Vulnerable road-user deaths in Brazil: a Bayesian hierarchical model for spatial-temporal analysis.

Reducing the road traffic injuries burden is relevant to many sustainable development goals (SDG), in particular SDG3 - to establish good health and well-being. To describe the spatial-temporal trends and identify hotspot regions for fatal road traffic injuries, a Bayesian hierarchical Poisson model was used to analyze data on vulnerable road users (bicyclist, motorcyclist and pedestrians) in Brazil from 1999 to 2016. During the study period, mortality rates for bicyclists remained almost unchanged (0.6 per 100,000 people) but rose dramatically for motorcyclists (from 1.0 in 1999 to 6.0 per 100,000 people in 2016) and decreased for pedestrians (from 6.3 to 3.0 per 100,000 people). Spatial analyses accounting for socio-economic factors showed that the central and northeastern microregions of Brazil are hotspot areas for fatal injuries among motorcyclists while the southern areas are for pedestrians.