ABSTRACT
Suicides from popular venues (known as "hotspots") are often publicized and may result in imitation by subsequent suicides that may lead to clustering of the suicides over time. In order to examine whether the suicides from the Golden Gate Bridge showed clustering, data from the 224 suicides during 1999-2009 were analyzed using the Anderson-Darling Test was run on the data against a null hypothesis of a negative exponential distribution (as would be generated by a homogenous Poisson process). It was found that the data were almost a perfect fit for the Poisson distribution and so showed no evidence of clustering beyond that expected to occur by chance alone. This indicates that there was no imitation or contagion in the suicides from the Golden Gate Bridge.
ABSTRACT
BACKGROUND: Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. AIM: This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. METHOD: Suicide dates were collected for MIT and Cornell for 1990-2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. RESULTS: Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). CONCLUSIONS: The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.
