Abstract. This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Modelpredicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies.

Background Studies showed that each year people lose their life on the road and many people are disabled. The majority of this disability was caused by orthopedic injury related to road traffic accidents. However, in the context of Ethiopia, studies ascribed to orthopedic injuries related to road traffic accidents are limited. The study aimed to assess the pattern of orthopedic injuries related to road traffic accidents among patients managed at the emergency department of Black Lion Hospital. Methods An institutional-based cross-sectional study was conducted on 354 victims of road traffic accidents with orthopedic injuries who were visiting the Emergency department of Black Lion Hospital. Patient charts were selected by systematic random sampling technique and the data was entered into Epi-data version 4.4.2.2 and exported to the static package for social science window version 26, and descriptive statistics were used for analysis. Results The study reveals that males were mostly injured persons (71.7%) with the age group of 13–24 were the most injured. Passenger car accounts 36.3% of causes of injury followed by motorbikes (27.4%) and lower limbs were the most common anatomic site of injuries (47.9). Of all injury types, a fracture is the most common one with 71.1%, especially lower limb fracture (42.1%). More than half victims (59.5%) had open wounds, and almost half of the study subjects (51.8%) experience Road traffic accidents while they are crossing or walking along the way. Conclusion Orthopedic injuries related to road traffic accidents are the main cause of death and disability in many individuals, especially in reproductive age groups. Therefore, policy-makers should be aware of different patterns of orthopedic injuries associated with a victim of road traffic accidents to have an appropriate and sustainable capacity to manage the orthopedic injuries.

Background The transfer time for critically ill patients from the emergency department (ED) to the Intensive care unit (ICU) must be minimal; however, some factors prolong the transfer time, which may delay intensive care treatment and adversely affect the patient’s outcome. Purpose To identify factors affecting intensive care unit admission of critically ill patients from the emergency department. Patients and methods A cross-sectional study design was conducted from January 13 to April 12, 2020, at the emergency department of Tikur Anbesa Specialized Hospital. All critically ill patients who need intensive care unit admission during the study period were included in the study. A pretested structured questionnaire was adapted from similar studies. The data were collected by chart review and observation. Then checked data were entered into Epi-data version 4.1 and cleaned data was exported to SPSS Version 25 for analysis. Descriptive statistics, bivariate and multivariate logistic regression were used to analyze the data. Result From the total of 102 critically ill patients who need ICU admission 84.3% of them had prolonged lengths of ED stay. The median length of ED stay was 13.5 h with an IQR of 7–25.5 h. The most common reasons for delayed ICU admission were shortage of ICU beds 56 (65.1%) and delays in radiological examination results 13(15.1%). On multivariate logistic regression p < 0.05 male gender (AOR = 0.175, 95% CI: (0.044, 0.693)) and shortage of ICU bed (AOR = 0.022, 95% CI: (0.002, 0.201)) were found to have a significant association with delayed intensive care unit admission. Conclusion there was a delay in ICU admission of critically ill patients from the ED. Shortage of ICU bed and delay in radiological investigation results were the reasons for the prolonged ED stay.

Background: Electrocardiography is a graphic representation of the electrical activity of the heart. According to previous literature, nurses have poor knowledge and skills about basic electrocardiography interpretation. For instance, a previous survey conducted in Turkey showed that only 38.1 percent of nurses were able to recognize ventricular fibrillation, 54.3% myocardial infarction, and 33.3% third-degree atrioventricular block. Objective: This study was aimed at assessing Nurses’ competency in electrocardiography interpretation in adult emergency rooms in Addis Ababa, Ethiopia, in 2021. Method: An institutional-based descriptive, cross-sectional study design was used to conduct the study. A total of 175 nurses in five randomly selected hospitals with adult emergency rooms were included in this study. Semi-structured, self-administered questionnaires were used to collect the data. Data were entered into Epi data and analyzed using SPSS version 26. A Fisher’s exact test was used to identify the relationship between dependent and independent variables. Results: Of 203 respondents, 175 actively participated, for a response rate of 86.2%. From those 175 nurses, 159 (90.9%) were not competent (scored < 65%), and the mean score was 6.82 ± 3.65 SD. Conclusion: The overall level of competency of nurses in electrocardiography interpretation is low. This implies most nurses in the emergency room do not monitor and manage a patient's electrocardiography for manifestations of arrhythmias, electrolyte disturbance and other cardiac abnormalities. Level of education and training were a determinant factor to enhance their competency.