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Criminal profiling to identify microbial serial killers
A new mathematical and computational method combining elements of criminal geographical profiling and Bayesian methods used in epidemiology has been developed by researchers in Queen Mary University of London and Texas State University in the USA to determine infection sources by geographical location of disease cases. The method, described in a paper in the journal Methods in Ecology and Evolution, had improved search efficiency compared to either of the other two methods in both simulations and real world situations.

In criminology, investigators use a method called geographical profiling in which they use information on the spatial locations of linked crimes such as murder or rape in order to determine the area where the perpetrator is most likely to live. This provides a way to narrow down the search, for example in cases which generate large numbers of names of potential suspects such as that of the Yorkshire Ripper. This method uses an algorithm called criminal geographic targeting (CGT). In recent times this method has been applied to identification of infection sources for diseases by using information on the locations of disease cases. This facilitates targeted intervention, for example in the case of malaria outbreaks. However, issues arise when trying to identify multiple sources, particularly when the number of sources is not known.

In the current study, the researchers claim to have solved the issue of identifying multiple sources, even when the number of sources is unknown. They tested their new model on both simulations and on real world situations such as data from a malaria outbreak in Cairo. Study author Dr Steve le Comber explained the effectiveness of the new model in identifying the breeding sites of the mosquitoes responsible for this outbreak: malaria. "The experts working in the field had to search almost 300 square km to find seven breeding sites, but our model found the same sites after searching just two thirds of this area…In fact our model found five of the seven sites after searching just 10.7 square km. This is potentially important since there is a lot of evidence suggesting that the best way to control outbreaks of malaria is to attack the mosquito breeding sites – but it is incredibly difficult to do in practice."

Another key advantage of the technique is that it takes only minutes to carry out on a computer, suggesting its potential in the important early stages of epidemics when control efforts are most likely to bear fruit. Thus an outbreak could be stopped in its tracks before it has the opportunity to spread. Dr le Comber concludes: "The model has potential to identify the source of other infectious diseases as well, and we're now working with public health bodies to develop it further for use with TB, cholera and Legionnaires' disease."


Verity, R., Stevenson, M. D., Rossmo, D. K., Nichols, R. A., and Le Comber, S. C. (2014). Spatial targeting of infectious disease control: identifying multiple, unknown sources. Methods Ecol Evol (1 April 2014), pp. n/a-n/a, doi:10.1111/2041-210x.12190

Press release: Queen Mary, University of London; available from [Accessed 22 June 2014]
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