How mapping America's "firearm ecosystem" could help lead to gun violence solutions
On April 16, 2007, about a year after Maurizio Porfiri moved to New York City to start his career as an engineering professor at New York University, one of his undergraduate students rushed into his office, desperate, saying, "Professor I'm really sorry."
At first, he didn't know what was going on, but then Porfiri saw on the news there had been a mass shooting at Norris Hall, Virginia Tech's engineering science and mechanics building, where he had received his doctorate and spent seven years studying in the department.
"I started calling people, but no one would reply. It was a disaster," Porfiri told CBS News. Porfiri was a teaching assistant for Liviu Librescu, the engineering professor who blocked the door to his classroom to allow students to escape out the window. Another of the professors in his Ph.D. committee was also among the 32 people killed that day, as were other colleagues and classmates who helped Porfiri become who he is "personally and professionally," he said.
After the mass shooting, it took Porfiri some time to figure out how to make sense of how he could help. "I couldn't imagine that I could do something meaningful," he recalled.
He found that the data and evidence in gun violence research mostly didn't utilize robust mathematical equations, Porifi said, so he decided to "see if we could use engineering techniques to bring insight into gun violence to help policymakers make good decisions informed by scientific evidence."
In 2020, the Italian native became the first researcher to receive a $2 million federal grant from the National Science Foundation earmarked specifically for gun-related research.
This week he published research on how "fame-seeking" mass shooters choose their locations. He has also published research on why gun owners purchase firearms after a mass shooting and statistical models for predicting monthly U.S. gun homicides.
Porfiri spoke to CBS News about the strides his engineering team at New York University has made in understanding gun violence, how engineering and mathematical equations can provide insights into gun violence, and what it means to map America's "firearm ecosystem."
CBS: What is different about your approach to finding solutions to gun violence?
Porfiri: It's the mathematical approach. Research in gun violence tends to be underfunded, so the field is not going to attract researchers from other fields that can attract innovation.
In gun violence, the level of engineering sophistication is not the same as that you find in other public health areas. I've seen gun violence research that takes different approaches but there are few mathematical approaches that are robust enough to take nuances into consideration.
So that's where I do believe there is a chance of making a big impact.
CBS: And how do you do that?
Porfiri: In one research project, we created mathematical models that can help a policymaker predict gun homicides, help them make decisions and understand violence better. Official gun data from the CDC has a very, very big delay. Typically a policymaker receives correct information between one to two years after the incident. So if you think of making some policymaking interventions, you are dealing with a data set that is one to two years old.
And things change very rapidly.
As a policymaker, I don't have many tools to make decisions that can help my community with an old data set. We build tools that can sort through and understand many different pieces of information; including Twitter, background checks, and Google Trends.
So policymakers don't have to wait two years. The data can tell you right away what's happening today, and what happened last year.
CBS: Can you solve gun violence with mathematical equations?
Porfiri: One of my research projects started when I attended a meeting that brought together experts from the FBI, psychologists, criminologists, etc. It was super interesting but it tended to be focused on cases, and what made this case special. If you go too deep on a single case it's difficult then to abstract it back again, because all the cases are different. The focus on cases doesn't allow researchers to then make sense of what the underlying behavior is. Because we have the ability to run these mathematical equations, we can provide information that shows patterns.
On the other side of the spectrum, there is machine learning and big data that may have too much of a comprehensive view; these equations may be missing underlying information and may end up providing recommendations that enforce the status quo.
We try to do something in between and base the mathematical equations based on an individual level. That is the space we occupy in our research.
What we can do is provide scientifically backed information for policymakers to act. That we can do. We try to make all of our data open-source so everyone can use it — with some exceptions. We don't publish the mass shooting database so as not to encourage more violence.
CBS: So how do you map America's "firearm ecosystem"?
Porfiri: Basically, the way we see the "firearm ecosystem" is a combination of different layers, that includes individual behavior, state-level behavior and the national level. We have to understand how policies shape individual behavior and then overall how these interactions define where we stand as a country.
So we try to understand what are the implication of individual choices on the legal system within a particular state. How states interact with each other from a legal point of view, in terms of adopting policies or removing the policy — understanding how these policies shape individual behavior. And then overall, how all these interactions define where we stand as a country, as the U.S., with respect to prevalence [of gun] violence.
CBS: What do we need to understand about these layers?
Porfiri: We are trying to address questions on the individual decision-making of people. What are the drivers? What is behind the decision-making and behavior of a mass shooter?
At the state level, we are trying to understand what laws are successful in reducing violence. We are trying to understand how states interact with respect to each other with respect to the legal environment. So for example, if state number one adopts a new policy, will that policy diffuse to other states? If so, why and when?
We have a lot of insights at different levels and we need to patch them together, but we are not there yet. There are a lot of gaps to fill even at the basic data-collection level. And that makes it very hard for us to then do quantitative work that can be translated into statistics and information that another person who is a policymaker can act upon.
We have many different threads we are following to help understand how the ecosystem connects — for example, tracing how people buy guns depending on their location and understanding the role of peer pressure when people buy guns. We are trying to build connections with cities to see if we can contribute ways to track illegal guns. We are running all the studies — individual, state and national now, separately — but we need to find ways to relate individual behavior to the state and then to the national level, but that we don't have yet.
CBS: Tell us about some of your research findings. You've done a number of studies; what stands out?
Porfiri: We looked at the number of mass shootings associated with firearm sales. But when we studied this idea we determined no association between mass shootings and gun purchases due to fear or instinct for protection.
So we started to look at other phenomena, and we collected data on media coverage of gun regulation and discovered a strong causality: People actually buy guns because after a mass shooting there is media coverage about potentially regulating guns. They may feel that their ability to purchase a gun can be curtailed and so gun sales go up.
So what we previously thought was the answer, actually wasn't true. When researchers apply something more mathematically robust, you can get a different answer. The story is entirely different.
Editor's note: This interview has been edited and condensed for clarity.