Road traffic injuries are a growing cause of morbidity and mortality in low- and middle-income countries (LMICs), with a particularly high burden in Africa, including in Kenya [1,2,3]. In Kenya road traffic incidents are among the leading causes of both morbidity and mortality [4,5,6,7,8,9]. Road traffic-associated injuries are particularly common among users of motorcycles and public transportation (mutatus/mini-bus), as well as among pedestrians [4, 8, 10]. Broadly, across age groups, Kenyans have poor seatbelt and helmet utilization . Among a cohort of head injured patients in a Kenyan emergency department (ED), none reported seatbelt or helmet use at the time of injury . Furthermore, the Kenyan public has recognized the key role vehicles and over crowded public transit play in increasing risk of injury on Kenyan roadways [13, 14].
Yet, systematic data collection for traffic incidents is broadly lacking across Africa, as well as in Kenya. The ability to target road and traffic safety improvements with tailored solutions requires an understanding of the burden of disease and the current strengths and weaknesses. Robust and accurate statistics around road traffic deaths, hospital data, population surveys, or police reports are often not available [1, 2]. Prior work in Kenya has identified the need to “improve the collection and availability of accurate [road traffic injury] data” in the country . There is recognized underreporting, variance from recognized international standards, and overall inadequate data collection around road traffic incidents in Kenya . Previously, the World Health Organization has estimated that nearly 80% of road traffic fatalities were unreported in prior Kenyan government data .
The majority of Kenyans have access to mobile telephones (91% penetration per capita, compared to 80% across Africa) and many Kenyans use social media (an average of nearly 3 hours per day), including an estimated 50% of Kenyans who use the popular microblog and social media platform Twitter . Prior research has evaluated crowdsourced data from mobile phone data and social media platforms such as Twitter to provide timely incident detection . However, the preponderance of prior work in the space has been performed in high-income countries with robust and publicly available crash data, utilized real time GPS or accelerometer data, or had evaluated unique newsworthy events, as opposed to routine social media postings [20,21,22].
This study aims to evaluate publicly available social media posts regarding road traffic incidents in Kenya. We hypothesize that the data from Twitter can be used as one of the few publicly available sources of road traffic incident data in Kenya given the paucity of available government or other reliable data sources. Furthermore, we detail the epidemiology of Kenyan road traffic incidents using information contained in Twitter posts.