Using Newark, New Jersey, as a pilot case, researchers successfully applied public health tracking methods to the city’s 2,366 homicides between 1982 and 2008 and found the killings weren’t randomly located but instead followed a pattern, evolving from the city’s center and moving southward and westward over time.
Like a flu bug that spreads to susceptible groups such as children and the elderly, homicide clusters in Newark—often fueled by gangs and guns—spread to areas consisting largely of poor and minority residents. Over time, the concentration of homicides effectively disappeared from one area and settled in another.
“By using the principles of infectious disease control, we may be able to predict the spread of homicide and reduce the incidence of this crime,” says April Zeoli, public health researcher in the School of Criminal Justice at Michigan State University.
Published in the journal Justice Quarterly, the study is one of the first to use analytic software from the field of medical geography to track long-term homicide trends. The method can be done in real time which would allow police to identify emerging hotspots, Zeoli says.
The researchers also identified areas of Newark that had no homicide clusters during the 26-year time frame of the study, despite being surrounded by deadly violence.
“If we could discover why some of those communities are resistant,” Zeoli says, “we could work on increasing the resistance of our communities that are more susceptible to homicide.”
Criminal justice researchers Jesenia Pizarro and Christopher Melde and medical geographer Sue Grady contributed to the study.
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