Press on behalf of the National Academy of Sciences.)

Objectives: The WHO currently recommends stool testing using GeneXpert MTB/Rif (Xpert) for the diagnosis of paediatric tuberculosis (TB). The simple one-step (SOS) stool method enables processing for Xpert testing at the primary healthcare (PHC) level. We modelled the impact and cost-effectiveness of implementing the SOS stool method at PHC for the diagnosis of paediatric TB in Ethiopia and Indonesia, compared with the standard of care., Setting: All children (age <15 years) presenting with presumptive TB at primary healthcare or hospital level in Ethiopia and Indonesia., Primary Outcome: Cost-effectiveness estimated as incremental costs compared with incremental disability-adjusted life-years (DALYs) saved., Methods: Decision tree modelling was used to represent pathways of patient care and referral. We based model parameters on ongoing studies and surveillance, systematic literature review, and expert opinion. We estimated costs using data available publicly and obtained through in-country expert consultations. Health outcomes were based on modelled mortality and discounted life-years lost., Results: The intervention increased the sensitivity of TB diagnosis by 19-25% in both countries leading to a 14-20% relative reduction in mortality. Under the intervention, fewer children seeking care at PHC were referred (or self-referred) to higher levels of care; the number of children initiating anti-TB treatment (ATT) increased by 18-25%; and more children (85%) initiated ATT at PHC level. Costs increased under the intervention compared with a base case using smear microscopy in the standard of care resulting in incremental cost-effectiveness ratios of US$132 and US$94 per DALY averted in Ethiopia and Indonesia, respectively. At a cost-effectiveness threshold of 0.5×gross domestic product per capita, the projected probability of the intervention being cost-effective in Ethiopia and Indonesia was 87% and 96%, respectively. The intervention remained cost-effective under sensitivity analyses., Conclusions: The addition of the SOS stool method to national algorithms for diagnosing TB in children is likely to be cost-effective in both Ethiopia and Indonesia., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Depletion of groundwater is accelerated due to an increase in water demand for applications in urbanized areas, agriculture sectors, and energy extraction, and dwindling surface water during changing climate. Managed aquifer recharge (MAR) is one of the several methods that can help achieve long-term water sustainability by increasing the natural recharge of groundwater reservoirs with water from non-traditional supplies such as excess surface water, stormwater, and treated wastewater. Despite the multiple benefits of MAR, the wide-scale implementation of MAR is lacking, partly because of challenges to select the location for MAR implementation and identify the MAR type based on site conditions and needs. In this review, we provide an overview of MAR types with a basic framework to select and implement specific MAR at a site based on water availability and quality, land use, source type, soil, and aquifer properties. Our analysis of 1127 MAR projects shows that MAR has been predominantly implemented in sites with sandy clay loam soil (soil group C) and with access to river water for recharge. Spatial analysis reveals that many regions with depleting water storage have opportunities to implement MAR projects. Analyzing data from 34 studies where stormwater was used for recharge, we show that MAR can remove dissolved organic carbon, most metals, E. coli but not efficient at removing most trace organics, and enterococci. Removal efficiency depends on the type of MAR. In the end, we highlight potential challenges for implementing MAR at a site and additional benefits such as minimizing land subsidence, flood risk, augmenting low dry-season flow, and minimizing salt-water intrusion. These results could help identify locations in the water-stressed regions to implement specific MAR for water sustainability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Earth observations offer potential pathways for accurately closing the water and energy balance of watersheds, a fundamental challenge in hydrology. However, previous attempts based on purely satellite-based estimates have focused on closing the water and energy balances separately. They are hindered by the lack of estimates of key components, such as runoff. Here, we posit a novel approach based on Budyko's water and energy balance constraints. The approach is applied to quantify the degree of long-term closure at the watershed scale, as well as its associated uncertainties, using an ensemble of global satellite data sets. We find large spatial variability across aridity, elevation, and other environmental gradients. Specifically, we find a positive correlation between elevation and closure uncertainty, as derived from the Budyko approach. In mountainous watersheds the uncertainty in closure is 3.9 ± 0.7 (dimensionless). Our results show that uncertainties in terrestrial evaporation contribute twice as much as precipitation uncertainties to errors in the closure of water and energy balance. Moreover, our results highlight the need for improving satellite-based precipitation and evaporation data in humid temperate forests, where the closure error in the Budyko space is as high as 1.1 ± 0.3, compared to only 0.2 ± 0.03 in tropical forests. Comparing the results with land surface model-based data sets driven by in situ precipitation, we find that Earth observation-based data sets perform better in regions where precipitation gauges are sparse. These findings have implications for improving the understanding of global hydrology and regional water management and can guide the development of satellite remote sensing-based data sets and Earth system models., (© 2021. The Authors.)

Data collected for the World Heart Federation's Scorecard project regarding the current state of cardiovascular disease prevention, control and management, along with related non-communicable diseases in Ethiopia are presented. Furthermore, the strengths, threats, weaknesses and priorities identified from these data are highlighted in concurrence with related sections in the accompanying infographic. Information was collected using open-source data sets from the World Bank, the World Health Organization, the Institute for Health Metrics and Evaluation, the International Diabetes Federation and relevant government publications.

Background: Anemia is a global public health problem; but its burden is disproportionately borne among children in the African Regions. The 2016 Ethiopia Demographic and Health Survey report showed that the prevalence of anemia among children 6-59 months of age was 57%; far exceeding the national target of 25% set for 2015. Although studies have been conducted in Ethiopia, multilevel analysis has rarely been used to identify factors associated with anemia among children. Therefore, this study aimed to identify individual and community-level factors associated with anemia among children 6-59 months of age by fitting a multilevel logistic regression model., Methods: The data was obtained from the 2016 Ethiopia Demographic and Health Survey, conducted from January to June 2016, and downloaded from the website http://www.DHSprogram.com. The sample was taken using two-stage stratified sampling. In stage one, 645 Enumeration Areas and in stage two 28 households per Enumeration Area were selected. A sample of 7790 children 6-59 months of age was included. Data were analyzed using STATA version 14. A multilevel logistic regression model was fitted and an adjusted odds ratio with a 95% confidence interval was obtained., Result: From the individual-level factors, anemia was associated most strongly with child age, wealth index, maternal anemia and child stunting followed by child underweight, child fever and birth order whereas from the community-level, the strongest odds of anemia occurred among children from Somali, Harari, Dire Dawa and Afar region followed by Oromia and Addis Ababa. Low community-poverty is a protective factor for anemia. The odds of anemia were 0.81 (95% CI: 0.66, 0.99) times lower for children who were living in communities of lower poverty status than children who were living in communities of higher poverty status. Children from Somali and Dire Dawa had 3.38 (95% CI: 3.25, 5.07) and 2.22 (95% CI: 1.42, 3.48) times higher odds of anemia, respectively than children from the Tigray region., Conclusions: This study shows that anemia among children 6-59 months of age is affected both by the individual and community level factors. It is better to strengthen the strategies of early detection and management of stunted and underweight children. At the same time, interventions should be strengthened to address maternal anemia, child fever and poverty, specifically targeting regions identified to have a high risk of anemia., Competing Interests: The authors have declared that no competing interests exist.

Riparian ecosystems provide various ecosystem services including habitat for a variety of plant and animal communities, biofiltering, and stabilizing stream and river systems. Due to their location, riparian zones often share long borders with agricultural fields where herbicides are commonly applied to eliminate unwanted plants. There is a general concern that exposure of riparian vegetation to off-target drifted herbicides may adversely impact their health and diversity. We utilized the Normalized Difference Vegetation Index (NDVI) to investigate the long-term (between 1992 and 2011) trend of riparian vegetation health at 17 locations in the Midwest and Great Plains areas of the United States, where herbicide usage was likely most intense. Assessment of NDVI data demonstrated that long-term vegetation health did not decline for the studied riparian zones located in proximity to croplands during spring months (April and May). During summer (June and July), while the long-term vegetation health did not decline for the majority of the sites, there were a few cases in Kansas and Nebraska with a decline in vegetation health (negative-trending NDVI). Cluster analysis of the negative-trending NDVI pixels showed that the majority of these pixels were randomly distributed throughout these riparian sites, indicating a lack of shared common causing factors. Similarly, proximity analysis suggested that distance from croplands was not associated with the decline of vegetation health found in these sites, suggesting that exposure to herbicide drift may not be a plausible factor because this would have shown higher impact on pixels closer to the cropland. Changes in canopy coverage and vegetation diversity also did not show any dependence on distance from croplands. Finally, the remote-sensing-based NDVI data sets used provide only an indirect way of assessing the impact of herbicide drift, and therefore, further work based on field survey data is recommended to completely isolate the impacts of herbicides. Integr Environ Assess Manag 2019;15:528-543. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

Background: The emergence of highly active antiretroviral therapy (HAART) has dramatically improved quality of life in prolonging survival of human immunodeficiency virus (HIV)-infected patients on treatment in developed as well as developing countries. However, the main shortcoming of HAART in long-term use is its potential to cause liver and kidney derangements that may be life threatening. The drugs are actively accumulated in the proximal renal tubule resulting in functional disturbance with mitochondrial injury being one of the most important targets recognized. Therefore, the aim of this study was to assess the adverse effects of HAART on kidney and liver functions among HIV-infected patients presenting to the University of Gondar Hospital, Ethiopia., Materials and Methods: An institution-based retrospective study was conducted from 2010 to 2015 on a subset of HIV-infected patients. Data were collected from the registration book of the University of Gondar Hospital antiretroviral clinic laboratory after checking the completeness of age, gender, creatinine, blood urea nitrogen, and alanine aminotransferase level. Data were entered and analyzed using SPSS version 20. Descriptive statistics, chi-square test, one-way analysis of variance, and logistic regression were done to determine associations. A P -value <0.05 was considered statistically significant., Results: A total of 275 study subjects were included in the study. Of these, 62.2% were females, and the overall prevalence of chronic kidney disease (CKD) before and after treatment was 3.6% and 11.7%, respectively. A majority of the CKD patients were in stage 3 for patients after treatment. The overall prevalence of hepatotoxicity was 6.5% and 16.7% before and after treatment, respectively. A majority of the patients developed Grade 2 hepatotoxicity 66.7% and 65.2% before and after treatment, respectively. Binary and multiple logistic regression analysis indicated that the female gender was a risk factor for CKD., Conclusion: The prevalence of nephrotoxicity and hepatotoxicity were high among patients who took HAART. Stage 3 nephrotoxicity and Grade 2 hepatotoxicity had the highest incidences of the total toxicities, and the female gender was a risk factor for nephrotoxicity. Further prospective studies are recommended to determine the effect of HAART and contributing factors., Competing Interests: The authors report no conflicts of interest in this work.

The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p < 0.05) bias in estimated parameters and model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes., (© 2014, National Ground Water Association.)

Objective: To assess the suitability of satellite temperature and precipitation datasets for investigating the dependence of Schistosoma mansoni disease transmission on meteorological conditions in an irrigated agricultural region in Ethiopia., Methods: Data used were monthly number of patients infected with S. mansoni and seeking treatment at the local hospital, monthly maximum air temperature from a local weather station, monthly average land surface temperature from MODIS satellite data, monthly total precipitation from a local rain gauge and precipitation estimates from four widely used satellite products, namely, TMPA 3B42RT, TMPA 3B42, CMORPH and PERSIANN. The number of patients was used as proxy for vector abundance., Results: Temperature and precipitation play a role in the transmission of S. mansoni disease. There is a weak but significant positive correlation between monthly maximum air temperature derived from a meteorological station (or average land surface temperature derived from MODIS satellite product) and the number of patients in the same month. There is a significant negative correlation between monthly precipitation volume (derived from rain gauge or satellite data) and number of patients at lags of 1 and 2 months., Conclusion: Satellite temperature and precipitation products provide useful information to understand and infer the relationship between meteorological conditions and S. mansoni prevalence., (© 2011 Blackwell Publishing Ltd.)

Background: Critically ill patients may require specialized care that is offered only at tertiary referral centers. As regionalization and specialization of critical care become more common, transportation of critically ill patients must be refined. Transportation of critically ill patients within a hospital, much less outside the hospital, is often deemed unsafe because of medical instability. We report, here, our results from 2 yrs' experience of transporting extremely ill patients with respiratory failure via a ground critical care transport service., Methods: A mobile intensive care unit was equipped and staffed to nearly recreate the intensive care environment. Staffing included a physician, nurse, respiratory therapist, and driver--all with extensive critical care experience. The mobile intensive care unit was equipped with a full pharmacy, advanced ventilatory equipment, and capability for full invasive hemodynamic monitoring. Data were analyzed by retrospective review. The predicted mortality rate, based on Pao2/Fio2 ratios, was compared with the actual mortality rate., Results: During a 2-yr period, 39 critically ill patients were transported. Thirty-six of the 39 were candidates for extracorporeal lung assist, with a mean positive end-expiratory pressure requirement of 15.9, a mean Fio2 requirement of .93, and a mean Pao2/Fio2 ratio of 59.8. Pulmonary arterial catheters and peripheral arterial catheters were in place in 66.6% and 72% of patients, respectively. Vasoactive medications were being infused in 56%, and 74% were receiving medical paralytics. One patient died during movement from the bed to the transport gurney. Other than one episode of transient hypotension, there were no complications or untoward outcomes related to transport. Unique therapeutic interventions were performed at the receiving facility on 34 of 39 patients. The predicted mortality rate, based on indicators of lung dysfunction, was 68% to 100%; the actual subsequent hospital mortality rate was 43%., Conclusions: When a mobile intensive care unit is properly staffed and equipped and patient stabilization is performed before transfer, severely ill patients with respiratory failure can be transferred safely. For patients with respiratory failure, there may be a survival advantage in transfer to regional centers of expertise.