The section highlights significant shortcomings in the Kenyan data
collection landscape, particularly as reported by the National Police Service (NPS) and
the National Transport and Safety Authority (NTSA). Official sources of data are found
to be lacking in quality, accuracy, and comprehensiveness, thus impeding a systematic
approach to addressing transportation issues, particularly regarding accidents and
fatalities. To overcome these limitations, the research proposes exploring alternative
data sources such as social media platforms and surveys, combined with advanced
analytical techniques like Natural Language Processing (NLP) and machine learning.
This approach aims to gain deeper insights into the causes of accidents and factors
contributing to high fatality rates. Recommendations include standardizing data
collection schemes, implementing digital reporting and data integration, fostering
interagency collaboration and mandatory reporting, establishing public awareness
campaigns, adopting international best practices, and reviewing legislation and
policies. These measures are essential for enhancing the quality and breadth of
transportation data and improving road safety in Kenya.
“ One Important Role for the City is to Conduct Studies to Document Areas of
Greatest Need, and to Facilitate Coordination between our Public and Private
Transportation Options to Weave it into a Dense Tapestry of Accessible and Reliable
Transportation.” — Mark Noble.
Keywords: Accident statistics, Kenyan transportation data, NLP, NTSA data, Twitter data, Topic modeling, User-generated data.