KWAZULU-NATAL June 2016 - the dpsa Reports/K… · 1.1 KwaZulu-Natal currently has 22 Thusong...

KWAZULU-NATAL

June 2016

Geographic Accessibility Analysis in relation to Thusong Service Centres in KwaZulu-Natal

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T A B L E O F C O N T E N T S

STUDY OF THE GEOGRAPHIC ACCESSIBILITY OF THUSONG SERVICE CENTRES IN KWAZULU-NATAL ......................................................................... 1

1 EXECUTIVE SUMMARY........................................................................................ 1

2 INTRODUCTION .................................................................................................... 3

2.1 OBJECTIVES AND SCOPE OF THE STUDY .......................................................................... 3

2.2 METHODOLOGY AND APPROACH ....................................................................................... 4

3 OVERVIEW OF KWAZULU-NATAL ....................................................................... 7

4 FINDINGS IN RELATION TO THE CURRENT ACCESSIBILITY OF THUSONG SERVICE CENTRES ........................................................................................... 16

4.1 GEOGRAPHIC DISTRIBUTION OF THUSONG SERVICE CENTRES AND THUSONG

SERVICE CLUSTERS ............................................................................................................ 16

4.2 POPULATION COVERAGE CURRENTLY PROVIDED BY THUSONG SERVICE

CENTRES AND THUSONG SERVICE CLUSTERS .............................................................. 18

4.3 CURRENT TRAVEL DISTANCES TO THUSONG SERVICE CENTRES AND THUSONG

SERVICE CLUSTERS ............................................................................................................ 24

5 OPTIMUM PROVISIONING AND LOCATION OF THUSONG SERVICE CENTRES ............................................................................................................ 25

5.1 DISTRIBUTION OF PROPOSED LOCATIONS ..................................................................... 25

5.2 POTENTIAL IMPROVEMENT IN POPULATION COVERAGE ............................................. 32

5.3 POTENTIAL REDUCTION IN TRAVEL DISTANCES ............................................................ 43

6 RECOMMENDATIONS AND CONSIDERATIONS .............................................. 45

7 NEED FOR FURTHER RESEARCH AND SCOPE FOR FUTURE STUDIES ..... 46

8 ANNEXURE 1 ...................................................................................................... 47


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LIST OF TABLES

Table 1: Thusong Service Centre Typology ........................................................................... 5

Table 2: Settlement typology .................................................................................................. 6

Table 3: Maximum travel distance per settlement typology .................................................... 7

Table 4: Current population coverage per settlement typology for KwaZulu-Natal ................ 18

Table 5: Population coverage per District Municipality, Metropolitan and Local Municipality in KwaZulu-Natal ..................................................................................................................... 20

Table 6: Average travel distance per settlement typology for KwaZulu-Natal ....................... 24

Table 7: Accessibility statistics per travel distance band for KwaZulu-Natal ......................... 24

Table 8: List of proposed locations ....................................................................................... 26

Table 9: Proposed optimal locations including catchment population ................................... 30

Table 10: Population coverage per settlement typology for KwaZulu-Natal based on the proposed provisioning of Service Centres ............................................................................ 33

Table 11: Accessibility statistics per Service Centre type ..................................................... 34

Table 12: Service Centres per Municipality in KwaZulu-Natal .............................................. 36

Table 13: Service Centres per Municipality in KwaZulu-Natal (continued) ............................ 37

Table 14: Summary of Thusong Service Centres, Thusong Service Clusters and proposed location ................................................................................................................................ 41

Table 15: Average travel distance improvement per settlement typology ............................. 43

Table 16: Accessibility statistics per travel distance band in KwaZulu-Natal ......................... 44


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LIST OF FIGURES

Figure 1: Orientation map of KwaZulu-Natal .......................................................................... 8

Figure 2: Population density map of KwaZulu-Natal ............................................................. 10

Figure 3: Percentage distribution of population by 5 year age group and gender ................. 11

Figure 4: Population percentage per settlement typology in KwaZulu-Natal ......................... 12

Figure 5: Settlement typology for KwaZulu-Natal ................................................................. 13

Figure 6: Economically active and unemployed or discouraged population density (ages 15 – 64 years) per Ward .............................................................................................................. 14

Figure 7: Thusong Service Centres and Thusong Service Clusters in KwaZulu-Natal .......... 16

Figure 8: Areas covered by Thusong Service Centres and Thusong Service Clusters in KwaZulu-Natal ..................................................................................................................... 17

Figure 9: Population coverage by Thusong Service Centres and Thusong Service Clusters 18

Figure 10: Map highlighting densely populated unserved areas in KwaZulu-Natal ............... 22

Figure 11: Map highlighting densely populated unserved areas in eThekwini Metropolitan Municipality .......................................................................................................................... 23

Figure 12: Map showing optimal proposed locations for KwaZulu-Natal ............................... 27

Figure 13: Thusong Service Centres and Clusters in relation to the 14 proposed locations in KwaZulu-Natal ..................................................................................................................... 31

Figure 14: Thusong Service Centres and Clusters in relation to the proposed locations in eThekwini Metropolitan Municipality and The Msunduzi Local Municipality .......................... 32

Figure 15: Total percentage coverage that could be achieved by adding the 14 proposed locations............................................................................................................................... 33

Figure 16: Current versus potential population coverage per settlement typology ................ 34

Figure 17: Current Service Centres including the 14 proposed locations per centre size in KwaZulu-Natal ..................................................................................................................... 42

Figure 18: Current Service Centres including the 14 proposed locations per centre size in eThekwini Metropolitan Municipality and The Msunduzi Local Municipality .......................... 43

Figure 19: Population covered in Amajuba District Municipality ............................................ 47

Figure 20: Population covered in eThekwini Metropolitan Municipality ................................. 48

Figure 21: Population covered in iLembe District Municipality .............................................. 48


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Figure 22: Population covered in Sisonke District Municipality ............................................. 49

Figure 23: Population covered in Ugu District Municipality ................................................... 49

Figure 24: Population covered in UMgungundlovu District Municipality ................................ 50

Figure 25: Population covered in Umkhanyakude District Municipality ................................. 50

Figure 26: Population covered in Umzinyathi District Municipality ........................................ 51

Figure 27: Population covered in Uthukela District Municipality ............................................ 51

Figure 28: Population covered in Uthungulu District Municipality ......................................... 52

Figure 29: Population covered in Zululand District Municipality ............................................ 52


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S T U D Y O F T H E G E O G R AP H I C A C C E S S I B I L I T Y O F T H U S O N G

S E RV I C E C E N T R E S I N K WAZ U L U - N ATA L

1 EXECUTIVE SUMMARY

1.1 KwaZulu-Natal currently has 22 Thusong Service Centres and 33 Thusong Service

Clusters, a total of 55. These comprise 16.03% of the total number of Service Centres

in the country.

1.2 eThekwini Metropolitan Municipality has the highest number of Service Centres in the

province consisting of 1 Thusong Service Centre and 5 Thusong Service Clusters

situated in central Durban, Pinetown, Chatsworth, Isipingo, Verulam and Clermont.

1.3 Existing Service Centres provide access to approximately 7.2 million people or 70.7%

of the KwaZulu-Natal population.

1.4 Population coverage tends to be better in major urban towns followed by metropolitan

areas with percentage coverage of 86.4% and 75.3% respectively. Coverage is poor in

rural towns where 1 821 012 people lack adequate access.

1.5 Although population coverage is good in eThekwini Metropolitan Municipality, the

municipality still has the highest number of people that lack adequate access, followed

by uMhlathuze Local Municipality and Umzimkhulu Local Municipality.

1.6 KwaZulu-Natal currently has 8 Service Centres with a catchment population above

200 000. Five (5) of these are situated in eThekwini Metropolitan Municipality, where

the Centre in Isipingo covers close to 700 000 people, followed by Verulam covering

600 000 people. There are currently no Service Centres in the province with a

catchment population below 20 000.

1.7 The study has identified 14 locations where additional Service Centres are required to

meet the high population demand. Thusong Service Centres could potentially be

established at 5 of these locations situated in Edendale, Edendale DD, Ntsikeni,

Ntuzuma and Wiggins. Since current services are already offered in the remaining 9

locations (Esikhawini, Inanda/Newtown, KwaMashu, Malagazi, Manguzi, Mondlo,

Nkandla, Umlazi and Umzimkulu), the inclusion of additional services could be

considered to establish Thusong Service Clusters. The combination of current Service

Centres and the 14 proposed locations could potentially increase the total population

coverage which is provided in the province from 70.7% to 79.46%.



1.8 The 14 additional locations could improve population coverage in all types of

settlements, particularly in rural towns and metropolitan areas where the majority of

the unserved population currently resides. Population coverage increases from 75.3%

(or 2 588 860 people) to 87.4% (or 3 005 904 people) in metropolitan areas followed

by rural towns where coverage increases from 63.8% (or 3 203 220 people) to 72.2%

(or 3 627 208 people).

1.9 The 14 proposed locations could potentially reduce the average travel distance to

Service Centres in the province from 16.7 km to 13.8 km. The greatest improvement

would occur in rural towns.

1.10 Access distance standards and population thresholds have been developed for

different types and sizes of Thusong Service Centres. The results of the accessibility

analysis indicate that Large Thusong Service Centres should have a maximum

threshold of 200 000 people; Small centres should have a maximum 60 000 threshold,

followed by periodic services such as Satellite Centres (20 000 people) and Mobile

Services (less than 10 000). Outreach Programmes should be extended to sparsely

populated areas. In order to limit the number of additional facilities and to minimise

cost in metropolitan areas, a maximum population threshold of 300 000 people should

be considered.



2 INTRODUCTION

2.1 OBJECTIVES AND SCOPE OF THE STUDY

2.1.1 The Department of Public Service and Administration commissioned a desktop study

in 2014 to investigate the geographic accessibility of Thusong Service Centres in all

provinces except Western Cape, for which a study had already been undertaken.

2.1.2 The overall objective of the study is to evaluate the levels of access to Thusong

Centres and to elicit recommendations for the optimum provisioning and location of

Thusong Service Centres. The intention is to increase population coverage while

minimising the need for the establishment of new facilities.

2.1.3 This study assesses the current availability and accessibility of Thusong Service

Centres in relation to actual distances travelled and in relation to the present location

of other government services. It also determines backlogs in the provisioning of

Centres while identifying specific areas where accessibility needs to be improved.

2.1.4 Key services which are considered in the study include those that are provided by the

Department of Home Affairs, Department of Labour, SA Social Security Agency and

selected services of the South African Police Service. These are services which

people require to transact their daily lives.

2.1.5 Results of the accessibility study show that 75% of the South African population

currently has access to a Service Centre within a maximum travel distance of 15 km in

urban areas, and 25 km in more sparsely populated rural areas. Access is however

uneven across provinces with Gauteng having the highest levels of coverage at 97%

and Northern Cape the lowest. North West Province is ranked 2nd lowest with 59%

coverage.

2.1.6 In order to achieve a more equitable distribution of Thusong Service Centres across

the country, it will be necessary to increase population coverage in some provinces to

similar levels. The intention would be to achieve coverage of about 75% in each

province, except Gauteng and Mpumalanga which already have 97% and 81%

coverage respectively. Special attention should be given to improving access in rural

towns since the largest number of unserved population resides in these areas.

2.1.7 Recommendations should be developed for the minimum and maximum population

thresholds for different types of Thusong Service Centres. The minimum and

maximum thresholds will define the centre size.



2.2 METHODOLOGY AND APPROACH

2.2.1 The Geographic Accessibility Analysis takes into account factors such as population

size and density, the distance for people to travel to service points, the availability of

roads, as well as population thresholds and capacity parameters of service points. The

analysis uses a movement network to determine travel distance, hence actual travel

distances are used.

2.2.2 The approach of this study was to optimise the provisioning and location of different

types of Thusong Service Centres to achieve at least 75% population coverage across

the country. In order to reduce the cost involved in establishing additional

infrastructure, optimum locations were identified to achieve the maximum possible

population coverage with the least number of additional facilities. The methodology

was implemented as follows:

2.2.2.1 Step 1: Collection and preparation of data

This step included the collection of various data sets and the preparation of the data

for use in a Geographic Information System (GIS). These included the 2011 Stats SA

Census data, facility data of departments and South African road network data. A

mapping exercise was done together with provincial managers of the Thusong Service

Centre programme to verify the current locations of Thusong Service Centres in 8 of

the 9 provinces (Western Cape was excluded since a previous study was already done

in the Province). A database of existing Thusong Service Centres and service points of

departments were developed.

2.2.2.2 Step 2: Assessment of the current provisioning and location of facilities

Accessibility modelling was done to determine the current population coverage of

Thusong Service Centres and Thusong Service Clusters. Catchment area analysis is

done to quantify the demand on each centre and to identify areas that are under-,

over- or poorly served. Backlog statistics and maps were then produced in relation to

the current provisioning of Service Centres.

2.2.2.3 Step 3: Facility location analysis to optimise the provisioning of facilities

Location analysis was done to identify the optimum number and location of facilities

and to identify other possible options for meeting the unserved population demand.

This analysis accepted the current locations of Thusong Service Centres and Thusong

Service Clusters while determining the minimum number of additional locations that

would be required to increase population coverage to set percentage. The proposed

population thresholds for Thusong Service Centres and Thusong Service Clusters

were applied to classify current facilities and proposed locations for Service Centres as

Large, Small or Satellite/Mobile Centres.

2.2.3 The Thusong Service Centre typology which was determined for the purpose of this

accessibility study is provided in Table 1. The typology was informed by the Thusong

Service Centre business plan and the findings of the accessibility analysis.



Thusong Urban Mall concept

Permanent facility located in a regional shopping mall.

Thusong Service Centres in such malls may provide a

wider range of services, including services of a

specialised nature. It is assumed that people gravitate

over larger distances towards central locations to access

a wide range of products, economic services and other

benefits. Thusong services are generally provided during

shopping hours.

Thusong Service Centre

Permanent structure where services of departments are

housed under 1 roof and where services are provided on

a daily basis (Monday – Friday).

Thusong Service Cluster

Permanent facilities of 3 or more departments which are

located in close proximity. These serve as de facto

Thusong Service Centres. In densely populated areas

the facilities of departments could be located in a radius

of 1 – 2 km, while facilities in more sparsely populated

areas could be clustered together within a 5 km radius

from each other.

Satellite Service Centre

Thusong Service Satellite Centre - permanent

infrastructure where all the Thusong Anchor Departments

have established periodic service delivery points, i.e.

operate according to fixed service delivery schedules.

Thusong Mobile Service

Thusong Mobile is a mobile service where all the

Thusong anchor departments and other relevant

government departments deliver integrated services in

outlying and more sparsely populated areas which have

intermittent small settlement clusters. In these areas it is

not financially viable to operate either a Thusong Service

Centre or a periodic Satellite Service. It should be noted

that road links (or lack thereof) and road conditions have

a major impact with respect to access times and/or the

delivery of Mobile Services.

Thusong Outreach Projects

Thusong Outreach Projects serve extreme sparsely

populated areas with no settlement clusters. Such a

service could possibly utilise Community Development

Workers (CDWs) to access far outlying areas where the

population density does not warrant a Thusong Mobile or

Thusong Service Satellite Centre.

Table 1: Thusong Service Centre Typology



2.2.4 The analysis is a desktop exercise that utilises the data analysis capabilities of

Geographic Information Systems (GIS) to identify optimal locations. For this reason,

the proposed locations identified in the study refer to generalised locations and not

exact locations.

2.2.5 Settlement typologies are defined to differentiate between urban and rural spaces. As

no single official classification currently exists in South Africa to distinguish between

urban and rural spaces, for the purpose of this study the South African Geospatial

Data Dictionary and its application, compiled by South African National Standards

(SANS) served as a standard and guide to differentiate urban and rural areas.

2.2.5.1 The CSIR guidelines for the provision of social facilities in South African settlements

were used as a general guideline to subdivide the urban and rural type into 5

settlement typologies based on population totals.

2.2.5.2 Table 2 depicts the settlement typology that is used in this study.

URBAN

Type Classification Description

Urban Metro Areas classified as urban and situated in Metropolitan areas

Urban Major Urban Town Urban areas with population above 25 000

Urban Urban Town Urban areas with population below 25 000

RURAL

Type Classification Description

Rural Rural Town Rural areas with population above 25 000

Rural Rural Rural areas with population below 25 000

Table 2: Settlement typology

2.2.6 Population Coverage is measured by calculating the distance people travel along a

travel network to their nearest Service Centre within the maximum allowed travel

distances. The maximum travel distance in urban areas is 15 km, and 25 km in more

sparsely populated rural areas. It is assumed for this study that people are more likely

to travel to their nearest Thusong Service Centre. Table 3 depicts the maximum travel

distances per settlement typology that were applied in the analysis.



Settlement Typology Maximum travel distance

Metro 15 km

Major Urban Town 15 km

Urban Town 15 km

Rural Town 25 km

Rural 25 km

Table 3: Maximum travel distance per settlement typology

3 OVERVIEW OF KWAZULU-NATAL

3.1 Geographic overview

3.1.1 KwaZulu-Natal is located in the southeast of the country, having a long shoreline

beside the Indian Ocean and sharing borders with 3 other provinces, including

Mpumalanga, Free State and Eastern Cape. It also borders the countries of

Mozambique, Swaziland and Lesotho. In 2011 the land area was 94 361 km2, making

it the 3rd smallest province after Gauteng and Mpumalanga.

3.1.2 The Province consists of 3 different geographical areas – the lowland Indian Ocean

coastal region, the central Natal Midlands and the mountainous areas of the

Drakensberg and Lebombo Mountains. These form a solid barrier rising over 3 000 m

beside the Lesotho border and low parallel ranges running southward from Swaziland.

3.1.3 Figure 1 is an orientation map of KwaZulu-Natal consisting of administrative

boundaries, towns and road infrastructure. Road infrastructure includes highways,

main roads, secondary roads, arterial roads and streets.

https://en.wikipedia.org/wiki/Indian_Ocean

https://en.wikipedia.org/wiki/Mozambique

https://en.wikipedia.org/wiki/Swaziland

https://en.wikipedia.org/wiki/Lesotho

http://www.southafrica.com/kwazulu-natal/natal-midlands/

http://www.southafrica.com/kwazulu-natal/drakensberg/



Figure 1: Orientation map of KwaZulu-Natal



3.2 Economic drivers

3.2.1 KwaZulu-Natal was South Africa’s 2nd largest economy in 2013, contributing on

average 16% to the country’s Gross Domestic Product (GDP)1. The province also

boasts the 3rd highest export capability and the 2nd highest level of industrialisation in

the country. The capital city is Pietermaritzburg.

3.2.2 The province as a whole produces considerable amounts of coal and timber. To the

north, Newcastle is the province's industrial powerhouse. Key outputs include

chemicals, synthetic rubber, cement, agriculture and electricity. The textile industry is

a major employer in the area. There are large aluminium-smelting plants at Richards

Bay on the north coast. Sugar refining is Durban's main industry. Other industries

located in the area include textile, clothing, chemicals, rubber, fertiliser, paper, vehicle

assembly and food-processing plants, tanneries, and oil refineries. Ecology tourism is

increasingly important to the economy of the province.

3.3 Demographic profile

3.3.1 In 2011 the population size of KwaZulu-Natal was 10.3 million or 20% of the total

South African population. While the population is growing, this is happening at a slow

pace. The 2015 midyear population estimate2 for this province is 10.9 million, second

to Gauteng which has an estimate of 13.2 million.

3.3.2 eThekwini had the largest population (34%), followed by uMgungundlovu (10%) and

uThungulu (9%). The greatest increase in population between 2001 and 2011

occurred in eThekwini (an increase of 11%), followed by uMkhanyakude (9%),

Amajuba (7%) and uMzinyathi (6%). The largest proportions of the population

concentrate in urban areas such as eThekwini while the population is more sparsely

populated in rural, farm-type settlement areas such as Zululand.

3.3.3 KwaZulu-Natal saw almost no net migration between 2006 and 2011. However this net

figure hides significant churn with 197,000 individuals migrating out of the Province

and 198,000 individuals migrating into the Province. The majority of out-migrants

(60%) have gone to Gauteng3. The largest in-migration has been from the Eastern

Cape (42%) while a further 1% moved from outside of South Africa. Furthermore 15%

of the KwaZulu-Natal population moved within the province.

1 Trade and Investment Kwazulu-Natal. 2015.http://www.tikzn.co.za/. Accessed on 30 November

2015

2 Stats SA. July 2015. Mid-year population estimates 2015

3 Housing Development Agency, 2013. KwaZulu-Natal: Informal Settlements Status

https://en.wikipedia.org/wiki/Newcastle,_KwaZulu-Natal

https://en.wikipedia.org/wiki/Richards_Bay

https://en.wikipedia.org/wiki/Richards_Bay

https://en.wikipedia.org/wiki/Chemicals

https://en.wikipedia.org/wiki/Fertiliser

https://en.wikipedia.org/wiki/Petroleum

http://www.tikzn.co.za/



3.3.4 The largest population group in 2011 was black Africans (87%) followed by Indian or

Asian (7%). The majority of the population speak IsiZulu as their first language,

followed by English.

3.3.5 Figure 2 displays the current population density of the province based on Census 2011

demographic data.

Figure 2: Population density map of KwaZulu-Natal



3.3.6 The population pyramid (Figure 3) shows a typical trend of developing countries such

as high fertility rates and low life expectancy rates, as well as higher life expectancy of

women against that of men. In 2011 the highest proportion of the KwaZulu-Natal

population was between the ages 0 - 4 years, as well as 15 - 29 years. There has

been a large decrease in the proportion of the population aged 5 - 14 years.

Figure 3: Percentage distribution of population by 5 year age group and gender

3.3.7 There is a noticeable difference in the population pyramids in urban compared to tribal

or traditional areas. Urban areas have a large population bulge in the 15 – 34 years

while tribal/traditional areas have a very large population bulge between the 0 – 24

year age group. KwaZulu-Natal had more females than males in 2011 with a sex ratio

of 91:100. All districts show a higher percentage of females than males. UMzinyathi

shows the highest gap between males and females with approximately 45% males and

55% females. The lowest gap is found in eThekwini followed by uMgungundlovu.

3.3.8 Age dependency ratios are a measure of how many of those aged 0 – 14 years (and

older than 65 years) depends on 100 individuals of the working age group (age 15 –

64 years). In 2011 uMzinyathi district recorded the highest (83) dependency ratio

followed by uMkhanyakude (81). Generally, all the districts which are mostly rural had

high dependency ratios. The lowest dependency ratio occurred in eThekwini (43).

3.3.9 Generally, the proportion of the population with a disability in the province stands at

8.4%. The results also show that 7% of males and 9.7% of females were disabled. The

15 10 5 0 5 10 15

00 - 04

05 - 09

10 - 14

15 - 19

20 - 24

25 - 29

30 - 34

35 - 39

40 - 44

45 - 49

50 - 54

55 - 59

60 - 64

65 - 69

70 - 74

75 - 79

80 - 84

85+

%

Male

Female



majority of District Municipalities have high proportions of the disabled population for

both males and females. However, a comparison of the proportions of the disabled

populations among the District Municipalities found that eThekwini is the only District

Municipality which has the lowest share of the disabled population in its total

population, with only 6.6% of the disabled people in the district’s population.

3.4 Settlement Typology

3.4.1 KwaZulu-Natal consists of all the settlement typology types that include metro, major

urban town, urban town, rural town and rural areas. The majority of people (48.94%)

reside in rural towns (Figure 4), followed by metro areas with 33.5%. See Figure 5 for

a geographic overview of settlement typologies in the Province.

Figure 4: Population percentage per settlement typology in KwaZulu-Natal

3.4.2 Areas situated in eThekwini Metropolitan Municipality includes Durban, Pinetown,

Umhlanga, Berea, Umlazi and Amanzimtoti. Pietermaritzburg, Richards Bay,

Newcastle, Ladysmith and Port Shepstone are some of the major urban towns in the

province. The largest portion of the province is covered by rural towns, which is also

the settlement typology type with the highest number of unserved population.

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

50.00%

Metro Major UrbanTown

Urban Town Rural Town Rural

33.50%

13.95%

3.01%

48.94%

0.61%



Figure 5: Settlement typology for KwaZulu-Natal

3.5 Employment rate

3.5.1 There has been an improvement in the official unemployment rate (age 15 – 64 years)

in KwaZulu-Natal as it dropped from 49% in 2001 to 33% in 2011. Nevertheless

uMkhanyakude and Zululand Districts still recorded official unemployment rates of

above 40% during Census 2011. The remaining districts recorded unemployment rates

above 30% with the lowest being recorded in eThekwini at 30.2%.

3.5.2 Overall, the KwaZulu-Natal official youth unemployment rate dropped from 58.4% in

2001 to 42.1% in 2011. UMzinyathi showed the largest decrease in youth

unemployment from 70% in 2001 to 45% in 2011, a drop of 25 percentage points.

Umkhanyakude, Zululand and Amajuba still showed youth unemployment rates above

50% in 2011. In 2015 the official youth unemployment rate in KwaZulu-Natal was



33.4%, which is much higher than that of adults at 13.8%. The national youth

unemployment rate stood at 36.9%4.

3.5.3 In 2011 the percentage of unemployed and discouraged individuals (age 15 – 64

years) in KwaZulu-Natal was very high in the Local Municipalities of eThekwini,

uMlalazi and Nqutu (Figure 6).

3.5.4 Figure 6 provides an illustration of the geographic distribution of unemployed or

discouraged persons per ward.

Figure 6: Economically active and unemployed or discouraged population density (ages 15 – 64

years) per Ward

3.6 Income

3.6.1 In 2011 the average annual household income of the KwaZulu-Natal was R83 053,

which is lower than the national average of R 103 195 but higher than Mpumalanga,

Free State, North West, Eastern Cape and Limpopo. In June 2015 the highest number

of social grants (3.9 million), mostly Child Support Grants, were issued in KwaZulu-

Natal. This was followed by Eastern Cape (2.7 million)5.

4 Stats SA, 2015. National and provincial labour market: Youth. Statistical release P0211.4.2

5 South African Social Security Agency. Fact Sheet: Issue no 6 of 2015 – 30 June 2015



3.7 Poverty

3.7.1 In spite of its high contribution to the country’s GDP, KwaZulu-Natal was ranked the 2nd

poorest province, after Eastern Cape, in both 2001 and 20116. However the poverty

headcount (percentage of people suffering from multidimensional deprivation)

decreased from 22.3% in 2001 to 11.0% in 2011. Key contributors to poverty included

unemployment, inadequate years of schooling and school attendance, the infant

mortality rate, as well as lack of access to basic services.

3.7.2 Msinga Municipality stands out as not only the poorest municipality in KwaZulu-Natal,

but also as the poorest municipality in South Africa. Approximately 37.2% of all

households in this municipality were measured as poor in 2011; however this is

significantly less than its headcount in 2001 which reported that 6 out of every 10

households (59.5%) were multi-dimensionally poor. In 2011, Mhlathuze had the lowest

poverty headcount in the province at 4.1%.

6 Stats SA, 2014. Report No. 03-10-08. South African Multidimensional Poverty Index, Creating a

multidimensional poverty index using census data. Pages 33-35



4 FINDINGS IN RELATION TO THE CURRENT

ACCESSIBILITY OF THUSONG SERVICE CENTRES

4.1 GEOGRAPHIC DISTRIBUTION OF THUSONG SERVICE CENTRES AND THUSONG SERVICE CLUSTERS

4.1.1 There are currently 55 Service Centres (within 41 of the 51 Municipalities) in KwaZulu-

Natal. These include 22 Thusong Service Centres and 33 Thusong Service Clusters

representing 16.03% of the total number of Service Centres in the country. (Figure 7).

Figure 7: Thusong Service Centres and Thusong Service Clusters in KwaZulu-Natal

4.1.2 This implies that 10 Municipalities have no Service Centres. See Figure 8 for a map

that displays the geographic distribution of Thusong Service Centres and Clusters in

the province.

4.1.3 eThekwini Metropolitan Municipality has the highest number of Service Centres in the

province consisting of 1 Thusong Service Centre and 5 Thusong Service Clusters

located in central Durban, Pinetown, Chatsworth, Isipingo, Verulam and Clermont.

4.1.4 Hibiscus Coast Local Municipality that includes Port Shepstone and Margate is ranked

2nd with 4 Thusong Service Centres and 1 Thusong Service Cluster.

4.1.5 The majority of Thusong Service Clusters are located in town centres. This occurrence

is part of the legacy of pervious town planning initiatives.

Thusong Service Centre, 22

Thusong Service Cluster, 33



Figure 8: Areas covered by Thusong Service Centres and Thusong Service Clusters in KwaZulu-Natal



4.2 POPULATION COVERAGE CURRENTLY PROVIDED BY THUSONG SERVICE CENTRES AND THUSONG SERVICE CLUSTERS

4.2.1 The results of the accessibility analysis show that 7 261 243 or 70.73% of the

population in KwaZulu-Natal currently have access to a Service Centre. The remaining

3 005 499 or 29.27% of the people in the province are not covered. These

percentages are illustrated in the pie chart in Figure 9.

Figure 9: Population coverage by Thusong Service Centres and Thusong Service Clusters

4.2.2 Table 4 indicates the number of people that have adequate access to Service Centres,

as well as those that lack such access. Population coverage tends to be better in

major urban towns followed by metropolitan areas with percentage coverage of 86.4%

and 75.3% respectively. Coverage is poor in rural towns where 1 821 012 people lack

adequate access. Hence the establishment of additional Service Centres in rural towns

should be given priority.

Settlement Typology

Population Covered Percentage Not Covered

Total Population

Metro 2 588 860 75.28% 850 153 3 439 013

Major Urban Town 1 238 231 86.44% 194 259 1 432 490

Urban Town 208 888 67.64% 99 939 308 827

Rural Town 3 203 220 63.76% 1 821 012 5 024 232

Rural 22 044 35.45% 40 136 62 180

Total 7 261 243 70.73% 3 005 499 10 266 742

Table 4: Current population coverage per settlement typology for KwaZulu-Natal

Population Covered

71%

Not Covered29%



4.2.3 KwaZulu-Natal is the province with the highest number of municipalities in the country

consisting of 1 metropolitan municipality and 50 local municipalities. Table 5 highlights

the current population coverage provided by Thusong Service Centres and Thusong

Service Clusters in each Local Municipality. Dannhauser Local Municipality has the

highest percentage coverage of 98.59%, followed by Hibiscus Coast Local Municipality

with 98.31% coverage.

4.2.4 Although coverage is good in eThekwini Metropolitan Municipality (75.21% coverage),

853 402 people still lack adequate access to a Service Centre. Coverage tends to be

worse in uMhlathuze Local Municipality where 143 478 lack adequate access to a

Service Centre. Umzimkhulu Local Municipality has 140 849 people which are not

covered.

District Municipality

Local and Metropolitan Municipality

Population Covered

Percentage Not

Covered Total

Population

DC21 Ezingoleni Local Municipality 34 782 66.20% 17 761 52 543

DC21 Hibiscus Coast Local Municipality

251 798 98.31% 4 320 256 118

DC21 Umdoni Local Municipality 72 675 92.14% 6 196 78 871

DC21 UMuziwabantu Local Municipality

90 254 93.48% 6 297 96 551

DC21 Umzumbe Local Municipality 104 104 64.67% 56 863 160 967

DC21 Vulamehlo Local Municipality 55 985 72.34% 21 407 77 392

DC22 Impendle Local Municipality 24 087 72.78% 9 010 33 097

DC22 Mkhambathini Local Municipality 17 495 27.71% 45 647 63 142

DC22 Mpofana Local Municipality 1 952 5.12% 36 149 38 101

DC22 Richmond Local Municipality 21 215 32.25% 44 578 65 793

DC22 The Msunduzi Local Municipality 579 108 93.63% 39 391 618 499

DC22 uMngeni Local Municipality 86 087 92.85% 6 628 92 715

DC22 uMshwathi Local Municipality 57 862 54.40% 48 497 106 359

DC23 Emnambithi/Ladysmith Local Municipality

217 170 91.47% 20 264 237 434

DC23 Imbabazane Local Municipality 68 593 60.68% 44 453 113 046

DC23 Indaka Local Municipality 71 688 69.54% 31 404 103 092

DC23 Okhahlamba Local Municipality 66 889 50.65% 65 182 132 071

DC23 Umtshezi Local Municipality 57 622 69.30% 25 523 83 145

DC24 Endumeni Local Municipality 62 506 96.38% 2 351 64 857

DC24 Msinga Local Municipality 105 097 59.19% 72 473 177 570

DC24 Nqutu Local Municipality 114 041 69.00% 51 242 165 283



District Municipality

Local and Metropolitan Municipality

Population Covered

Percentage Not

Covered Total

Population

DC24 Umvoti Local Municipality 49 445 47.96% 53 646 103 091

DC25 Dannhauser Local Municipality 100 693 98.59% 1 436 102 129

DC25 Emadlangeni Local Municipality 4 406 12.79% 30 038 34 444

DC25 Newcastle Local Municipality 331 399 91.23% 31 864 363 263

DC26 Abaqulusi Local Municipality 75 152 35.61% 135 902 211 054

DC26 eDumbe Local Municipality 2 018 2.46% 80 018 82 036

DC26 Nongoma Local Municipality 150 060 77.01% 44 809 194 869

DC26 Ulundi Local Municipality 112 318 59.65% 75 986 188 304

DC26 UPhongolo Local Municipality 108 487 85.27% 18 739 127 226

DC27 Hlabisa Local Municipality 38 783 53.92% 33 141 71 924

DC27 Jozini Local Municipality 94 503 50.67% 91 988 186 491

DC27 Mtubatuba Local Municipality 123 850 70.60% 51 567 175 417

DC27 The Big 5 False Bay Local Municipality

36 0.10% 35 211 35 247

DC27 Umhlabuyalingana Local Municipality

40 374 25.76% 116 346 156 720

DC28 Mfolozi Local Municipality 84 078 68.43% 38 787 122 865

DC28 Mthonjaneni Local Municipality 40 679 85.07% 7 142 47 821

DC28 Nkandla Local Municipality 15 631 13.66% 98 777 114 408

DC28 Ntambanana Local Municipality 67 006 90.14% 7 327 74 333

DC28 uMhlathuze Local Municipality 190 979 57.10% 143 478 334 457

DC28 uMlalazi Local Municipality 177 090 82.91% 36 497 213 587

DC29 KwaDukuza Local Municipality 179 769 77.76% 51 404 231 173

DC29 Mandeni Local Municipality 128 184 92.85% 9 870 138 054

DC29 Maphumulo Local Municipality 75 028 77.56% 21 705 96 733

DC29 Ndwedwe Local Municipality 128 143 91.00% 12 677 140 820

DC43 Greater Kokstad Local Municipality

58 652 88.89% 7 328 65 980

DC43 Ingwe Local Municipality 50 222 49.96% 50 305 100 527

DC43 Kwa Sani Local Municipality 413 3.20% 12 484 12 897

DC43 Ubuhlebezwe Local Municipality 44 552 43.81% 57 140 101 692

DC43 Umzimkhulu Local Municipality 39 423 21.87% 140 849 180 272

ETH eThekwini Metropolitan Municipality

2 588 860 75.21% 853 402 3 442 262

Total 7 261 243 70.73% 3 005 499 10 266 742

Table 5: Population coverage per District Municipality, Metropolitan and Local Municipality in

KwaZulu-Natal



4.2.5 Figures 10 and 11 show densely populated areas in KwaZulu-Natal where people lack

adequate access to Service Centres. These areas span across municipal boundaries

and are highlighted by red circles and located in:

4.2.5.1 eThekwini Metropolitan Municipality

4.2.5.2 Manguzi, Umhlabuyalingana Rural

4.2.5.3 Surrounding areas of Richards Bay

4.2.5.4 Nkandla, Nkandla Rural

4.2.5.5 Umzimkhulu

4.2.6 The highlighted areas are significant due to their high concentration of unserved

population in both rural towns and metropolitan areas.



Figure 10: Map highlighting densely populated unserved areas in KwaZulu-Natal



Figure 11: Map highlighting densely populated unserved areas in eThekwini Metropolitan

Municipality

4.2.7 No current centre in KwaZulu-Natal has a catchment population below 20 000. The

Centre with the lowest catchment population is a Thusong Service Centre in the rural

areas of Richmond Local Municipality with a catchment population of 22 505.

4.2.8 KwaZulu-Natal currently has 8 Service Centres with a catchment population above

200 000. Five (5) of these are situated in eThekwini Metropolitan Municipality, where

the Centre in Isipingo covers close to 700 000 people, followed by Verulam covering

600 000 people. Centres outside the metropolitan with a significantly high catchment

population are situated in Pietermaritzburg, Richards Bay and Newcastle.

4.2.9 More than 5.6 million people in KwaZulu-Natal receive coverage from Thusong Service

Clusters, followed by Thusong Service Centres covering just over 1.6 million people.

Eight thousand (8 000) people in the province receive coverage from Service Centres

in adjacent provinces.



4.3 CURRENT TRAVEL DISTANCES TO THUSONG SERVICE CENTRES AND THUSONG SERVICE CLUSTERS

4.3.1 The average travel distance to the nearest Service Centre is 16.7 km. See Table 6.

People in rural areas travel on average 32.5 km to a Service Centre compared to only

11.4 and 9 km for those living in metropolitan areas and major urban towns

respectively.

Settlement Typology Average travel distance to nearest

Service Centre (km)

Metro 11.4

Major Urban Town 9.0

Urban Town 15.3

Rural Town 22.4

Rural 32.5

Total 16.7

Table 6: Average travel distance per settlement typology for KwaZulu-Natal

4.3.2 Table 7 sets out the population coverage per travel distance band and per settlement

typology. The majority of people in the province reside in rural towns followed by

metropolitan areas. Close to 22% (21.8%) of the population in KwaZulu-Natal need to

travel more than 25 km to reach a Service Centre with the highest number of people

situated in rural towns.

Distance Band

Metro Major Urban

Town Urban Town

Rural Town

Rural Total Percentage

0 – 5 km 641 497 456 122 117 429 386 401 1799 1 603 248 15.60%

>5 – 10 km 1 116 988 521 254 39 859 576 960 3283 2 258 344 22.00%

>10 – 15 km 830 375 260 855 51 600 748 756 4 798 1 896 384 18.50%

>15 – 25 km 607 880 138180 22 394 1 491 103 12 164 2 271 721 22.10%

>25 – 40 km 235 777 41 613 50 224 1 207 978 20 505 1 556 097 15.20%

>40 km 6496 14 466 27 321 613 034 19 631 680 948 6.60%

Total 3 439 013 1 432 490 308 827 5 024 232 62 180 10 266 742 100.00%

Table 7: Accessibility statistics per travel distance band for KwaZulu-Natal



5 OPTIMUM PROVISIONING AND LOCATION OF

THUSONG SERVICE CENTRES

5.1 DISTRIBUTION OF PROPOSED LOCATIONS

5.1.1 The accessibility analysis identified 14 additional locations in the province where

access to services need to be improved in order to meet the population demand – the

provisioning of services at these locations would increase the total number of Thusong

Service Centres (including Clusters) in KwaZulu-Natal from 55 to 69. Figure 12

provides a geographic view of the 14 proposed locations.

5.1.2 Locations are proposed in densely populated areas to increase population coverage

and to reduce high population demand of existing centres. These locations were

positioned to cover the maximum number of people with the least number of additional

facilities, while taking into consideration the current location of service points of other

departments. See Table 8.

5.1.3 Lack of road infrastructure in certain areas, natural barriers such as mountain ranges

and large rivers, as well as scattered pockets of densely populated settlements made it

difficult to identify optimal locations for Service Centres.

5.1.4 Six (6) proposed locations could provide coverage to unserved population in

predominantly rural towns where the highest number of unserved people reside. Five

(5) locations were identified in eThekwini Metropolitan Municipality and

Pietermaritzburg to reduce population demand on existing centres. The remaining 3

proposed locations could potentially provide coverage in eThekwini Metropolitan

Municipality to unserved population from KwaMashu, Ntuzuma, Inanda, Illovo,

Cele/Vumengazi and Kingsburgh.

5.1.5 Based on the results of the analysis 42 of the 51 municipalities in the province will

have Service Centres. These include the existing Service Centres and the 14

proposed locations. Nine (9) municipalities will not have Service Centres. These

include:

5.1.5.1 Umzumbe Local Municipality

5.1.5.2 Ezingoleni Local Municipality

5.1.5.3 Mpofana Local Municipality

5.1.5.4 Mkhambathini Local Municipality

5.1.5.5 Emadlangeni Local Municipality

5.1.5.6 eDumbe Local Municipality

5.1.5.7 The Big 5 False Bay Local Municipality

5.1.5.8 Mfolozi Local Municipality

5.1.5.9 Kwa Sani Local Municipality



5.1.6 As settlements in these municipalities are widely scattered, the deployment of Mobile

Services should be considered.

5.1.7 The 14 proposed Centre locations are:

Number Municipality Town

1 eThekwini Metropolitan Municipality KwaMashu

2 eThekwini Metropolitan Municipality Umlazi

3 eThekwini Metropolitan Municipality Wiggins, Durban

4 eThekwini Metropolitan Municipality Inanda

5 The Msunduzi Local Municipality Edendale, Pietermaritzburg

6 eThekwini Metropolitan Municipality Malagazi

7 eThekwini Metropolitan Municipality Ntuzuma

8 uMhlathuze Local Municipality Esikhawini, Richards Bay

9 The Msunduzi Local Municipality Edendale DD, Pietermaritzburg

10 Abaqulusi Local Municipality Mondlo, Abaqulusi Rural

11 Umzimkhulu Local Municipality Umzimkulu

12 Umhlabuyalingana Local Municipality Manguzi

13 Nkandla Local Municipality Nkandla

14 Umzimkhulu Local Municipality Ntsikeni, Umzimkhulu Rural

Table 8: List of proposed locations

5.1.8 The following section provides a detailed description of each of the 14 proposed

locations.

5.1.9 eThekwini Metropolitan Municipality

5.1.9.1 Although eThekwini Metropolitan Municipality currently has 5 Thusong Service

Clusters and 1 Thusong Service Centre, coverage is still inadequate since 800 000

people in the municipality lack coverage. The catchment population of 3 existing

Centres (situated in central Durban, Isipingo and Verulam) is also exceptionally high,

exceeding 500 000 people respectively.

5.1.9.2 Six (6) proposed locations were identified in eThekwini Metropolitan Municipality to

increase coverage and to reduce high population demand on existing Centres. Four

(4) of these locations are proposed as Thusong Service Centres and the remaining 2

as Thusong Service Clusters (since services of at least 2 Departments are already

offered in these 2 areas). The 6 proposed locations include: KwaMashu, Umlazi,

Wiggins, Ntuzuma, Inanda/ Newtown and Malagazi. See Table 9 for a list of services

currently offered in the 6 proposed locations.

5.1.9.3 Proposed locations in Wiggins/Durban and Umlazi could potentially reduce excessive

population demand on current Centres in central Durban, Isipingo and Chatsworth.



Figure 12: Map showing optimal proposed locations for KwaZulu-Natal

5.1.9.4 The densely populated areas of KwaMashu, Ntuzuma and Inanda, north of Durban are

not covered by Thusong Service Centres or Clusters. The accessibility analysis

identified 3 proposed locations that could provide coverage to unserved people in

these areas and potentially reduce high population demand on the current Thusong

Service Cluster situated in Verulam. The 3 proposed locations were identified in

Inanda, KwaMashu and Ntuzuma.

5.1.9.5 The proposed location in Malagazi (south of Durban) could provide additional

coverage to more than 80 000 unserved population that includes densely populated

areas of Malagazi, Illovo North, Cele/Vumengazi and Kingsburgh. People in

Amanzimtoti will also benefit from this proposed location since the nearest centre to

Amanzimtoti is situated in Isipingo.

5.1.10 Edendale, Pietermaritzburg

5.1.10.1 The Thusong Service Cluster in central Pietermaritzburg provides services to more

than 570 000 people suggesting possible under provisioning of Service Centres in the

area. Two (2) Thusong Service Centres were proposed in the densely populated areas

of Edendale to relieve pressure on the existing Cluster. The 2 proposed locations



could reduce population demand in central Pietermaritzburg to approximately 230 000

(that is closer to the 200 000 population threshold in major urban towns). Current

services close to these proposed locations include the South African Police Service

and SA Social Security Agency.

5.1.11 Esikhawini, Richards Bay

5.1.11.1 Esikhawini (approximately 25 km south of Richards Bay) was proposed to cover the

densely populated areas of Esikhawini, Sikhalasenkosi, Mahunu, Ongoye and

surrounding areas.

5.1.11.2 The proposed location could also reduce population demand on the existing Thusong

Service Cluster located in central Richards Bay, covering more than 200 000

people. Services of the Department of Home Affairs and the South African Police

Service are already offered in Esikhawini, hence additional services of the Department

of Labour or SA Social Security Agency are required to establish a Service Cluster.

5.1.12 Mondlo, Abaqulusi Rural

5.1.12.1 Mondlo is situated between Vryheid and Dundee consisting of densely populated

formal and traditional residential areas. A Thusong Service Cluster in Mondlo (where

current services of the South African Police Service and SA Social Security Agency

are already offered) could provide coverage to more than 80 000 people in

predominantly rural towns. Services of the Department of Labour or Department of

Home Affairs are required to establish a Thusong Service Cluster.

5.1.13 Umzimkulu and Ntsikeni

5.1.13.1 Umzimkhulu Local Municipality that is characterised by densely populated pockets of

rural towns has 140 000 unserved people and is ranked 3rd highest the province. Lack

of road infrastructure and natural barriers made it difficult to identify optimal locations

in the municipality, hence access to services in Umzimkhulu is poor.

5.1.13.2 Two (2) proposed locations were identified in the municipality to reduce the high

number of unserved population. A Thusong Service Cluster is proposed in the town of

Umzimkulu where current services of the SA Social Security Agency and the South

African Police Service are offered. Services of the Department of Home Affairs are

also present in Umzimkhulu but not close enough to the SA Social Security Agency

and South African Police Service to establish a Thusong Service Cluster. The 2nd

location is proposed in Ntsikeni, approximately 50 km northwest of Umzimkulu to cover

approximately 50 000 people. A Thusong Service Centre is proposed in Ntsikeni since

only services of the South African Police Service are currently offered in the area.



5.1.14 Manguzi, Umhlabuyalingana Rural

5.1.14.1 The proposed location in Manguzi, Umhlabuyalingana rural is situated in the northern

parts of the Province close the Mozambique border. The closest Service Centre to

Manguzi is situated in Mbazwana (approximately 60 km south of Manguzi). A Thusong

Service Cluster is proposed in Manguzi to provide coverage to 60 000 people in mostly

rural town areas. Services of the SA Social Security Agency and of the South African

Police Service are already offered in Manguzi. Services of the Department of Home

Affairs are also present but not close enough to the SA Social Security Agency and

South African Police Service to serve as a Cluster.

5.1.15 Nkandla, Nkandla Rural

5.1.15.1 Nkandla Local Municipality is characterised by mountainous rural areas with partial

road infrastructure limiting accessibility to Service Centres. Close to 100 000 people in

the municipality are not covered by Thusong Service Centres or Clusters, hence a

Thusong Service Cluster is proposed in Nkandla that could provide coverage to more

than 50 000 people. Current services in Nkandla include the SA Social Security

Agency and South African Police Service.

5.1.16 Table 9 provides details about the 14 proposed locations, including the type, size,

catchment population and additional services that are required.

Number Municipality Town Centre

Size

Existing services in close

proximity to each other

Required Facilities

Catchment Population

Proposed Centre Type

1 eThekwini Metropolitan Municipality

KwaMashu Large (Metro)

SAPS and SASSA

Dept of Labour and Home Affairs

384 379 Thusong Service Cluster


Umlazi N Large (Metro)

SASSA and SAPS

Dept of Labour, Home Affairs



Wiggins Large (Metro)

SAPS

Dept of Labour, Home Affairs and SASSA

282 117 Thusong Service Centre


Inanda, Newtown

Large (Metro)

SAPS and SASSA



5 The Msunduzi Local Municipality

Edendale Large SASSA

Dept of Labour, Home Affairs and SAPS



Malagazi Large (Metro)

Home Affairs and SAPS

Dept of Labour and SASSA




Number Municipality Town Centre

Size

Existing services in close

proximity to each other

Required Facilities

Catchment Population

Proposed Centre Type


Ntuzuma C Large (Metro)

SAPS



8 uMhlathuze Local Municipality

Esikhawini J

Large Home Affairs and SAPS

Dept of Labour and SASSA


9 The Msunduzi Local Municipality

Edendale DD

Large SAPS



10 Abaqulusi Local Municipality

Mondlo B Large SAPS and SASSA



11 Umzimkhulu Local Municipality

Umzimkulu Large SAPS and SASSA



12 Umhlabuyalingana Local Municipality

Manguzi Small SAPS and SASSA



13 Nkandla Local Municipality

Nkandla Small SAPS and SASSA



14 Umzimkhulu Local Municipality

Ntsikeni Small SAPS



Table 9: Proposed optimal locations including catchment population

5.1.17 Figure 13 and 14 show the geographic location of current Thusong Service Centres

and Thusong Service Clusters in relation to the 14 proposed optimal locations.



Figure 13: Thusong Service Centres and Clusters in relation to the 14 proposed locations in KwaZulu-Natal



Figure 14: Thusong Service Centres and Clusters in relation to the proposed locations in eThekwini Metropolitan Municipality and The Msunduzi Local Municipality

5.2 POTENTIAL IMPROVEMENT IN POPULATION COVERAGE

5.2.1 The addition of the 14 proposed locations to the existing 55 Thusong Service Centres

and Thusong Service Clusters in the province could potentially increase the population

coverage provided by Service Centres from 70.7% to 79.46%.

5.2.2 Coverage would be extended to 900 000 people and all settlement types would benefit

particularly rural towns and metropolitan areas where the majority of unserved

population currently resides. The chart in Figure 15 shows the cumulative population

coverage which could be achieved by adding the 14 locations to the current mix of

Thusong Service Centre and Clusters.



Figure 15: Total percentage coverage that could be achieved by adding the 14 proposed locations

5.2.3 Table 10 compares the current percentage coverage per settlement typology with the

potential coverage that could be reached when the proposed locations are added to

the current mix of Thusong Service Centres and Clusters. Population coverage could

increase from 75.3% (or 2 588 860 people) to 87.4% (or 3 005 904 people) in

metropolitan areas, followed by rural towns where coverage could increase from

63.8% (or 3 203 220 people) to 72.2% (or 3 627 208 people). Figure 16 displays a

chart with the current and potential population coverage per settlement typology.

Settlement Typology

Current Population

Covered

Current Percentage Coverage

Potential Population Coverage (Including proposed locations)

Potential Percentage Coverage

Improvement in Population Coverage

(number of people)

Metro 2 588 860 75.28% 3 005 904 87.41% 417 044

Major Urban Town 1 238 231 86.44% 1 284 514 89.67% 46 283

Urban Town 208 888 67.64% 217 632 70.47% 8 744

Rural Town 3 203 220 63.76% 3 627 208 72.19% 423 988

Rural 22 044 35.45% 22 904 36.83% 860

Total 7 261 243 70.73% 8 158 162 79.46% 896 919

Table 10: Population coverage per settlement typology for KwaZulu-Natal based on the proposed provisioning of Service Centres

Population Covered

79%

Not Covered21%



Figure 16: Current versus potential population coverage per settlement typology

5.2.4 Table 11 indicates the total cumulative population coverage which is provided by

current and proposed Service Centres. Proposed locations could provide coverage to

2.69 million people (of which 897 000 have never had coverage before). The proposed

locations would also reduce pressure on some existing Service Centres.

Service Centre Type Population Covered Percentage of

Covered Population

Current Thusong Service Clusters 3 891 916 47.7%

Proposed Locations 2 689 801 19.2%

Current Thusong Service Centres 1 568 317 33.0%

Coverage received from adjacent provinces

8 128 0.1%

Total 8 158 162 100%

Table 11: Accessibility statistics per Service Centre type

5.2.5 Table 12 provides details on existing and proposed Service Centres and the

population coverage they provide per municipality in KwaZulu-Natal. It also refers to

the number of existing service points of other departments in each municipality. The

table can assist the Province in making decisions about which proposed Service

Centres should be given priority.

5.2.5.1 The current footprint of the South African Police Service and SA Social Security

Agency comprise 234 and 73 service points respectively. Proposed locations that were

identified in the spatial analysis are generally in close proximity to the service points of

the South African Police Service and the SA Social Security Agency. (Table 12 and

13).

5.2.5.2 Based on the mix of Thusong Service Centres, Clusters and proposed locations,

Msunduzi Local Municipality has the highest population coverage of 99.3%, followed

by Dannhauser Local Municipality with 98.6%.

0

1 000 000

2 000 000

3 000 000

4 000 000

Metro Major UrbanTown

Urban Town Rural Town Rural

Current Population Covered Potential Population Coverage (Including proposed locations)



5.2.5.3 eThekwini Metropolitan Municipality has 12 Service Centres that include 6 current

Centres and 6 proposed locations, followed by Hibiscus Coast Local Municipality with

5 Service Centres.



Table 12: Service Centres per Municipality in KwaZulu-Natal

Dis

tric

t

Mu

nic

ipa

lity

Mu

nic

ipa

lity

Co

ve

red

Po

pu

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No

t

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To

tal

Po

pu

lati

on

Th

us

on

g

Se

rvic

e C

en

tre

Th

us

on

g

Se

rvic

e

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ste

r

Pro

po

se

d

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ca

tio

ns

To

tal N

um

be

r o

f

Se

rvic

e C

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tre

s

Ho

me

Aff

air

s

De

pa

rtm

en

t o

f

La

bo

ur

SA

PS

SA

SS

A

DC

21

Ezin

go

leni L

ocal M

unic

ipalit

y3

4 7

82

66

.20

%1

7 7

61

52

54

30

00

00

02

1

DC

21

Hib

iscus C

oast L

ocal

Munic

ipalit

y2

51

38

59

8.1

5%

4 7

33

25

6 1

18

41

05

41

62

DC

21

Um

do

ni L

ocal M

unic

ipalit

y7

2 6

75

92

.14

%6

19

67

8 8

71

10

01

20

21

DC

21

UM

uziw

ab

antu

Lo

cal

Munic

ipalit

y9

0 2

54

93

.48

%6

29

79

6 5

51

01

01

10

21

DC

21

Um

zum

be

Lo

cal M

unic

ipalit

y1

04

10

46

4.6

7%

56

86

31

60

96

70

00

01

03

0

DC

21

Vula

me

hlo

Lo

cal M

unic

ipalit

y6

1 0

80

78

.92

%1

6 3

12

77

39

21

00

11

02

0

DC

22

Imp

end

le L

ocal M

unic

ipalit

y2

4 0

87

72

.78

%9

01

03

3 0

97

10

01

10

31

DC

22

Mkham

bath

ini L

ocal

Munic

ipalit

y1

9 9

09

31

.53

%4

3 2

33

63

14

20

00

00

02

1

DC

22

Mp

ofa

na L

ocal M

unic

ipalit

y1

95

25

.12

%3

6 1

49

38

10

10

00

00

01

1

DC

22

Ric

hm

ond

Lo

cal M

unic

ipalit

y2

5 9

49

39

.44

%3

9 8

44

65

79

31

00

12

13

1

DC

22

The

Msund

uzi L

ocal

Munic

ipalit

y6

14

23

29

9.3

1%

4 2

67

61

8 4

99

01

23

11

10

3

DC

22

uM

ng

eni L

ocal M

unic

ipalit

y8

6 0

87

92

.85

%6

62

89

2 7

15

01

01

10

41

DC

22

uM

shw

ath

i L

ocal M

unic

ipalit

y5

7 8

62

54

.40

%4

8 4

97

10

6 3

59

01

01

20

71

DC

23

Em

nam

bithi/L

ad

ysm

ith

Lo

cal M

unic

ipalit

y2

17

17

09

1.4

7%

20

26

42

37

43

41

10

22

16

1

DC

23

Imb

ab

azane

Lo

cal

Munic

ipalit

y6

8 5

93

60

.68

%4

4 4

53

11

3 0

46

10

01

10

60

DC

23

Ind

aka L

ocal M

unic

ipalit

y7

1 6

88

69

.54

%3

1 4

04

10

3 0

92

10

01

00

11

DC

23

Okhahla

mb

a L

ocal

Munic

ipalit

y6

6 8

89

50

.65

%6

5 1

82

13

2 0

71

10

01

20

42

DC

23

Um

tshe

zi L

ocal M

unic

ipalit

y5

7 6

22

69

.30

%2

5 5

23

83

14

50

10

11

13

2

DC

24

End

um

eni L

ocal M

unic

ipalit

y6

2 6

75

96

.64

%2

18

26

4 8

57

01

01

11

32

DC

24

Msin

ga L

ocal M

unic

ipalit

y1

05

09

75

9.1

9%

72

47

31

77

57

01

00

15

05

1

DC

24

Nq

utu

Lo

cal M

unic

ipalit

y1

24

95

27

5.6

0%

40

33

11

65

28

30

10

11

03

1

DC

24

Um

vo

ti L

ocal M

unic

ipalit

y4

8 5

84

47

.13

%5

4 5

07

10

3 0

91

01

01

10

62

DC

25

Dannhause

r L

ocal

Munic

ipalit

y1

00

69

39

8.5

9%

1 4

36

10

2 1

29

11

02

10

31

DC

25

Em

ad

lang

eni L

ocal

Munic

ipalit

y5

78

21

6.7

9%

28

66

23

4 4

44

00

00

00

31

DC

25

Ne

wcastle

Lo

cal M

unic

ipalit

y3

31

39

99

1.2

3%

31

86

43

63

26

30

20

22

15

3



Table 13: Service Centres per Municipality in KwaZulu-Natal (continued)

Dis

tric

t

Mu

nic

ipa

lity

Mu

nic

ipa

lity

Co

ve

red

Po

pu

lati

on

Pe

rce

nta

ge

Co

ve

rag

e

No

t

Co

ve

red

To

tal

Po

pu

lati

on

Th

us

on

g

Se

rvic

e C

en

tre

Th

us

on

g

Se

rvic

e

Clu

ste

r

Pro

po

se

d

Lo

ca

tio

ns

To

tal N

um

be

r o

f

Se

rvic

e C

en

tre

s

Ho

me

Aff

air

s

De

pa

rtm

en

t o

f

La

bo

ur

SA

PS

SA

SS

A

DC

26

Ab

aq

ulu

si L

ocal M

unic

ipalit

y1

42

84

96

7.6

8%

68

20

52

11

05

40

11

21

16

3

DC

26

eD

um

be

Lo

cal M

unic

ipalit

y2

01

82

.46

%8

0 0

18

82

03

60

00

00

02

1

DC

26

No

ng

om

a L

ocal M

unic

ipalit

y1

50

06

07

7.0

1%

44

80

91

94

86

90

10

11

02

1

DC

26

Ulu

nd

i L

ocal M

unic

ipalit

y1

12

31

85

9.6

5%

75

98

61

88

30

40

10

12

16

2

DC

26

UP

ho

ng

olo

Lo

cal

Munic

ipalit

y1

08

48

78

5.2

7%

18

73

91

27

22

61

10

21

02

1

DC

27

Hla

bis

a L

ocal M

unic

ipalit

y3

8 7

83

53

.92

%3

3 1

41

71

92

40

10

11

02

1

DC

27

Jo

zin

i L

ocal M

unic

ipalit

y9

4 5

03

50

.67

%9

1 9

88

18

6 4

91

11

02

20

62

DC

27

Mtu

batu

ba L

ocal M

unic

ipalit

y1

23

85

07

0.6

0%

51

56

71

75

41

70

10

11

03

1

DC

27

The

Big

5 F

als

e B

ay L

ocal

Munic

ipalit

y3

60

.10

%3

5 2

11

35

24

70

00

01

01

0

DC

27

Um

hla

buyalin

gana L

ocal

Munic

ipalit

y1

00

28

66

3.9

9%

56

43

41

56

72

01

01

24

02

2

DC

28

Mfo

lozi L

ocal M

unic

ipalit

y8

4 0

78

68

.43

%3

8 7

87

12

2 8

65

00

00

00

10

DC

28

Mth

onja

ne

ni L

ocal

Munic

ipalit

y4

0 9

13

85

.55

%6

90

84

7 8

21

01

01

10

11

DC

28

Nkand

la L

ocal M

unic

ipalit

y6

9 3

47

60

.61

%4

5 0

61

11

4 4

08

10

12

30

41

DC

28

Nta

mb

anana L

ocal

Munic

ipalit

y6

7 0

06

90

.14

%7

32

77

4 3

33

10

01

00

10

DC

28

uM

hla

thuze

Lo

cal

Munic

ipalit

y2

90

05

48

6.7

2%

44

40

33

34

45

70

11

24

16

2

DC

28

uM

lala

zi L

ocal M

unic

ipalit

y1

90

17

98

9.0

4%

23

40

82

13

58

70

10

11

05

2

DC

29

Kw

aD

ukuza L

ocal

Munic

ipalit

y1

79

76

97

7.7

6%

51

40

42

31

17

30

10

11

12

1

DC

29

Mand

eni L

ocal M

unic

ipalit

y1

28

18

49

2.8

5%

9 8

70

13

8 0

54

01

01

10

61

DC

29

Map

hum

ulo

Lo

cal

Munic

ipalit

y7

5 0

28

77

.56

%2

1 7

05

96

73

31

00

11

01

1

DC

29

Nd

we

dw

e L

ocal M

unic

ipalit

y1

29

80

49

2.1

8%

11

01

61

40

82

01

00

11

03

2

DC

43

Gre

ate

r K

oksta

d L

ocal

Munic

ipalit

y5

9 3

43

89

.94

%6

63

76

5 9

80

01

01

11

51

DC

43

Ing

we

Lo

cal M

unic

ipalit

y5

7 5

28

57

.23

%4

2 9

99

10

0 5

27

01

01

10

31

DC

43

Kw

a S

ani L

ocal M

unic

ipalit

y4

13

3.2

0%

12

48

41

2 8

97

00

00

10

11

DC

43

Ub

uhle

be

zw

e L

ocal

Munic

ipalit

y4

6 4

09

45

.64

%5

5 2

83

10

1 6

92

01

01

10

23

DC

43

Um

zim

khulu

Lo

cal

Munic

ipalit

y1

54

23

78

5.5

6%

26

03

51

80

27

20

02

21

04

1

ET

HE

the

kw

ini M

etr

op

olit

an

Munic

ipalit

y3

00

5 9

04

87

.32

%4

36

35

83

44

2 2

62

15

61

21

15

62

10

To

tal

8 1

56

88

87

9.4

5%

2 1

09

85

41

0 2

66

74

22

23

31

46

97

61

72

34

73



5.2.6 A summary of the existing Thusong Service Centres, Thusong Service Clusters, as

well as the proposed optimal locations with their respective catchment population are

displayed in Table 14. The information in the table provides clarity on:

5.2.6.1 Population demand per Service Centre.

5.2.6.2 Suggested Service Centre sizes based on the proposed population thresholds for

Large, Small and Satellite/Mobile Centres.

5.2.6.3 Service Centre types (including existing and proposed Service Centres).

5.2.7 Ten (10) centres are classified as Large (Metro) Centres, 39 as Large Centres and 20

as Small Centres, which increases the total number of Service Centres in KwaZulu-

Natal to 69 from the current 55.

5.2.8 The Service Centre with the highest catchment population is the proposed centre in

KwaMashu that could provide coverage to just over 384 000 people, followed by the

proposed centre in Umlazi covering almost 340 000 people. Both locations were

identified to relieve population pressure from existing centres.

5.2.9 The current Thusong Service Cluster in Madadeni (situated close to Newcastle) covers

280 000 people. Additional Centres were not proposed in the area since the Thusong

Service Cluster in central Newcastle (approximately 12 km from Madadeni covering

only 56 000 people) could also support the high population demand in Madadeni.

District Municipality Town Centre Centre

Size Catchment Population


KwaNzimakwe Thusong Service Centre

Small 47 872


Gcilima Thusong Service Centre

Large 70 347


Nyandezulu Thusong Service Centre

Large 96 848


Port Shepstone Thusong Service Cluster

Small 56 928


Sidobe Thusong Service Centre

Large 77 355

DC21 Umdoni Local Municipality Ifafa Glebe Thusong Service Centre

Large 110 927

DC21 UMuziwabantu Local Municipality

Harding Thusong Service Cluster

Large 125 660

DC21 Vulamehlo Local Municipality

Dududu Thusong Service Centre

Large 73 178

DC22 Impendle Local Municipality

Impendle Thusong Service Centre

Small 24 754

DC22 Richmond Local Municipality

Mbila Thusong Service Centre

Small 22 505





DC22 The Msunduzi Local Municipality

Edendale DD Proposed Location Large 155 802


Pietermaritzburg Thusong Service Cluster

Large 232 622


Edendale Proposed Location Large 246 278

DC22 uMngeni Local Municipality Howick Thusong Service Cluster

Large 90 065

DC22 uMshwathi Local Municipality

New Hanover Thusong Service Cluster

Small 37 785


Driefontein Thusong Service Centre

Small 45 674


Ladysmith Thusong Service Cluster

Large 170 655

DC23 Imbabazane Local Municipality

Imbabazane Thusong Service Centre

Large 63 121

DC23 Indaka Local Municipality Ekuvukeni Thusong Service Centre

Large 83 886

DC23 Okhahlamba Local Municipality

Dukuza Thusong Service Centre

Large 66 889

DC23 Umtshezi Local Municipality

Estcourt Thusong Service Cluster

Large 65 046

DC24 Endumeni Local Municipality

Dundee Thusong Service Cluster

Large 60 037

DC24 Msinga Local Municipality Tugela Ferry Thusong Service Centre

Large 97 497

DC24 Nqutu Local Municipality Nqutu Thusong Service Cluster

Large 115 235

DC24 Umvoti Local Municipality Greytown Thusong Service Cluster

Small 43 999

DC25 Dannhauser Local Municipality

Dannhauser Thusong Service Cluster

Small 22 561

DC25 Dannhauser Local Municipality

Nellieville Thusong Service Centre

Large 72 934

DC25 Newcastle Local Municipality

Newcastle Central


Small 56 621

DC25 Newcastle Local Municipality

Madadeni B Thusong Service Cluster

Large 273 923

DC26 Abaqulusi Local Municipality

Mondlo B Proposed Location Large 96 969

DC26 Abaqulusi Local Municipality

Vryheid Thusong Service Cluster

Small 59 496

DC26 Nongoma Local Municipality

Nongoma Thusong Service Cluster

Large 128 632

DC26 Ulundi Local Municipality Ulundi Thusong Service Cluster

Large 108 855

DC26 UPhongolo Local Municipality

Belgrade Thusong Service Centre

Small 50 467





DC26 UPhongolo Local Municipality

Pongola A Thusong Service Cluster

Large 63 433

DC27 Hlabisa Local Municipality Hlabisa Thusong Service Cluster

Large 64 888

DC27 Jozini Local Municipality Jozini Thusong Service Centre

Large 67 803

DC27 Jozini Local Municipality Ingwavuma Thusong Service Cluster

Small 27 857

DC27 Mtubatuba Local Municipality

Mtubatuba Thusong Service Cluster

Large 149 283


Manguzi Proposed Location Small 59 912


Mbazwana Thusong Service Centre

Small 39 792

DC28 Mthonjaneni Local Municipality

Melmoth Thusong Service Cluster

Small 40 510

DC28 Nkandla Local Municipality Nkandla Proposed Location Small 53 950

DC28 Nkandla Local Municipality Ntolwane Thusong Service Centre

Small 41 147

DC28 Ntambanana Local Municipality

Ntambanana Rural

Thusong Service Centre

Large 88 576

DC28 uMhlathuze Local Municipality

Richards Bay Central


Large 153 821

DC28 uMhlathuze Local Municipality

Esikhawini J Proposed Location Large 197 456

DC28 uMlalazi Local Municipality Eshowe Thusong Service Cluster

Large 126 441

DC29 KwaDukuza Local Municipality

Stanger Ext 5 Thusong Service Cluster

Large 165 861

DC29 Mandeni Local Municipality Sundumbili Thusong Service Cluster

Large 156 512

DC29 Maphumulo Local Municipality

Umphumulo Thusong Service Centre

Large 85 586

DC29 Ndwedwe Local Municipality

Bamshela Thusong Service Centre

Large 107 489

DC43 Greater Kokstad Local Municipality

Kokstad Thusong Service Cluster

Large 71 069

DC43 Ingwe Local Municipality Bulwer Thusong Service Cluster

Small 47 087

DC43 Ubuhlebezwe Local Municipality

Ixopo Thusong Service Cluster

Small 33 751

DC43 Umzimkhulu Local Municipality

Ntsikeni Proposed Location Small 52 682

DC43 Umzimkhulu Local Municipality

Umzimkulu Proposed Location Large 91 618


KwaMashu Proposed Location Large (Metro)

384 379






Inanda, Newtown Proposed Location Large (Metro)

272 248


Ntuzuma C Proposed Location Large (Metro)

224 748


Wiggins Proposed Location Large (Metro)

282 117


Umlazi N Proposed Location Large (Metro)

338 520


Malagazi Proposed Location Large (Metro)

233 122


Isipingo Rail Thusong Service Cluster

Large (Metro)

242 607


Westcliff Thusong Service Cluster

Large (Metro)

277 518


New Germany Thusong Service Cluster

Large (Metro)

201 477


Archie Gumede Thusong Service Centre

Large 158 534


Litchie Farm Thusong Service Cluster

Large (Metro)

260 388


Stamford Hill Thusong Service Cluster

Large 173 853

Table 14: Summary of Thusong Service Centres, Thusong Service Clusters and proposed locations

5.2.10 Figure 17 and 18 show the location and size of Service Centres, including the 14

proposed locations for KwaZulu-Natal.



Figure 17: Current Service Centres including the 14 proposed locations per centre size in

KwaZulu-Natal



Figure 18: Current Service Centres including the 14 proposed locations per centre size in

eThekwini Metropolitan Municipality and The Msunduzi Local Municipality

5.3 POTENTIAL REDUCTION IN TRAVEL DISTANCES

5.3.1 The additional 14 proposed locations would reduce the average travel distance to

Service Centres from 16.7 km to 13.8 km. The average travel distance in metropolitan

areas decreases by 3.4 km followed by rural town areas where the average travel

distance decreases by 3 km. See Table 15.

5.3.2 The deployment of additional Satellite/Mobile Services would reduce the average

travel distance further, especially in rural towns.

Settlement Typology

Average travel distance to nearest Service Centre (km)

Average travel distance to nearest Service Centre

(km), including proposed locations

Improvement (km)

Metro 11.4 7.9 3.4

Major Urban Town 9.0 7.1 1.9

Urban Town 15.3 14.6 0.7

Rural Town 22.4 19.4 3.0

Rural 32.5 31.4 1.1

Total 16.7 13.8 2.9

Table 15: Average travel distance improvement per settlement typology



5.3.3 Currently, 6.6% or 680 948 people in KwaZulu-Natal travel more than 40 km to reach a

Service Centre. Proposed optimal locations reduces this figure to 4.3% or 443 425

people. See Table 16.

5.3.4 Major improvements occur in metropolitan areas where the percentage of people that

live within 5 km of a Service Centre increases from 18.65% (or 641 497 people) to

46% (or 1 581 511 people).

5.3.5 Based on the proposed provisioning of Service Centres, close to 65% of the population

is within 15 km of a Centre (including proposed locations), compared to the current

56%. The number of people living within 25 km of a Service Centre increases from

78.21% to 82.87%.

Distance Band

Metro Major Urban

Town Urban Town

Rural Town

Rural Total Percentage

0 – 5 km 1 581 511 677 355 126 173 528 026 1799 2 914 864 28.39%

>5 – 10 km 1 116 237 452 432 39 859 722 887 3283 2 334 698 22.74%

>10 – 15 km 308 156 154 727 51 600 856 232 4 798 1 375 513 13.40%

>15 – 25 km 223 364 111435 15 245 1 520 063 13 024 1 883 131 18.34%

>25 – 40 km 203 249 33 837 48 629 1 008 870 20 526 1 315 111 12.81%

>40 km 6496 2 704 27 321 388 154 18 750 443 425 4.32%

Total 3 439 013 1 432 490 308 827 5 024 232 62 180 10 266 742 100.00%

Table 16: Accessibility statistics per travel distance band in KwaZulu-Natal



6 RECOMMENDATIONS AND CONSIDERATIONS

6.1 The accessibility study has identified measures which could be taken to improve the

population coverage which is provided by different types of Thusong Service Centres

in KwaZulu-Natal. Optimum locations for additional Service Centres have been

identified in 14 densely populated areas where access is currently inadequate.

6.2 Key factors which should be considered include:

6.2.1 Only establish Service Centres in locations that could potentially maximise population

coverage and relieve high population demand – focusing on such areas would

minimise the need for additional infrastructure investment in the longer term. This

approach is financially more sustainable.

6.2.2 Give priority to improving access to Service Centres in rural towns and metropolitan

areas as most people that currently lack access live in such areas.

6.2.3 Give priority to areas which suffer socio-economic stress such as high levels of

unemployment and multidimensional deprivation.

6.3 Key recommendations are the following:

6.3.1 Service Centres should be established at 14 proposed locations. These Centres could

potentially increase accessibility in the province from 70.7% (or 7 261 243 people) to

79.46% (or 8 158 162 people). The 14 proposed locations include:

Thusong Service Clusters

6.3.1.1 KwaMashu in eThekwini Metropolitan Municipality

6.3.1.2 Umlazi in eThekwini Metropolitan Municipality

6.3.1.3 Inanda, Newtown in eThekwini Metropolitan Municipality

6.3.1.4 Malagazi in eThekwini Metropolitan Municipality

6.3.1.5 Esikhawini, Richards Bay in uMhlathuze Local Municipality

6.3.1.6 Mondlo in Abaqulusi Local Municipality

6.3.1.7 Umzimkulu in Umzimkhulu Local Municipality

6.3.1.8 Manguzi in Umhlabuyalingana Local Municipality

6.3.1.9 Nkandla in Nkandla Local Municipality

Thusong Service Centres

6.3.1.10 Wiggins, Durban in eThekwini Metropolitan Municipality

6.3.1.11 Edendale, Pietermaritzburg in The Msunduzi Local Municipality

6.3.1.12 Ntuzuma in eThekwini Metropolitan Municipality

6.3.1.13 Edendale DD, Pietermaritzburg in The Msunduzi Local Municipality

6.3.1.14 Ntsikeni in Umzimkhulu Local Municipality



6.3.2 Nine (9) municipalities do not have a Service Centre within their boundaries. Some of

these receive coverage from facilities in adjacent municipalities. The deployment of

additional Satellite/Mobile Centres should be considered.

6.3.3 Further location analysis is recommended to determine the most suitable sites for the

establishment of these Thusong Service Centres and Clusters. Location analysis

should include a physical location assessment and feasibility study to recognise the

practicality of each location.

6.3.4 The following population thresholds have been applied to determine the optimum

provisioning of Service Centres in the Province. These should be applied to determine

the need for Service Centres in the future:

6.3.4.1 Large Metropolitan Centres – 300 000 people

6.3.4.2 Large Centres – 200 000 people

6.3.4.3 Small Centres – 60 000 people

6.3.4.4 Satellite/Mobile Centres – Less than 20 000 people

6.4 Potential benefits emanating from the recommendations

6.4.1 The implementation of the proposed measures could potentially provide access to an

additional 900 000 people and the high population demand on the existing Service

Centres, especially in eThekwini Metropolitan Municipality could be reduced.

7 NEED FOR FURTHER RESEARCH AND SCOPE FOR

FUTURE STUDIES

7.1 The study identified the need for further research in respect of the following: 7.1.1 Profiling the population catchment areas of all Thusong Service Centres in relation to

their service delivery, socio-economic, environmental and infrastructural

characteristics.

7.1.2 Reviewing the current mix of services that are provided at Thusong Service Centres.

Services should speak to the needs of service beneficiaries and the prevailing socio-

economic realities, in particular, youth unemployment and multi-dimensional

deprivation. Community should be consulted in order to define these challenges more

clearly and to identify appropriate and coordinated responses from the state.

7.1.3 Collection of user statistics and other operational end facilities data to gain insights

regarding type of services that are required more frequently.

7.1.4 Maintenance and updating of the database of Thusong Service Centres.



7.1.5 Possible utilisation of the South African Postal Services facilities and the deployment

of Mobile Services within sparsely populated areas.

8 ANNEXURE 1

8.1 Figures 19 to 29 illustrate the population coverage which is provided by the existing

Service Centres, as well as the 14 proposed locations in each District Municipality and

Metropolitan Municipality.

Figure 19: Population covered in Amajuba District Municipality



Figure 20: Population covered in eThekwini Metropolitan Municipality

Figure 21: Population covered in iLembe District Municipality



Figure 22: Population covered in Sisonke District Municipality

Figure 23: Population covered in Ugu District Municipality



Figure 24: Population covered in UMgungundlovu District Municipality

Figure 25: Population covered in Umkhanyakude District Municipality



Figure 26: Population covered in Umzinyathi District Municipality

Figure 27: Population covered in Uthukela District Municipality



Figure 28: Population covered in Uthungulu District Municipality

Figure 29: Population covered in Zululand District Municipality

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