Introduction: The burden of road traffic injuries (RTI) is worsening globally, particularly in low- and middle-income countries (LMIC) and among the young and economically productive populations. A major barrier to improving road safety in India and other LMIC is that existing RTI data sources are severely limited by poor population coverage and data quality. This dissertation explores the reliability and feasibility of using a novel data source with verbal autopsy (VA) methods for the purposes of RTI surveillance in India.
Methods: The reliability of the VA methods was assessed using physician agreement on the specific categories of injury death as the metric. Next, a nationally representative household mortality survey with VA methods was used to directly estimate the age- and gender-specific RTI death rates and to identify context-specific RTI risk factors in India. Finally, a national spatial database was constructed to quantify potential access to trauma care in relation to the spatial distribution of RTI deaths in India.
Results: Across a broad array of application settings in India, the level of physician agreement was high indicating that the VA methods were reliable in distinguishing RTI deaths among other specific categories of injury deaths. The estimated 183,600 RTI deaths in 2005 from the mortality survey were over 50% more than the national police statistics. Of these RTI deaths, 65% were males between ages 15-59 years, 68% were pedestrians and other vulnerable road users, and over 55% occurred at the scene of collision, within minutes of collision, and/or involved a head injury. The existing community health centres and district hospitals in the Indian public health system had inadequate trauma care capacity but were suitably located to allow broad spatial access to timely trauma care for the majority of RTI deaths in India, which were most problematic in the northern states of Punjab, Haryana, Himachal Pradesh and in Tamil Nadu.
Conclusions: Properly designed VA studies can provide accurate and reliable RTI surveillance data and assist in identifying context-specific road safety interventions.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/43589 |
| Date | 09 January 2014 |
| Creators | Hsiao, Marvin Min-Yen |
| Contributors | Jha, Prabhat, Nathens, Avery B. |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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