Author: Mitchel Chatukuta Publisher: ISBN: Category : Languages : en Pages : 488
Book Description
Background: Road traffic injuries (RTIs) are a major problem worldwide. In this mixedmethods thesis I investigated the trend of RTIs in Namibia, which is one of the worst affected countries globally. I also investigated the long-term impacts of RTIs and the role of a fuel levy fund - The Motor Vehicle Accident Fund (MVAF) - in enhancing the availability of rehabilitation and counselling services to RTI survivors in Namibia. Methods: Using quantitative methods, I conducted analysis of data sets on RTIs from 2012 to 2014. Descriptive analysis was used to characterise crashes, injuries and deaths, and people affected. Further to this, I conducted multinomial logistic regression in order to investigate the likelihood of having been injured or killed. Using qualitative methods, I conducted semi-structured interviews with RTI survivors in Namibia, and healthcare workers involved in caring for them, in order to investigate the long-term impacts of RTIs and the availability of rehabilitation and counselling services to road injury survivors in Namibia and the role played by the MVAF. Results: The quantitative analysis showed over 2012-2014, the rates of injury and death had risen by 3.9% and 1.1%. Logistic regression identified the road user group had the greatest influence on the risk of being injured and killed. The method of transportation to hospital had the greatest influence on the risk of dying among those admitted to hospital. The qualitative analysis showed that RTIs are associated with long-term physical and mental health sequalae, financial hardships, and various social problems. The analysis also showed the MVAF is effectively helping to enhance access to rehabilitation and other health services for RTI survivors. Conclusion: The present study adds to the knowledge of the long-term impact of RTIs and presents new information from Namibia, where no previous studies of this kind have been done.
Author: Marjorie Peden Publisher: DIANE Publishing ISBN: 1437904068 Category : Transportation Languages : en Pages : 67
Book Description
Every day thousands of people are killed and injured on our roads. Millions of people each year will spend long weeks in the hospital after severe crashes and many will never be able to live, work or play as they used to do. Current efforts to address road safety are minimal in comparison to this growing human suffering. This report presents a comprehensive overview of what is known about the magnitude, risk factors and impact of road traffic injuries, and about ways to prevent and lessen the impact of road crashes. Over 100 experts, from all continents and different sectors -- including transport, engineering, health, police, education and civil society -- have worked to produce the report. Charts and tables.
Author: Jeffrey Cailis Bullard Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 0
Book Description
Road traffic crashes are a leading cause of serious injuries and fatalities globally. They also place unnecessary developmental and economic burdens on low- and middle-income countries (LMICs) as they account for most of the world's road related deaths. This is typically due to both the increased frequency of dangerous crash types and the increased severity of said crash types. Rollover crashes while quite rare are a particularly dangerous crash type among other various crash types. In the case of Namibia, rollover crashes reportedly accounted for 34% of both road related injuries and fatalities in Namibia for 2020. Therefore, it crucial to understand the contributing factors and their associated effects on rollover crash severities in these countries. This thesis aims to investigate the significant factors influencing crash severities and their associated impact magnitudes on single vehicle rollover crashes in Namibia by adopting a mixed logit with heterogeneity in means and variances approach for 2014-2016 historical crash records. Additionally, roadside safety features such as paved road shoulder are a crucial component in the mitigation of these rollover crash types. While the lack of road safety features is an issue in LMICs, so is the ability to map the presence of said features. This a case study on the B2 highway in Namibia, aiming to classify images of the road according to the size of the road shoulder is also conducted. Google Street View images are labeled based to their road shoulder quality (none, up to two feet, larger than two feet). Based on the labeled images, we train a deep-artificial-neural-network to classify images according to those labels. Results indicate that rollover crashes in Namibia are influenced by several explanatory variables. Additionally, results from the deep-learning model have the potential to lower costs of mapping road safety features in LMIC.
Author: Mitchel Chatukuta
Author: National Road Safety Council of Namibia
Author: 
Author: National Road Safety Council
Author: Marjorie Peden
Author: Maano Nalikolekwe Shimanda
Author: 
Author: Jeffrey Cailis Bullard
Author: Michael Fitzharris
Author: Silas Nghishihange