When investigating a serial crime such as murder or rape, police forces worldwide use a geographic profiling tool that mathematically analyzes the spatial locations of crimes to infer the criminal’s likely anchor point – a home or workplace, for example.

Now, a team at Queen Mary University of London has adapted the tool to successfully locate the breeding sites of mosquitoes behind an outbreak of malaria.

Reporting in the journal Methods in Ecology and Evolution, the team says the approach has the potential to track other infectious diseases.

Geographic profiling can be of great help when the numbers to investigate are so big you need a way to look at the overall pattern rather than examine individual incidences.

For instance, UK police working on the Yorkshire Ripper case in the 1980s – where the list of murder suspects ran to some 280,000 names – used geographic profiling to prioritize their investigations.

Recently, spurred by the success of geographic profiling in criminology, scientists have applied it to other fields. For example, by using foraging sites as the starting data, biologists can locate the nests or roosts of animals.

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The UK team is using their geographic profiling model to help trace the source of malaria outbreaks.

Meanwhile, other scientists have been working on adapting the mathematics of geographic profiling to apply it to epidemiology – to identify disease sources from the addresses of infected individuals.

Snow’s classic study of the 1854 London cholera outbreak is often cited as an example of successful epidemiology. Applying geographic profiling to this case – using 321 disease sites to evaluate the location of 13 water pumps – ranked the source of the outbreak, the Broad Street pump, in the top 0.2% of the profile.

Now, a group led by Dr. Steve Le Comber, a senior lecturer in the School of Biological and Chemical Sciences at Queen Mary University of London, has shown that their geographic profiling model can help trace the source of malaria outbreaks.

Taking data from an outbreak of malaria in Cairo, they used the addresses of infected patients to locate the breeding sites of the mosquitoes that spread the disease.

The model was able to find the malaria mosquito breeding sites after searching only two thirds of the 300 km2 that the experts had to search to find the sites.

Dr. Le Comber further explains:

In fact our model found five of the seven sites after searching just 10.7 km2. 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.”

He and his team describe their model as “a new, rigorous mathematical and computational method” that combines the advantage of “Bayesian methods” traditionally used in biology and the “criminal geographic targeting (CGT) algorithm used in criminology.”

“We demonstrate that our method combines the advantages of both previous methods, particularly in cases featuring large data sets and multiple sources,” they note.

The model takes only minutes on a computer, making it a useful tool to have in the early stages of an outbreak, when control efforts are most likely to be effective in stopping the spread.

“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,” says Dr. Le Comber.

Meanwhile, Medical News Today recently reported on another study by a team at Imperial College London that has taken a step closer to eradicating malaria by finding a way to make malaria mosquitoes produce only male offspring.