Incorporating spatial dependence in simultaneously modeling crash frequency and severity

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A joint econometric framework for modeling crash counts by severity (2018, background): “Anumber of studies have also examined crash frequency and crash severity simultaneously by building on multinomial-Poisson transformation (Chiou and Fu 2013, 2015; Chiou, Fu, and Chih-Wei 2014).”
A Novel Hybrid Method for Measuring the Spatial Autocorrelation of Vehicular Crashes: Combining Moran’s Index and Getis-Ord G i * Statistic (2017, methodology): “Generalized Poisson models were utilized [24] to explore the spatial autocorrelation of crashes, and found that spatial correlation sharply decreases at distances exceeding 7 km, and shorter road segments with high crash frequency tend to have higher spatial dependency.”
Incorporating temporal correlation into a multivariate random parameters Tobit model for modeling crash rate by injury severity (2018, background): “…crash frequencies at different degrees of injury (Ma and Kockelman 2006; Song et al. 2006; Park and Lord 2007; Ma, Kockelman, and Damien 2008; El-Basyouny and Sayed 2009; Chiou and Fu 2013, 2015; Barua, El-Basyouny, and Islam 2014, 2016; Chiou, Fu, and Chih-Wei 2014; Dong, Clarke, et al. 2016).”