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The importance of reliable data for planning, monitoring and evaluating injury prevention interventions is unquestionable; lack of reliable injury estimates undoubtedly affects governments' ability to recognise the seriousness of the issue and to effectively address it. This is now becoming more urgent as more than one of the recently adopted post-2015 sustainable development goals call for a safer environment.1 Initiatives such as the Global Burden of Disease and WHO's Global Health Estimates have attempted to fill this information gap at global, regional and national levels.2 ,3 They apply statistical methods to available reported data from countries to generate mortality and morbidity estimates for external causes of injuries. Remarkably, those estimates have consistently pointed to the public health threat posed by injuries in low and middle income countries (LMIC). For example, the most recent estimates revealed disability-adjusted life year rates that were much higher in sub-Saharan Africa, Latin America and Southeast Asia than in the high income countries (HIC) of North America, Western Europe and Asia-Pacific.4 However, these attempts are limited in their ability to provide disaggregated data that are often needed for local-level planning, monitoring and evaluation of intervention. At the same time, they brought to light the glaring gaps in quantity and quality of input data available from LMIC that make the derived estimates for those countries less accurate.4
Since the release of the World Report on Violence and Health in 2002,5 all major WHO injury prevention reports and global monitoring reports have also been highlighting the large gaps in nationally reported data. Calls on countries to strengthen national routine data collection, conduct research and establish monitoring and evaluation mechanisms were coupled with the development of various proposals for mechanisms to achieve that with a range of potential data sources.6 ,7 …
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