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In this overview, the problems with the implementation of such data are discussed.
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In the absence of such data, implementation strategies are best-guess rather than data-driven.
The analysis of such data requires the implementation of multilevel statistical methods that adjust for this clustering.
The design and implementation of such strategies require data on erosion rates and understanding of the factors that control the delivery of sediment through the catchment system.
However, implementation of such program requires relevant accident data, which are normally unavailable or limited in developing countries.
Furthermore the paper identifies a set of pre-requisites that are fundamental to the successful implementation of such mechanisms, namely monitoring and data sharing, financial and technical capacity, particularly in nations that are most at risk with the least data infrastructure.
In such methods, although both the graphical topology and the joint probability distribution could be learnt and defined from the data set, there were many shortcomings as implementation of such approach required large amount of qualified data.
The practical implementation of such a scheme, relative to the DSTO Ingara data, will be explored in subsequent research.
However, data suggest that the implementation of such programs is incomplete, and a large majority even in these states still are not yet covered.
What do the current data say about the successful implementation of such a model?
Pediatric-specific data about the effectiveness of implementation of such programs are limited especially in the Middle East.
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