Biology:Safety in numbers

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Short description: Hypothesis
Critical Mass, San Francisco, April 29, 2005 and Muni Metro tram on J Church line

Safety in numbers is the hypothesis that, by being part of a large physical group or mass, an individual is less likely to be the victim of a mishap, accident, attack, or other bad event. Some related theories also argue (and can show statistically)[citation needed] that mass behaviour (by becoming more predictable and "known" to other people) can reduce accident risks, such as in traffic safety – in this case, the safety effect creates an actual reduction of danger, rather than just a redistribution over a larger group.

In biology

The mathematical biologist W.D. Hamilton proposed his selfish herd theory in 1971 to explain why animals seek central positions in a group. Each individual can reduce its own domain of danger by situating itself with neighbours all around, so it moves towards the centre of the group.[1] The effect was tested in brown fur seal predation by great white sharks. Using decoy seals, the distance between decoys was varied to produce different domains of danger. The seals with a greater domain of danger had as predicted an increased risk of shark attack.[2] Antipredator adaptations include behaviour such as the flocking of birds, herding of sheep[3] and schooling of fish.[4] Similarly, Adelie penguins wait to jump into the water until a large enough group has assembled, reducing each individual's risk of seal predation.[5] This behavior is also seen in masting and predator satiation where the predators are overwhelmed with an abundance of prey during a period of time resulting in more of the prey surviving.

In road traffic safety

Amsterdam, 1982

In 1949 R. J. Smeed reported that per capita road fatality rates tended to be lower in countries with higher rates of motor vehicle ownership.[6] This observation led to Smeed's Law.

In 2003 P. L. Jacobsen[7] compared rates of walking and cycling, in a range of countries, with rates of collisions between motorists and cyclists or walkers. He found an inverse relationship that was hypothesised to be explained by a concept described as 'behavioural adaptation', whereby drivers who are exposed to greater numbers of cyclists on the road begin to drive more safely around them. Though an attractive concept for cycling advocates, it has not been empirically validated. Other combined modelling[8][9] and empirical evidence suggests that while changes in driver behaviour might still be one way that collision risk per cyclist declines with greater numbers,[10] the effect can be easily produced through simple spatial processes akin to the biological herding processes described above.[11]

Without considering hypotheses 1 or 3, Jacobsen concluded that "A motorist is less likely to collide with a person walking and bicycling if more people walk or bicycle." He described this theory as "safety in numbers."[7]

Safety in numbers is also used to describe the evidence that the number of pedestrians or cyclists correlates inversely with the risk of a motorist colliding with a pedestrian or cyclist. This non-linear relationship was first shown at intersections.[12][13] It has been confirmed by ecologic data from cities in California and Denmark, and European countries, and time-series data for the United Kingdom and the Netherlands.[7] The number of pedestrians or bicyclists injured increases at a slower rate than would be expected based on their numbers. That is, more people walk or cycle where the risk to the individual pedestrian or bicyclist is lower.[14][15] A 2002 study into whether pedestrian risk decreased with pedestrian flow, using 1983-86 data from signalized intersections in a town in Canada, found that in some circumstances pedestrian flow increased where the risk per pedestrian decreased.[16]

After cycling was promoted in Finland, there was a 75% drop in cyclists deaths and the number of trips increased by 72%.[17]

In England, between 2000 and 2008, serious bicycle injuries declined by 12%. Over the same period, the number of bicycle trips made in London doubled.[18][19][20] Motor vehicle traffic decreased by 16%, bicycle use increased by 28% and cyclist injuries had decreased by 20% in the first year of operation of the London Congestion Charge.[21] In January 2008, the number of cyclists in London being treated in hospitals for serious injuries had increased by 100% in six years. Over the same time, they report, the number of cyclists had increased by 84%.[22] In York, comparing the periods 1991-93 and 1996–98, the number of bicyclists killed and seriously injured fell by 59%. The share of trips made by bicycle rose from 15% to 18%.[23]

In Germany, between 1975 and 2001, the total number of bicycle trips made in Berlin almost quadrupled. Between 1990 and 2007, the share of trips made by bicycle increased from 5% to 10%. Between 1992 and 2006, the number of serious bicycle injuries declined by 38%.[24][25] In Germany as a whole, between 1975 and 1998, cyclist fatalities fell by 66% and the percent of trips made by bicycle rose from 8% to 12%.[26]

In America, during the period 1999-2007, the absolute number of cyclists killed or seriously injured decreased by 29% and the amount of cycling in New York city increased by 98%.[27][28][29] In Portland, Oregon, between 1990 and 2000, the percentage of workers who commuted to work by bicycle rose from 1.1% to 1.8%. By 2008, the proportion has risen to 6.0%; while the number of workers increased by only 36% between 1990 and 2008, the number of workers commuting by bicycle increased 608%. Between 1992 and 2008, the number of bicyclists crossing four bridges into downtown was measured to have increased 369% between 1992 and 2008. During that same period, the number of reported crashes increased by only 14%.[30][31][32]

In Copenhagen, Denmark, between 1995 and 2006, the number of cyclists killed or seriously injured fell by 60%. During the same period, cycling increased by 44% and the percent of people cycling to work increased from 31% to 36%.[33]

In the Netherlands, between 1980 and 2005, and cyclist fatalities decreased by 58% and cycling increased by 45%.[34]

During 7 years of the 1980s, admissions to hospital of cyclists declined by 5% and cycling in Western Australia increased by 82%. [35]

See also

References

  1. Hamilton, W. (1971). "Geometry for the selfish herd". Journal of Theoretical Biology 31 (2): 295–311. doi:10.1016/0022-5193(71)90189-5. PMID 5104951. Bibcode1971JThBi..31..295H. 
  2. De Vos, Alta; O'Riain, M. Justin (2010). "Sharks shape the geometry of a selfish seal herd: experimental evidence from seal decoys". Biology Letters 6 (1): 48–50. doi:10.1098/rsbl.2009.0628. PMID 19793737. 
  3. King, Andrew J.; Wilson, Alan M.; Wilshin, Simon D.; Lowe, John; Haddadi, Hamed; Hailes, Stephen; Morton, A. Jennifer (2012). "Selfish-herd behaviour of sheep under threat". Current Biology 22 (14): R561–R562. doi:10.1016/j.cub.2012.05.008. PMID 22835787. http://discovery.ucl.ac.uk/1366736/1/1366736.pdf. 
  4. Orpwood, James E.; Magurran, Anne E.; Armstrong, John D.; Griffiths, Siân W. (2008). "Minnows and the selfish herd: effects of predation risk on shoaling behaviour are dependent on habitat complexity". Animal Behaviour 76 (1): 143–152. doi:10.1016/j.anbehav.2008.01.016. 
  5. Alcock, John (2001). Animal Behavior: An Evolutionary Approach. Sunderland, MA: Sinauer Associates. 
  6. Smeed, R. J. (1949-01-01). "Some Statistical Aspects of Road Safety Research". Journal of the Royal Statistical Society. Series A (General) 112 (1): 1–34. doi:10.2307/2984177. 
  7. 7.0 7.1 7.2 Jacobsen, P. L. (2003). "Safety in numbers: more walkers and bicyclists, safer walking and bicycling". Injury Prevention 9 (3): 205–209. doi:10.1136/ip.9.3.205. PMID 12966006. "A motorist is less likely to collide with a person walking and bicycling if more people walk or bicycle.". 
  8. Thompson, Jason; Savino, Giovanni; Stevenson, Mark (2015-02-17). "Reconsidering the Safety in Numbers Effect for Vulnerable Road Users: An Application of Agent-Based Modeling". Traffic Injury Prevention 16 (2): 147–153. doi:10.1080/15389588.2014.914626. ISSN 1538-9588. PMID 24761795. https://figshare.com/articles/journal_contribution/1007605. 
  9. Thompson, Jason; Wijnands, Jasper S.; Savino, Giovanni; Lawrence, Brendan; Stevenson, Mark (2017-08-01). "Estimating the safety benefit of separated cycling infrastructure adjusted for behavioral adaptation among drivers; an application of agent-based modelling". Transportation Research Part F: Traffic Psychology and Behaviour 49: 18–28. doi:10.1016/j.trf.2017.05.006. ISSN 1369-8478. 
  10. Thompson, Jason; Savino, Giovanni; Stevenson, Mark (2016-03-01). "A model of behavioural adaptation as a contributor to the safety-in-numbers effect for cyclists". Transportation Research Part A: Policy and Practice 85: 65–75. doi:10.1016/j.tra.2015.12.004. ISSN 0965-8564. 
  11. Thompson, Jason Hugh; Wijnands, Jasper S.; Mavoa, Suzanne; Scully, Katherine; Stevenson, Mark R. (2019-10-01). "Evidence for the 'safety in density' effect for cyclists: validation of agent-based modelling results" (in en). Injury Prevention 25 (5): 379–385. doi:10.1136/injuryprev-2018-042763. ISSN 1353-8047. PMID 30315090. https://injuryprevention.bmj.com/content/25/5/379. 
  12. Brüde, U., Larsson, J. (1993). "Models for predicting accidents at junctions where pedestrians and cyclists are involved. How well do they fit?". Accident Analysis and Prevention 25 (5): 499–509. doi:10.1016/0001-4575(93)90001-D. PMID 8397652. http://urn.kb.se/resolve?urn=urn:nbn:se:vti:diva-3370. "According to results obtained, the risk - the number of accidents involving unprotected road users per unprotected road user - increases with increasing numbers of motor vehicles but decreases with increasing numbers of pedestrians and cyclists.". 
  13. Leden, L., Gårder, P., Pulkkinen, U. (2000). "An expert judgment model applied to estimating the safety effect of a bicycle facility". Accident Analysis and Prevention 32 (4): 589–599. doi:10.1016/S0001-4575(99)00090-1. PMID 10868762. "An analysis of the relationship between bicycle flow and the number of reported accidents in the experimental area shows that the relative risk — when risk is defined as the number of expected (reportable) accidents per passing bicyclist — decreases with increasing bicycle flow". 
  14. Elvik, R. (2009). "The non-linearity of risk and the promotion of environmentally sustainable transport". Accident Analysis and Prevention 41 (4): 849–855. doi:10.1016/j.aap.2009.04.009. PMID 19540975. "Several studies show that the risks of injury to pedestrians and cyclists are highly non-linear. This means that the more pedestrians or cyclists there are, the lower is the risk faced by each pedestrian or cyclist.". 
  15. Leden, L. (2002). "Pedestrian risk decrease with pedestrian flow. A case study based on data from signalized intersections in Hamilton, Ontario". Accident Analysis and Prevention 34 (4): 457–464. doi:10.1016/S0001-4575(01)00043-4. PMID 12067108. "When risks for pedestrians were calculated as the expected number of reported pedestrian accidents per pedestrian, risk decreased with increasing pedestrian flows and increased with increasing vehicle flow.". 
  16. CBA of Cycling. Nordic Council of Ministers. 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:norden:org:diva-1870. 
  17. "The London Cycling Action Plan. Transport for London, London, UK". Transport for London. 2004. http://www.tfl.gov.uk/assets/downloads/businessandpartners/cycling-action-plan.pdf. 
  18. "Cycling in London: Final report. Transport for London, London". Transport for London. 2008. http://www.tfl.gov.uk/assets/downloads/businessandpartners/cycling-in-london-final-october-2008.pdf. 
  19. "Central London congestion charging: Impacts monitoring, Sixth Annual Report. Transport for London, London". Transport for London. 2008. http://www.tfl. Retrieved 2020-03-29. 
  20. Transport for London (April 2005). "Congestion Charging: Third Annual Monitoring Report". http://www.tfl.gov.uk/assets/downloads/corporate/ThirdAnnualReportFinal.pdf. 
  21. Nicholas Cecil (2008-01-28). "Number of cyclists treated for serious injuries doubles". Evening Standard. http://www.thisislondon.co.uk/standard/article-23434443-details/Number+of+cyclists+treated+for+serious+injuries+doubles/article.do. 
  22. Harrison, J. (2001). "Planning for more cycling: The York experience bucks the trend". World Transport Policy & Practice 7 (4). 
  23. Senatsverwaltung fuer Stadtentwicklung. Office of Urban Development, Berlin, Germany (2003). Focus on bicycling. 
  24. Pucher, J.; Buehler, R. (2007). "At the frontiers of cycling: Policy innovations in the Netherlands, Denmark, and Germany". World Transp. Policy Pract. 13 (3): 8–57. 
  25. Pucher, J.; Dijkstra, L. (2000). "Making walking and cycling safer: lessons from Europe". Transportation Quarterly 54 (3): 25–50. 
  26. NYC DOT (2008). Safe Streets NYC: Traffic Safety Improvements in New York City. 
  27. A Joint Report from the New York City Departments of Health and Mental Hygiene, Parks and Recreation, Transportation, and the New York City Police Department (2005). Bicyclist Fatalities and Serious Injuries in New York City 1996-2005. 
  28. New York City Commuter cyclist indicator. http://www.nyc.gov/html/dot/downloads/pdf/commuter_cycling_indicator_and_data_2009.pdf. 
  29. US Census Bureau (2009). U.S. Census website. https://www.census.gov. Retrieved 2020-03-29. 
  30. City of Portland, Portland Bureau of Transportation (2008). Portland bicycle counts 2008. 
  31. City of Portland (2008). Portland's 2008 bicycle friendly community application, Portland, OR. 
  32. City of Copenhagen Traffic Department (2007). Copenhagen, city of cyclists: bicycle account 2006. http://www.vejpark2.kk.dk/publikationer/pdf/464_Cykelregnskab_UK.%202006.pdf. Retrieved 2010-10-14. 
  33. Ministerie van Verkeer en Waterstaat (2007). Cycling in the Netherlands. 
  34. Robinson, D. (2005). "Safety in numbers in Australia: more walkers and bicyclists, safer walking and bicycling". Health Promotion Journal of Australia 16 (1): 47–51. doi:10.1071/he05047. PMID 16389930. http://www.cycle-helmets.com/hpja_2005_1_robinson.pdf. 

External links