aDepartment of Criminology and Justice, Loyola University New Orleans, New Orleans, LA, USA; bDepartment of Justice Studies, Lasell University, Newton, MA, USA

ABSTRACT This study examines the number and location of residential burglaries before and after a tornado that struck New Orleans, Louisiana in February 2017. Using calls for service to the New Orleans Police Department, Weather Service data and geospatial referencing, we found that the number of residential burglaries increased in the short-term aftermath of the tornado and that the increase in suitable targets caused by the tornado appears to be an important predictor of post-tornado burglary in that timeframe. We conclude with implications for policy and practice that stem from our !ndings.

ARTICLE HISTORY Received 21 April 2020 Accepted 9 June 2020

KEYWORDS Burglary; tornado; New Orleans; concentrated disadvantage; routine activities

Introduction

The study of disasters has long had its home in sociology (Dynes Dynes 1970; Dynes, De Marchi, and Pelanda 1987; Dynes and Tierney 1994; Fischer 2008; Mileti 1987; Quarantelli 1978, 1987; Rodriguez, Quarantelli, and Dynes 2007; Wenger 1987). Systematic disaster research beginning in the middle of the 20th century revealed post-disaster reactions characterized by altruism, cooperation, and ration- ality and not by antisocial or criminal behavior. In light of these empirical realities, theories of collective behavior were modi!ed to include focus on disruption of the existing social structure by a precipitating event such as a disaster and on norms and behaviors that emerge in the wake of such an event (Wenger 1987). These revisions had a dual e"ect: they provided a new framework for understanding behavior in disaster and they paved the way for the persistent claim that criminal behavior was a rarity in disaster. According to Dynes (1970), disasters do not create disorganization. Rather, they create organization in which the emergent norms support prosocial behavior. Barton (1969) called this the informal mass assault, which refers to the prosocial behavior that emerges in the wake of disaster to solve shared problems, such as tending to the injured and removal of the deceased, as part of the therapeutic community. Similarly, Drabek (1986) !nds that while disaster survivors do experience fear, they nevertheless act in a composed, rational, and adaptive way in the wake of disaster that includes providing assistance to other survivors. Moreover, the desire to help is not limited to survivors – those who are not directly impacted by a disaster have been observed going in droves to the a"ected area to provide relief.

A robust sociological literature !nds that looting is rare in the wake of disaster (Drabek 1986, 2010; Dynes and Quarantelli 1968a; Dynes 1968b, 1968c; Quarantelli and Dynes 1970; Quarantelli 1994, 2008; Quarantelli and Dynes 1970). The prevailing belief that looting inexorably follows disasters is presumed to be just one aspect of disaster mythology (Quarantelli 2008; Wenger et al. 1975); other mythical antisocial behaviors thought to accompany disasters are panic #ight (Johnson, Feinberg,

CONTACT Kelly Frailing [email protected] Department of Criminology and Justice, Box 55, Loyola University New Orleans, New Orleans, LA 70118, USA

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and Johnston 1994), mass hysteria (Stallings 1994), and price gouging (Fischer 2008). The over- arching conclusion of disaster sociology is that disasters engender a therapeutic community among survivors, which serves to minimize antisocial behavior, such as crime.

However, major disasters of the late 20th and early 21st centuries demanded a reexamination of these long-held conclusions drawn by disaster sociologists. Widespread looting in the wakes of Hurricanes Hugo (1989) and Katrina (2005) led some scholars to theorize that pre-disaster conditions, especially those related to social strati!cation and crime, were important in understanding why the behavioral response to these disasters was so di"erent from what had been previously observed, namely the emergence of a therapeutic community characterized by altruism and prosocial helping behavior (Akimoto 1987; Albala-Bertrand 1993; Barsky, Trainor, and Torres 2006; Brown 2012; Drabek 2010; Quarantelli 2006, 2007; Tierney, Bevc, and Kuligowski 2007). These two disasters in particular and the theorizing around them paved the way for disaster criminology, a new !eld that examines criminal and other antisocial behavior in the wake of disasters. Relying on the theories and methods of criminology, disaster criminologists have argued that property crime, interpersonal violence, and fraud increase in the wake of some disasters (Frailing and Harper 2017). Most of the empirical work on property crime, particularly burglary, in the wake of disaster so far has focused on Hurricane Katrina (Frailing and Harper 2007, 2010a, 2010b, 2015a; Frailing, Harper, and Serpas 2015b, Frailing and Harper 2016a), and !nds that certain social structural indicators, including population loss, high unemployment, low wages, family disruption, and a segregated school system are associated with increases in the burglary rate in the month after Katrina in New Orleans as compared to the month before. Empirical work focused on property crime and other disasters bears out similar conclusions (Leitner and Helbich 2011; Siman 1977; Teh 2008; Walker, Sim, and Keys-Mathews 2014; Yu et al. 2017; Zahnow et al. 2017; Zhou 1997, but see Breetzke, King, and Fabris-Rotelli 2018; Zahran et al. 2009).

Applicable theories for disaster criminology

Criminologists who study disaster (e.g., Frailing and Harper 2017) have typically applied two theories to understand crime in the wake of disaster, particularly residential burglary. The !rst of these is routine activity theory. Routine activity theory is part of the environmental criminology paradigm, which ‘is a family of theories that share a common interest in criminal events and the immediate circumstances in which they occur’ (Wortley and Mazerolle 2011, p. 1). Routine activity theory (Cohen and Felson 1979) holds that three elements – motivated o"enders, suitable targets, and the absence of capable guardianship, either formal or informal, must be present together in time and space for crime to occur. Disasters may create suitable targets, increase the number of motivated o"enders, and may diminish especially formal guardianship; they may also change people’s routine activities so that they become suitable targets in the presence of motivated o"enders and the absence of capable guardianship.

As noted above, disaster criminologists have also investigated the macro-level social structural indicators in the areas impacted by disaster. This is in line with the social disorganization theory, which holds that poverty, residential instability, and ethnic heterogeneity (Shaw and McKay 1942) as well as family disruption (Sampson 1986) are important neighborhood-level characteristics asso- ciated with crime in the area. Social disorganization theory has also taken into account the notion of concentrated disadvantage. Concentrated disadvantage is a concept aimed at capturing deprivation and is typically comprised of indicators such as poverty, unemployment, female-headed households, and receipt of public assistance. Research has shown concentrated disadvantage is important in predicting crime at the neighborhood level (Krivo and Peterson 1996; Sampson, Raudenbush, and Earls 1997; Wilson 1987).

The legitimacy of disaster criminology as a sub!eld is predicated on the continued testing of its propositions as laid out in Frailing and Harper (2017), namely that some crimes increase after a disaster and that these increases are in part predictable by criminological theory. Here, we examine

2 K. FRAILING ET AL.

burglary before and after the February 2017 tornado in New Orleans, Louisiana in order to test three of Frailing and Harper (2017) hypotheses. The !rst of these hypotheses is that concentrated disadvantage is associated with pre-disaster burglary. The second is that burglaries increase in the short-term aftermath of a disaster and then return to pre-disaster levels, and the third is that areas characterized by concentrated disadvantage will see the greatest increases in post-disaster burglary.

The New Orleans tornado

Though New Orleans is no stranger to hurricane impacts, tornados are relatively rare. However, despite this statistical pattern, on 7 February 2017 six tornados hit southeastern Louisiana and three hit the New Orleans metro area. The most serious of them was the tornado that hit New Orleans East in the morning at approximately 11:12 am. This EF-3 tornado lasted 20 minutes, had a maximum wind speed of 150 miles an hour, a width of 600 yards and a path length of 10.1 miles. It damaged 638 homes and 40 businesses, about half of which were considered total losses (NWS 2017a).

Pre-tornado burglary and concentrated disadvantage

New Orleans East is comprised of six neighborhoods, three of which, Plum Orchard, Read Boulevard East, and Read Boulevard West, were in the path of the tornado, whereas Pines Village, Little Woods, and West Lake Forest were not.

In order to determine the number of burglaries before and after the tornado, we utilized the New Orleans Police Department’s (NOPD’s) publicly available calls for service database, which includes the location of each call for service by latitude and longitude (NOPD 2017). We retrieved all the calls for service for residential burglaries in the NOPD’s Seventh District, which covers the three neighbor- hoods under investigation here, from 1 December 2016 to 30 April 2017. This timeframe allowed us to examine residential burglaries across all six neighborhoods as far as 2 months before and 2 months after the tornado.

As seen in Table 1, commonalities across the neighborhoods impacted by the tornado include population loss, majority African American population, an increase in percent female-headed house- hold, a decrease in average household income, and an increase in the percent of vacant properties. Importantly, Table 1 also includes characteristics associated with concentrated disadvantage.

We created a concentrated disadvantage measure for the 2015 data comprised three key vari- ables: (1) percent of vacant property, (2) percent female-headed households, and (3) percent Black. While these variables are a somewhat atypical construction of concentrated disadvantage, they loaded on a single factor with an Eigenvalue of 4.082 with a Cronbach’s alpha of.901, above the thresholds of 1 and .800, respectively. We then employed a negative binomial regression analysis to test the measure’s ability to predict pre-disaster burglary by neighborhood. Table 2 presents the results of the negative binomial regression (NBR) analysis for only those neighborhoods within the path of the tornado (Plum Orchard, Read Boulevard East, and Read Boulevard West) and for the time period of 2 months after the tornado. As shown, our measure of concentrated disadvantage was not a signi!cant predictor of burglary for these three neighborhoods. Similarly, Table 3 shows the results of the negative binomial regression for those neighborhoods that were not within the path of the tornado. Again, our measure of concentrated disadvantage was not a signi!cant predictor of burglaries for the two-month period following the tornado. Subsequent analyses (not shown) were conducted for the number of burglaries 1 week, 2 weeks, and 1 month before and after the date of the tornado. This included separate analyses for both clusters of neighborhoods (those impacted by the tornado and those not) and all neighborhoods together. Like our !rst two analyses, our measure of concentrated disadvantage was not a predictor of burglary counts.

We further explored the possibility of an association between concentrated disadvantage and number of burglaries by conducting bivariate correlations between counts for time periods and concentrated disadvantage. Table 4 presents the results for the association between the number of

JOURNAL OF CRIME AND JUSTICE 3

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4 K. FRAILING ET AL.

burglaries 2 months prior to the tornado and concentrated disadvantage and the number of burglaries 2 months after the tornado and concentrated disadvantage. There was no signi!cant association between concentrated disadvantage and the total number of burglaries in either time- frame. Subsequent analyses (not shown) were conducted for 2 weeks, 1 month, and 2 months before and after the tornado. Results for these analyses also indicated non-signi!cant associations between the number of burglaries and concentrated disadvantage.

Burglaries before and after the New Orleans tornado

As seen in Table 5, there was an overall increase in residential burglaries 1 week, 2 weeks, and 1 month after the tornado for the area in question. The increase in residential burglaries was not uniformly spread over neighborhoods, though. The Plum Orchard, Read Boulevard West, and Read Boulevard East neighborhoods, the three neighborhoods directly impacted by the tornado, saw an increase in residential burglaries at each of the time periods. Nor was the increase in residential burglaries uniformly spread over time. The increase in residential burglaries is largely con!ned to the !rst month after the tornado. By the 2-month mark, the number of residential burglaries had returned to (and even dipped slightly below) the pre-tornado number.

In order to determine where residential burglaries occurred before and after the tornado, we created dot maps showing the location of residential burglaries before and after the tornado using geospatial referencing in ArcMap. Included in each of these dot maps is the path of the tornado (NWS 2017b); inclusion of the path allowed us to investigate the association between the occurrence of the tornado and changes in residential burglary. Figures 1–4 show the location of residential burglaries 1 week, 2 weeks, 1 month, and 2 months before and after the tornado, as well as the path of the tornado itself. Plum Orchard appears to retain its pre-disaster burglary patterns after the tornado. However, residential burglaries concentrated around the path of the tornado in the Read Boulevard West and Read Boulevard East neighborhoods in particular beginning within the week after the tornado; this was a stark change from pre-tornado burglary patterns.

Table 2. NBR Predicting Burglary Counts for Neighborhoods in the Tornado Path.

Coe!cient Std. Error Z p

Intercept 4.477 1.883 2.378 0.017 Concentrated Disadvantage "0.054 0.044 "1.223 0.221

Source: The authors.

Table 3. NBR Predicting Burglary Counts for Neighborhoods outside of the Tornado Path.

Coe!cient Std. Error Z p

Intercept 26.26 14.49 1.812 0.070 Concentrated Disadvantage "0.481 0.296 "1.627 0.104

Source: The authors.

Table 4. Correlations Between Concentrated Disadvantage (CD) and Burglaries.

Two Months Before Two Months After CD 0.350 "0.006 p 0.4961 0.991

Source: The authors.

JOURNAL OF CRIME AND JUSTICE 5

Applying criminological theory

We believe the routine activity theory is potentially useful in helping to understand this change. Routine activity theory (Cohen and Felson 1979) holds that three elements – motivated o"enders, suitable targets, and the absence of capable guardianship, either formal or informal, must be present together in time and space for crime to occur. As the theory itself does, we put aside the notion of

Table 5. Number of Residential Burglaries Before and After the New Orleans Tornado by Neighborhood.

Before After Total Before Total After

Time Period One Week 8 23

Little Woods 7 4 Pines Village 0 2 West Lake Forest 0 1 Plum Orchard* 0 3 Read Blvd E* 0 4 Read Blvd W* 1 3

Two Weeks 17 34 Little Woods 10 13 Pines Village 2 2 West Lake Forest 0 1 Plum Orchard* 1 4 Read Blvd E* 1 5 Read Blvd W* 1 4

One Month 31 50 Little Woods 15 18 Pines Village 2 3 West Lake Forest 4 4 Plum Orchard* 2 4 Read Blvd E* 1 10 Read Blvd W* 2 5

Two Months 84 83 Little Woods 39 38 Pines Village 6 5 West Lake Forest 17 7 Plum Orchard* 4 9 Read Blvd E* 4 12 Read Blvd W* 4 5

* indicates a neighborhood directly impacted by the tornado. Source: Adapted from NOPD (2017).

Figure 1. Tornado Path Burglaries One Week Before and After. Source: The authors.

6 K. FRAILING ET AL.

motivated o"enders and focus on target suitability and capable guardianship to explain the !ndings in the Read Boulevard neighborhoods. The tornado may have created a number of suitable targets – as noted above, over 600 homes were damaged by the tornado – and the usual guardianship that prevents homes from being suitable targets for burglary, namely, the presence of their residents, was presumably absent in the wake of the tornado, especially for those homes that sustained great or total damage, which as noted above was about half of the impacted structures. In other words, the tornado may have increased the number of suitable targets and decreased the capable guardianship of those targets, facilitating an increase in burglary in those neighborhoods especially.

Discussion

Our !ndings do not provide support for the !rst hypothesis that concentrated disadvantage would be associated with pre-disaster burglary. This may be because there is relatively little variation among the three neighborhoods of interest in terms of characteristics that comprised the concen- trated disadvantage index. The neighborhoods are too similar on these characteristics for any of them to show an impact on burglary. We did !nd support for the second hypothesis that residential

Figure 2. Tornado Path Burglaries Two Weeks Before and After. Source: The authors.

Figure 3. Tornado Path Burglaries One Month Before and After. Source: The authors.

JOURNAL OF CRIME AND JUSTICE 7

burglaries would increase in the immediate aftermath of the tornado, then return to pre-disaster levels. This !nding is inconsistent with conclusions drawn by disaster sociologists, which as seen above, tend to reveal the emergence of a therapeutic community that serves to keep antisocial behavior low. These !ndings are very likely due to the timeframe of the study and the methodolo- gical techniques used for measuring crime; as Frailing and Harper (2017) argue, the criminological approach is preferred when determining the type and extent of antisocial behavior after a disaster.

We did not !nd support for our third hypothesis that indicators of concentrated disadvantage would explain post-disaster burglary. Here, and in conjunction with better understanding the temporary increase in post-disaster burglary, it is useful to draw on routine activity theory as described above. It is presumable that the tornado created suitable targets and facilitated the absence of capable guardianship in the Read Boulevard neighborhoods in particular. The otherwise rare burglary neighborhoods of Read Boulevard West and especially Read Boulevard East experi- enced an increase in residential burglaries that were concentrated near the path of the tornado. In fact, these two neighborhoods largely drove the post-disaster increase in residential burglary in New Orleans East as a whole for the !rst 2 months and especially the !rst month after the disaster. In a quite meaningful sense, these two neighborhoods could be considered ‘hot spots,’ areas where crime regularly and predictably occurs. (Sherman, Gartin, and Buerger 1989).

Limitations

Like any study, this one is not without limitations. Probably the most important of these is the nature of our data. Calls for service only represent those incidents reported to the police. It could be that there were more residential burglaries than are re#ected in the calls for service. It could also be that calls for service for residential burglaries, particularly those in the short-term wake of the tornado, were actually losses due to the tornado itself. Moreover, it is important to note that the number of burglaries in the timeframe is relatively low, which means that changes could be due to chance, and the timeframe itself may be too short to account for longer term variations in burglary that could be independent of the tornado. In other words, relying on calls for service data to determine the number, timing, and location of residential burglaries before and after a disaster is imperfect at best. Nevertheless, we can presume enough accuracy in these data to draw the aforementioned conclusions, at least tentatively.

Another important limitation is our designation of the variables that indicate concentrated disadvantage. It could be the case that our selected indicators, namely poverty, female-headed households, and renting, do not fully capture the e"ects of concentrated disadvantage and therefore

Figure 4. Tornado Path Burglaries Two Months Before and After. Source: The authors.

8 K. FRAILING ET AL.

do not permit the e"ects of concentrated disadvantage on pre- or post-disaster burglary (if any) to be observed. It could also be the case that the indicators from 2015 are too dated to reveal the e"ects of concentrated disadvantage in 2017. Moreover, examining these indicators at the census tract level rather than the block level, which we were unable to do, may have obscured the e"ects (if any) of concentrated disadvantage on burglary. While we believe our selected indicators are valid and thorough, we nevertheless acknowledge these potential shortcomings.

Finally, it could be the case that either target suitability or the absence of capable guardianship is far more important than the other in determining where post-disaster burglaries will occur. We simply do not have enough information on the extent of the damage to each of the 84 burglarized residences out of the over 600 that were damaged to determine whether the residence was a suitable target but ostensibly had capable guardianship (i.e., residents were still able to live there), or whether both elements of routine activity theory were in play. Moreover, we do not have information about target suitability or capable guardianship within the neighborhoods in this study that preceded the tornado and how the tornado impacted them, if at all. We believe we have su$cient evidence to presume that both suitable targets and the absence of capable guardianship are important in understanding post- disaster burglary, but acknowledge that this presumption may be incomplete.

Conclusion

As noted, the legitimacy of disaster criminology as a discipline hinges on empirical tests like the one described here. We believe our !ndings mostly support the contentions disaster criminologists have laid out (i.e., Frailing and Harper 2017), and have potentially useful policy and practice implications. For example, disaster response plans for local law enforcement should include the provision of guardianship in disaster-stricken areas, particularly those where typical informal guardianship is temporarily unavailable as a result of the disaster. Importantly, the guardianship provided by law enforcement should last well into the post-disaster period (Frailing and Harper 2016b). Of course, due to the dynamic nature of disasters and the damage they cause, law enforcement may be consumed with search and rescue operations and unable to provide formal guardianship, especially in the immediate aftermath of a disaster (Harper 2016). One way to supplement the guardianship provided by law enforcement is with clearly marked and weather-resistant crime cameras, such as those recently installed throughout New Orleans. Through their ubiquity, these cameras are designed to deter crime, including post-disaster crime (Stein 2018; La Vigne et al. 2011).

Finally, we believe further and more nuanced investigations similar to this one are important so that the circumstances, both those that precede and those that follow disasters, which facilitate crime can be better understood so that disaster crime can be reduced or even prevented.

Disclosure statement

No potential con#ict of interest was reported by the authors.

Notes on contributors

Kelly Frailing earned her doctorate in Criminology from the University of Cambridge and is currently an Associate Professor and Graduate Program Coordinator in the Department of Criminology and Justice at Loyola University New Orleans. She is the coeditor of Criminalization of Mental Illness: A Reader, and of all three editions of Crime and Criminal Justice in Disaster. She is the coauthor of both editions of Fundamentals of Criminology: New Dimensions and of Toward a Criminology of Disaster: What We Know and What We Need to Find Out.

Thomas Zawisza is an assistant professor at Lasell University. His main research interests include using eye-tracking technology as a medium to study burglar target selection, investigating distance and direction of crime and victimiza- tion, and how non-disastrous natural phenomenon a"ects crime patterns. His most recent works appeared in the

JOURNAL OF CRIME AND JUSTICE 9

Journal of Police and Criminal Psychology, Crime Prevention and Community Safety, and in the Journal of Contemporary Criminology.

Dee Wood Harper, Jr. (Ph.D., LSU, 1967) Emeritus Professor of Sociology, Criminology and Justice at Loyola University, New Orleans has published extensively on the problem of crime and disaster since Hurricane Katrina. Beginning with a session at the Southern Sociological Society meetings in New Orleans in the Spring of 2006 on crime and policing during Katrina, a chapter in The Sociology of Katrina through three editions of Crime and Criminal Justice in Disaster, and more recently, Toward a Criminology of Disaster. Currently, we (with Kelly Frailing) are laying the groundwork for testing theories focusing on fraud and other criminal behavior linked to the COVID-19 Pandemic in the United States.

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