Near miss road traffic accidents and associated factors among truck drivers in Gamo zone, southern Ethiopia by using a contributory factors interaction model.

Background: Road traffic accidents (RTAs) are among the leading causes of injuries, fatalities, and the resulting increase in financial burdens worldwide. Every year, RTAs cause numerous serious injuries and fatalities in Ethiopia. it is important to understand how prevalent near-miss crash accidents are, and which by definition could have injured the victim but did not result in an actual accident. The determinants of these near-misses are essential in road crash accident reduction strategies. In spite of the fact that near-miss accidents are much more common than actual losses or injuries, very little research has been conducted on them. Thus, this study was intended to assess the near-miss accidents and associated factors among truckers in Gamo zone, southern Ethiopia. Methodology: The community-based cross-sectional study was employed from May 12 to July 10,2022, using a structured interviewer-administered questionnaire. A simple random sampling technique was used to select participants. The data were analyzed using the statistical package for social sciences. A binary and multivariate logistic regression model was used to identify the determinants of near-miss accidents. A statistical significance level was set at p < 0.05. Results: About 72.5% of truckers had experienced near-miss road traffic accidents. The majority of the near-miss accidents were caused by speeding, followed by driving on the wrong side of the road and skidding, 65 (22.6%), 39 (13.5%), and 38 (13.2%), respectively. Driving frequency per week, location of accidents, condition of the road, sleeping status, and weather conditions were significantly associated with near-miss accidents. Conclusion: The prevalence of near-miss accidents is high in the Gamo zone. Being a younger and less educated driver, high driving frequency per week, driving on major roads and junctions, foggy weather, and inadequate sleep all contribute to the occurrence of accidents. Road safety measures that could address these identified factors are required to mitigate potential RTAs.

Identification of determinant factors for crash severity levels occurred in Addis Ababa City, Ethiopia, from 2017 to 2020: using ordinal logistic regression model approach.

BACKGROUND: Road traffic Injuries (RTI) are multifaceted occurrences determined by the combination of multiple factors. Also, severity levels of injuries from road traffic accidents are determined by the interaction of the composite factors. Even though most accidents are severe to fatal in developing countries, there is still a lack of extensive researches on crash severity levels and factors associated with these accidents. Hence, this study was intended to identify severity levels of road traffic injuries and determinant factors in Addis Ababa City, Ethiopia. METHODS: The study was conducted in Addis Ababa, the capital city of Ethiopia, using secondary data obtained from the Addis Ababa Police Commission office. The ordinal logistic regression model was used to investigate road traffic injury severity levels and factors worsening injury severity levels using the recorded dataset from October 2017 to July 2020. RESULTS: A total of 8458 car accidents were considered in the study, of which 15.1% were fatal, 46.7% severe, and 38.3% were slight injuries. The results of the ordinal logistic regression analysis estimation showed that being a commercial truck, college and above level educated driver, rollover crash, motorbike passengers, the crash day on Friday, and darkness were significantly associated factors with crash injury severity levels in the study area. On the contrary, driving experience (> 10 years), passenger of the vehicle, two-lane roads, and afternoon crashes were found to decrease the severity of road traffic injuries. CONCLUSIONS: Road traffic injury reduction measures should include strict law enforcement in order to maintain road traffic rules especially among commercial truckers, motorcyclists, and government vehicle drivers. Also, it is better to train drivers to be more alert and conscious in their travels, especially on turning and handling their vehicles while driving.

Epidemiological characteristics of deaths from road traffic accidents in Addis Ababa, Ethiopia: a study based on traffic police records (2018-2020).

INTRODUCTION: Road traffic accidents are a major cause of fatal and nonfatal injuries, causing permanent disabilities, and other indirect health complications. Each year, road traffic accidents (RTA) cause a lot of fatalities and injuries in Ethiopia, putting the country among the list of the most affected countries by RTA in the world. Despite the high rates of road traffic collisions in Ethiopia, very little is known about the factors that contribute to fatal RTA in the country. OBJECTIVES: the objective of this study is to assess the epidemiological characteristics of deaths from road traffic accidents in Addis Ababa, Ethiopia: A study based on traffic police records (2018-2020). METHOD: A retrospective observational study design was conducted used in this study. All road traffic accident victims reported to Addis Ababa police station between 2018 and 2020 were study population and the collected data was evaluated with Statistical Package for the Social Sciences (SPSS) version 26 software. Binary logistic regression model was used to indicate the association between dependent and independent variables. Statistically, significant associations were declared at P < 0.05. RESULT: There were 8458 recorded road traffic accidents in Addis Ababa during 2018-2020. Among these accidents, 1274 (15.1%) caused death while 7184 (84.1%) caused an injury. Males accounted for 77.1% of the decedents (sex ratio of almost 3.36:1). The majority 1020 (80%) of the fatality occurred on a straight road and 1106 (86.8%) of the fatality occurred in dry weather. Weekday 1.243 (AOR, 1.234, 95 CI, 1.071-1.443), driver educational status below grade twelve 0.326(AOR 0.326, CI, 0.285-0.374), and commercial truck vehicle 1.682 (OR, 1.696, CI, 1.410-2.040) were statistically associated with fatality after adjusting for potential confounding variables. CONCLUSION: The prevalence of RTA fatality in Addis Ababa is high. The accidents that occurred during the weekdays were more fatal. Driver's educational status, weekdays, and vehicle type were factors associated with mortality. There is a need to introduce road safety interventions that targeted identified factors in this study to reduce fatalities attributed to RTIs.

Prehospital characteristics of COVID-19 patients transported by emergency medical service and the predictors of a prehospital sudden deterioration in Addis Ababa, Ethiopia.

BACKGROUND: Severally ill COVID-19 patients may require urgent transport to a specialized facility for advanced care. Prehospital transport is inherently risky; the patient's health may deteriorate, and potentially fatal situations may arise. Hence, early detection of clinically worsening patients in a prehospital setting may enable selecting the best receiving facility, arranging for swift transportation, and providing the most accurate and timely therapies. The incidence and predictors of abrupt prehospital clinical deterioration among critically ill patients in Ethiopia are relatively limited. STUDY OBJECTIVES: This study was conducted to determine the incidence of sudden clinical deterioration during prehospital transportation and its predictors. METHODS: A prospective cohort study of 591 COVID-19 patients transported by a public EMS in Addis Ababa. For data entry, Epi data V4.2 and SPSS V 25 were used for analysis. To control the effect of confounders, the candidate variables for multivariable analysis were chosen using a p 0.25 inclusion threshold from the bivariate analysis. A statistically significant association was declared at adjusted relative risk (ARR) ≠ 1 with a 95 % confidence interval (CI) and a p value < 0.05 after adjusting for potential confounders. RESULTS: The incidence of prehospital sudden clinical deterioration in this study was 10.8%. The independent predictors of prehospital sudden clinical deterioration were total prehospital time [ARR 1.03 (95%; CI 1.00-1.06)], queuing delays [ARR 1.03 (95%; CI 1.00-1.06)], initial prehospital respiratory rate [ARR 1.07 (95% CI 1.01-1.13)], and diabetic mellitus [ARR 1.06 (95%; CI 1.01-1.11)]. CONCLUSION: In the current study, one in every ten COVID-19 patients experienced a clinical deterioration while an EMS provider was present. The factors that determined rapid deterioration were total prehospital time, queueing delays, the initial respiratory rate, and diabetes mellitus. Queueing delays should be managed in order to find a way to decrease overall prehospital time. According to this finding, more research on prehospital intervention and indicators of prehospital clinical deterioration in Ethiopia is warranted.

Characteristics and Outcomes of Mechanically Ventilated Patients at Adult ICU of Selected Public Hospitals in Addis Ababa, Ethiopia.

Introduction: Mechanical ventilation is the primary method of supporting organ function for patients admitted to intensive care units (ICU). The information on the characteristics and outcomes of patients requiring mechanical ventilation is essential to understanding the causes of mortality among mechanically ventilated patients. However, the available literature in developing countries, including Ethiopia, is limited. Objective: The objective of this study was to assess the characteristics and outcomes of mechanically ventilated patients in adult intensive care units in selected public hospitals, in Addis Ababa, Ethiopia, from 2019 to 2020. Methods: An institutional-based cross-sectional study design was employed. All adult patients who were mechanically ventilated and admitted to ICU for at least 24 hours between July 2019 and July 2020 were included in the study. The collected data were evaluated with SPSS version 26 software. Multiple logistic regression models were used to indicate the association between dependent and independent variables. The variables, which have an independent association with poor outcomes, were identified with a p-value less than 0.05. Results: Of 180 mechanically ventilated patients, 98(54.4%) were male. The main reason for ventilation was respiratory failure. The mean duration of stay on the ventilator was 7.09± 6.06, and the mortality rate in mechanically ventilated patients was 41.7%. The mortality rate was higher in patients with cardiac diseases 43(57.70%). Inotropic use, not taking sedation, and length of stay on a mechanical ventilator were independently associated with mortality. Conclusion: The mortality rate of mechanically ventilated patients in the selected public hospitals was high. The clinicians must strive to balance the necessity and benefit of sedation use with the potential to negatively affect the patient outcome. In addition, the risk:benefit assessment of ventilation must be done for all patients requiring ventilator support.