Postby newie » Fri Oct 05, 2012 5:46 pm
I have been a bit surprised that there hasn't been more discussion of the recent UNSW study by Olivier et al. I guess most people don't have access to the journal article and it is hard to know what to conclude from newspaper reports. Anyway I have had a look at the article and it seems to me that the data in it could mean the end of any hopes for a repeal of the MHL. I can't imagine any politician being “brave” enough to support a repeal of the law in the light of these numbers. Hopefully the formatting doesn't go astray.
Table 2
Bicycle related head injury and limb fracture hospitalisations in New South Wales for 1991–2010.
Year, Head, Arm, NSW pop, BI, CC, ERASS
1991, 590, 660, 5.9
1992, 648, 760, 6.0
1993, 635, 839, 6.0
1994, 634, 882 , 6.1
1995, 667, 964 , 6.1
1996, 732, 1114, 6.2
1997, 745, 1058, 6.3
1998, 750, 1144, 6.3
1999, 756, 1115, 6.4
2000, 828, 1334, 6.5, 0.9
2001, 715, 1171, 6.6, 0.8, NA, 400800
2002, 795, 1241, 6.6, 1.1, 1552, 429100
2003, 806, 1390, 6.7,1.0, 1693, 404300
2004, 882, 1457, 6.7, 1.2, 1870, 481700
2005, 847, 1583, 6.8, 1.2, 2251, 474200
2006, 1004, 1622, 6.8. 1.2, 2622, 468300
2007, 878, 1576, 6.9, 1.4, 2958, 447400
2008, 840, 1623, 7.0, 1.2, 3121, 539600
2009, 769, 1619, 7.2, 1.1, 3915, 503600
2010, 706, 1620, 7.2, NA, 3974, 603500
BI=bicycle imports (millions), CC= Sydney CBD cycling counts, NSW population in millions.
Sources: Admitted Patients Data Collection (HOIST), NSW Ministry of Health; Cycling Promotion Fund. CPF Annual Report 2009/10. Canberra (AUST): CPF; NSW Roads and
Maritime Services; Exercise, Recreation and Sport Survey (ERASS), Australian Sports Commission (2010).
While I was looking it up I came across another article published by a group in the Netherlands which I found a bit surprising. Here is the abstract.
“Governments aim to promote a shift from car to bicycle, but concerns about road safety seem to represent an important argument against this encouragement. This study examines the road safety impact of a modal shift from short car trips to cycling in Dutch municipalities. The road safety effect is estimated using Accident Prediction Models (APMs) that account for the non-linearity of risk. APMs are developed utilizing Negative Binomial regression. This study is the first to develop APMs using crash and mobility data from municipalities, and utilizing these models to estimate the effects of changing modal splits of current car and bicycle use to modal splits that actually exist in these municipalities. The results suggest that, under conditions such as in Dutch municipalities, transferring short trips made by cars to bicycles does not change the number of fatalities, but increases the number of serious road injuries. The neutral effect on fatalities, despite the high fatality risk for cyclists, can be explained by there being fewer cars on the road to pose a risk to others, the shorter length of bicycle trips compared to the car trips they replace, and the “safety in numbers” phenomenon. The rise in the number of serious road injuries is due wholly to the high number of cycling crashes with no other vehicle involved. The effect of a modal shift
is dependent on the age of the population in which the shift is concentrated, and can be influenced by measures affecting cyclists’ injury risk.”