Punjab Police City Division: Strategic Planning Document for Crime Control Institute of Development and Economic Alternatives (IDEAS) City Division, Lahore

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0. Introduction The purpose of this strategic planning document is to provide evidence on the level, nature and distribution of crime in Lahore Police’s City Division. The document will be used by the SP’s office in its effort to devise effective crime control strategies and plan an optimal deployment of crime prevention resources in collaboration with SHOs of the division and crime prevention squads assigned to the division. The evidence is based on 21 months (1 Jan 2013- 1st October 2014) of geo- coded reported crime (FIR) data that has been collated through collaboration between the office of DIG investigation Lahore, Punjab Information Technology Board (PITB), IDEAS and the Technology for People Initiative (TPI) at the Lahore University of Management Sciences. Section 1 provides a background of the police station and beat structure in the division. Section 2 provides evidence on the distribution of crime across police stations for both crimes against property and person. It also provides evidence on the type of reported crime that dominates the Division. It also identifies the high crime police stations in the division. Section 3 assesses the case for targeted prevention below the police station level. It does this by providing evidence on the concentration of reported crime across localities (an area of approx. of 0.25km sq) in the Division. It also documents how stable the pattern of crime concentration has been at this level. Section 4 identifies the specific place-based features of localities that cause them to be high crime.Section 5 looks at the chronic and recently active localities as well the temporal distribution of crime in the highest crime localities. The last section summarizes the main recommendations. 1. Overview of City Division City division is located in the north-west region of Lahore and covers most of the old-city area. It comprises of 22 police stations and approximately 119 beats. Figure 1 shows the mapping of beats and police stations in the division and Table A1 (appendix A) shows the number of beats in the Police stations of the division.

Figure 1: Police Station and Beats in City Division

City division experienced a total of 3469 crimes against property (burglary/theft, dacoity, motorcycle theft, other vehicle theft, robbery and vehicle snatching) and 1064 crimes against person (murder, attempted murder, hurt and kidnapping for ransom) between 1st January 2013 and 1st October 2014. Figure 2 shows that compared to the other divisions in terms of crime against property, City is one of the low crime divisions and accounts for around 13% of total crime against property in Lahore.

Figure 2: Division Level Crime against Property Incidents

In terms of crime against person, however, it is the second highest crime division and accounts for 24% of all crimes against person and 20% of all homicides (Figures 3 and 4). Figure 3: Division Level Crime against Person Incidents

Figure 4: Divisional Level Homicide Incidents

Although the level of crime against property in the Division has been much lower than the Lahore average there was a sharp rise in the monthly trend of crime against property in the City Division in August 2013 (Figure 5). This sharp rise followed a secular decline between January and July 2013 and has remained stable since then. Crime against person has remained higher in the Division compared to the Lahore average – however homicide rates have been fairly similar to the Lahore average. This suggests that non-homicide crimes against person are higher in City Division compared to the rest of Lahore.

Figure 5: Monthly Trajectory of Property, Person and Homicide Crime: City Division Compared to the Lahore Average

Figure 6 shows that the distribution of crime in the Division is dominated by street crime, in particular motor vehicle theft, robbery and burglary. Therefore, preventing street crime has to be an important objective of the crime prevention plan in the City Division. The two main challenges for the Division are to: (a) Devise strategies to lower the relatively higher levels of crime against person (b) Bring the crime against property rates down to the pre-August 2013 levels.

Figure 6: City Division – Distribution of Crime by Category

City Division - Distribution Across Crime Categories 40

33.27 30

22.57

20 16.57 percent

10.00

10 6.16

2.66 2.93 0.57 1.37 0

Dacoity Kidnapping for Ransom Vehicle Snatching Murder Hurt Other Theft Burglary Robbery MotorVehicle Theft

Source: Geo-located FIR data (Jan 2013 - Oct 2014)

2. Patterns at the Police Station Levels This section looks at the degree of variation in crime against property and person in the City division at the police station level. Figures 7 and 8 show that both crimes against property and person are highly concentrated in a few divisional police stations. The top two police stations, Islampura and Shahdara, account for 37% of the reported crime against property incidents during the period under analysis (Figure 7). Similarly the top 5 police stations1 account for approximately 60% of the reported crime against property incidents. The extent of concentration is put into perspective by the finding that the bottom 10 police stations account for only 13% of the crime against property incidents.

1 The top five police stations in terms of crime against property are Islampura, Shahdara, Shahdara Town, Shadbagh and Shafiqabad.

Figure 7: Distribution of Crime Against Property across Police Stations

We find a similar pattern in terms of crime against person (Figure 8). The top two police stations, Shahdara and Shahdara town, account for approximately 30% of the reported crime. The top five2 police stations account for 55% of the reported crime against person incidents.

2 The top five police stations in terms of crime against person are Shahdara, Shahdara Town, Islampura, Shafiqabad and Badami Bagh.

Figure 8: Distribution of Crime Against Person Across Police Stations

The same pattern holds for homicide with Shahdara and Shahdara Town accounting for 30% of total homicides incidents in the division. We find that the top 53 police stations account for 54% of homicide incidents (Figure 9).

3 The top five police stations in terms of homicide are Shahdara, Shahdara Town, Shadbagh, Shafiqabad and Misri Shah.

Figure 9: Distribution of Homicide Incidents Across Police Stations

We also find that the concentration of crime has been stable over time.In fact, there has been considerable divergence in monthly crime against property trends since July 2013 between the top five police stations and stations that fall in the lower percentiles in terms of crime incidence (Figure 10). The monthly crime incidence in the top 5 police stations has become almost three times higher than the incidence in the remaining divisional police stations post-July 2013.

Figure 10: Trend in Crimes Against Person and Property at the Police Station Level

Differences in the total crime incidence between the top two police stations and others remain once we have accounted for the variation in the strength of the operations staff deployed across police stations. Figure 11 plots the total crime incidence per operations police officers (the numbers relate to operations upper staff, which includes ASIs, SIs and Inspectors) for all divisional police stations. We find that total crime per officer is significantly higher in Islampura and Shahdara.

Figure 11: Crime Against Property and Person per IO (operations)

This is largely because the staff strength in these stations is not commensurate with the degree of crime in these two stations. This can be ascertained from Figure 12 that plots the operations officer strength in the division against total crime incidents at the police station level. As expected we find a positive correlation between officer strength and crime incidents, which suggests that high crime police stations have greater officer deployment. However, the two outliers that standout are Islampura and Shahdara, where the deployment is not commensurate with the incident to officer ratio that is being maintained in the division. Increasing the police strength in these stations is one strategy that the division may consider.

Figure 12: Police Strength and Crime Incidents in the Division

This analysis reveals considerable concentration of both crimes against person and property at the police station level with this concentration worsening over time. The police stations that stand out are Islampura, Shahdara, Shahdara Town, Shadbagh and Shafiqabad. However, the next section shows that there are clear dividends associated with analyzing the concentration of crime at a more granular level. Analysis at this level of granularity provides richer information in terms of planning for targeted crime prevention.

3. High crime “localities” and clusters – evidence for ‘hot spot’ policing For the purpose of our analysis we define a “locality” as a 0.5km by 0.5 km grid overlaid on city division. Since each grid is of the same size, it controls for any differences in crime levels due to a larger area/population. There are a total of 335 “localities” in City Division. Figure 13a/b below shows the level of concentration in these grids for crimes against property and crimes against person.

Figure 13a: Level of Concentration at the grid level for crimes against property:

Crime against property distribution across grids 25 22.51 20 15

11.99 10 Percent Grids

4.39 5

2.05 0

15 percent of crime 25 percent of crime 50 percent of crime 75 percent of crime

Source: Geo-coded data (Jan 2013 - Oct 2014)

Figure 13b: Level of Concentration at the grid level for crimes against person:

Crime against person distribution across grids 21.64 20

15 13.74 10 Percent Grids

5 4.09

2.05 0

15 percent of crime 25 percent of crime 50 percent of crime 75 percent of crime

Source: Geo-coded data (Jan 2013 - Oct 2014)

As we can see, there is a very high level of concentration for both property and person crimes - approx. 12% of localities (40 localities) account for 50% of all crimes against property in the division and 14% of localities (47 localities) account for 50% of all crime against person in the division. Out of the total 335 localities, 212 are non-zero crime localities. In order to assess the level and stability of crime incidents in these localities, we have categorized the non-zero crime localities as follows: highest crime localities (top 10% - 23 grids), high crime localities (60th- 90th percentile), medium crime (30th -60th percentile), and low crime localities (below 30th percentile). The tables suggest that the highest crime localities both in terms of crimes against property and against person account for a major proportion of total crime happening in the division. The highest and high crime localities combined account for almost three fourths of total crime. Figure 14 shows that the highest crime localities remain high crime over the two year period, apart from the dip in June/July 2013. This suggests that the highest crime localities have a ‘chronic’ crime problem. We will further analyze the chronic nature of these localities in the next section.

Table 3: Crimes Against Property and Person at the Level of Localities

Average Crimes Total Crimes Against Against Property Total Property and and Person % Total Crime Against Property Category Localities Person Incidents and Person Incidents Incidents per locality Highest Crime (top 21 1363 64.9 29% 21)

High Crime (next 47) 47 1656 35.2 35%

Medium Crime 71 1241 17.5 26% (middle 71)

Low Crime (bottom 73 319 4.4 7% 73)

Table 4: Crimes Against Property at the Locality Level:

Average Crimes Total Crimes Against Against Property Total Property Incidents % Total Crime Against Property Category Localities Incidents per locality Incidents Highest Crime (top 19 1245 59.3 26% 19)

High Crime (next 46) 46 1690 35.2 36%

Medium Crime 68 1259 17.5 18% (middle 68)

Low Crime (bottom 66 368 4.4 5% 66)

Table 5: Crimes Against Person at the Locality Level:

Average Crimes Total Crimes Against Against Person Person Total Incidents Incidents % Total Crime Against Person Category Localities per locality Incidents Highest Crime (top 20 1008 50.4 21.3% 20)

High Crime (next 47) 47 1582 33.7 33.5%

Medium Crime 51 1151 22.5 24.3% (middle 51)

Low Crime (bottom 74 775 10.5 16.4% 74)

Figure 14: Crime Against Property and Person Trajectory

Monthly trend in Crime Against Property and Person 4 3 2 1 Crime Against Property 0

Jul 13 Jul 14 Jan 13Feb 13Mar 13Apr 13May 13Jun 13 Aug 13Sep 13Oct 13Nov 13Dec 13Jan 14Feb 14Mar 14Apr 14May 14Jun 14 Aug 14Sep 14 month

Highest crime localities High Crime localities Medium Crime localities Low Crime localities

Source: Geo- coded data (1 Jan 2013 - 1 Oct 2014)

4. What causes crime to cluster in the high and highest crime localities? Place-based correlates of crime In criminology literature, a lot of emphasis is placed on the importance of ‘place-based’ correlates of crime. For our analysis we look at “crime generators” – landmarks4 such as banks, market places, parks, educational institutions, hospitals, and government buildings. Figure 15 below shows the distribution of these landmarks across the locality categories. We can see that most of these landmarks are found in the highest and high crime localities. This is especially true for banks and parks. This suggests a positive correlation between these landmarks and crime.

4 The landmarks data was obtained from the Technology of People Initiative (TPI)

Figure 15:

Place-Based Correlates of Crime By Category 4 3 2 1 Mean Landmarks Mean 0

High Crime Low Crime Highest Crime Medium Crime

Banks Parks Educational Institutions Markets Government Offices Hospitals

Source: Geo-located FIR data (Jan 2013 - Oct 2014)

To assess the robustness of this descriptive result, we do a more rigorous analysis. We analyze the correlation between the minimum distance from the center of a locality to a landmark and the number of crimes occurring in that locality. The hypothesis here is that the closer the landmark is to the center of the locality, the higher the number of crimes occurring in that locality - thus a negative relation between the distance to a locality and crime occurrence. The results suggest that crime is highly correlated with the landmarks specifically with roads, parks and banks. Motor vehicle theft and robberies mainly take place outside parks and banks and all types of property crimes take place around roads. Crimes against person tend to cluster around markets and roads5. These findings suggest that crime happens more around public places and commercial areas as compared to residential areas. This could be due to the mobile nature of the population in these areas that make these areas easier targets. Roads may be affected more by crime dues to easier escape routes for criminals.

5 These results are gauged from regression analysis.

5. Where should Policing efforts be concentrated? Identifying Chronic and Recently Active Localities and Temporal Patterns of Crime

5.1 Chronic and Recently Active Localities The purpose of this section is to identify highest and high crimes localities that show a chronic criminogenic tendency or have a repeated propensity for crime incidents to occur over time. We also identify localities that have been recently active in terms of reported crime incidence. For the purpose of this analysis we use the following definitions: 1) Chronic localities: The international literature defines a high crime area to be chronic if it is active (i.e. has at least one crime incident occurring per month) in terms of crime incidence for at least 8.5 months in one year (Gorr and Lee 2012). Ion our case, we consider localities to be chronic if they are active for at least 16 of the 22 months we have data on.

2) Recently active localities: These are localities that have been active (i.e. have at least one crime incident occurring per month) during the last three months of the period of analysis.

Table 4 shows that 19 out of 21 highest crime localities are chronic in terms of the above definition. That is, these are locations in which at least one crime incident has occurred in 16 months during the period 1st January 2013-1st October 2014. Furthermore, all of these chronic highest crime localities have been recently active. These are clearly localities in which crime has been occurring repeatedly. Identifying strategies that can reduce crime in these localities promises high dividends for the Division. The list and maps of the chronic highest crime localities as well as the list of chronic high crime localities that have been recently active are given in the appendix in order to support the crime prevention planning exercise.

Table 6: Chronic and Recently Active Localities in the Division

Category Total Total chronic Total chronic Total localities with localities (Not more localities with recent recent activity (last than 3.5 out activity three months have at of 12 months least 1 crime occurring have zero in them) crimes) Highest Crime 21 19 18 18 localities (top 21) High Crime 47 27 23 23 localities (Next 47)

5.2. Temporal Analysis of Crime For better police resource allocation, we have analyzed the levels of crime in the recently active highest crime localities. This analysis tells us which days of the week and times of the day crime- levels peak in these problem areas. Figures 16 A – H show the distribution of the different types of crime over the week. Overall, crime levels tend to peak in the start of the week and then on Saturday (figure 16 A). If we look at property crimes (figure 16B) we see a similar pattern but for crimes against person, especially attempted murder rates (figure 16 C-E) we see that crime levels peak during the middle of the week. Burglary/theft and Motor vehicle theft is more evenly distributed over the week. However, robbery/dacoity is seen to peak on the weekend (figure 16 H). Figure 16 A: Crimes Against Property and Person

Figure 16 B: Crimes Against Property

Figure 16 C: Crimes Against Person

Figure 16 D: Attempted Murder

Figure 16 E: Homicide

Figure 16 F: Burglary/Theft

Figure 16 G: Motor Vehicle Theft

Figure 16H: Robbery / Dacoity

If we look at the temporal pattern over time, we see that overall crime peaks in the latter half of the day i.e. between 12pm-11pm (Figure 17A). Both crimes against person and property follow a similar pattern (figures 17B-H). In all categories crime levels seem to peak around noon.

Figure 17A: Crimes Against Property and Person

Figure 17 B: Crimes Against Property

Figure 17 C: Crimes Against Person

Figure 17 D: Attempted Murder

Figure 17 E: Homicide

Figure 17 F: Burglary

Figure 17 G: Motor Vehicle Theft

Figure 17 G: Robbery/ Dacoity

6. Main Recommendations The main recommendations based on the evidence presented in this document are: 1) The two main challenges for the Division are to devise strategies to lower the relatively high levels of crime against person and to bring the crime against property rates down to the pre- August 2013 levels.

2) Analysis reveals considerable concentration of both crime against person and property at the police station level. The police stations that stand out are Islampura, Shahdara, Shahdara Town. Shadbagh and Shafiqabad. Increasing police deployment between Police stations is a strategy that the Division may consider.

3) In spite of the evidence of concentration at the Police Station level we recommend a targeted crime prevention approach at the locality level. This is because there is a high level of concentration of crime at this level – 12% of localities account for 50% of total crimes against property in the division. We also find that the concentration of crime at the locality level has shown a fairly stable trajectory over time. Therefore, we strongly recommend that the targeted locality level crime prevention approach focuses on the top highest crime localities in terms of reported crime incidence (Appendix provides a list of these locations).

4) We also find that crime is highly correlated with banks and roads and this correlation is robust to controlling for population and total number of landmarks in the locality. We recommend that a situational policing strategy is adopted where each of the localities is observed to see what structural features are resulting in crime being clustered in those areas. The scanning and problem-solving is important here to identify what strategies will work in which areas, keeping in view the specific place structures.

Appendix A

Table A1: List of Highest and High Crime Localities

PoliceStation Locality Total Crime Total Crime Against Property Against Person (Jan 2013 - Oct (Jan 2013 - Oct 2014) 2014) Data Darbar Data Darbar 40 48 Gowalmandi Meo hospital 67 73 Islampura Islampura 69 84 Naulakha Naulakha 40 52 Islampura Akhary buss stop 117 137 Shadbagh Shadbagh 47 54 Shahdara Ferozewala kchery GT road 45 52 Islampura Islampura 52 58 Shadbagh Shadbagh 41 49 New Anarkali Urdu bazar 40 56 Islampura Islampura 55 60 New Anarkali Fiaz road 46 55 Mochi Gate Shah alam market 51 63 Akbari Gate Mochi bagh ground 42 52 Shadbagh Shadbagh 53 58 Lower Mall Kacha rashid road 41 44 Islampura National park 55 64 Shahdara Mian Wazeer park 52 60 Islampura Near Baba ground 64 74 New Anarkali New Anarkali 71 94 Islampura Islampura 41 46 Shahdara Shahdara 43 51 Akbari Gate Akbari Gate 23 33 Lorry Adda Auto market 22 26 Rang Mahal Ainak Mahal Building 24 33 Shahdara Town Shahdara Town 22 29 Misri Shah Bilal Road 17 19 Shafiqabad Shafiqabad 35 43 Misri Shah Misri Shah 27 35 Naulakha Naulakha 30 36 Tibbi City Tibbi City 27 39 Shafiqabad Shafiqabad 28 39 Shahdara KPS school streete Miraj park 28 39 Shafiqabad Shafiqabad 17 26 Sanda National Town 33 37 Naulakha Naulakha 22 28 Masti Gate Masti Gate 26 31 Shahdara Shahdara 38 51 Data Darbar Bilal ganj bery wala chok 36 46 Misri Shah Misri Shah 23 27 Shadbagh Shadbagh 18 20

Gujjar Pura Koat Khawaja Saeed 15 19 Naulakha Naulakha 27 30 Misri Shah Misri Shah 15 18 Shadbagh Shadbagh 20 24 Misri Shah Aziz road 26 35 Shadbagh Shadbagh 19 24 Gowalmandi Gowalmandi 23 30 Old Anarkali Kapoor Thala House 26 28 Bhati Gate Bhati Gate 22 35 Ravi Road Ravi Road 17 24 Misri Shah Misri Shah 26 28 Shafiqabad Shafiqabad 23 30 Shahdara Shahdara 17 22 Shafiqabad Shafiqabad 30 47 Naulakha Naulakha 20 26 Islampura Islampura 30 34 Ravi Road Ravi Road 32 35 Shahdara - 19 22 Shahdara - 21 26 Islampura Islampura 33 46 Shafiqabad Mali pura Petrol Pump Band Road 15 21 Gowalmandi Gowalmandi 30 45 Ravi Road Sabzi mandi Ravi road 21 32 Badami Bagh Badami Bagh 17 22 Islampura - 38 43 Shafiqabad Shafiqabad 37 46 Islampura Islampura 33 40 Shahdara Shahdara 15 16 Lower Mall Lower Mall 31 33 Shadbagh Shadbagh 21 24 Misri Shah Misri Shah 23 25 Shahdara Town Paracha Colony 23 28 Shafiqabad Shafiqabad 16 21 Shahdara Shahdara 30 40 Shafiqabad Amin park 30 39 Shahdara Machis factory ground 28 38 Shahdara Shahdara 21 23 Tibbi City Tibbi City 28 35 Lower Mall Lower Mall 29 36

Table A2: Recently Active Highest Crime Localities