An in-depth analysis of the Victims of Crime Survey data collected in 2015/16 and data from the South African Police Services (SAPS).

1. Victims of Crime 2015/16
Thematic Report
Towards achieving the NDP goal of eliminating crime by 2030
Presented by:
Dr Pali Lehohla, Statistician-General
Statistics South Africa

2. Why do we need crime statistics?
Safety NDP and MTSF Statistics
Crime creates anxiety in
society and this has a negative
effect on the quality of life and
economic development.
Its reduction is therefore a
priority on the national agenda
Chapter 12 of the National
Development Plan lists crime
reduction as a strategic priority.
The NDP envisions that people
living in South Africa should have
no fear of crime
One of the broad strategic
outcomes of the MTSF (2014-
2019) is:
“All People in South Africa are,
and feel safe”
In order to achieve the national
strategic outcomes on crime, it is
important to measure the levels,
trends and patterns of crime and
victimisation in SA
The South African Police Service
and VOCS data provide
complementary official sources of
crime statistics in SA

3. About the survey
The Victims of Crime Survey (VOCS) is a household-based survey that
examines crime from the point of view of the victims. Focus is on
peoples perceptions and experience of crime.
VOCS was conducted by Statistics South Africa (Stats SA) in 1998.
The Institute for Security Studies (ISS) conducted the 2003 and
2007 versions of the VOCS.
Stats SA continued to run the survey from 2011 onwards, based on
a sample size of approximately 30 000 households
VOCS is a countrywide survey consisting of private households in all
9 provinces of SA

4. Examine the trends
and spatial distribution
of housebreaking and
home robbery
To identify predictors of
housebreaking and home
robbery
To compare VOCS
estimates and SAPS crime
statistics
Objectives of the Thematic Report
1 2 3

5. Tracking the achievement of NDP goal
using SAPS and VOCS data
CRIME FREE SOUTH AFRICA BY 2030

6. 2492783
2150347
2168254
2250257
2183001
2100000
2150000
2200000
2250000
2300000
2350000
2400000
2450000
2500000
2550000
2004 2006 2008 2010 2012 2014 2016 2018
Total Crime
Total crime reported to the South African Police, 2005 - 2016
Total crime reported to the police declined
sharply between 2005 and 2008, the period
leading to the World Cup. A period of fluctuation
followed.

7. Total crime reported as percentage of the population, 2005 - 2016
0
1
2
3
4
5
6
2004 2006 2008 2010 2012 2014 2016 2018
Crime rate
To 2024
To 2059
If the decline between 2005 – 2008
continued zero crime rate would
have been achieved in 2024.
Monitoring “crime per capita” may be a more objective way
to assess progress. Crime per capita steadily declined
between 2005 and 2016 but rate too slow. At this rate, zero
crime rate will be achieved in 2059.

8. Not all crime committed is reported to the police
Under-reporting
for housebreaking
was 47%
Under-reporting is still a serious challenge.
Under-reporting
for home robbery
was 34%
VOCS estimated that in 2015/16 under-reporting for
housebreaking was 47% and 34% for home robbery

9. Percentage of households that reported housebreaking and home robbery to the
police, VOCS 2010 - 2016
2010 2011 2013/14 2014/15 2015/16
Housebreaking/burglary 58,9 58,1 58,6 51,8 53,5
Home robbery 57,1 60,0 62,4 60,4 65,8
58,9%
Housebreaking/burgla…
53,5%
57,1%
Home robbery
65,8%
50,0
52,0
54,0
56,0
58,0
60,0
62,0
64,0
66,0
68,0
70,0
Percentage
Between 2010 and 2016 the reporting of
housebreaking /burglary declined while home
robbery reporting increased.

10. 5,9%
4,5%
2,0%
3,7%
0
1
2
3
4
5
6
7
2004 2006 2008 2010 2012 2014 2016 2018
Trends of Crime Rates
Burglary Home robbery
Per capita crime trends for housebreaking /burglary and home robbery,
2005 - 2016
Percentage
Police records also show the same trends on
reporting of burglary and home robbery. The
increase in home robbery reporting may create
a negative perception that crime is increasing.

11. SAPS data VOCS estimate C.I. CV (%)
Western Cape 47 668 64 945 (47 642 - 82 247) 13,6
Eastern Cape 23 428 39 626 (29 510 - 49 741) 13,0
Northern Cape 6 480 7 713 (3 915 - 11 511) 25,1
Free State 15 377 24 941 (15 716 - 34 166) 18,9
KwaZulu-Natal 43 478 55 474 (41 571 - 69 378) 12,8
North West 17 961 15 476 (8 828 - 22 125) 21,9
Gauteng 62 653 129 290 (104 217 - 154 364) 9,9
Mpumalanga 18 141 24 353 (15 656 - 33 050) 18,2
Limpopo 15 479 23 372 (14 828 - 31 916) 18,7
South Africa 253 716 385 191 (346 254, - 424 127) 5.2
SAPS reported burglaries vs VOCS estimates of incidents reported to the
police for 2015/16
While SAPS and VOCS figures disagree nationally, they agree in most provinces except
Eastern Cape, Free State and Gauteng. SAPS figures lie within 95% CI of VOCS estimates.

12. SAPS reported home robberies vs VOCS estimates of incidents reported
to the police for 2015/16
SAPS data VOCS estimate C.I. CV (%)
Western Cape 2 574 15 567 (8 402 - 22 731) 23,5
Eastern Cape 2 052 8 519 (4 501 - 12 536) 24,1
Northern Cape 110 721 (0 - 1 748) 72,7
Free State 770 6 412 (2 178 - 10 646) 33,7
KwaZulu-Natal 4 135 16 774 (10 090 - 23 458) 20,3
North West 1 270 7 225 (2 295 - 12 156) 34,8
Gauteng 7 602 33 265 (22 327 - 44 202) 16,8
Mpumalanga 1 071 15 206 (8 438 - 21 974) 22,7
Limpopo 1 275 7 245 (2 713 - 11 777) 31,9
South Africa 20 281 110 933 (92 456 - 129 411) 8,5
A comparison for home robbery by province is not possible because the estimation error
is too large in 4 of the 9 provinces. In provinces where the estimation error is reasonable
there is no agreement between SAPS data and VOCS estimates. SAPS figures too low

13. Victimisation trends according to VOCS

14. A declining trend is seen in the proportion of households that
experienced crime in the past 12 months for both male-headed and
female-headed households.
12,1%
10,2%
9,2%
7,0%
10,0% 9,8%
7,5%
6,0%
0,0
2,0
4,0
6,0
8,0
10,0
12,0
14,0
2011 2013/14 2015/16 CS 2016
Percentage
Male Female
Proportion of households that experienced crime in the last 12 months by gender
Note that male-headed households are more at risk than
female-headed households.

15. 0,0
1,0
2,0
3,0
4,0
5,0
6,0
2010 2011 2013/14 2014/15 2015/16
Percentage
Car theft
Housebreaking/burglary
Home robbery
Theft of livestock
Theft of crops
Murder
Theft from car
Deliberate damaging of
dwellings
Motor vehicle vandalism
Theft of bicycle
Trends of various types of household crimes during the period 2010 to 2015/16
Housebreaking/burglary has in
general been declining since 2011.
Other types of crimes have been declining or
stagnant since 2010

16. Housebreaking/burglary
Home robbery
Theft out of motor vehicle
Theft of livestock/poultry and other
animals
Theft of motor vehicle
Other crime
Motor vehicle vandalism
Deliberate damaging of dwellings
Theft of bicycle
Theft of crops planted by household
Murder
Distribution of types of crime experienced by South African households in 2015/16
Housebreaking/burglary
accounts for over 50% of
all crimes experienced by
households, followed by
home robbery at 11,9%
and theft of motor vehicle
at 10,4%
Housebreaking/burglary
accounts for over
50% of all
crimes
(8,6%)
(4,0%)

17. Households’ perceptions of crime

18. Perceptions on trends of violent crime by year
2011 2012 2013/14 2014/15 2015/16
Increased 31,7 32,5 41,2 43,7 41,8
Decreased 42,9 38,2 31,7 28,7 28,1
Stayed the same 25,5 29,2 27,1 27,6 30,1
31,7%
43,7% 41,8%
42,9%
28,1%
25,5%
30,1%
20,0
25,0
30,0
35,0
40,0
45,0
Percentage
The proportion of households that think that violent crime increased in the past 3 years grew from 31,7%
in 2011 to 41,8% in 2015/16 while the proportion of household that think violent crime decreased during
the last 3 years declined from 42,9% in 2011 to 28,1% in 2015/16.

19. 89,2% 85,4% 86,8% 85,4% 83,7%
36,9% 35,9% 34,8%
31,0% 30,7%
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
80,0
90,0
100,0
2011 2012 2013/14 2014/15 2015/16
Safe during the day Safe when it is dark
Feeling of safety walking alone during the day and in the dark,
2011 - 2015/16
Households that feel safe walking alone in their
neighbourhoods when it is dark continued to
decline

20. Victimisation by population group and
province

21. 2011 2015/16
Population
group
Percent of
households
Std.
Error
Percent of
households
Std.
Error
percent
Change
Black
African
10,5 0,32 8,1 0,23 -22,9%
Coloured 10,8 0,78 10,4 0,81 -3,7%
Indian/Asian 11,7 1,8 8,2 0,14 -29,9%
White 17,2 1,0 12,0 0,95 -30,2%
Victimisation change by population group of the household
head between 2011 and 2015/16
White and Indian/Asian
population groups
experienced the sharpest
decline in the rate of
victimisation
The coloured group
experienced the least
decline.
100*(12-17,2)/17,2 = -30,2%

22. Victimisation change by province of the household between
2011 and 2015/16
2011 2015/16
Percentage Std. Error Percentage Std. Error Change (%)
Western Cape 15,0 0,84 11,5 0,79 -23,3
Eastern Cape 10,0 0,66 10,3 0,62 +3,0
Northern Cape 9,9 1,30 7,6 0,99 -23,2
Free State 9,4 0,75 7,3 0,78 -22,3
Kwazulu Natal 10,1 0,56 7,7 0,50 -23,8
North West 12,0 0,85 7,3 0,81 -39,2
Gauteng 11,6 0,73 9,3 0,47 -19,8
Mpumalanga 13,4 0,90 9,3 0,73 -30,6
Limpopo 8,5 0,65 5,1 0,47 -40,0
Limpopo
experienced the
sharpest decline
in rate of
victimisation
while the Eastern
Cape experienced
an increase of 3%

23. Victimisation change by province of the household between 2011 and
2015/16
15,0%
10,0% 9,9%
9,4%
10,1%
12,0%
11,6%
13,4%
8,5%
11,5%
10,3%
7,6%
7,3%
7,7%
7,3%
9,3% 9,3%
5,1%
0,0
2,0
4,0
6,0
8,0
10,0
12,0
14,0
16,0
WC EC NC FS KZN NW GP MP LP
Percentage
2011 2015/16
Limpopo
experienced the
sharpest decline in
rate of victimisation
Eastern Cape experienced an increase of 0,3%

24. Victimisation by district of the household in 2015/16
City of Cape Town, Christ Hani, Amathole, Gert
Sibande, Umkhanyakude, Sisonke and Alfred
Nzo had the highest levels of victimisation in
2015/16

25. Housebreaking/burglary and home
robbery

26. * The results above must be used cautiously due to the low accuracy of some of the estimates particularly
estimates for the number of convicted and on-going cases. In addition, the fact only crimes experienced during the
past year were included and convictions take much longer to realise makes the estimates unreliable.
Housebreaking Home Robbery
Number Std. Error CV (%) Number Std. Error CV (%)
Experienced 727 130 26 302 3,6 171 739 11 792 6,9
Reported 385 191 19 866 5,2 110 933 9 428 8,5
Arrested 71 358 8 192 11,5 20 897 3 951 18,9
Convicted 10 266 3 016 29,4 4 589 1 758 38,3
Case on-going 6 561 2 209 33,7 3 095 1 672 54,0
Incidents of housebreaking and home robbery experienced, reported, perpetrators
arrested, convicted and cases on-going in 2015/16

27. Percentage of housebreaking and home robbery at various stages of the justice system
53,0%
18,5%
14,3%
9,2%
64,6%
18,8%
22,0%
14,8%
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
Reported Arrested Convicted Case on-going
Housebreaking Robbery
Percentage
The percentages arrested,
convicted and on-going cases were
computed from the number of
cases reported to the police.
Note the estimates for the
convicted and case-ongoing are
not very accurate due to
mismatch between reference
period and time it takes to
finalise cases, and the standard
errors are large.

28. Characteristics of households satisfied with the police
Estimate Std. Error t-Value Pr(>|t|) Odds ratio
Intercept 0,18 0,322 0,549 0,5833 1,19
Gender (Male) -0,11 0,213 -0,512 0,6094 0,90
Race (Coloured) 0.31 0,333 0,923 0,3570 1,36
Race (White) 1.16 0,335 3,450 0,0007 *** 3,18
Education level -0,04 0,106 -0,390 0,6967 0,96
Arrested? (No) -0,88 0,264 -3,330 0,0010 ** 0,42
Arrested? (Do not know) -0,00 1,008 0,002 0,9987 1,00
* Households that reported crime and an arrest was made had 2.4 times the odds of being
satisfied by police than households were no arrest was made. 1/0.42 = 2.4
* Whites had 3 times the odds of being satisfied with police service than blacks Africans.
* Asian/Indian race was excluded from the analysis because of the low number of households
(Only 9 Indian/Asian households reported crime to the police).

29. Results show that when the household head is male the odds of
housebreaking are significantly higher (Odds 1,3 times) than when the
household head is female.
Households here the head has a Bachelor’s degree or equivalent have
significantly greater odds of housebreaking than households where the
head has no schooling.
Existence of community crime prevention forums (CCPF)*, long distance to
police stations and lengthy police response times to emergency calls are
factors that increase the odds of housebreaking.
*Possible explanation is that CCPF may have been formed in areas where
housebreaking incidents were high.
Characteristics of victims of housebreaking
Results from logistic regression analysis of VOCS data

30. Level of education and police emergency response time are significant
predictors of home robbery
When the head of household has a high level of education (post graduate
degree) the odds of experiencing home robbery were more than 5 times
compared to a household where the head had no education. This may be
due to economic well being associated with high level of education.
Where the police were never expected to arrive after an emergency
phone call the odds of experiencing home robbery were more than 2
times compared to a household where the police were expected to
respond in less than 30 minutes.
Characteristics of victims of home robbery
* For details of the regression analysis refer to the report
Results from logistic regression analysis of VOCS data

31. The odds of a white-headed household reporting housebreaking were about
3 times more than that of a black African-headed household.
Households where the head has education level 3 (post matric qualification
but less than bachelor’s degree) have about 3 times greater odds of
reporting housebreaking than households headed by persons without
schooling.
The odds of reporting housebreaking to the police are 1.78 times more for
households located in urban formal areas than households located in urban
informal areas.
1/0.563 = 1.78
Characteristics of households that report housebreaking
* For details of the regression analysis refer to the report
Results from logistic regression analysis of VOCS data

32. Race was not a significant predictor of home robbery reporting. Home
robbery had a high rate of reporting to the police than housebreaking.
Where a community crime prevention forum (CCPF) exists the odds of
reporting home robbery are more than 4 times compared to areas
where there is no CCPF.
Characteristics of households that report home robbery
* For details of the regression analysis refer to the report
Results from logistic regression analysis of VOCS data

33. Summary and conclusions: Incidents and
reporting of housebreaking and home robbery

34. • Gender and education level of the head of household, existence of CCPF,
distance to police station and police response time to emergency calls
were significant predictors of housebreaking and home robbery incidents.
• Possible explanation for female-headed household being less likely to
experience housebreaking may be that such households tend to have
someone at home most of the time compared to male-headed
households.
• Where CCPF don’t exist the odds of housebreaking are lower than where
they exist. Possible explanation is that CCPF may exist because of high
crime levels already experienced.
• Possible interventions to mitigate against housebreaking and home
robbery include bringing police stations closer to the people and improving
police response times.

35. • Race and education level of the head of household, geographical
location of the household and existence of CCPF were significant
predictors of housebreaking and home robbery reporting.
• A household in an urban formal area has greater odds of reporting
housebreaking to the police than a household in an urban informal
area.
• Where CCPF exists the odds of reporting home robbery are more
than 4 times higher than where they don’t exist.
• Possible interventions to mitigate against under-reporting of
housebreaking and home robbery include promoting formations of
CCPF especially in urban informal settlements.

36. Thank you