Introduction

South Africa’s health landscape is shaped by entrenched socio-economic and environmental disparities, including elevated exposure to climate risks, persistent multidimensional poverty, and high unemployment.1 These factors intensify differential exposure and vulnerability to disease across provinces. South Africa also ranks among the top 25 countries globally for disability-adjusted life-years (DALYs) lost to mental disorders, with depression and anxiety alone accounting for an estimated 2.5 % of total years lived with disability.2

The country continues to bear the world’s largest national HIV burden. While diagnostic coverage is high, persistent gaps in treatment access and viral suppression, particularly among children, adolescents and key populations, underscore the need for targeted interventions.3 Tuberculosis (TB), including drug-resistant strains with modest treatment success rates, further compounds the epidemiological burden at the HIV and TB syndemic interface.4 Co-morbid depression and anxiety reduce antiretroviral adherence by up to 35%, amplifying morbidity and onward transmission risk.5

Maternal and neonatal health indicators reveal preventable mortality despite high institutional delivery rates and increasing caesarean section prevalence. This suggests that quality of care and emergency response capacity remain critical challenges. Declines in childhood immunisation coverage and under-five mortality rates that exceed Sustainable Development Goal (SDG) thresholds point to weaknesses in primary prevention systems. Concurrently, high levels of tobacco and alcohol use perpetuate avoidable burdens of chronic disease and injury.6,7 Emerging evidence links perinatal depression with suboptimal breastfeeding and immunisation uptake, underscoring the need for integrated maternal mental health services.8

Within this broader context, mental health has gained increasing policy and programmatic attention.9 Advances include the expansion of routine mental health indicators, the establishment of policy frameworks with defined targets, and the growth of longitudinal cohort platforms that enhance surveillance capacity. However, critical limitations persist. These include the limited integration of community-based and informal care data, insufficient disaggregation for equity-focused analyses, and inconsistent measurement standards. These gaps constrain the utility of available data for comprehensive planning, monitoring and evaluation. Productivity losses linked to untreated common mental disorders are estimated at 4–5% of South Africa’s gross domestic product (GDP), making mental health investment not only a rights imperative but also an economic priority.10

Health system performance and capacity constraints also affect the accessibility and quality of mental health services. These include uneven utilisation of primary health care (PHC), disparities in workload and bed occupancy, maldistribution of clinical and specialised human resources, and persistent financing inequities. Recent flood-related displacement in KwaZulu-Natal doubled the prevalence of post-traumatic stress symptoms among affected adolescents, highlighting how climate shocks magnify mental health needs.11

With a particular focus on mental health, this paper:

  1. consolidates the most recent multisource indicators across key health domains, with an enhanced focus on mental health;

  2. critically appraises the national health data architecture, including routine systems, longitudinal cohorts and administrative sources, highlighting strengths and limitations that affect interpretability and policy relevance; and

  3. identifies cross-cutting challenges related to equity, quality and governance that should inform integrated policy development and resource allocation strategies in pursuit of universal health coverage and the Sustainable Development Goals (SDGs) for 2030.

Data sources

Box 1 lists the key new or updated international and national sources consulted for this analysis. Specific references and the current indicator definitions are provided in the data tables.

Box 1.Sources used for this paper
International South African
  • Institute for Health Metrics (IHME)2
  • Global Cancer Observatory (GLOBOCAN)12
  • World Health Organization (WHO) Global Tuberculosis Report 202413
  • International Diabetes Federation (IDF) Diabetes Atlas 202514
  • WHO Immunization update 202515
  • WHO Mental Health Atlas 202016
  • State of Global Air 202417
  • State of the World’s Children 202418
  • Tobacco Atlas6
  • Joint United Nations Programme on HIV/AIDS (UNAIDS) data 202419
  • United Nations Development Programme (UNDP) Human Development Report 2023/241
  • WHO African Region Health Expenditure Atlas 202320
  • WHO Global Health Observatory21
  • WHO World Health Statistics 20257
  • WHO World Malaria Report 202422
  • Council for Medical Schemes (CMS) Industry Report 202323
  • Health Professionals Council of South Africa (HPCSA) Statistics24
  • National Cancer Registry25
  • National Treasury Health Expenditure data26
  • National Institute for Communicable Diseases (NICD) Surveillance Reports27
  • Personnel Administration System (PERSAL)28
  • Road Traffic Management Corporation (RTMC) Road Fatalities 202429
  • Saving Mothers 202330
  • South African Community Epidemiology Network on Drug Use (SACENDU)31
  • Statistics South Africa (Stats SA) General Household Survey (GHS) 202432
  • Stats SA Labour Force Surveys up to the 4th quarter of 202433
  • Stats SA Mid-year Population Estimates 202434
  • Stats SA Mortality and Causes of Death 202135
  • Stats SA Recorded Live Births 202336
  • The 2022 Antenatal HIV Sentinel Survey37
  • Thembisa v4.7 HIV and AIDS model38
  • District Health Information System (DHIS)39

Mental health indicators

The availability of mental health indicator datasets in South Africa, as outlined in Table 1, provides a foundational basis for monitoring and evaluating mental health trends and service delivery across the country. These datasets ─ derived from global and local sources such as the GBD, the WHO’s Mental Health Atlas, the DHIS, Stats SA, and surveys such as the South African National and Nutrition Examination Survey (SANHANES) and South African National HIV Prevalence, Incidence, Behaviour and Communication Survey (SABSSM) VI ─ offer valuable insights into the burden of mental illness, service utilisation, and treatment coverage.

One of the key strengths of these datasets lies in their routine collection and national coverage, which allows for longitudinal tracking of mental health indicators at national and sub-national levels. This is particularly important for identifying regional disparities and informing targeted interventions. The inclusion of indicators such as the number of mental health admissions, outpatient visits, and availability of mental health professionals provides a comprehensive view of the mental health system’s capacity and performance. However, outcome-orientated metrics such as 30-day re-admission, relapse and remission rates remain largely absent. Incorporating such measures would allow for assessment of service effectiveness and progress towards recovery-focused care.

Table 1.Global and local mental health data sources
Domain Most recent source (year) What you get
Population burden and epidemiology IHME GBD results tool (2024 release) DALYs, years of lived with disability (YLDs), prevalence and incidence for every mental-disorder category, 1990–2024
Stats SA: Mortality and Causes of Death series (latest: deaths registered 2021, issued 2024) Suicide and other mental-disorder International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) codes by age, sex, province
SABSSM VI National HIV Survey (fieldwork 2022, report 2024) K-10 psychological-distress scale and socio-demographics for 27 000 adults
SANHANES II (2023) Depressive-symptom prevalence, comorbidity with NCDs, health-behaviour correlates
National Planning Commission: Situational Analysis of Mental Health in SA (May 2024) Synthesises DHIS 2017–2023 caseload trends, facility audits and province comparisons
Service coverage and quality DHIS Standardised Mental Health Indicator Set (five routine indicators) PHC caseload, new-treatment rate, separation rate, involuntary admissions, child/adolescent attempted suicide rate
CMS Industry Report (private sector), 2023 Admissions for mental health institutions, mental health coverage, claims by workforce type
Mental-health workforce and beds WHO Mental Health Atlas – SA country profile (2020 edition, still the latest) Psychiatrists, psychologists, psychiatric nurses per 100 000; in-patient-bed ratios; legislation status
HPCSA Annual Report 2023/24 Registered practitioners by speciality and province (psychiatry, psychology, counselling)
Budget and expenditure National Department of Health (NDoH) Annual Report 2023/24 + Provincial BAS datasets Programme 2 sub-programme: Mental Health spend; performance targets
Policy indicators and targets National Mental Health Policy Framework and Strategic Plan 2023–2030 30 headline indicators with 2020 baseline and 2030 targets; specifies DHIS and human resources (HR) data flows
Help-seeking and sentiment UNICEF U-Report Youth Mental Health poll (2023/24) Perceived need for support, barriers, preferred channels (≈28 000 SA respondents)
Civil society service statistics South African Depression and Anxiety Group (SADAG) / South African Federation for Mental Health (SAFMH) helpline data (2023/24) Call volumes by age, gender, issue; regional heat-maps

Several limitations constrain the utility of these datasets. Firstly, the reliance on administrative data may lead to under-reporting or misclassification, especially in under-resourced settings where data-quality assurance mechanisms are weak. Secondly, the indicators often focus on service outputs rather than outcomes, limiting the ability to assess the effectiveness of mental health interventions. Additionally, the absence of disaggregated data by age, gender and socio-economic status hampers equity analyses. A further blind spot is the near-total exclusion of community-based, informal and digital mental health services, despite evidence that they comprise up to 40% of first-contact care in rural districts.9

Despite the growing recognition of mental health as a public health priority, there remains a significant gap in the literature and policy discourse regarding the role and extent of private-sector service provision in South Africa. Much of the existing analysis tends to focus predominantly on public-sector challenges, thereby overlooking the contributions, limitations and regulatory complexities of private mental health care. This lack of comprehensive coverage obscures a full understanding of the mental health landscape, particularly in terms of access, equity and quality of care across socio-economic groups. Future iterations should routinely integrate Council for Medical Schemes (CMS) claims data and large-insurer electronic records to create a full system view.

Another critical gap is the limited integration of community-based and informal mental health services into the national reporting systems. Given the significant role of Traditional Health Practitioners and Community Health Workers in mental health care, their exclusion from official statistics presents an incomplete picture of service provision. Furthermore, the datasets do not adequately capture the social determinants of mental health, such as poverty, violence and substance abuse, which are essential for a holistic understanding of mental health trends.

To enhance the relevance and impact of mental health indicators, there is a need for improved data governance, including standardised definitions, regular audits, and capacity-building for data collection and analysis. Integrating mental health indicators into broader health and development monitoring frameworks, such as the SDGs, could also elevate their policy visibility and resource prioritisation.

Longitudinal datasets supporting mental health monitoring

The availability of longitudinal mental health datasets (Table 2) in South Africa represents a significant advancement in the monitoring and evaluation of mental health outcomes. These datasets, such as Birth-to-Forty (Bt40), Dikgale, Mamabolo and Mothiba (DIMAMO) health and demographic surveillance systems (HDSS), and the Drakenstein Child Health Survey (DCHS), provide valuable insight into the temporal dynamics of mental health conditions across diverse populations. Their longitudinal nature allows for the tracking of mental health trajectories, identification of risk and protective factors, and evaluation of interventions over time.

A key strength of these datasets lies in their diversity of target populations, ranging from children and adolescents to older adults, and their inclusion of both urban and rural settings. This heterogeneity enhances the generalisability of findings and supports the development of context-specific mental health policies. Moreover, the integration of mental health indicators into broader health and demographic surveillance systems, such as South African Population Research Infrastructure Network (SAPRIN) and Health and Ageing in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSi), facilitates a more holistic understanding of mental health within the broader determinants of health framework.

However, several limitations must be acknowledged. Firstly, there is variability in the consistency and depth of mental health measures across studies, with some relying on self-reported symptoms and others using validated diagnostic tools. Secondly, access to data remains uneven, with some datasets being publicly available and others requiring direct contact with principal investigators, potentially limiting their utility for broader research and policy development. Thirdly, while many studies are ongoing, others have ceased data collection, raising concerns about sustainability and long-term impact.

Table 2.Summary of longitudinal datasets
Study name Institution, country Years active Target group Mental health disorder
Bt40 University of Witwatersrand (WITS), South Africa 1990─ ongoing Mothers and children (birth to 40 years) Depression, major depressive disorder (MDD), behavioural disorders, unspecified disruptive, impulse control, and conduct disorder
DIMAMO HDSS South African Medical Research Council (SAMRC) and University of Limpopo, South Africa 1996─ ongoing adult residents (15 years and older) Anxiety, depression, general anxiety disorder (GAD), MDD
DCHS University of Cape Town (UCT), South Africa 2012─ ongoing Pregnant women and children Depression, post-traumatic stress disorder (PTSD), distress
Evidence for Better Lives Study (EBLS) University of Cambridge 2019─ ongoing Pregnant women, fathers Psychological distress
Global Flourishing Study (GFS) Center for Open Science, Gallup, Harvard, United States of America (USA) 2022─ ongoing Varied1 Anxiety, depression
HAALSi SAMRC and WITS, South Africa 2014─ ongoing Adults ≥40 years Depression, PTSD, well-being
WHO Study on Global AGEing and Adult Health (SAGE) WHO: China, Ghana, India, Mexico, Russian Federation and South Africa 2002─ ongoing Adults ≥18 years Depression, well-being
Vukuzazi Africa Health Research Institute (AHRI), South Africa 2018─ ongoing Adults ≥15 years Alcohol use disorder (AUD), anxiety, depression, distress, well-being
Transfer Project UNICEF, Food and Agriculture Organization of the United Nations (FAO), University of North Carolina, Italy and USA 2008─ ongoing Varied1 Depression, distress,
well-being
SAPRIN SAMRC, South Africa 2016─ ongoing Varied1 Depression, MDD, anxiety
Siyakhula Cohort AHRI, South Africa 2012─ ongoing Children 7–11 years Attention Deficit/Hyperactivity Disorder (ADHD), anxiety, depression AUD,
antisocial behaviour,
GAD,
substance-related and addictive disorder
Prospective Urban and Rural Epidemiological Study (PURE) Public Health Research Institute, McMaster University, Canada 2001─ ongoing Varied1 Depression, MDD
National Income Dynamics Study (NIDS) UCT, and the Department
of Planning, Monitoring and Evaluation (DPME), South Africa
2008─ stopped Varied1 Depression, MDD
Migration Health Follow-up Study (MHFUS) Mpumalanga Province and Brown University, South Africa and USA 2018─ ongoing Adults 18–40 years Depression, MDD
International Epidemiologic Databases to Evaluate AIDS ─ Southern Africa (IeDEA-SA) UCT and University of Bern, South Africa and Switzerland 2006─ ongoing Varied1 Anxiety, depression, PTSD, suicide

1Age group or sex not outlined

The implications of these datasets for mental health policy and planning are profound. They offer a foundation for evidence-based decision-making, enable the identification of emerging trends, and support the evaluation of mental health interventions. To maximise their impact, efforts should be made to harmonise data-collection methodologies, ensure open access where feasible, and promote the integration of mental health indicators into national health information systems. Additionally, aligning indicator metadata with the WHO Indicator Metadata Registry List will facilitate international comparability.21

In conclusion, the landscape of mental health data in South Africa has evolved significantly, offering a diverse array of sources that collectively enhance understanding of mental health needs, service delivery, and population-level trends. Routine indicator datasets, such as those from the DHIS and national surveys, provide essential insights into system performance and access to care, while longitudinal cohort studies offer depth and nuance in understanding mental health trajectories over time. However, both types of data systems face challenges related to completeness, standardisation, and accessibility. Addressing these limitations through improved data governance, integration across platforms, and investment in sustainable data infrastructure is critical. Doing so will not only strengthen the evidence base for mental health policy and planning, but will also ensure that mental health is adequately prioritised within South Africa’s broader health and development agenda.

On a global level, demographic transitions are reshaping health systems and policy priorities. Many countries are experiencing declining fertility rates, increasing life expectancy and ageing populations, which are trends that mirror South Africa’s shift from a youthful to a more mature population structure.40 These shifts are already changing the mental health profile where, for example, dementia prevalence is projected to double by 2040, while depression among older adults is rising in tandem with multimorbidity.41

According to the United Nations’ World Population Prospects (2024),42 the global fertility rate has dropped to 2.3 children per woman, with significant regional variation. High-income countries often report rates below replacement level, while parts of sub-Saharan Africa still experience higher fertility.

Urbanisation

Urbanisation continues to accelerate worldwide, with over 56% of the global population now residing in urban areas. This trend places immense pressure on urban infrastructure, housing and health services, particularly in rapidly growing cities across Asia and Africa.43 South Africa’s concentration of population in Gauteng and KwaZulu-Natal reflects this global urban shift. Rapid urban growth is associated with increased exposure to crime, social isolation and ‘eco-anxiety’, which are all recognised drivers of common mental disorders in young adults.44

Ageing index

Ageing populations, especially in Europe, East Asia, and parts of Latin America, are driving demand for chronic disease management, geriatric care, and long-term health financing strategies. The global ageing index is rising, with countries like Japan and Italy already facing ratios above 50.42 South Africa’s ageing index of 33.5 suggests that it is entering this phase, necessitating proactive planning for age-appropriate services. Provincially, the Western Cape (33.1) and Gauteng (26.8) reflect more advanced demographic transitions compared to provinces like KwaZulu-Natal and Limpopo (both 18.8). This shift has implications for the burden of non-communicable diseases and the design of age-appropriate health services. Integrating geriatric psychiatry and caregiver-support indicators into routine surveillance would provide an early warning of service gaps.45

Population and births

The 2024 mid-year population estimates from Statistics South Africa34 reveal a national population of just over 63 million, with Gauteng (25.3%) and KwaZulu-Natal (19.5%) together accounting for nearly 45% of the total. Mental health-related disability benefits already cluster in these two provinces, highlighting the importance of co-locating psychosocial services within existing urban PHC networks. This concentration underscores the continued urbanisation trend and the associated pressure on infrastructure and health services in these provinces.

Live birth registrations in 2023 totalled 932 138, with the highest numbers recorded in Gauteng (219 023) and KwaZulu-Natal (205 831), aligning with their population shares. However, the total fertility rate has declined to 2.4 children per woman,34 indicating a continued demographic transition. This is also reflected in Figure 1 which shows that between 2004 and 2024, South Africa’s population pyramid transitioned from a youthful, broad-based structure to a more column-like shape, reflecting declining birth rates, a growing working-age population, and an increasingly ageing society. The crude death rate is estimated at 8.7 per 1 000 population, although provincial disaggregation is lacking, which limits more granular mortality analysis.

Figure 1
Figure 1.South Africa age-sex pyramid: 2004 vs 2024 (projected 2040 dashed)

Source: StatsSA Mid-year Estimates (MYE), 202434; United Nations Department of Economic and Social Affairs (UN DESA), 202442

Population density figures highlight stark contrasts where Gauteng’s density of 876.4 people/km² far exceeds the national average of 51.6, while the Northern Cape remains sparsely populated at just 3.7 people/km² (Table 3). High-density informal settlements report up to three-fold higher rates of depression and alcohol-use disorders than rural areas.46 These disparities have direct implications for service delivery models, with rural provinces requiring logistical and infrastructural approaches that differ from those needed in urban centres.

Table 3.Demographic indicators by province
Indicator Period Sex|Age|
Series|Cat
SA EC FS GP KZN LP MP NC NW WC Ref
Ageing index 2024 both sexes
mid-year
33.5 27.6 25.1 26.8 18.8 18.8 20.3 25.4 21.3 33.1 a
Crude death rate (deaths
per 1 000 population)
2024 both sexes
mid-year
8.7 a
Live birth occurrences registered 2023 vital registration total 932 138 101 901 44 552 219 023 205 831 114 688 74 967 24 490 55 520 91 146 b
Population 2024 both sexes
mid-year
63 015 904 a
female mid-year 32 129 704 a
male mid-year 30 886 200 a
Population % by province 2024 both sexes
mid-year
100 11.4 4.8 25.3 19.5 10.2 8.0 2.2 6.6 12.0 a
Population density
(per km2)
2024 mid-year 51.5 42.5 23.4 876.4 130.5 50.9 66.1 3.7 39.6 58.4 a
Public sector dependent (uninsured) population 2023 both sexes all ages GHS 52 491 846 5 895 776 2 624 569 12 916 030 10 716 242 5 640 806 4 424 424 1 107 729 3 690 519 5 475 946 a
2024 both sexes all ages GHS 53 369 336 5 856 558 2 648 787 13 099 118 10 740 162 5 609 642 4 424 424 1 099 882 3 681 986 5 498 056 a
Total fertility rate 2022-2024 female mid-year 2.4 a

Sources:
a: StatsSA MYE 202434
b: StatsSA Recorded Live Births 202336

Indicator [units]: Definition

• Ageing index [Number]: Ratio of the number of people 65+ to the number under 15 years, i.e. a value of 16 means that there are 16 people aged 65 and older for every 100 under 15 years of age. Calculated as ([65+/0─14]*100).

• Crude death rate [per 1 000 population]: Number of deaths in a year per 1 000 population.

• Live birth occurrences registered [Number]: The number of live birth occurrences registered.

• Population [Number]: Total number of people. Projected population figures are based on various projection models attempting to quantify the expected effects of HIV and AIDS on population growth.

• Population % by province [Percentage]: Proportion of South African population in each province (calculated from population per province and population for the whole of South Africa).

• Population density [people per km2]: The number of people per square kilometre.

• Public sector-dependent (uninsured) population [Number]: This is an adjustment of the total population to the number assumed to be dependent on services in the public health sector based on medical scheme (health insurance) coverage. It is calculated by subtracting the number of people with medical scheme cover (determined from medical scheme membership reports, or surveys indicating percentage of population on medical schemes) from the total population.

• Total fertility rate [Number]: The average number of children that a woman gives birth to in her lifetime, assuming that the prevailing rates remain unchanged.

Uninsured population estimates

The reliance on public health systems is a common feature in many low- and middle-income countries. With 85% of South Africans being dependent on public health services, the challenge of equitable resource allocation is shared globally.32 Incorporating a short validated mental health screening tool (e.g. PHQ-9, GAD-7) into the next General Household Survey (GHS) would enable province-level prevalence estimates for the first time.

As the estimated uninsured populations per province and district are important denominators for a wide range of indicators, the estimates of the uninsured population in South Africa down to district level has been updated (Table 4). The proportion of uninsured to insured individuals has not shifted significantly in recent years, as high costs continue to pose a barrier to private medical aid. Nevertheless, regular updates to these estimates are essential to ensure continued relevance and accuracy in health system planning and decision-making.

Table 4.Uninsured population estimates, 2024
Province District municipality name District municipality code Calculated coverage % Uninsured population % 2022 estimates (Population source:
Census 2022)
2024 estimates (Population source:
GHS 2024 Mid-year)
2022 population Covered Not covered 2024 population Covered Not covered
Eastern Cape Buffalo City BUF 20.9% 79.1% 975 255 203 828 771 427 967 961 202 304 765 657
Western Cape Cape Town CPT 27.8% 72.2% 4 772 846 1 326 851 3 445 995 4 856 044 1 349 980 3 506 064
Western Cape West Coast DC1 18.5% 81.5% 497 394 91 819 405 575 506 064 93 419 412 645
Eastern Cape Sarah Baartman DC10 10.3% 89.7% 533 253 54 925 478 328 529 265 54 514 474 751
Eastern Cape Amathole DC12 5.8% 94.2% 871 601 50 553 821 048 865 082 50 175 814 907
Eastern Cape Chris Hani DC13 5.4% 94.6% 828 387 44 733 783 654 822 192 44 398 777 794
Eastern Cape Joe Gqabi DC14 5.5% 94.5% 393 048 21 618 371 430 390 108 21 456 368 652
Eastern Cape OR Tambo DC15 4.7% 95.3% 1 501 702 70 580 1 431 122 1 490 570 70 057 1 420 513
Free State Xhariep DC16 12.5% 87.5% 131 901 16 488 115 413 135 444 16 931 118 513
Free State Lejweleputswa DC18 14.0% 86.0% 679 746 95 164 584 582 698 007 97 721 600 286
Free State Thabo Mofutsanyane DC19 11.2% 88.8% 831 421 93 119 738 302 853 758 95 621 758 137
Western Cape Cape Winelands DC2 18.7% 81.3% 862 703 161 498 701 205 877 741 164 313 713 428
Free State Fezile Dabi DC20 15.2% 84.8% 509 912 77 507 432 405 523 611 79 589 444 022
KwaZulu-Natal Ugu DC21 7.1% 92.9% 773 402 54 834 718 568 766 480 54 343 712 137
KwaZulu-Natal uMgungundlovu DC22 7.9% 92.1% 1 235 715 98 116 1 137 599 1 224 655 97 238 1 127 417
KwaZulu-Natal uThukela DC23 6.2% 93.8% 789 092 48 608 740 484 782 030 48 173 733 857
KwaZulu-Natal uMzinyathi DC24 5.2% 94.8% 649 261 34 021 615 240 643 450 33 717 609 733
KwaZulu-Natal Amajuba DC25 7.2% 92.8% 687 408 49 356 638 052 681 256 48 914 632 342
KwaZulu-Natal Zululand DC26 5.2% 94.8% 942 794 48 742 894 052 934 356 48 306 886 050
KwaZulu-Natal uMkhanyakude DC27 4.7% 95.3% 738 437 35 002 703 435 731 828 34 689 697 139
KwaZulu-Natal King Cetshwayo DC28 6.7% 93.3% 1 021 344 68 839 952 505 1 012 203 68 222 943 981
KwaZulu-Natal iLembe DC29 6.5% 93.5% 782 661 50 951 731 710 775 656 50 495 725 161
Western Cape Overberg DC3 19.8% 80.2% 359 446 71 314 288 132 365 712 72 557 293 155
Mpumalanga Gert Sibande DC30 10.5% 89.5% 1 283 459 135 277 1 148 182 1 262 083 133 024 1 129 059
Mpumalanga Nkangala DC31 10.6% 89.4% 1 588 684 168 718 1 419 966 1 562 224 165 908 1 396 316
Mpumalanga Ehlanzeni DC32 9.8% 90.2% 2 270 897 221 640 2 049 257 2 233 355 217 975 2 015 380
Limpopo Mopani DC33 7.9% 92.1% 1 372 873 108 869 1 264 004 1 337 338 106 051 1 231 287
Limpopo Vhembe DC34 8.0% 92.0% 1 653 022 132 076 1 520 946 1 610 290 128 662 1 481 628
Limpopo Capricorn DC35 9.1% 90.9% 1 447 103 132 121 1 314 982 1 409 649 128 701 1 280 945
Limpopo Waterberg DC36 9.7% 90.4% 762 862 73 616 689 246 743 116 71 711 671 405
North West Bojanala DC37 14.9% 85.1% 1 624 144 242 485 1 381 659 1 774 192 264 887 1 509 305
North West NM Molema DC38 11.3% 88.7% 937 723 106 338 831 385 1 024 175 116 141 908 034
North West Dr RS Mompati DC39 9.5% 90.5% 508 192 48 126 460 066 555 044 52 563 502 481
Western Cape Garden Route DC4 20.8% 79.2% 838 457 174 315 664 142 853 072 177 354 675 718
North West Dr K Kaunda DC40 14.0% 86.0% 734 203 102 862 631 341 801 892 112 345 689 547
Gauteng Sedibeng DC42 18.7% 81.3% 1 190 688 222 540 968 148 1 256 328 234 808 1 021 520
KwaZulu-Natal Harry Gwala DC43 5.2% 94.8% 563 893 29 548 534 345 558 846 29 284 529 562
Eastern Cape Alfred Nzo DC44 4.3% 95.7% 936 462 40 268 896 194 926 458 39 967 889 491
North West John Taolo Gaetsewe DC45 14.6% 85.4% 272 454 39 887 232 567 275 869 40 387 235 482
Limpopo Sekhukhune DC47 7.8% 92.2% 1 336 805 103 870 1 232 935 1 302 203 101 181 1 201 022
Gauteng West Rand DC48 21.7% 78.3% 998 466 216 867 781 599 1 053 510 228 822 824 688
Western Cape Central Karoo DC5 14.7% 85.3% 102 173 14 999 87 174 103 954 15 260 88 694
Northern Cape Namakwa DC6 15.8% 84.3% 148 935 23 457 125 478 150 802 23 751 127 051
Northern Cape Pixley ka Seme DC7 14.1% 85.9% 216 589 30 582 186 007 219 304 30 966 188 338
Northern Cape Z F Mgcawu DC8 15.8% 84.2% 283 624 44 813 238 811 287 179 45 374 241 805
Northern Cape Frances Baard DC9 15.7% 84.3% 434 343 68 192 366 151 439 788 69 047 370 741
Gauteng Ekurhuleni EKU 22.4% 77.6% 4 066 691 910 939 3 155 752 4 290 880 961 157 3 329 723
KwaZulu-Natal eThekwini ETH 21.0% 79.0% 4 239 901 889 107 3 350 794 4 201 953 881 150 3 320 803
Gauteng Johannesburg JHB 19.8% 80.2% 4 803 262 951 046 3 852 216 5 068 057 1 003 475 4 064 582
Free State Mangaung MAN 18.7% 81.3% 811 431 151 738 659 693 833 230 155 814 677 416
Eastern Cape Nelson Mandela Bay NMA 21.3% 78.7% 1 190 496 253 576 936 920 1 181 593 251 679 929 914
Gauteng Tshwane TSH 30.0% 70.0% 4 040 315 1 212 095 2 828 220 4 263 050 1 278 915 2 984 135
South Africa 15.7% 84.3% 62 026 876 9 718 433 52 308 443 63 015 904 9 963 491 53 052 413

Methodology

To estimate the uninsured population per district, estimates of medical scheme coverage at that level were first determined. The GHS captures medical scheme coverage; however, it is statistically representative at the provincial level. The Census, on the other hand, provides detailed population data at the district level but does not record medical scheme coverage. Applying the average provincial medical scheme coverage from the GHS to all districts in the Census would not accurately reflect district-level demographics, as key factors influencing coverage (such as income or educational level) can vary greatly between districts, even within the same province.

To create a representative estimate, a small area estimation model was built to estimate medical scheme coverage within districts in provinces. The model was trained on the GHS 202432 using key variables to predict medical scheme coverage. The relationships between these variables were then used to predict coverage probabilities for households in the Census 2022 microdata. This approach enabled more granular and realistic estimates at the district level, overcoming the limitations of both datasets when used in isolation. A more detailed methodology is available on request.

Results

The small area estimation model produced detailed estimates of medical scheme coverage across South African districts. The key findings showed that medical scheme coverage rates differ between districts within provinces, as expected. These results highlight the socio-economic and demographic differences that cannot be captured by high-level provincial averages alone. The updated estimates indicate that approximately 84.3% of the population remains uninsured nationally, with higher uninsured proportions being concentrated in rural and lower-income districts.

Socio-economic and environmental risk factors

Across the globe, socio-economic and environmental determinants are increasingly recognised as critical drivers of health outcomes. Crucially, they also explain an estimated 30–40% of the variance in common mental disorder prevalence, underscoring why mental health cannot be separated from broader development agendas.47 The WHO and United Nations Development Programme (UNDP) have consistently highlighted how poverty, lack of access to quality education, unemployment, inadequate housing, and harmful environmental exposures shape population health and contribute to widening health inequities.

Air pollution

Air pollution is now the second-largest leading risk factor for premature death world. The impact of particulate matter (PM2.5) on global life expectancy is comparable to that of smoking, more than four times that of high alcohol use, more than five times that of transport injuries like car crashes, and more than six times that of HIV/AIDS.48 According to the 2024 State of Global Air Report, 99% of the world’s population lives in places with unhealthy levels of PM2.5 pollution, and air pollution from PM2.5 and ozone was estimated to contribute to 8.1 million deaths worldwide.48 Urban centres in South and East Asia, parts of Africa, and Latin America face particularly high PM2.5 levels, mirroring the challenges seen in South Africa’s industrial provinces like Gauteng and Mpumalanga. Long-term exposure to PM2.5 is also linked to higher odds of depression (OR 1.11 per 10 µg/m³) and cognitive decline,49 making clean-air policy a mental health as well as a cardiovascular imperative. In 2022, Gauteng recorded the highest PM2.5 levels at 43.14 µg/m³, followed by Free State (26.08) and Mpumalanga (22.76), all well above the WHO guideline of 5 µg/m³.17 Western Cape, by contrast, reported the lowest level at 4.3 µg/m³, reflecting regional disparities in environmental exposure.

Poverty

Multidimensional poverty remains a global concern, especially in low- and middle-income countries. In South Africa, adults living in the bottom income quintile face twice the prevalence of psychological distress compared with the top quintile.50 While global extreme poverty has declined, over 1.1 billion people still experience multidimensional poverty, with the largest burdens occurring in sub-Saharan Africa and South Asia. Like South Africa, many countries face overlapping deprivations in health, education and living standards, which compound vulnerability to disease and limit access to care.1 South Africa’s Human Development Index (HDI) stands at 0.7, placing it 105th globally which is indicative of moderate development but persistent inequality. While only 0.9% of the population is classified as being in severe multidimensional poverty, 12.2% are considered as being vulnerable to it.1 The largest contributor to deprivation is standard of living (47.4%), followed by health (39.5%) and education (13.1%). These figures highlight the interlinked nature of poverty and health, where inadequate housing, poor nutrition, and limited access to services compound health risks. Notably, 3% of adults aged 20 years and older have no formal schooling, with the highest rates recorded in Limpopo (5.7%) and Mpumalanga (5.5%).32

Unemployment

Unemployment and under-employment are global challenges, especially among youth, which in South Africa exceeds 45%.33 The International Labour Organization (ILO) reports that youth unemployment rates are three times higher than adult rates globally, with significant implications for mental health, social cohesion, and long-term economic stability.51 The official unemployment rate remains high at 32.9%, with Eastern Cape (39.3%), North West (40.4%), and Free State (37.9%) facing the highest rates. Western Cape, at 19.6%, is the only province below 20%, reflecting stronger labour market absorption.33

Climate change

Climate change amplifies existing vulnerabilities. The April 2022 floods in KwaZulu-Natal doubled probable post-traumatic stress symptoms among displaced adolescents,11 illustrating how extreme weather fuels mental health crises. Rising temperatures, extreme weather events and environmental degradation disproportionately affect low-income populations and exacerbate health risks. Countries worldwide are increasingly adopting a ‘Health in All Policies’ approach to address these interconnected challenges through multisectoral collaboration.52

Housing and basic services

Housing and basic service access indicators further illustrate inequality. Nationally, 84.1% of households live in formal dwellings, but informal housing remains prevalent in provinces like Western Cape (18.6%) and North West (17.2%). Access to piped water is high nationally (87.7%) but drops to 62.9% in Limpopo and 69.9% in Eastern Cape. Similarly, access to improved sanitation is lowest in Limpopo (62.2%) and Mpumalanga (66.6%), compared to 97.1% in Western Cape.32

These socio-economic and environmental indicators, as illustrated in Table 5, underscore the need for a multisectoral approach to health. Health system interventions alone are insufficient. Progress towards universal health coverage and improved population well-being will require co-ordinated action across housing, education, employment, sanitation, and environmental regulation. Embedding health equity into all policies and strengthening interdepartmental collaboration are essential to mitigate the health impacts of socio-economic and environmental risk factors.52

Table 5.Socio-economic and environmental risk indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Air pollution level in cities (particulate matter [PM]) 2022 AQLI PM2.5 23.3 11.9 26.1 43.1 20.2 14.3 22.8 13.6 29.6 4.3 a
Education as a contributor of deprivation in dimension to overall multidimensional poverty 2023/24 both sexes all ages UNDP 13.1 b
Education level: percentage of population with no schooling 2024 both sexes 20+ years GHS 3.0 3.7 2.7 1.1 3.8 5.7 5.5 3.7 5.2 0.9 c
Formal dwellings 2024 both sexes all ages GHS 84.1 77.0 84.0 82.3 84.5 95.3 90.6 85.2 82.7 80.8 c
Health as a contributor of deprivation in dimension to overall multidimensional poverty 2023/24 both sexes all ages UNDP 39.5 b
Percentage of female-headed households 2024 female GHS 42.4 48.8 43.2 37.3 46.8 46.5 46.7 45.8 38.8 39.7 c
female GHS Rural 47.1 c
female GHS Urban 40.4 c
Percentage of households by type of housing 2024 both sexes GHS Formal 84.1 77.0 84.0 82.3 84.5 95.3 90.6 85.2 82.7 80.8 c
both sexes GHS Informal 11.7 4.6 14.9 17.2 4.9 2.5 6.7 14.1 17.2 18.6 c
both sexes GHS Other 0.3 0.6 0.0 0.5 0.3 0.1 0.0 0.3 0.0 0.4 c
both sexes GHS Traditional 3.9 17.7 1.1 0.1 10.3 2.2 2.7 0.4 0.1 0.2 c
Percentage of households using electricity for cooking 2024 both sexes GHS 90.2 93.4 92.8 83.2 93.5 96.6 89.4 90.9 90.1 96.0 c
Percentage of households with access to improved sanitation 2024 both sexes GHS Formal 83.1 89.9 86.4 91.3 77.8 62.2 66.6 84.3 72.7 97.1 c
Percentage of households with access to piped water 2024 both sexes GHS 87.7 69.9 94.8 98.0 82.9 62.9 87.5 95.1 86.0 99.0 c
Percentage of households with no toilet / bucket toilet 2024 both sexes GHS Formal 0.7 2.4 0.9 0.1 0.6 0.6 1.2 3.6 1.3 0.0 c
Percentage of households with refuse removal 2024 both sexes GHS Communal refuse dump 6.2 4.2 5.6 4.7 8.0 3.9 3.0 8.0 7.1 c
both sexes GHS Dump or leave rubbish anywhere 1.8 c
both sexes GHS Other 0.3 2.6 4.4 2.1 1.1 2.3 2.0 7.3 0.3 c
both sexes GHS Own refuse dump 28.1 49.8 16.3 44.3 64.5 49.0 23.9 5.7 1.0 c
both sexes GHS Removed at least once per week 61.3 43.4 73.7 49.9 25.3 45.1 65.8 84.3 91.5 c
both sexes GHS Removed less than once per week 2.3 c
Percentage of households with telephone (telephone in dwelling or cell-phone) 2024 both sexes GHS 3.9 7.3 8.9 1.9 2.6 2.0 8.6 5.9 4.2 c
both sexes GHS Cell and landline 3.3 1.4 3.1 1.7 3.7 3.0 1.5 1.7 5.1 c
both sexes GHS Only cell 92.8 91.3 87.9 96.4 93.6 94.9 90.0 92.3 90.7 c
both sexes GHS Only landline 0.1 0.1 0.1 0.0 0.1 0.1 0.0 0.1 0.1 c
Population in severe multidimensional poverty 2023/24 both sexes all ages UNDP 0.9 b
Population vulnerable to multidimensional poverty 2023/24 both sexes all ages UNDP 12.2 b
Standard of living as a contributor of deprivation in dimension to overall multidimensional poverty 2023/24 both sexes all ages UNDP 47.4 b
Unemployment rate (official definition) 2024 Q4 both sexes 15-64 years LFS 32.9 39.3 37.9 34.7 32.3 33.3 35.4 29.5 40.4 19.6 d

Sources:
a: AQLI 202417
b: HDR 2023/241
c: StatsSA GHS 202432
d: Labour Force Survey Q4 202433

Indicator [units]: Definition

• Air pollution level in cities (particulate matter [PM]) [ug/m3]: Annual mean concentration of particulate matter of less than 2.5 microns of diameter (PM2.5) [ug/m3] (or of less than 10 microns [PM10] if PM2.5 is not available) in cities.

• Education level: percentage of population with no schooling [Percentage]: Percentage of people in a given age group who have received a particular level of education. Data are presented for the percentage of population aged 20 years and older with no schooling. In some cases, the indicator is presented for a different age category, depending on what is available in the source.

• Education as a contributor of deprivation in dimension to overall multidimensional poverty [Percentage]: The proportion of the MPI (poverty burden) attributable to education-related deprivations.

• Formal dwellings [Percentage]: Percentage of households living in formal dwellings.

• Health as a contributor of deprivation in dimension to overall multidimensional poverty [Percentage]: The percentage share of overall multidimensional poverty that is attributable to deprivations in the health dimension (nutrition and child mortality).

• Percentage of female-headed households [Percentage]: Percentage of female-headed households.

• Percentage of households by type of housing [Percentage]: Percentage of households that are categorised as formal, informal, traditional or other.

• Percentage of households using electricity for cooking [Percentage]: Percentage of households using electricity as their main energy source for cooking.

• Percentage of households with access to improved sanitation [Percentage]: Percentage of households using improved sanitation facilities (including flush to piped sewer system, flush to septic tank, flush/pour flush to pit, flush/pour flush to elsewhere).

• Percentage of households with access to piped water [Percentage]: Includes households with piped water in dwelling, piped water inside yard, or piped water on a community stand (<200m away or further).

• Percentage of households with no toilet / bucket toilet [Percentage]: Percentage of households that have no toilet, or were using a bucket toilet.

• Percentage of households with refuse removal [Percentage]: Percentage of households that have refuse removal by the local authority at least once a week.

• Percentage of households with telephone (telephone in dwelling or cell phone) [Percentage]: Percentage of households with a telephone in the dwelling or a cellular telephone.

• Population in severe multidimensional poverty [Percentage]: The proportion of people who are multidimensionally poor and deprived in at least half of the weighted indicators.

• Population vulnerable to multidimensional poverty [Percentage]: The proportion of people who are not yet multidimensionally poor but are deprived in 20–33% of the weighted indicators, and are thus at risk of falling into multidimensional poverty.

• Standard of living as a contributor of deprivation in dimension to overall multidimensional poverty [Percentage]: The percentage share of overall multidimensional poverty that is attributable to deprivations in the standard of living dimension (e.g. housing, assets, electricity, water, sanitation, and cooking fuel).

• Unemployment rate (official definition) [Percentage]: The official definition of the unemployed is that they are those people within the economically active population (aged 15─65) who:

   (a) did not have a job or business during the seven days prior to the interview,
   (b) want to work and are available to work within two weeks of the interview, and
   (c) have taken active steps to look for work or to start some form of self-employment in the four weeks prior to the interview.

HIV

Although significant progress has been made in prevention, diagnosis and treatment, HIV remains a major public health challenge. According to UNAIDS,19 approximately 39 million people are living with HIV worldwide, with sub-Saharan Africa accounting for nearly two-thirds of the global burden. South Africa continues to have the highest national prevalence, but similar patterns are observed in countries like Nigeria, Mozambique, and Kenya.19

The global push toward the UNAIDS 95-95-95 targets for epidemic control has seen uneven progress. While many high-income countries have achieved or are close to achieving these targets, several low- and middle-income countries still face gaps, particularly in treatment access and viral suppression among adolescents and key populations. These gaps are likely to worsen due to the cuts in US funding for HIV programmes, which have already led to declines in testing and treatment in several countries. The results from a recent modelling exercise show that longer-term reductions in donor funding could lead to an additional 10.8 million HIV infections and 2.9 million deaths by 2030, over and above what would have occurred with the support of HIV programmes remaining in place.53

According to Thembisa v4.7,38 KwaZulu-Natal (1.95 million) and Gauteng (1.86 million) account for nearly half of all people living with HIV (PLHIV) in South Africa, underscoring the need for sustained, province-specific responses. The South African National AIDS Council’s (SANAC) National Strategic Plan (NSP) 2023─20283 outlines ambitious targets for HIV and TB to help South Africa eliminate these diseases as public health threats by 2030.

Table 6.HIV 2028 targets summary
Target area Baseline value (year) 2028 goal
New HIV infections 198 311 (2021) ↓ to 81 467 annually
Mother-to-child transmission 0.91% (2021/22) at 10 weeks, 2.9% at 18 months ↓ to 0.46% at 10 weeks, 1.4% at 18 months
Treatment cascade (95-95-95) 94.2% know status (2022) → 75% on ART (2022) → 92% virally suppressed (2022) 96.5% know status → 95% on ART → 97% virally suppressed
AIDS-related deaths 71 663 (2021) ↓ to 52 580 annually
Key populations HIV prevalence
  • FSW: 57.9% (2022),
  • MSM: 29.9% (2022),
  • PWID: 21% (2017),
  • TG: 51.9% (2021),
  • Inmates: 17.5% (2021)
↓ across all groups
  • FSW: 48.5%
  • MSM: 26.1%
  • PWID: 16%
  • TG: 45%
  • Inmates: 17.5%
PHC client treated for mental disorders 69 139 (2021/22) 256 708

Source: SANAC HIV, TB; STI NSP, 20253
FSW = female sex worker; MSM = men who have sex with men; PWID = people who inject drugs; TG = transgender

Encouragingly, the first 95 target, which is knowledge of HIV status, has been largely achieved, with 95% of PLHIV being aware of their status.19 However, gaps remain in treatment and viral suppression, particularly among adolescents and key populations.

HIV prevalence

HIV prevalence among antenatal clients aged 15–49 remains high at 21.5% in 2024, with the highest rates shown in KwaZulu-Natal (27.3%) and Mpumalanga (28.1%).38 These figures reinforce the need for integrated sexual and reproductive health services and continued investment in prevention of mother-to-child transmission (PMTCT) programmes.

The data also highlight the disproportionate burden among key populations, where HIV prevalence is estimated at 62.3% among sex workers, 58.0% among transgender people, and 29.7% among men who have sex with men.19 This calls for targeted, rights-based interventions and the removal of structural barriers to care ─ even more so as key populations are being disproportionately affected by the US funding cuts which specifically prevent any funding in HIV programmes being allocated to support them.

Antiretroviral therapy coverage

In response to the global funding cuts, South Africa launched the Close the Gap campaign in February 2025 which aims to enrol an additional 1.1 million PLHIV on life-saving treatment by the end of 2025.53 According to the 2024 DHIS data, antiretroviral therapy (ART) coverage (the second 95) stands at 77.1% nationally, but is notably lower among children aged 0–14 (60.6%) and youth aged 15–24 (54.3%). Provinces such as Limpopo (65.1%) and Mpumalanga (73.4%) fall below the national average, while KwaZulu-Natal leads with 86.6% coverage.39 Among key populations, ART coverage is highest among female sex workers (74.5%) and lowest among men who have sex with men (63.7%), reflecting persistent barriers to access and stigma.19

Viral suppression

As illustrated by Figure 2, viral load suppression (the third 95) remains below target at 66.8% nationally, with even lower rates among children (41.2%) and men aged 15 and older (61.3%). Western Cape (54.4%) and KwaZulu-Natal (78.8%) show the widest provincial variation, highlighting the importance of differentiated care models and adherence support.54

Figure 2
Figure 2.HIV care cascade: national vs key populations, 2024

Source: DHIS39; UNAIDS, 202419

HIV and mental health integration

Mental health integration into HIV care is gaining traction worldwide. The bidirectional relationship between HIV and mental health, whereby depression, anxiety and trauma affect ART adherence and outcomes, is increasingly recognised. Countries like Brazil and Thailand have begun to embed psychosocial support into HIV programmes, aligning with South Africa’s strategic emphasis on integrated care.55 The 2023–2028 NSP3 explicitly elevates mental health within Goal 1, Objective 1.7 “Integrate and standardise delivery and access to mental health services”, recognising the bidirectional links between HIV, TB, sexual and gender-based violence (SGBV), human rights violations, inequalities, and mental health. By foregrounding integration, the NSP positions routine HIV/TB platforms as entry-points for early identification of depression, anxiety and trauma, and for referral pathways that include psychosocial support, law and policy reform, redress mechanisms, dignified survivor-centred services, and sensitised health facilities and personnel. This strategic emphasis strengthens the rationale for embedding mental health screening and support within adherence clubs, adolescent/youth models, PMTCT, and key population programmes to accelerate progress towards achieving the second and third 95s (Table 7).3

Table 7.HIV indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Total living with HIV 2024 Q1 both sexes all ages NDoH-Thembisa 7 850 921 881 854 429 252 1 909 663 1 979 164 717 039 754 588 105 977 542 361 531 023 a
People living with HIV (PLHIV) 2023 both sexes 0─14 years Global report 160 000 b
both sexes all ages Global report 7 700 000 b
female 15 years and older Global report 4 900 000 b
male 15 years and older Global report 2 600 000 b
2024 both sexes all ages Thembisa 4.7 7 881 970 885 252 408 309 1 861 750 1 946 960 722 302 807 350 103 883 494 362 558 817 c
HIV prevalence (age 15─49) 2023 both sexes 15─19 years Global report 17.1 b
HIV prevalence (total population) 2023 both sexes all ages Global report Prisoners 7.0 b
both sexes all ages Global report Sex workers 62.3 b
both sexes all ages Global report Transgender people 58.0 b
male all ages Global report Men who have sex with men 29.7 b
Percentage of people living with HIV (PLHIV) who know their status (1st 95) 2023 both sexes 0─14 years Global report 87.0 b
both sexes all ages Global report 95.0 b
female 15 years and older Global report 96.0 b
male 15 years and older Global report 94.0 b
Number of patients receiving ART 2024 both sexes all ages Thembisa 4.7 6 076 240 646 495 334 960 1 377 300 1 686 160 470 411 626 080 76 154 386 137 365 441 c
Antiretroviral coverage (2nd 95) 2024 both sexes 0─4 years Thembisa 4.7 60.6 59.9 51.9 42.8 55.6 46.9 49.8 69.0 55.3 67.0 c
both sexes 15─24 years Thembisa 4.7 54.3 46.4 62.5 52.5 67.8 42.6 56.7 46.8 57.7 38.9 c
both sexes all ages Thembisa 4.7 77.1 73.1 82.0 74.0 86.6 65.1 77.6 73.4 78.1 65.4 c
both sexes all ages Thembisa 4.7 Female sex worker clients 71.3 66.4 78.5 70.0 84.1 55.9 72.9 66.7 72.2 59.3 c
both sexes all ages Thembisa 4.7 Men who have sex with men 63.7 59.8 67.7 63.6 78.0 48.3 64.4 58.3 64.4 51.2 c
female 15 years and older Thembisa 4.7 80.4 76.3 84.9 76.9 89.1 69.5 80.9 76.8 81.8 68.2 c
female 15─24 years Thembisa 4.7 53.8 45.7 60.8 51.0 66.6 42.2 55.9 46.3 57.4 38.0 c
female all ages Thembisa 4.7 Female sex workers 74.5 70.5 80.1 70.7 86.0 63.1 76.9 71.5 76.5 60.7 c
male 15 years and older Thembisa 4.7 71.6 67.0 78.6 70.5 84.0 56.7 73.1 66.9 72.7 59.6 c
males 15─24 years Thembisa 4.7 55.5 48.3 65.9 56.0 70.4 43.4 58.6 48.0 58.5 41.2 c
HIV viral load suppression (3rd 95) 2023 both sexes 0─14 years Global report 47.0 b
both sexes 0─14 years Thembisa 4.7 <400 copies/ml 41.2 39.5 38.7 31.3 42.7 29.3 33.2 45.1 36.5 54.4 c
both sexes all ages Global report 71.0 b
both sexes all ages Thembisa 4.7 <400 copies/ml 66.8 63.2 73.9 65.8 78.8 55.6 66.6 63.5 67.8 61.8 c
female 15 years and older Global report 75.0 b
female 15 years and older Thembisa 4.7 <400 copies/ml 70.4 66.9 77.4 69.1 82.0 60.2 70.5 67.4 72.1 64.9 c
male 15 years and older Thembisa 4.7 <400 copes/ml 61.3 56.8 69.9 62.0 75.6 47.2 61.5 56.9 61.9 56.3 c
males 15 years and older Global report 64.0 b
HIV prevalence among antenatal clients 2023 15─49 years Thembisa 4.7 22.4 24.5 24.0 21.8 28.7 17.2 29.0 13.2 22.4 13.9 c
2024 15─49 years Thembisa 4.7 21.5 23.8 23.0 21.0 27.3 16.7 28.1 12.8 21.5 13.4 c
HIV testing coverage 2023 both sexes 15+ years Thembisa 4.7 83.4 82.2 81.4 85.5 87.3 79.8 84.6 79.2 85.5 83.6 c
Male circumcision
(% of men who are circumcised)
2023 15─49 years Thembisa 4.7 64.1 80.1 66.4 73.5 58.0 92.4 79.5 39.8 55.9 44.9 c
2024 15─49 years Thembisa 4.7 65.6 80.4 67.6 75.1 50.4 92.7 81.1 41.7 57.6 45.6 c

Sources:
a: DHIS39
b: UNAIDS 202419
c: Thembisa v4.738

Indicator [units]: Definition

• Antiretroviral coverage (2nd 95) [Percentage]: The number of patients receiving ART, divided by the number needing treatment. The denominator has changed over time, due to changes in treatment guidelines affecting the criteria for treatment eligibility. The latest definition is that all HIV-infected patients should be on ART. This indicator is also one of the UNAIDS 95-95-95 global targets for epidemic control.

• HIV prevalence (age 15─49) [Percentage]: Percentage of population (age 15─49) estimated to be HIV-positive.

• HIV prevalence (total population) [Percentage]: Percentage of population estimated to be HIV-positive.

• HIV prevalence among antenatal clients [Percentage]: Percentage of women surveyed testing positive for HIV.

• HIV testing coverage [Percentage]: Percentage of target population who have been tested for HIV.

• HIV viral load suppression (3rd 95) [Percentage]: Percentage of people on ART who are virologically suppressed (VL level <= 1 000 copies/mL). This indicator is also one of the UNAIDS 95-95-95 global targets for epidemic control.

• Male circumcision (% of men who are circumcised) [Percentage]: The percentage of men (15─59 years, unless otherwise specified) who have been circumcised.

• Number of patients receiving ART [Number]: Number of patients receiving ART.

• People living with HIV (PLHIV) [Number]: The number of people who are HIV-positive.

• Percentage of people living with HIV (PLHIV) who know their status (1st 95) [Percentage]: Percentage of people living with HIV who know their HIV status. This indicator is also one of the UNAIDS 95-95-95 global targets for epidemic control.

• Total living with HIV [Number]: The estimated number of people who are HIV-positive.

Tuberculosis

Tuberculosis remains one of the top infectious disease killers, with an estimated 10.6 million people falling ill and 1.3 million deaths in 2023, according to the WHO Global TB Report.13 The burden is disproportionately concentrated in low- and middle-income countries, with India, Indonesia, China, the Philippines, Pakistan, Nigeria, and Bangladesh accounting for two-thirds of global cases. Drug-resistant TB poses a growing threat worldwide, with nearly half a million cases of rifampicin-resistant TB reported annually. Treatment success rates for multidrug-resistant TB (MDR-TB) remain below 60% globally, mirroring challenges seen in South Africa.13

Integration of TB and HIV services is a global priority, especially in high-burden regions. Innovations such as shorter treatment regimens, digital adherence technologies, and community-based care models are being scaled up to improve outcomes. Similar to the national Close the Gap campaign for HIV epidemic control, the End TB campaign in South Africa is a national effort to reduce TB incidence and mortality by 2035. The campaign’s initial phase focuses on expanding TB testing to reach 5 million people by 2025/26, with the goal of diagnosing 250 000 new TB cases. This effort is part of a broader strategy to eliminate TB as a public health threat in South Africa. Achieving the End TB targets will require sustained investment, political commitment, and multisectoral action to address the social determinants of TB, including poverty, malnutrition, and housing conditions.56

TB incidence

With an estimated incidence rate of 427 per 100 000 population in 2023,13 South Africa remains among the top 10 countries with the highest burden of TB, accounting for two-thirds of all TB infections globally.3 Among PLHIV, the incidence is particularly high at 230 per 100 000, reflecting the persistent syndemic relationship between TB and HIV. Similar to HIV, the SANAC NSP 2023─2028 outlines South Africa’s targets for TB for 2028, which are outlined in Table 8. The targets include increasing the TB case detection rate to 95% from 77% in 2022,57 indicating that nearly a quarter of cases may remain undiagnosed or unreported. In addition to this, the NSP seeks to increase TB treatment success across all forms of TB to 95% by 2028.3

Table 8.TB 2028 targets summary
Target area Baseline (year) 2028 goal
TB case detection 58% (2020) ↑ to 95%
TB incidence 304 000 (2021) 215 000
TB treatment success DS-TB: 78% (2020) and
MDR/XDR-TB: 66% (2019)
↑ to 90% for DS-TB and 75% MDR-/XDR-TB
TB preventive therapy (TPT) 63% 80% coverage with shorter regimens
TB mortality 56 000 (2021) Significant reduction (modelled)
TB screening and diagnosis Scale up digital chest X-rays, urine LAM, and universal screening

Source: SANAC HIV, TB & STI NSP, 20253
DS-TB = drug-susceptible tuberculosis; MDR/XDR-TB = multi-drug resistant / extensively drug-resistant tuberculosis

Drug-resistant TB

Drug-resistant TB continues to pose a significant threat. In 2022, 7 109 MDR-TB patients were recorded in the national cohort, with KwaZulu-Natal (1 736) and Eastern Cape (1 610) reporting the highest numbers.58 Treatment outcomes remain suboptimal: the national MDR-TB treatment success rate was 62.4%, with Western Cape trailing at just 52.5%. Loss to follow-up rates were also high, particularly in Western Cape (24.2%) and Gauteng (20.6%), suggesting systemic challenges in patient retention and adherence support.

Extensively drug-resistant TB (XDR-TB) outcomes are even more concerning. The national XDR-TB treatment success rate was only 51.0%, with mortality rates reaching 34.8% in Mpumalanga and 34.3% in Northern Cape. These figures highlight the urgent need for improved diagnostics, second-line treatment access, and patient-centred care models.

HIV and TB co-infection

The intersection of TB and HIV remains a critical concern. In 2022, 54% of TB incident cases were co-infected with HIV in South Africa, and the TB mortality rate among PLHIV was 49 per 100 000 in 2023.13 While the overall TB mortality rate has declined to 90 per 100 000, the mortality rate in South Africa remains among the highest globally. Notably, the mortality rate excluding HIV has plateaued at 39 per 100 000, indicating that broader TB control efforts must be intensified beyond the HIV-positive population. Interestingly, the 2021 StatsSA Causes of Death report showed that TB went from being ranked as the second-highest cause of death in 2019 (accounting for 5.5% of deaths) to the seventh-highest cause of death in 2021 (accounting for 2.9% of deaths).35

Efforts to address the social determinants of TB must also extend to the psychological and emotional well-being of patients. Depression, anxiety and stress not only reflect social disadvantage but also pose direct barriers to achieving the End TB targets, as demonstrated by a global review and meta-analysis. The review, which included a pooled estimate of 8 086 TB patients, reported a prevalence of 32.5% for anxiety, 32.9% for comorbid depression, and 52.7% for stress with the highest prevalence reported in the African region.35 More locally, a qualitative study based in Khayelitsha, Cape Town, found that patients living with HIV-associated TB scored higher in themes related to physical, social, and mental health aspects of health-related quality of life (HRQoL) assessments. In particular, concerns and coping within the mental health domain emerged as dominant themes.59

While individual studies have explored the psychological impact of HIV and TB separately,60,61 there is a notable lack of nationally representative evidence focusing specifically on the psychosocial experiences of those co-infected with HIV and TB. This represents a critical research gap, particularly in high-burden settings like South Africa, where understanding and addressing the compounded mental health challenges of co-infection could significantly improve care outcomes. Taken together, these global and local findings underscore the need to integrate psychosocial support into TB and HIV programmes as a core component of achieving the End TB targets.

These indicators underscore the need for a re-invigorated TB response that integrates prevention, early detection and treatment adherence, while ensuring alignment with HIV care services for individuals with HIV/TB co-infection. Strengthening community-based care, expanding access to newer TB regimens, and addressing social determinants such as poverty and malnutrition will be essential to achieving the End TB targets (Table 8).62

Table 9.TB indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
All MDR-TB patients in cohort 2022 both sexes all ages EDRWeb 7 109 1 610 267 810 1 736 226 363 315 348 1 434 a
Case detection rate (all forms) 2022 both sexes Global TB (2023) 77 b
HIV prevalence in TB incident cases 2022 both sexes Global TB 54 b
Incidence of TB (all types) (per 100 000) 2023 both sexes all ages Global TB 427 c
both sexes all ages Global TB PLHIV 230 c
Reported cases of MDR-TB 2022 WHO 7 590 b
TB MDR client death rate 2022 both sexes all ages EDRWeb 15.6 17.4 21.3 12.8 13.8 19.0 16.8 15.6 18.4 14.6 a
TB MDR client loss to follow-up rate 2022 both sexes all ages EDRWeb 17.5 17.7 12.7 20.6 15.3 8.8 9.6 16.8 11.5 24.2 a
TB MDR treatment success rate 2022 both sexes all ages EDRWeb 62.4 61.2 62.2 64.4 68.5 63.3 66.7 64.8 67.0 52.5 a
TB XDR client death rate 2022 both sexes all ages EDRWeb 20.1 21.2 28.1 22.2 14.2 21.4 34.8 34.3 15.0 15.6 a
TB XDR client loss to follow-up rate 2022 both sexes all ages EDRWeb 16.2 12.9 9.4 18.1 16.8 7.1 4.3 11.4 10.0 25.0 a
TB XDR treatment success rate 2022 both sexes all ages EDRWeb 51 55.4 46.9 47.2 52.2 50.0 56.5 54.3 65.0 42.8 a
Tuberculosis death rate per 100 000 (in HIV-positive people) 2023 both sexes Global TB 49 c
Tuberculosis mortality rate per 100 000 2022 both sexes all ages Global TB 90 b
Tuberculosis mortality rate per 100 000 (excluding HIV) 2022 Global TB 39 b
2023 both sexes Global TB 39 c

Sources:
a: EDRWeb63
b: Global TB database57
c: Global TB 202413

Indicator [units]: Definition

• Case detection rate (all forms) [Percentage]: Proportion of incident cases of TB (all types) that were notified. For a given country, it is calculated as the number of notified cases of TB in one year divided by the number of estimated incident cases of TB in the same year, and expressed as a percentage.

• HIV prevalence in TB incident cases [Percentage]: Percentage of new TB cases that are HIV-positive.

• Incidence of TB (all types) [per 100 000 population]: Estimated number of cases of tuberculosis (all types) per 100 000 population (for the year).

• Reported cases of MDR-TB [Number]: Number of laboratory-diagnosed cases of MDR-TB. MDR-TB is defined as resistance to rifampicin and isoniazid, with or without resistance to other first-line anti-TB drugs.

• TB MDR client death rate [Percentage]: The percentage of TB clients (MDR-TB) who died.

• TB MDR client loss to follow-up rate [Percentage]: The percentage of TB clients (MDR-TB) who are lost to follow-up.

• TB MDR treatment success rate [Percentage]: The percentage of TB clients (MDR-TB) cured plus those who completed treatment.

• TB XDR client death rate [Percentage]: The percentage of TB clients (XDR-TB) who died.

• TB XDR client loss to follow-up rate [Percentage]: The percentage of TB clients (XDR-TB) who are lost to follow-up.

• TB XDR treatment success rate [Percentage]: XDR-TB clients who successfully complete treatment as a proportion of XDR-TB clients started on treatment.

• Tuberculosis death rate per 100 000 (in HIV-positive people) [per 100 000 population]: Number of deaths due to TB in HIV-positive people per 100 000 population.

• Tuberculosis mortality rate per 100 000 [per 100 000 population]: Number of deaths due to tuberculosis (all types) reported per 100 000 population (for the year).

Maternal and reproductive health

Maternal mortality ratio

According to WHO, the global maternal mortality ratio declined by over 40% between 2000 and 2023, but progress has stalled in many low- and middle-income countries. Sub-Saharan Africa continues to account for approximately 70% of global maternal deaths, with leading causes including haemorrhage, hypertensive disorders, and sepsis.64

The institutional maternal mortality ratio (iMMR) was 111.7 per 100 000 live births in 2023 in South Africa, with the highest provincial ratios found in North West (156.5), Free State (139.5), and Eastern Cape (140.4).30 These figures contrast with the WHO national estimate of 118 per 100 000, highlighting discrepancies between facility-based and modelled estimates. Routine DHIS data show a similar picture, with an overall facility ratio of 101 and the same provinces at the extremes. More than half of these deaths are still judged as preventable, underscoring ongoing gaps in the timeous management of haemorrhage, hypertension and infection.30

Access to skilled birth attendance

Although access to skilled birth attendance has improved ─ reaching 87% in 2024 ─ the quality of care and emergency obstetric services remains uneven. Caesarean section rates are rising worldwide, with some countries exceeding the WHO-recommended threshold of 10–15%, raising concerns about over-medicalisation.65 In contrast, many low-resource settings still face barriers to timely surgical intervention. Nationally, the institutional delivery rate stands at 78.4%, with Limpopo (90.3%) and Free State (85.5%) outperforming the national average, while Northern Cape (69.4%) and Eastern Cape (71.2%) lag behind.39 Caesarean section rates remain high at 32.4% nationally, with KwaZulu-Natal reporting the highest rate at 38.9%, raising questions about clinical appropriateness and access to emergency obstetric care.39

Contraception

Access to modern contraception has expanded globally, yet unmet need remains high in parts of South Asia and sub-Saharan Africa. The global health community increasingly emphasises respectful maternity care, adolescent-friendly services, and integration of sexual and reproductive health with HIV and mental health services.66 These global trends offer important lessons and benchmarks for South Africa’s ongoing efforts to improve maternal and reproductive health outcomes.

Teenage pregnancy

High adolescent fertility rates remain a concern in many regions, particularly in West and Central Africa, where rates exceed 100 births per 1 000 girls aged 15–19 years.64 In South Africa, teenage pregnancy remains a significant concern, where over 122 000 facility-based deliveries were recorded among girls aged 10–19 years. KwaZulu-Natal (31 088) and Gauteng (19 836) accounted for the highest numbers. Statistics South Africa’s Vital Registration Register mirrors the magnitude of the problem, logging just over 100 000 live births to 15–19-year-olds in 2023.36 The facility delivery rate for this age group is 14.1%, peaking at 18.0% in Eastern Cape.39 Condom use among young women aged 15–24 has declined to 26.2% nationally, according to THEMBISA 4.7,38 suggesting a worrying trend in sexual risk behaviour. The trend threatens to undermine gains in HIV prevention and heightens the risk of unintended and unsupported pregnancy.

Neonatal deaths

Neonatal outcomes have barely shifted. The facility-based neonatal mortality rate stands at 9.9 deaths per 1 000 live births, down slightly from recent years but stubbornly high in Free State and Northern Cape and at its lowest in Western Cape. While the WHO estimates are not disaggregated provincially, neonatal mortality remains high at 11.6 per 1 000 live births,67 underscoring the need for improved perinatal care, as this rate has increased from 2021.

Termination of pregnancies

The data also show that 137 331 terminations of pregnancy (ToPs) were performed in 2023, with Gauteng (35 363) and Western Cape (20 624) leading in service provision.39 This reflects both access and demand, but also points to the need for strengthened contraceptive services and post-abortion care.

These indicators reveal a health system that is succeeding at bringing more women into care earlier, but has yet to translate such access into faster reductions in maternal and newborn deaths. Closing the provincial equity gaps, re-energising HIV and pregnancy-prevention efforts among adolescents, and sharpening the quality of intrapartum and emergency obstetric care will be critical if South Africa is to restart progress towards achievement of the SDG targets for 2030.

Perinatal mental health challenges and economic considerations

A review informed by a significant proportion of South African studies suggests that women in Africa experience a range of perinatal mental disorders, including depression and psychosis, often linked to socio-economic and poverty-related factors operating at multiple levels.68 However, evidence on the health and social impacts of these conditions, the availability of context-specific interventions, and patterns of mental healthcare use remains limited.68 In quantifying the economic toll, models suggest that perinatal depression and anxiety in South Africa account for a lifetime cost of USD 2.8 billion per annual birth cohort ─ a figure that rises when post-traumatic stress disorder is included.69 Despite progress in mental health policies and interventions, there remains a significant gap in economic investment to meet perinatal mental health needs, which in itself is a barrier to meeting these needs (Table 9).

Table 10.Maternal and reproductive indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Condom use at last sex 2023 female 15─24 years THEMBISA 4.7 26.2 24.2 26.1 29.5 31.0 22.5 30.4 26.2 26.7 33.6 a
female 25─49 years THEMBISA 4.7 29.2 25.5 26.2 24.7 31.9 22.9 30.1 23.3 26.0 25.3 a
Delivery 10─14 years in facility 2023/24 female 10─14 years DHIS 2 716 395 106 430 610 375 293 70 151 286 b
Delivery 10─19 years in facility 2023/24 female 10─19 years DHIS 122 302 16 222 5 501 19 836 31 088 16 637 11 827 3 608 7 676 9 907 b
Delivery 15─19 years in facility 2023 female 15─19 years vital registration 100 095 c
2023/24 female 15─19 years DHIS 119 586 15 827 5 395 19 406 30 478 16 262 11 534 3 538 7 525 9 621 b
Delivery in 10─19 years in facility rate 2023/24 female DHIS 14.1 18.0 13.3 9.9 16.6 15.0 16.6 17.2 14.0 11.0 b
Delivery by Caesarean section rate 2023 female NCCEMD 32.2 33.7 34.8 32.9 38.4 26.9 24.2 25.3 26.9 32.9 d
2023/24 female DHIS 32.4 33.9 34.1 33.2 38.9 26.7 24.3 26.6 26.7 33.0 b
Delivery in facility ─ total 2023/24 DHIS 866 582 89 881 41 392 200 367 186 725 111 151 71 388 21 027 54 739 89 912 b
Delivery in facility rate 2023/24 female DHIS 78.4 71.2 85.5 76.8 78.9 90.3 78.3 81.5 69.4 78.4 b
Live birth in facility 2023/24 both sexes DHIS 861 717 89 137 41 100 199 342 184 881 110 790 71 140 21 793 54 068 89 466 b
Maternal death in facility 2023/24 female DHIS 915 131 47 223 173 121 83 28 64 45 b
Maternal mortality in facility ratio 2023/24 female DHIS 100.6 136.2 104.8 107.3 89.2 104.7 109.4 115.8 110.2 48.3 b
Maternal mortality ratio (MMR) 2023 female WHO 118.0 e
Maternal mortality ratio in facility / institutional (iMMR) 2022 female NCCEMD 109.9 128.9 116.2 121.7 87.8 114.7 137.4 117.4 116.8 70.8 d
2023 female NCCEMD 111.7 140.4 139.5 107.6 88.1 120.2 138.3 134.6 156.5 71.8 d
Neonatal mortality rate (NMR) (deaths <28 days old per 1 000 live births) 2022 both sexes WHO 11.6 f
Number of maternal deaths 2022 female NCCEMD 1 062 133 55 266 189 143 113 26 70 67 d
2023 female NCCEMD 987 129 60 217 169 136 101 35 75 65 d
female WHO 1 400 e
Teenage pregnancy 2024 female 14─19 years GHS 3.8 g
ToPs (terminations of pregnancy) 2023/24 DHIS 137 331 15 566 7 041 35 363 23 470 14 072 9 408 1 871 9 916 20 624 b

Sources:
a: Thembisa v4.738
b: DHIS39
c: StatsSA Recorded Live Births 202336
d: Saving Mothers 202330
e: WHO MMR 202564
f: Global Health Observatory21
g: StatsSA GHS 202432

Indicator [units]: Definition

• Condom use at last sex [Percentage]: Percentage of those who reported ever having had sex, who used a condom the last time they had sex. Note that the precise definition of this indicator varies between surveys.

• Delivery 10─14 years in facility [Number]: Delivery where the mother is 10─14 years old. These deliveries are done in facilities under the supervision of trained medical/nursing staff.

• Delivery 15─19 years in facility [Number]: Delivery where the mother is 15─19 years old. These deliveries are done in facilities under the supervision of trained medical/nursing staff.

• Delivery 10─19 years in facility [Number]: Delivery where the mother is 10─19 years old. These deliveries are done in facilities under the supervision of trained medical/nursing staff.

• Delivery by Caesarean section rate [Percentage]: Delivery by Caesarean section as a proportion of total deliveries in health facilities.

• Delivery in 10─19 years in facility rate [Percentage]: Deliveries to women younger than 20 years as a proportion of total deliveries in health facilities.

• Delivery in facility ─ total [Number]: Any delivery taking place in a health facility under the supervision of trained medical/nursing staff.

• Delivery in facility rate [Percentage]: Deliveries in health facilities as a proportion of expected deliveries in the population. Expected deliveries are estimated as population under 1 year multiplied by 1.025 to compensate for still births and infant mortality.

• Live birth in facility [Number]: Live birth resulting from a delivery in a facility.

• Maternal death in facility [Number]: Maternal death is death occurring during pregnancy, childbirth or puerperium within 42 days of termination of pregnancy, irrespective of the duration and site of pregnancy and the cause of death (obstetric and non-obstetric).

• Maternal mortality in facility ratio [per 100 000 live births]: Women who die as a result of childbearing, during pregnancy or within 42 days of delivery or termination of pregnancy, per 100 000 live births, and where the death occurs in a health facility.

• Maternal mortality ratio (MMR) [per 100 000 live births]: The number of women who die as a result of childbearing, during the pregnancy or within 42 days of delivery or termination of pregnancy in one year, per 100 000 live births during that year.

• Maternal mortality ratio in facility / institutional (iMMR) [per 100 000 live births]: The number of women who die as a result of childbearing, during the pregnancy or within 42 days of delivery or termination of pregnancy in one year, per 100 000 live births during that year. Refers only to institutional / facility-based deaths, not representing the entire population. Note that the WHO Core List definition is per 100 000 deliveries (not live births) ─ number of maternal deaths among 100 000 deliveries in health facilities/institutions. For the estimates from NCCEMD: The confidential enquiry into maternal deaths system is not set up to determine the maternal mortality ratio (MMR) for a country. Live birth data were obtained from the DHIS. It must be noted that the confidential enquiry system is not designed for calculating ratios and rates. It is dependent on reporting; the more complete the reporting, the more accurate the estimates of the MMR.

• Neonatal mortality rate (NMR) (deaths <28 days old per 1 000 live births) [per 1 000 live births]: Number of deaths within the first 28 days of life, in a year, per 1 000 live births during that year. Also called Neonatal Death Rate (NDR).

• Number of maternal deaths [Number]: The number of women who die as a result of childbearing, during the pregnancy or within 42 days of delivery or termination of pregnancy in one year. In the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, 1992 (ICD-10), WHO defines maternal death as: The death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes. For countries using ICD-10 coding for registered deaths, all deaths coded to the maternal chapter (O codes) and A34 (maternal tetanus) were counted as maternal deaths. Note that the system of Confidential Enquiries into Maternal Deaths (NCCEMD) captures only institutional deaths, and thus is known to miss deaths occurring at home. The confidential enquiry system is ideally suited to identifying the most common causes of death and ranking the causes of death according to priority.

• Teenage pregnancy [Percentage]: Percentage of women aged 15─19 who are mothers or who have ever been pregnant.

• ToPs (terminations of pregnancy) [Number]: The number of terminations of pregnancy.

Child health

Child health has seen significant improvements over the past decades, yet disparities remain stark across regions. According to UNICEF and WHO, global under-five mortality has declined by over 50% since 1990, but sub-Saharan Africa still accounts for more than half of all under-five deaths. Immunisation coverage has plateaued in many countries, with the COVID-19 pandemic causing setbacks in routine vaccinations. In 2023, an estimated 25 million children missed out on essential vaccines worldwide.15

Malnutrition continues to be a leading cause of child morbidity and mortality, with 148 million children under five being affected by stunting and 45 million by wasting. Conversely, childhood obesity is rising, particularly in middle-income countries, posing new challenges for health systems. Mental health and developmental delays are also gaining attention, with global initiatives calling for integrated early childhood development programmes. These global trends underscore the need for resilient PHC systems, equitable access to services, and targeted interventions to address both infectious and non-communicable threats to child health.18

Immunisation

Child health outcomes in South Africa continue to reflect both progress and persistent gaps in service coverage and equity. Immunisation coverage has declined across several key vaccines: BCG coverage dropped from 79% in 2023 to 74% in 2024, and DTP3 coverage also stands at 74% from 79% in those same years.15 Measles coverage shows slightly better performance in 2024, with 81% for the first dose and 82% for the second dose, yet still falls short of the 95% target required for herd immunity.

The pneumococcal conjugate vaccine (PCV) third-dose coverage also declined slightly from 83% in 2023 to 81% in 2024, mirroring the trend seen in other immunisation indicators. This decline may reflect broader systemic issues in routine child health services, including supply-chain constraints and workforce shortages, challenges in vaccine uptake (possibly linked to service disruptions), vaccine hesitancy, and access barriers.70

Child mortality

Under-five mortality remains a pressing concern. According to the UNICEF State of the World’s Children Report, the 2023 estimate for South Africa was 34.7 deaths per 1 000 live births, with boys (37.2) experiencing higher mortality than girls (31.9).18 The 2024 mid-year estimate34 shows a modest improvement to 28.6, but this still exceeds the SDG target of 25 per 1 000. Similarly, child mortality in the 1–4-year age group was 10.4 per 1 000 in 2023, again with higher rates among boys (11.1) than girls (9.8).21

Orphanhood

Orphanhood data from the 2024 GHS32 reveals concerning levels of parental orphanhood among children under 18 years. Nationally, 7.6% of children are paternal orphans, with Free State (10.7%) and Northern Cape (9.3%) reporting the highest rates. Maternal orphanhood is lower at 2.7% nationally, but still significant, particularly in Western Cape (4.3%). These figures underscore the need for strengthened social protection and psychosocial support for vulnerable children.

Collectively, these findings underscore the need to reinvigorate primary health care and immunisation outreach, especially in under-served areas, by bolstering health information systems, optimising vaccine delivery, and tackling the social determinants that shape child health.70

Balancing challenges and resilience in orphaned adolescents

Addressing the mental health challenges of orphaned and vulnerable children is critical, yet nationally representative data remain scarce. Evidence from a study conducted in the City of Tshwane shows a 21% prevalence of depressive symptoms among orphaned adolescents in township secondary schools.71 Further research on maternally orphaned adolescents reveals maladaptive behaviours, including suicidal thoughts, poor self-perception, silence, psychological distress, risky behaviours, and social withdrawal.72 In contrast, a more recent study by the same authors identifies protective behaviours among some orphans, such as resilience fostered through participation in meaningful daily activities.73 Taken together, these findings point to both significant vulnerabilities and notable strengths among orphaned adolescents, underscoring the urgent need for nationally representative studies to inform targeted mental health interventions more effectively (Table 10).

Table 11.Child health indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
BCG coverage 2023 both sexes WHO/UNICEF 79.0 a
2024 both sexes WHO/UNICEF 74.0 a
Child mortality (deaths between 1 and 4 years per 1 000 live births) 2023 both sexes WHO 10.4 b
female WHO 9.8 b
male WHO 11.1 b
DTP3 coverage 2024 both sexes WHO/UNICEF 74.0 a
Measles 1st dose under 1 year coverage 2023 both sexes WHO/UNICEF 83.0 a
2024 both sexes WHO/UNICEF 81.0 a
Measles 2nd dose coverage 2024 both sexes WHO/UNICEF 82.0 a
Orphanhood 2024 both sexes <18 years GHS double 1.5 1.7 1.8 1.0 1.8 1.9 1.7 1.8 2.5 0.9 c
both sexes <18 years GHS maternal 2.7 3.0 2.6 2.6 3.0 2.1 2.5 3.3 4.3 1.3 c
both sexes <18 years GHS paternal 7.6 7.6 10.7 6.5 8.6 6.3 9.3 7.5 8.1 5.9 c
PCV 3rd dose coverage 2023 both sexes WHO/UNICEF 83.0 a
2024 both sexes WHO/UNICEF 81.0 a
Under 5 mortality rate (deaths under 5 years per 1 000 live births) 2023 both sexes WHO/UNICEF 34.7 d
female WHO/UNICEF 31.9 d
male WHO/UNICEF 37.2 d
2024 both sexes mid-year 28.6 e

Sources:
a: Immunization 202415
b: Global Health Observatory21
c: StatsSA GHS 202432
d: State of the World’s Children 202418
e: StatsSA MYE 202434

Indicator [units]: Definition

• BCG coverage [Percentage]: The proportion of expected live born babies who received BCG under 1 year of age (note: usually given immediately after birth).

• Child mortality (deaths between 1 and4 years per 1 000 live births) [per 1 000 live births]: The number of children aged 12 months to 5 years (i.e. to the end of the 4th year) who die in a year, per 1 000 live births.

• DTP3 coverage [Percentage]: The proportion of children who received their third DTP doses (normally at 14 weeks).

• Measles 1st dose under 1 year coverage [Percentage]: Children under 1 year who received measles 1st dose, as a proportion of population under 1 year.

• Measles 2nd dose coverage [Percentage]: Children 1 year (12 months) who received measles 2nd dose, as a proportion of the 1 year population.

• Orphanhood [Percentage]: Proportion of children under 18 years whose biological mother, biological father or both parents have died.

• PCV 3rd-dose coverage [Percentage]: Children under 1 year who received PCV 3rd dose, normally at 9 months as a proportion of population under 1 year.

• Under 5 mortality rate (deaths under 5 years per 1 000 live births) [per 1 000 live births]: The number of children under 5 years who die in a year, per 1 000 live births during the year. It is a combination of the infant mortality rate, plus the age 1─4 mortality rate.

Non-communicable diseases

The global rise of non-communicable diseases (NCDs), driven by ageing populations, urbanisation, unhealthy diets, physical inactivity, tobacco use, and harmful alcohol consumption is the leading cause of death, accounting for over 70% of all deaths worldwide. Cardiovascular diseases, cancers, chronic respiratory diseases, and diabetes are the most prevalent, with low- and middle-income countries bearing over 85% of premature deaths. The mortality rate from major NCDs among adults aged 30–70 years is 22.7%,7 reflecting the cumulative impact of late diagnosis, poor treatment adherence, and limited access to quality chronic care.74

Mental health

Mental health, which is often under-recognised, is increasingly prioritised in global health agendas, with the WHO Comprehensive Mental Health Action Plan 2013–2030 calling for universal access to mental health care. Suicide mortality remains high globally at 22.3 per 100 000, highlighting the intersection of mental health and broader NCD burdens.75

South Africa’s NCD burden mirrors these global trends, and the country’s efforts to integrate mental health and chronic disease management align with international best practices. Figure 3 illustrates that the highest burden of mental disorders in South Africa are depression and anxiety2 based on global modelling estimates; however, local mental health indicators show concerning gaps. The new treatment rate for mental disorders is negligible in most provinces, and the mental health separation rate varies widely, from 0.9 in Northern Cape to 18.0 in Gauteng, suggesting uneven access to in-patient mental health services. This is particularly concerning given that the Northern Cape recorded the highest rate of suicide at 6.6% in the StatsSA Causes of Death report.35

A graph of mental disorders AI-generated content may be incorrect.
Figure 3.Burden of mental disorders in South Africa, 2024

Source: IHME, 20242

Cancer

According to GLOBOCAN,12 in South Africa, the age-standardised cancer incidence rate is 203.4 per 100 000 population, with prostate (62.0), breast (47.8), and cervical cancer (33.2) being among the most common. Notably, male cancer incidence (232.4) exceeds that of females (190.4), reflecting gendered risk exposures and screening disparities. National Cancer Registry (NCR) data for 2023 show lower incidence rates, which is likely to be due to under-reporting or differences in case capture, underscoring the need for improved cancer surveillance, as discussed in Ndlovu, et al. (2024).76

Diabetes and hypertension

Diabetes prevalence among adults aged 20–79 years is estimated at 7.2%,14 with detection and treatment rates remaining low. In 2023/24, only 87 792 new diabetes clients aged 45 years and older were recorded, and detection rates for adults aged 18 years and older remain below 0.6% in most provinces.39 Hypertension detection is slightly better, with 113 340 new cases among 18–44-year-olds and 168 956 among those aged 45 years and older, but detection rates still hover below 1% in most provinces. These trends suggest substantial under-diagnosis and missed opportunities for early intervention within routine systems in the public health sector. Strengthening surveillance, improving access to essential medicines, and addressing social determinants are critical components of the global response to NCDs (Table 11).

Table 12.NCD indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Cancer incidence rate, by type of cancer (per 100 000 population) 2022 both sexes age-standardised GLOBOCAN all cancers 203.4 a
both sexes age-standardised GLOBOCAN bladder 4.1 a
both sexes age-standardised GLOBOCAN colorectal 13.5 a
female age-standardised GLOBOCAN all cancers 190.4 a
female age-standardised GLOBOCAN bladder 1.7 a
female age-standardised GLOBOCAN breast 47.8 a
female age-standardised GLOBOCAN cervix 33.2 a
female age-standardised GLOBOCAN colorectal 11.3 a
female age-standardised GLOBOCAN ovary 5.1 a
male age-standardised GLOBOCAN all cancers 232.4 a
male age-standardised GLOBOCAN bladder 7.8 a
male age-standardised GLOBOCAN colorectal 17.0 a
male age-standardised GLOBOCAN prostate 62.0 a
2023 female age-standardised NCR all cancers 108.9 b
female age-standardised NCR bladder 0.9 b
female age-standardised NCR breast 32.9 b
female age-standardised NCR cervix 23.0 b
female age-standardised NCR colorectal 6.5 b
female age-standardised NCR lung 2.8 b
female age-standardised NCR ovary 1.8 b
male age-standardised NCR all cancers 119.0 b
male age-standardised NCR bladder 4.0 b
male age-standardised NCR breast 0.9 b
male age-standardised NCR colorectal 10.2 b
male age-standardised NCR lung 6.5 b
male age-standardised NCR prostate 47.0 b
Diabetes client treatment new 45 years and older 2023/24 DHIS 87 792 9 881 3 330 22 318 20 518 8 308 11 035 1 931 5 105 5 366 c
Diabetes new client 18 years and older detection rate 2023/24 DHIS 0.4 0.4 0.3 0.3 0.4 0.5 0.6 0.4 0.3 0.2 c
Diabetes prevalence 2024 both sexes 20─79 years Diabetes Atlas age-standardised 7.2 d
Hypertension client treatment new 18─44 years 2023/24 DHIS 113 340 11 887 7 859 28 500 21 745 10 190 10 001 4 402 8 230 10 526 c
Hypertension client treatment new 45 years and older 2023/24 DHIS 168 956 22 125 9 413 38 940 36 962 17 182 18 516 3 755 11 154 10 909 c
Mental Health Quotient 2023 both sexes all ages MHQ 52.3 e
female all ages MHQ 45.8 e
male all ages MHQ 59.2 e
Mental health separation rate 2023/24 DHIS 3.9 2.7 18.0 2.5 2.6 2.6 2.5 0.9 1.6 4.3 c
Mortality between 30 and 70 years from cardiovascular. cancer. diabetes or chronic respiratory disease 2021 both sexes 30-70 years WHO 22.7 f
Suicide mortality rate (per 100 000 population) 2021 both sexes WHO 22.3 f

Sources:
a: GLOBOCAN12
b: NCR25
c: DHIS39
d: IDF Diabetes Atlas 202514
e: MHQ 202477
f: World Health Statistics 20257

Indicator [units]: Definition

• Cancer incidence rate, by type of cancer [per 100 000 population]: Number of new cancers of a specific site/type occurring per 100 000 population. Numerator: Number of new cancer cases diagnosed in a specific year. This may include multiple primary cancers occurring in one patient. The primary site reported is the site of origin and not the metastatic site. In general, the incidence rate would not include recurrences. Denominator: The at-risk population for the given category of cancer. The population used depends on the rate to be calculated. For cancer sites that occur only in one sex, the sex-specific population (e.g. females for cervical cancer) is used.

• Diabetes client treatment new 18─44 years [Number]: Newly diagnosed clients 18─44 years with a fasting blood glucose of >7mmol/L or random blood glucose >11.1mol/L.

• Diabetes client treatment new 45 years and older [Number]: Newly diagnosed clients 45 years and older with a fasting blood glucose of >7mmol/L or random blood glucose >11.1mol/L.

• Diabetes prevalence [Percentage]: Percentage of people with diabetes. WHO Core indicator is: Age-standardised prevalence of raised blood glucose/diabetes among persons aged 18+ years or on medication for raised blood glucose. Defined as: fasting plasma glucose value >= 7.0 mmol/L (126 mg/dL) or on medication for raised blood glucose among adults aged 18+ years.

• Hypertension client treatment new 18─44 years [Number]: Total number of new hypertension clients aged 18─44 years put on treatment.

• Hypertension client treatment new 45 years and older [Number]: Total number of new hypertension clients 45 years and older put on treatment.

• Mental health separation rate [Percentage]: Proportion of clients admitted for mental health problems. In-patient separations is the total of in-patient discharges, in-patient deaths and in-patient transfers out.

• Mental Health Quotient (MHQ) [Percentage]: The MHQ provides an aggregate metric of well-being. An aggregate mental well-being score based on these aspects (the MHQ) positions individuals on a spectrum from Distressed to Thriving. The positive range of the scale represents the spectrum of normal functioning, and is a 200-point scale calibrated to a mean of 100 based on pre-pandemic responses in 2019, similar to the IQ scale. The negative range of the scale represents mental well-being scores associated with a negative impact on the ability to function, and is associated with clinical-level risks and challenges.

• Mortality between 30 and 70 years from cardiovascular, cancer, diabetes or chronic respiratory disease [Percentage]: Unconditional probability of dying between exact ages 30 and 70 from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease. Deaths from these four causes will be based on the following ICD codes: I00–I99, COO–C97, E10–E14 and J30–J98. According to WHO Core Indicators: Modelling, using multiple inputs, is often used if no complete and accurate data are available. Age standardisation is done for comparability over time and between populations.

• Suicide mortality rate [per 100 000 population]: Suicide rate per 100 000 population in a specified period (age-standardised).

Nutrition

On a global and local level, nutrition is recognised as a cornerstone of health across the life course. The WHO reports that while global stunting rates among children under five have declined, over 148 million children remain stunted, with the highest burden being in South Asia and sub-Saharan Africa. Simultaneously, childhood overweight and obesity are rising rapidly, particularly in middle-income countries, reflecting a global nutrition transition marked by increased consumption of ultra-processed foods and sedentary lifestyles.78

Exclusive breastfeeding

Exclusive breastfeeding rates vary widely, with global averages at 48%, far below the 70% target set by the WHO. Micronutrient deficiencies, including iron, vitamin A and iodine, continue to affect billions, particularly women and children. In response, countries are adopting multisectoral strategies that integrate nutrition into health, education, and agriculture policies. Global initiatives such as the Scaling Up Nutrition (SUN) movement and the UN Decade of Action on Nutrition are driving co-ordinated action. South Africa’s dual burden of under-nutrition and obesity mirrors global trends, underscoring the need for comprehensive, equity-focused nutrition policies. Locally, exclusive breastfeeding rates remain suboptimal, with only 43.3% of infants being exclusively breastfed at the time of the third hexavalent vaccine dose in 2023/24. Provincial disparities are stark, where KwaZulu-Natal leads at 55.6%, while Limpopo (32.1%) and Mpumalanga (34.1%) fall well below the national average.39 These figures highlight missed opportunities for early-life nutrition and immune protection.

Obesity

Childhood and adolescent obesity and overweight rates are rising in South Africa. Among children aged 5–9 years, 6.9% are obese and 19.5% are overweight, while among adolescents aged 10–19, 7.2% are obese and 21.8% are overweight.78 Gender disparities are notable, where 9.6% of adolescent girls are obese compared to 4.9% of boys, and 29.4% of girls are overweight compared to 14.4% of boys. These trends reflect dietary shifts, sedentary lifestyles, and socio-environmental influences, and signal future increases in diabetes, cardiovascular disease, and other NCDs.79

Among adults, the situation is even more concerning. Over half (55%) of adults aged 18 and older are overweight, with 30.8% classified as obese. The gender gap is pronounced, with 71.3% of women being overweight or obese compared to 37.2% of men in South Africa. Conversely, underweight remains a concern for 5.2% of adults, particularly among men (8.2%), reflecting a dual burden of malnutrition.7 Stunting among children under five remains high at 24.4%, indicating chronic under-nutrition and its long-term developmental consequences.80

Micronutrients

Micronutrient deficiencies also persist. Vitamin A supplementation coverage for children aged 12–59 months was 69.5% nationally in 2023/24, with wide provincial variation from 85.7% in KwaZulu-Natal to just 47.9% in Northern Cape.39 These gaps suggest uneven implementation of child health programmes and highlight the need for strengthened outreach and supply-chain management.

There is a need for a comprehensive, life-course approach that includes promoting breastfeeding, improving school-based nutrition and physical activity programmes, scaling up community-based screening and counselling, and addressing the social determinants of health that drive poor nutrition and lifestyle risk factors. Without decisive action, the rising tide of NCDs threatens to overwhelm the health system and reverse gains in life expectancy and quality of life.81

Nutrition and mental health

Recent South African studies reveal a strong link between malnutrition and mental health in children and adolescents. Food insecurity remains a major issue, with children in food-insecure households having over 60% higher odds of anxiety and depression compared to those in food-secure homes.82,83 Under-nutrition marked by stunting and micronutrient deficiencies adversely affects cognitive development and school readiness, especially in female-headed or informal households where food insecurity is more prevalent.84 Concurrently, rising adolescent overweight and obesity were found to be linked to increased depression and low self-esteem, particularly among girls.85 This dual burden of malnutrition highlights the need for integrated policies addressing both nutrition and mental health to improve children’s lifelong well-being (Table 12).

Table 13.Nutrition indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Infant exclusively breastfed at DTaP-IPV-Hib-HBV 3rd dose rate 2023/24 both sexes DHIS 43.3 39.6 44.1 47.3 55.6 32.1 34.1 50.9 32.7 38.7 a
Infant exclusively breastfed at DTaP-IPV-Hib-HBV (Hexavalent) 3rd dose 2023/24 both sexes DHIS 385 579 37 290 16 697 97 979 106 155 36 224 25 444 10 790 18 655 36 345 a
Obesity 2022 both sexes 5─9 years WHO crude estimates 6.9 b
both sexes 5─19 years WHO crude estimates 7.1 b
both sexes 10─19 years WHO crude estimates 7.2 b
female 5─9 years WHO crude estimates 8.0 b
female 5─19 years WHO crude estimates 9.0 b
female 10─19 years WHO crude estimates 9.6 b
male 5─9 years WHO crude estimates 5.8 b
male 5─19 years WHO crude estimates 5.2 b
male 10─19 years WHO crude estimates 4.9 b
Overweight 2022 both sexes 5─9 years WHO crude estimates 19.5 b
both sexes 5─19 years WHO crude estimates 21.0 b
both sexes 10─19 years WHO crude estimates 21.8 b
both sexes 18 years and older WHO age-standardised 55.0 b
female 5─9 years WHO crude estimates 21.7 b
female 5─19 years WHO crude estimates 26.7 b
female 10─19 years WHO crude estimates 29.4 b
female 18 years and older WHO age-standardised 71.3 b
male 5─9 years WHO crude estimates 17.3 b
male 5─19 years WHO crude estimates 15.4 b
male 10─19 years WHO crude estimates 14.4 b
male 18 years and older WHO age-standardised 37.2 b
2024 both sexes <5 years WHO 12.8 c
Percentage of adults overweight or obese 2022 both sexes 18 years and older WHO age-standardised 30.8 b
female 18 years and older WHO age-standardised 45.8 b
male 18 years and older WHO age-standardised 13.9 b
Stunting 2024 both sexes <5 years WHO 24.4 c
Underweight 2022 both sexes 18 years and older WHO age-standardised 5.2 b
female 18 years and older WHO age-standardised 2.5 b
male 18 years and older WHO age-standardised 8.2 b
Vitamin A dose 12─59 months 2023/24 both sexes DHIS 4 705 259 551 250 206 531 1 010 538 1 065 793 494 782 505 950 82 013 356 460 431 942 a
Vitamin A dose 12─59 months coverage 2023/24 both sexes DHIS 69.5 76.1 58.9 64.9 85.7 55.4 81.2 47.9 72.3 50.4 a

Sources:
a: DHIS39
b: Global Health Observatory21
c: World Health Statistics 20257

Indicator [units]: Definition

• Infant exclusively breastfed at DTaP-IPV-Hib-HBV 3rd dose rate [Percentage]: Infants exclusively breastfed at 14 weeks as a proportion of the DTaP-IPV-Hib-HBV 3rd dose vaccination. Take note that DTaP-IPV-Hib-HBV 3rd dose (Hexavalent) was implemented in 2015 to include the HepB dose.

• Infant exclusively breastfed at DTaP-IPV-Hib-HBV (Hexavalent) 3rd dose [Number]: Infant reported to be exclusively breastfed at DTaP-IPV-HepB-Hib (Hexavalent) 3rd dose immunisation (preferably 14 weeks after birth).

• Obesity [Percentage]: Percentage of people with a body mass index (BMI) (body mass in kg divided by the square of the height in m) equal to or more than 30kg/m2.

• Overweight [Percentage]: Children: Proportion of children with weight for height over 2 standard deviations from the norm (reference population median). Adults: Percentage of people with body mass index (BMI) of 25-29.9 kg/m2. BMI is weight in kg divided by the square of height in m. WHO Core Indicators for children under 5 years of age and adults (aged 18+ years). Rates in adults to be age-standardised. In adolescents, the definitions of overweight and obesity vary by age and gender. The prevalence of overweight is defined as the percentage of adolescents with sex-specific BMI-for-age above +1 SD from the WHO 2007 growth reference median, and the prevalence of obesity as the percentage of adolescents with sex-specific BMI-for-age above +2 SD from the WHO 2007 growth reference median.

• Percentage of adults overweight or obese [Percentage]: Percentage of adults (15+ years) who are either overweight or obese according to standard BMI cut-offs.

• Stunting [Percentage]: Proportion of children with height for age under 2 standard deviations from the norm (reference population median).

• Underweight [Percentage]: Children: Proportion of children with weight for age under 2 standard deviations from the norm (reference population median). Adults: Percentage of people with body mass index (BMI) <18.5 kg/m2. BMI is weight in kg divided by the square of height in m.

• Vitamin A dose 12─59 months [Number]: Vitamin A dose given to a child, preferably every six months from the age of 12 to 59 months.

• Vitamin A dose 12─59 months coverage [Percentage]: Proportion of children aged 12─59 months who received vitamin A 200 000 units, preferably every six months. The denominator is therefore the target population 1─4 years multiplied by 2.

Injuries and risk behaviours

Injuries and risk behaviours remain leading contributors to premature mortality and disability. The global estimates state that over 1.3 million people die annually from road traffic injuries, with low- and middle-income countries accounting for more than 90% of these deaths. Homicide rates are highest in Latin America and parts of sub-Saharan Africa, reflecting the intersection of socio-economic inequality, urban violence, and weak law enforcement. Substance use, particularly alcohol and tobacco, continues to drive a significant share of the global disease burden.86 The Global Burden of Disease Study attributes over 7 million deaths annually to tobacco use, and 3 million to harmful alcohol consumption. Among adolescents, early initiation of smoking, alcohol and drug use is a growing concern worldwide, with rising trends in e-cigarette use and synthetic drugs. Countries such as Iceland87 and Australia88 have implemented successful school- and community-based prevention programmes, offering models for reducing youth risk behaviours. Globally, there is increasing recognition of the need for integrated, multisectoral strategies that combine public health, education, law enforcement, and social services to address the root causes of injuries and risk behaviours.

Interpersonal violence and road traffic fatalities

The data reflected in Table 13 highlight the persistent burden of violence, road traffic injuries, and substance use. The national homicide mortality rate remains alarmingly high at 33.8 per 100 000 population,67 positioning South Africa among the countries with the highest levels of interpersonal violence globally. Road traffic fatalities also remain a major concern, with 10 339 deaths recorded in 2024 which was an increase from 10 180 in 2023, despite a slight decline in the rate per 100 000 population from 19.4 to 19.3.29 Provinces such as Gauteng (2 218 deaths) and KwaZulu-Natal (2 069) continue to bear the brunt of road-related mortality, reflecting both high vehicle density and systemic road safety challenges.

Substance abuse

Substance use data from SACENDU Phase 5431 further underscore the scale of the problem. In the first half of 2024 alone, Gauteng recorded 4 782 admissions for alcohol and drug abuse, followed by the Western Cape (1 727) and KwaZulu-Natal (872). Among individuals under 19, cannabis dominates as the primary drug of abuse, accounting for up to 84% of cases in some provinces, while alcohol, mandrax and methamphetamine also feature prominently.31 These patterns point to the urgent need for targeted prevention and treatment strategies, particularly for adolescents.

Prevalence of smoking and alcohol consumption

Tobacco use remains widespread, with 20.2% of individuals aged 15 and older in South Africa reporting smoking in 2022.6 The gender disparity is stark: 35.1% of adult males smoke compared to just 6.5% of females. Alarmingly, smoking prevalence among South African children aged 10–14 years is also high at 21.3% for boys and 17.7% for girls, suggesting early initiation and inadequate enforcement of tobacco control measures.

Alcohol consumption per capita among those aged 15 years and older stands at 7.8 litres annually,7 reinforcing South Africa’s classification as a high-consumption country.89 This, combined with the high rates of alcohol-related admissions and road fatalities, signals the need for stronger policy interventions, including regulation, taxation, and public education.

Table 14.Risk and injuries indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Mortality rate attributed to unintentional poisoning (per 100 000 population) 2021 both sexes WHO 1.7 a
Mortality rate due to homicides (per 100 000 population) 2021 both sexes WHO 33.8 a
Road accident fatalities 2023 both sexes RTMC 10 180 1 132 539 2 313 1 985 1 089 955 301 641 1 225 b
2024 both sexes RTMC 10 339 1 202 596 2 218 2 069 1 060 963 281 769 1 181 b
Road accident fatalities per 100 000 population 2021 both sexes WHO 24.5 a
2023 both sexes RTMC 19.4 b
2024 both sexes RTMC 19.3 b
Number of admissions for alcohol and other drug abuse Jan─Jun 2024 both sexes all ages SACENDU 261 4 782 872 1 727 c
Prevalence of smoking 2022 both sexes 10─14 years Tobacco Atlas 19.5 d
both sexes 15 years and older Tobacco Atlas 20.2 d
female 10─14 years Tobacco Atlas 17.7 d
female 15 years and older Tobacco Atlas 6.5 d
male 10─14 years Tobacco Atlas 21.3 d
male 15 years and older Tobacco Atlas 35.1 d
Primary drug of abuse as % of all drugs of abuse Jan─Jun 2024 both sexes <19 years SACENDU alcohol 2 2 12 12 c
both sexes <19 years SACENDU cannabis 76 84 75 69 c
both sexes <19 years SACENDU cocaine 9 1 1 4 c
both sexes <19 years SACENDU heroin 0 0 1 0 c
both sexes <19 years SACENDU mandrax 8 6 1 8 c
both sexes <19 years SACENDU methamphethamine 6 1 0 1 c
both sexes all ages SACENDU alcohol 14 20 37 21 c
both sexes all ages SACENDU cannabis 29 29 31 21 c
both sexes all ages SACENDU cocaine 6 2 12 5 c
both sexes all ages SACENDU heroin 1 19 11 9 c
both sexes all ages SACENDU mandrax 3 4 1 8 c
both sexes all ages SACENDU methamphethamine 12 24 2 34 c
Total alcohol per capita (age 15+ years) consumption (litres
per year)
2022 both sexes WHO 7.8 a

Sources:
a: World Health Statistics 20257
b: RTMC 202429
c: SACENDU Phase 5431
d: Tobacco Atlas 20256

Indicator [units]: Definition

• Mortality rate attributed to unintentional poisoning (per 100 000 population) [Rate]: Number of deaths from unintentional poisonings (by age and sex), for the year indicated.

• Mortality rate due to homicides (per 100 000 population) [Rate]: A homicide is the killing of a person by another with intent to cause death or serious injury. Infanticide should be included. Cases where the perpetrator was merely reckless or negligent should be excluded.

• Number of admissions for alcohol and other drug abuse [Number]: Number of patients admitted for treatment by treatment centres who are part of the SACENDU Project sentinel surveillance system.

• Prevalence of smoking [Percentage]: Proportion of the population who currently smoke.
This indicator is also known as ‘Current smokers (%)’. Note that the indicator may be given just for cigarettes or for other tobacco products. The WHO Core indicator is ‘Age-standardised prevalence of current tobacco use among persons aged 18+ years’ and is defined as: Age-standardised prevalence of current tobacco use among persons aged 18+ years.

• Primary drug of abuse as % of all drugs of abuse [Percentage]: Percentage breakdown of the primary drug of abuse reported by patients admitted to treatment centres that are part of the SACENDU sentinel surveillance system.

• Road accident fatalities [Number]: Estimated number of deaths due to road traffic fatal injury in the specified year.

• Road accident fatalities per 100 000 population [Rate]: Estimated road traffic fatal injury deaths per 100 000 population.

• Total alcohol per capita (age 15+ years) consumption (litres per year) [litres per year]: Total alcohol per capita is the total amount (sum of recorded alcohol per capita three-year average and unrecorded alcohol per capita) of alcohol consumed per adult (15+ years) in a calendar year, in litres of pure alcohol.

Infectious diseases

Despite advances in prevention, surveillance, diagnostics, treatment and control, infectious diseases continue to pose significant public health challenges. The resurgence of diseases like cholera and measles in various regions underscores the fragility of health systems and the importance of sustained immunisation and water sanitation efforts.90 The WHO estimates that over 1.3 billion people remain at risk of neglected tropical diseases, with climate change and urbanisation contributing to the spread of vector-borne illnesses such as malaria and dengue. Cross-border mobility and global trade have also heightened the risk of rapid disease transmission, necessitating stronger international collaboration and early warning systems.91

Disease outbreaks like cholera, measles and malaria can have significant psychosocial impacts on individuals and communities, including increased anxiety, grief and stigma, which can disrupt social structures and mental well-being. Furthermore, healthcare workers face unique challenges and potential psychological distress during outbreaks, highlighting the need for comprehensive mental health support.92

Cholera

Despite significant progress in disease surveillance and control, South Africa continues to face recurrent outbreaks and persistent burdens from key infectious diseases. Cholera re-emerged as a public health concern in 2023, with 1 395 reported cases and a case fatality rate of 3.4% which is well above the WHO threshold of 1%.93 The 47 reported deaths underscore gaps in water, sanitation and rapid response systems, particularly in vulnerable communities.

Measles

Measles outbreaks also persisted, with 1 029 laboratory-confirmed cases in 2023 and 833 in 2024.94 Gauteng and Mpumalanga reported the highest case counts, suggesting gaps in immunisation coverage and outbreak containment. The increase in cases in provinces like KwaZulu-Natal and Western Cape between 2023 and 2024 signals the need for intensified catch-up campaigns and improved vaccine confidence.

Malaria

Malaria remains endemic in several provinces, with 4 384 cases reported by the NICD in 2023,27 and a higher estimate of 5 291 cases from WHO sources.22 The rise in malaria cases in Botswana, Eswatini and South Africa is likely to be driven by several factors, such as difficulties in maintaining high coverage of vector control measures, increased cross-border movement (particularly between Mozambique and Eswatini and South Africa for economic reasons), and weaknesses in surveillance systems. Other contributing factors include the influence of climate change disasters on malaria transmission patterns, under-reporting, and delays in case detection, investigation and response in 2022.22 Limpopo (2 137 cases) and Mpumalanga (635) continue to bear the brunt of transmission, while Gauteng (830) and KwaZulu-Natal (332) reflect increasing urban and peri-urban exposure. The 113 malaria-related deaths in 2023 highlight the need for sustained vector control, early diagnosis, and treatment access, especially in border regions and mobile populations.22

These trends reflect the ongoing vulnerability of South Africa’s population to preventable infectious diseases. Strengthening early warning systems, improving outbreak preparedness, and ensuring equitable access to vaccines and treatment are critical. Moreover, integrating infectious disease surveillance with broader health system strengthening, particularly in PHC and community outreach, will be essential to mitigate future outbreaks and reduce mortality.95

Outbreaks and the mental health system gap

Infectious disease outbreaks such as cholera, measles and malaria not only cause physical harm but also trigger significant psychological and social impacts including heightened anxiety, fear and stress, as seen during and after COVID-19.96,97 These effects are intensified by South Africa’s under-resourced mental health system where nationally, about 5% of the health budget goes to mental health and only ~25% of people who need care receive it,98,99 despite policy commitments in the National Mental Health Policy Framework and Strategic Plan 2023–2030 (NMHPFSP).9 High burdens of depression, anxiety and psychological distress among people living with HIV compound vulnerability during outbreaks (Table 14).100

Table 15.Infectious disease indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Case fatality rate: cholera 2023/24 WHO 3.4 a
Reported cases of cholera 2023/24 WHO 1 395 a
Reported cases of cholera
(per 100 000)
2023/24 WHO 2.5 a
Reported cases of malaria 2023 both sexes all ages NICD 4 384 50 70 830 332 2 137 635 18 118 194 b
both sexes all ages WHO 5 291 c
Reported cases of measles 2023 NICD lab-diagnosed 1 029 8 34 284 33 435 40 19 113 63 d
2024 NICD lab-diagnosed 833 52 48 311 114 25 53 43 127 60 d
Reported deaths from cholera 2023/24 WHO 47 a
Reported deaths from malaria 2023 both sexes all ages WHO 113 c

Sources:
a: Global Cholera Dashboard93
b: NICD NMC 202427
c: World Malaria 202422
d: NICD Dashboard94

Indicator [units]: Definition

• Case fatality rate: cholera [Percentage]: Number of deaths divided by the number of cases expressed as a percentage.

• Reported cases of cholera [per 100 000 population]: The number of cases of cholera reported to the National Department of Health per 100 000 population (for the relevant year). Also known as incidence of cholera or ‘Attack rate’.

• Reported cases of cholera [Number]: The number of cases of cholera reported to the National Department of Health. Since case-reporting of notifiable diseases has been incomplete and delayed for several years, the number of laboratory-confirmed cases from NHLS has been included where available, although these would be expected to include only a subset of the total number of notified cases.

• Reported cases of malaria [Number]: The number of cases of malaria reported to the National Department of Health.

• Reported cases of measles [Number]: The number of cases of measles reported to the National Department of Health per year.

• Reported deaths from cholera [Number]: The number of deaths from cholera reported to the National Department of Health.

• Reported deaths from malaria [Number]: The number of deaths from malaria reported to the National Department of Health or recorded in vital registration (ICD-10 codes B50-B54).

Health facilities

Health facility performance is a critical determinant of health system effectiveness. Countries with well-distributed and adequately resourced health infrastructure tend to achieve better health outcomes.101 The WHO recommends optimal bed occupancy rates range between 75% and 85%, balancing efficiency with surge capacity. Many high-income countries maintain average lengths of stay that are shorter than six days through efficient care co-ordination and post-discharge support. In contrast, low- and middle-income countries often face challenges such as under-utilisation in rural areas and overcrowding in urban centres.102

Globally, nurse workloads and facility standards are key indicators of service quality, with the WHO advocating for workload-sensitive staffing models and universal adoption of quality improvement frameworks. South Africa’s performance reflects global strengths, such as high medicine availability, as well as challenges, including regional disparities in infrastructure and staffing. Lessons from countries that have successfully decentralised services and invested in PHC revitalisation may offer valuable insights for strengthening South Africa’s health facility performance.

Psychiatric health facilities

South Africa’s mental healthcare system leans heavily on specialised psychiatric hospitals for in-patient care, with a smaller proportion of services offered at general hospitals.98 The NMPHFSP does, however, outline plans to downscale specialist mental healthcare facilities and upscale community-based care facilities, in line with WHO recommendations.103

Figure 4 shows the distribution of the 23 specialised psychiatric hospitals within the public sector in South Africa. The distribution of psychiatric facilities across the country reveals a concentration in urban and peri-urban areas, with notable clusters in provinces such as Gauteng, KwaZulu-Natal, and the Western Cape. These provinces host multiple specialised psychiatric hospitals, reflecting their higher population densities and more developed healthcare infrastructure. In contrast, provinces like Mpumalanga have no facilities, which may indicate limited access to specialised mental health services in more rural or sparsely populated regions. This uneven distribution underscores the need for strategic planning to improve equitable access to psychiatric care across all provinces, particularly in under-served areas.

Figure 4
Figure 4.Specialist psychiatric hospitals by province, 2024

Source: DHIS39

Average length of stay

The performance of South Africa’s health service infrastructure, as reflected in Table 15, reveals a system under pressure but showing signs of resilience and responsiveness. The national average length of stay (ALOS) across all hospitals was 6.4 days, with Gauteng (7.5) and Eastern Cape (7.0) reporting the longest stays which potentially reflects higher patient acuity or delayed discharges. In district hospitals, the ALOS was shorter at 4.5 days, with Free State (3.4) and Northern Cape (3.4) at the lower end, suggesting more efficient throughput or lower case complexity.39

The ALOS in specialised psychiatric hospitals across South Africa reflects considerable variation (Figure 5), highlighting differences in provincial mental health service delivery. While the national average is just under 183 days, some provinces, particularly the Free State and Limpopo, show markedly longer hospital stays, suggesting a predominance of long-term admissions or systemic factors affecting discharge. In contrast, provinces such as the Western Cape and Northern Cape report much shorter stays, possibly due to more community-based care options or higher patient turnover. These variations may be influenced by differences in bed availability, referral pathways, and the extent of mental health integration into primary and community care services. Addressing these disparities is important for ensuring equitable, efficient, and patient-centred psychiatric care nationwide.103

Figure 5
Figure 5.Average length of stay: specialised psychiatric hospitals in public sector

Source: DHIS39

Bed utilisation

Bed utilisation rates offer further insight into system capacity. The national in-patient bed utilisation rate as recorded in the public health routine system was 69.4%, with Western Cape (86.7%) and Gauteng (78.7%) operating near or above optimal thresholds, while Eastern Cape (59.1%) and KwaZulu-Natal (62.2%) reported under-utilisation. District hospital bed utilisation was lower at 61.4% nationally, with Western Cape again leading at 86.9%.39 These figures suggest regional imbalances in demand and capacity, with implications for referral patterns and resource allocation.

Primary Health Care utilisation

Primary Health Care indicators show mixed performance. The PHC utilisation rate was 1.7 visits per person per year nationally, below the recommended benchmark of 3.0. Utilisation was highest in Eastern Cape (2.1) and Limpopo (2.0), and lowest in Gauteng (1.2), suggesting access barriers or service delivery gaps in urban areas. Among children under five, the utilisation rate was higher at 3.0, with Limpopo (3.7) and Western Cape (3.2) performing well.

In-patient mortality

In-patient mortality remains a concern, with a national crude death rate of 4.7%. Eastern Cape (6.3%) and Gauteng (5.4%) reported the highest rates, while Western Cape had the lowest at 3.4%. The total number of in-patient deaths exceeded 165 000, with district hospitals accounting for nearly 44% of these. Notably, national central hospitals in Gauteng and Western Cape reported high mortality volumes, reflecting their role in managing complex cases.

Professional Nurse workloads

The PHC Professional Nurse workload averaged 23.3 patients per day, with the highest burdens in Eastern Cape (27.3) and KwaZulu-Natal (26.9), raising concerns about staff burnout and quality of care. Encouragingly, 78% of clinics nationally met the Ideal Clinic standards, with KwaZulu-Natal, North West, and Western Cape achieving 97% compliance. However, Limpopo (42%) and Northern Cape (35%) lag significantly, highlighting the need for targeted quality improvement initiatives.

Availability of medicines

Medicine availability remains strong, with 89% of Ideal Clinics reporting 90% tracer medicine availability. This is a positive sign of supply-chain stability, although continued vigilance is needed to prevent stock-outs, particularly in rural provinces.

Overall, the health service indicators reflect a health system that is functional but uneven. Addressing disparities in infrastructure, staffing and service quality will be essential to achieving equitable access and improving health outcomes across provinces.

Table 16.Health services indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZ LP MP NC NW WC Ref
Average length of stay ─ total 2023/24 DHIS 6.4 7.0 5.8 7.5 6.9 5.7 4.8 5.7 6.2 5.7 a
Average length of stay (district hospitals) 2023/24 DHIS 4.5 4.9 3.4 5.1 5.3 4.4 4.5 3.4 4.5 3.6 a
Birth registration coverage 2023 both sexes Live births of current registration 80.7 b
Complaints resolution rate 2023/24 DHIS 92.8 93.0 89.1 93.6 93.5 94.6 88.5 82.3 95.4 a
Complaints resolution rate within 25 working days 2023/24 DHIS 95.9 97.5 93.5 95.2 95.3 98.9 98.4 85.8 97.0 a
In-patient bed utilisation rate ─ total 2023/24 DHIS 69.4 59.1 62.4 78.7 62.2 69.8 64.2 61.5 73.7 86.7 a
In-patient bed utilisation rate (district hospitals) 2023/24 DHIS 61.4 48.8 51.4 72.8 55.2 68.7 61.5 52.8 66.2 86.9 a
In-patient crude death rate 2023/24 both sexes DHIS 4.7 6.3 4.2 5.4 4.7 4.6 4.4 5.2 4.7 3.4 a
In-patient deaths ─ total 2023/24 both sexes DHIS 165 341 25 430 10 649 37 229 32 543 16 321 10 292 3 907 9 182 19 788 a
DHIS District Hospital 72 529 13 519 4 718 6 588 15 893 10 035 6 271 1 599 3 397 10 509 a
DHIS National Central Hospital 21 264 1 415 699 13 144 684 0 0 0 0 5 322 a
DHIS PHC/CHC 580 0 0 37 69 0 0 451 0 23 a
DHIS Provincial Tertiary Hospital 22 194 4 174 1 086 4 782 3 289 2 423 2 071 1 184 3 034 151 a
DHIS Regional Hospital 45 902 5 748 2 914 12 613 12 392 3 845 1 939 655 2 731 3 065 a
International Health Regulations (IHR) core capacity index 2024 WHO 63.0 c
Number of beds Mar 2024 DHIS District Hospital 31 360 6 118 1 674 2 596 8 731 4 240 2 900 577 1 240 3 284 a
DHIS public sector 85 119 13 111 4 822 17 873 20 506 7 853 4 721 1 636 4 480 10 117 a
Number of health facilities Mar 2024 DHIS CHC/CDC 359 43 10 42 23 26 58 33 48 76 a
DHIS Clinic 3 150 735 210 332 597 451 241 130 269 185 a
DHIS District Hospital 253 65 25 12 42 30 23 11 12 33 a
DHIS Military Hospital 3 1 1 1 a
DHIS National Central Hospital 9 1 1 4 1 2 a
DHIS Provincial Tertiary Hospital 18 3 1 3 3 2 2 1 2 1 a
DHIS Regional Hospital 48 5 4 9 13 5 3 1 3 5 a
DHIS Specialised Psychiatric Hospital 23 4 1 3 5 3 1 2 4 a
DHIS Specialised TB Hospital 25 10 3 1 4 1 6 a
OHH headcount under 5 years coverage 2023/24 DHIS 117 85 95 99 160 116 114 98 110 126 a
Patient Day Equivalent 2023/24 DHIS 30 808 628 3 871 881 1 881 297 7 264 514 6 695 183 2 863 895 1 803 704 613 994 1 598 498 4 215 662 a
DHIS District Hospital 4 041 4 079 3 139 4 345 4 051 3 798 4 974 7 281 4 641 3 043 a
Percentage Ideal Clinics 2023/24 IC status 78 63 91 96 97 42 97 35 97 87 d
Percentage Ideal Clinics with 90% of tracer medicines available 2023/24 IC 89 91 88 90 97 87 87 85 89 90 d
PHC headcount total 2023/24 both sexes all ages DHIS 104 773 184 13 943 191 5 206 919 5 206 919 19 293 430 24 040 578 12 462 544 8 167 138 2 683 013 7 117 778 a
PHC Professional Nurse clinical work load 2023/24 DHIS 23.3 27.3 24.9 23.7 26.9 19.0 26.2 18.7 17.5 21.0 a
PHC utilisation rate 2023/24 DHIS 1.7 2.1 1.8 1.2 2.0 2.0 1.7 2.0 1.7 1.6 a
PHC utilisation rate under 5 years 2023/24 DHIS 3.0 3.1 3.0 2.4 3.1 3.7 3.1 3.1 2.8 3.2 a

Sources:
a: National Treasury26
b: Medical Schemes 202323
c: World Health Statistics 20257

Indicator [units]: Definition

• Average length of stay ─ total [Days]: The average number of days that an admitted patient spends in hospital before separation.

• Average length of stay (district hospitals) [Days]: The average number of days that an admitted patient spends in hospital before separation.

• Birth registration coverage [Percentage]: Percentage of births that are registered within one month of age in a civil registration system.

• Complaints resolution rate [Percentage]: Complaints resolved as a proportion of complaints received.

• Complaints resolution rate within 25 working days [Percentage]: Complaints resolved within 25 working days as a proportion of all complaints resolved.

• In-patient bed utilisation rate ─ total [Percentage]: A measure of the average number of beds that are occupied ─ expressed as the proportion of all available bed days, which is calculated as the number of actual beds multiplied by the average number of days in a month (30.42).

• In-patient bed utilisation rate (district hospitals) [Percentage]: A measure of the average number of beds that are occupied ─ expressed as the proportion of all available bed days, which is calculated as the number of actual beds multiplied by the average number of days in a month (30.42).

• In-patient crude death rate [Percentage]: Proportion of admitted clients/separations who died during hospital stay. In-patient separations is calculated as the total of day clients, in-patient discharges, in-patient deaths, and in-patient transfers out.

• In-patient deaths ─ total [Number]: An in-patient death is a death recorded against an admitted in-patient, including the death of a patient admitted earlier on the same day. The total is specialities plus all others that do not appear on the identified specialities.

• International Health Regulations (IHR) core capacity index [Percentage]: Percentage of attributes of 13 core capacities that have been attained at a specific point in time. The 13 core capacities are: (1) National legislation, policy and financing; (2) Co-ordination and National Focal Point communications; (3) Surveillance; (4) Response; (5) Preparedness; (6) Risk communication; (7) Human resources; (8) Laboratory; (9) Points of entry; (10) Zoonotic events; (11) Food safety; (12) Chemical events; (13) Radio-nuclear emergencies.

• Number of beds [Number]: The total number of beds in a health facility.

• Number of health facilities [Number]: The total number of health facilities.

• OHH headcount under 5 years coverage [Percentage]: Children 5 years and older in the population who received care during Ward-based Outreach Team visits.

• Patient Day Equivalent [Number]: The sum of in-patient days total x 1, Day patient total x 0.5, and OPD/Emergency total headcount x 0.3333333.

• Percentage Ideal Clinics [Percentage]: Percentage of fixed PHC facilities assessed on the Ideal Clinic dashboard that achieved Ideal Clinic status (silver, gold, platinum or diamond status).

• Percentage Ideal Clinics with 90% of tracer medicines available [Percentage]: Percentage of Ideal Clinics with 90% of the tracer medicines available.

• PHC headcount total [Number]: All individual clients attending Primary Health Care services at a facility.

• PHC Professional Nurse clinical work load [Clients per nurse per day]: The average number of clients seen per Professional Nurse per Professional Nurse clinical work day.

• PHC utilisation rate [Average number of visits per person]: The average number of PHC visits per person per year in the population.

• PHC utilisation rate under 5 years [Average number of visits per person under 5 years]: The average number of PHC visits per year per person under 5 years of age in the population.

Health personnel

The health workforce crisis remains a major barrier to achieving universal health coverage where there is a projected shortfall of 10 million health workers by 2030, primarily in low- and lower-middle-income countries.104 Many nations face similar challenges to South Africa, including maldistribution of health professionals, urban─rural disparities, and shortages in specialised cadres such as mental health professionals. High-income countries often rely on international recruitment to fill gaps, which can exacerbate workforce shortages in source countries. Task-shifting and Community Health Worker programmes have been adopted globally to address these gaps, with countries like Ethiopia, Brazil, and India demonstrating scalable models.105

Strengthening health workforce information systems, improving retention strategies, and aligning training with population health needs are global priorities echoed in the WHO Global Strategy on Human Resources for Health.106 A closer look at South Africa’s human resources for health reveals a system marked by both progress and persistent inequities. Rather than a uniform distribution, the data show significant provincial disparities in the availability of key health professionals. For example, the national average of medical practitioners in the public sector stands at 35.6 per 100 000 population, but this ranges from 28.0 in Free State to 40.7 in Northern Cape.28

Human resources for mental health

South Africa faces a persistent and inequitable shortage of human resources for mental health across disciplines and levels of care. There is a severe shortage of trained mental healthcare providers, with considerable variation between provinces (Figure 6).107 Psychologists, for instance, are available at just 1.5 per 100 000 nationally in the public sector, with even lower densities in provinces such as the Free State (0.9) and Mpumalanga (0.9), reflecting critical shortages in specialised and allied health professions.107 The WHO Mental Health Atlas estimates for South Africa are only 1.59 psychiatrists, 15.36 psychologists and 86.23 social workers per 100 000 overall, with just 0.11 child and adolescent psychiatrists per 100 000.16 These figures mask deep public–private and urban–rural disparities: approximately 80% of psychiatrists work in the private health sector, and the vast majority are based in urban areas in just two provinces: Gauteng and the Western Cape.108 In the public sector, which serves most of the population, psychiatrist density is only 0.38 per 100 000 compared to 4.98 per 100 000 in the private sector.109 The NMHPFSP acknowledges “major shortfalls in human resources” and reports densities among the uninsured population of just 0.31 psychiatrists and 0.97 psychologists per 100 000.9 These shortages contribute to hospital-centric models of care, limited community-based services, and significant service bottlenecks, with the most pronounced deficits to be found in rural areas and in child and adolescent mental health. Addressing these gaps requires accelerated workforce expansion, strategic redistribution, and supported task-sharing to extend equitable mental health coverage nationwide.

Figure 6
Figure 6.Mental health workforce per 100 000 population by province

Source: PERSAL28

To address the shortage of specialist mental healthcare providers, South Africa has adopted task-sharing models in line with WHO recommendations. Task-sharing refers to the structured redistribution of responsibilities traditionally performed by specialist mental health professionals, such as psychiatrists and psychologists, to non-specialist health workers. This approach aims to expand access to mental health services, particularly in resource-constrained settings like South Africa.107

Nurses

Nursing remains the backbone of the health system, with Professional Nurses at 141.3 per 100 000 nationally. However, the distribution again varies widely from 91.8 in Western Cape to 187.5 in Eastern Cape. The density of Enrolled Nurses and Nursing Assistants also reflects this imbalance, with Limpopo and Eastern Cape reporting the highest ratios. There is a need for targeted workforce planning and retention strategies, particularly in under-served provinces.

Medical doctors

The gap between registered and employed professionals is another concern. For example, while 53 408 medical practitioners are registered with the Health Professions Council of South Africa (HPCSA)24 (as of October 2024), only 16 493 are employed in the public sector. This suggests that a significant proportion of the workforce is either in the private sector or not actively practising, raising questions about workforce absorption and distribution.

To address these challenges, South Africa must strengthen its Human Resources for Health (HRH) strategy through improved forecasting, equitable deployment, and incentives for rural service. The 2030 National Human Resources for Health Strategy outlines many of these priorities, but implementation remains uneven. Without a concerted effort to align workforce supply with population health needs, the goal of universal health coverage will remain out of reach.

Table 17.Number of health personnel practising in the public sector by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Number of clinical associates registered 2024 Oct both sexes HPCSA 1 266 a
Number of CS clinical psychologists 2024 Mar both sexes public sector 66 4 3 33 8 3 3 1 3 8 b
Number of CS dentists 2024 Mar both sexes public sector 223 17 29 46 43 21 16 13 22 16 b
Number of CS dieticians 2024 Mar both sexes public sector 213 18 20 60 37 13 19 13 27 6 b
Number of CS doctors 2024 Mar both sexes public sector 2 457 276 112 473 321 343 325 88 260 259 b
Number of CS environmental health practitioners 2024 Mar both sexes public sector 179 4 16 34 5 42 24 14 40 b
Number of CS nurses 2024 Mar both sexes public sector 2 449 300 195 577 284 192 255 59 238 349 b
Number of CS occupational therapists 2024 Mar both sexes public sector 336 62 27 90 66 13 26 21 16 15 b
Number of CS optometrists 2024 Mar both sexes public sector 184 6 6 54 104 7 2 4 1 b
Number of CS pharmacists 2024 both sexes SAPC 959 139 22 219 203 136 66 16 59 99 c
2024 Mar both sexes public sector 734 67 45 163 152 82 54 45 74 52 b
Number of CS physiotherapists 2024 Mar both sexes public sector 431 69 30 102 74 16 31 27 53 29 b
Number of CS radiographers 2024 Mar both sexes public sector 396 34 13 104 83 30 36 10 49 37 b
Number of CS speech therapists 2024 Mar both sexes public sector 271 31 10 68 86 11 19 13 25 8 b
Number of dental practitioners 2024 Mar both sexes public sector 945 146 43 215 113 148 74 28 50 128 b
Number of dental practitioners registered 2024 Oct both sexes HPCSA 6 756 a
Number of dental specialists 2024 Mar both sexes public sector 127 2 91 1 4 1 28 b
Number of dental therapists 2024 Mar both sexes public sector 342 17 1 42 100 121 22 26 12 1 b
Number of dental therapists registered 2024 Oct both sexes HPCSA 928 a
Number of enrolled nurses 2024 Mar both sexes public sector 27 570 3 225 1 054 6 667 9 226 2 642 835 198 976 2 747 b
Number of environmental health practitioners 2024 Mar both sexes public sector 444 19 87 133 79 33 47 13 33 b
Number of environmental health practitioners registered 2024 Oct both sexes HPCSA 4 107 a
Number of medical practitioners 2024 Mar both sexes public sector 16 493 1 939 600 4 128 3 869 1 438 1 008 374 1 079 2 058 b
Number of medical practitioners (including specialists) registered 2024 Oct both sexes HPCSA 53 408 a
Number of medical researchers 2024 Mar both sexes public sector 34 4 19 4 2 1 1 3 b
Number of medical specialists 2024 Mar both sexes public sector 4 529 177 326 1 763 813 77 62 40 162 1 109 b
Number of nursing assistants 2024 Mar both sexes public sector 33 221 5 222 2 091 6 441 5 438 4 324 2 011 785 2 692 4 217 b
Number of occupational therapists 2024 Mar both sexes public sector 1 041 110 47 266 143 189 54 25 40 167 b
Number of occupational therapists registered 2024 Oct both sexes HPCSA 6 233 a
Number of optometrists and opticians 2024 Mar both sexes public sector 65 65 b
Number of pharmacists 2024 Mar both sexes public sector 5 714 938 386 1 180 856 608 370 107 258 1 011 b
Number of pharmacists registered 2024 both sexes SAPC 17 929 2 008 612 6 116 2 860 869 905 270 1 198 3 057 c
Number of physiotherapists 2024 Mar both sexes public sector 1 127 134 47 193 265 150 78 33 76 151 b
Number of physiotherapists registered 2024 Oct both sexes HPCSA 8 783 a
Number of professional nurses 2024 Mar both sexes public sector 72 845 11 047 2 334 15 271 17 838 8 308 6 507 1 445 4 945 5 150 b
Number of psychologists 2024 Mar both sexes public sector 732 72 21 215 101 124 34 14 42 109 b
Number of psychologists registered 2024 Oct both sexes HPCSA 9 511 a
Number of radiographers 2024 Mar both sexes public sector 2 888 367 146 846 593 213 114 71 115 423 b
Number of radiographers registered 2024 Oct both sexes HPCSA 8 892 a
Number of speech therapists and audiologists 2024 Mar both sexes public sector 580 61 12 143 144 52 44 17 31 76 b
Number of student nurses 2024 Mar both sexes public sector 497 38 329 126 4 b

Sources:
a: HPCSA24
b: PERSAL28

Table 18.Health personnel per 100 000 uninsured population by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Density of dentistry personnel (per 100 000 population) 2023 both sexes WHO 0.2 a
Density of midwifery personnel (per 100 000 population) 2022 both sexes WHO 63.9 a
Density of pharmaceutical personnel
(per 100 000 population)
2022 both sexes WHO 2.7 a
Dental practitioners per 100 000 population 2024 Mar both sexes public sector 2.2 2.7 2.8 2.0 1.5 2.9 2.1 3.6 1.9 2.4 b
Dental specialists per 100 000 population 2024 Mar both sexes public sector 0.2 0.1 0.7 0.0 0.1 0.0 0.5 b
Dental therapists per 100 000 population 2024 Mar both sexes public sector 0.6 0.3 0.0 0.3 1.0 2.1 0.5 2.3 0.3 0.0 b
Enrolled nurses per 100 000 population 2024 Mar both sexes public sector 51.7 53.3 41.4 51.8 87.2 45.9 19.3 17.4 25.4 45.9 b
Environmental health practitioners per 100 000 population 2024 Mar both sexes public sector 1.2 0.4 4.0 1.3 0.8 1.3 1.6 2.4 1.9 b
Medical practitioners per 100 000 population 2022 both sexes WHO 7.9 a
2024 Mar both sexes public sector 35.6 36.6 28.0 35.7 39.6 30.9 30.8 40.7 34.9 38.7 b
Medical specialists per 100 000 population 2024 Mar both sexes public sector 8.5 2.9 12.8 13.7 7.7 1.3 1.4 3.5 4.2 18.5 b
Nursing assistants per 100 000 population 2024 Mar both sexes public sector 62 86 82 50 51 75 47 69 70 70 b
Occupational therapists per 100 000 population 2024 Mar both sexes public sector 3 3 3 3 2 4 2 4 2 3 b
Pharmacists per 100 000 population 2024 Mar both sexes public sector 12 17 17 10 10 12 10 13 9 18 b
Physiotherapists per 100 000 population 2024 Mar both sexes public sector 3 3 3 2 3 3 3 5 3 3 b
Professional nurses per 100 000 population 2024 Mar both sexes public sector 141 188 99 123 171 148 156 132 135 92 b
Psychologists per 100 000 population 2024 Mar both sexes public sector 2 1 1 2 1 2 1 1 1 2 b
Radiographers per 100 000 population 2024 Mar both sexes public sector 6 7 6 7 6 4 4 7 4 8 b
Speech therapists and audiologists per
100 000 population
2024 Mar both sexes public sector 2 2 1 2 2 1 2 3 2 1 b

Sources:
a: World Health Statistics 20257
b: PERSAL28

Health financing

Many low- and middle-income countries continue to struggle with inadequate public health spending, high out-of-pocket expenditures, and limited financial risk protection. While South Africa has met the Abuja target of allocating at least 15% of government expenditure to health, most African countries fall short, with the regional average hovering around 9%. Globally, the average government health expenditure as a share of GDP is 6.6%, with high-income countries spending over 8% and low-income countries often below 2%. Out-of-pocket spending remains a major barrier to access in many regions, accounting for over 40% of total health expenditure in some countries, leading to catastrophic health costs and impoverishment.20

Mental health programme expenditure

Mental healthcare spending in South Africa is estimated to account for 5% of the total public health budget. However, six out of nine provinces allocate less than this benchmark.98,103 In South Africa, mental healthcare services are predominantly concentrated at the top of the healthcare system, mainly within secondary hospitals and specialist facilities.107 An estimated 86% of the mental health budget is reportedly spent on in-patient care, with nearly half of that going to tertiary hospitals.98 This leaves significantly fewer resources available at other levels of care, especially within community-based services ─ thus going against the WHO’s optimal mix of services pyramid, which recommends integrating mental health into primary health care and limiting the number of psychiatric hospitals or specialist services providing long-term chronic care.107

An analysis of provincial health budget allocations to mental health care showed that Gauteng (6.2%), KwaZulu-Natal (5.0%), and the Western Cape (7.5%) allocate a higher-than-average share, indicating stronger prioritisation of mental health. In contrast, provinces such as the Eastern Cape (2.8%), Limpopo (2.6%), and the North West (3.1%) dedicate a smaller proportion of their budgets to this area.109 In their analysis of health expenditure on mental health programmes across provinces, Docrat, et al. (2019)109 highlighted that PHC receives the lowest contribution from the total mental health budget, followed by district hospitals. The PHC expenditure also includes the costs of medication for people living with severe mental health conditions who are discharged from hospitals and community health centres.107

Key recommendations for improving mental health financing emphasise optimising the use of existing resources. This includes aligning human resource allocations and budgets with actual service demands; restructuring hospital platforms to support shorter in-patient stays and expanded out-patient care; and redirecting funds to fully operationalise under-utilised facilities rather than investing in new infrastructure.98

Health programmes expenditure

The percentage of expenditure per programme by province, as illustrated in Figure 7, shows that District Health Services saw increased prioritisation in provinces such as KwaZulu-Natal and the Eastern Cape, suggesting an emphasis on PHC and community-level service delivery. Although there was a slight decline, Central Hospital Services expenditure has dominated in provinces like Free State, Mpumalanga and Limpopo, indicating continued reliance on tertiary care infrastructure in these regions. Overall, Health Facilities Management, Health Sciences and Training, and Emergency Health Services remained relatively stable across provinces, showing consistent investment in infrastructure, workforce development, and emergency response.

Figure 7
Figure 7.Percentage of expenditure per programme by province, 2018/19 compared to 2023/24

Source: BAS (National Treasury)26

Medical scheme coverage

Medical scheme coverage remains highly unequal. Nationally, only 14.7% of the population is covered by medical schemes, with Gauteng (39%) and Western Cape (15%) far exceeding provinces like Northern Cape (2%) and Free State (5%). This entrenches a two-tiered health system, where access to private care is concentrated among wealthier, urban populations. The pensioner ratio within medical schemes, which is 9.4% overall and 11.4% among females, also highlights the ageing of the insured population, with implications for scheme sustainability and benefit design.23

Table 19.Health financing indicators by province
Indicator Period Sex|Age|Series|Cat SA EC FS GP KZN LP MP NC NW WC Ref
Expenditure per patient day equivalent (district hospitals) 2023/24 BAS real 2023/24 prices 3 754 3 913 3 049 4 493 3 853 3 596 3 655 3 469 4 683 3 193 a
Medical scheme beneficiaries 2023 both sexes all ages med schemes 9 127 453 668 146 414 470 3 529 855 1 302 597 498 749 578 240 192 648 499 642 1 411 888 b
female all ages med schemes 4 908 106 b
male all ages med schemes 4 219 347 b
Medical scheme coverage 2023 both sexes all ages med schemes 14.7 7.0 5.0 39.0 14.0 5.0 6.0 2.0 5.0 15.0 b
female all ages med schemes 54.0 b
male all ages med schemes 46.0 b
Pensioner ratio 2023 both sexes all ages med schemes 9.4 b
female all ages med schemes 11.4 b
male all ages med schemes 8.9 b
Provincial & LG District Health Services expenditure per capita (uninsured) 2023/24 BAS real 2023/24 prices 2 355 2 608 2 305 1 834 2 644 2 788 2 529 2 647 2 086 2 283 a
Provincial & LG PHC expenditure per capita (uninsured) 2023/24 BAS real 2023/24 prices 1 448 1 440 1 563 1 352 1 676 1 305 1 378 1 630 1 370 1 415 a
Provincial & LG PHC expenditure per PHC headcount 2023/24 BAS real 2023/24 prices 724.4 625.7 758.0 882.6 729.2 599.6 719.5 683.1 726.2 701.1 a
Total net official development assistance to medical research and basic health sectors per capita (US$) by recipient country 2022 WHO 1.5 c

Sources:
a: National Treasury26
b: Medical Schemes 202323
c: World Health Statistics 20257

Indicator [units]: Definition

• Expenditure per patient day equivalent (district hospitals) [Rand (real prices)]: Average cost per patient per day seen in a hospital (expressed as Rand per patient day equivalent).

• Medical scheme beneficiaries [Number]: Number of medical scheme beneficiaries, as reported by the Medical Schemes Council.

• Medical scheme coverage [Percentage]: Proportion of population covered by medical schemes

• Pensioner ratio [Percentage]: Proportion of members of medical schemes who are 65 years or older, in registered medical schemes.

• Provincial & LG District Health Services expenditure per capita (uninsured) [Rand (real prices)]: Provincial expenditure on District Health Services (all sub-programmes except 2.8 Coroner services) plus net local government expenditure on PHC per uninsured population.

• Provincial & LG PHC expenditure per capita (uninsured) [Rand (real prices)]: Provincial expenditure on sub-programmes of DHS (2.2 ─ 2.7) plus net local government expenditure on PHC per uninsured population.

• Provincial & LG PHC expenditure per PHC headcount [Rand (real prices)]: Provincial expenditure on sub-programmes of DHS (2.2 ─ 2.7) plus net local government expenditure on PHC divided by PHC headcount from DHIS.

• Total net official development assistance to medical research and basic health sectors per capita (US$) by recipient country [Percentage]: Gross ODA disbursements from all donors to those sectors, divided by recipient population.

Table 20.Trends in overall provincial health expenditure by programme, nominal prices (Rand million, nominal prices), 2013/14 – 2023/24
Financial Year
Programme FY 2014 FY 2015 FY 2016 FY 2017 FY 2018 FY 2019 FY 2020 FY 2021 FY 2022 FY 2023 FY 2024
1. Administration 3 578 3 599 4 313 4 462 4 690 5 129 5 368 8 799 7 596 7 273 7 207
2. District Health Services 57 991 64 181 69 854 76 540 83 671 90 978 98 688 109 448 115 084 116 406 118 957
3. Emergency Health Services 5 352 5 556 6 025 6 435 7 380 7 671 8 394 8 660 8 791 9 817 10 464
4. Provincial Hospital Services 26 420 28 694 29 576 29 675 32 262 34 275 36 609 37 623 39 134 40 607 43 442
5. Central Hospital Services 23 559 25 804 29 529 33 736 37 437 41 120 44 608 47 516 47 227 50 010 51 560
6. Health Sciences and Training 4 039 4 248 4 529 5 107 4 916 5 037 5 115 4 796 4 792 5 270 5 314
7. Health Care Support Services 1 877 1 322 2 834 1 796 1 806 4 661 2 301 3 469 3 073 2 936 3 072
8. Health Facilities Management 7 895 7 491 8 514 8 316 8 651 9 014 9 844 11 526 10 433 10 236 10 574
Local government expenditure 2 869 3 389 3 730 4 103 4 199 4 858 4 828 5 392 5 158 5 140 5 285
Other 0 0 0 0 0 0 0 -14 0 0 0
Grand Total 133 581 144 283 158 903 170 171 185 013 202 744 215 755 237 229 241 273 247 697 255 877

Expenditure per patient day equivalent

There are still persistent disparities in health spending across provinces and between insured and uninsured populations, as shown in Table 18. Nationally, the average expenditure per patient day equivalent (PDE) in district hospitals was R3 754, with Gauteng (R4 493) and North West (R4 683) spending significantly above the national average, while Free State (R3 049) and Western Cape (R3 193) reported the lowest.26 These differences may reflect variations in input costs, service delivery models, and efficiency, but also raise concerns about equity and resource allocation.

District Health Services expenditure

Per capita expenditure on District Health Services for the uninsured population averaged R2 355 nationally, with Limpopo (R2 788) and KwaZulu-Natal (R2 644) at the higher end, and Gauteng (R1 834) at the lowest despite its large uninsured population.26 This suggests a potential mismatch between population need and financial allocation. Similarly, PHC expenditure per capita ranged from R1 305 in Limpopo to R1 676 in KwaZulu-Natal, while PHC expenditure per headcount was highest in Gauteng (R882.6) and lowest in Limpopo (R599.6), indicating differences in service utilisation and cost structures.

Official development assistance

South Africa received just USD1.50 per capita in official development assistance (ODA) for medical research and basic health in 2022, underscoring the need for greater domestic investment in health system strengthening. While ODA plays a supplementary role, reliance on external funding is not sustainable for core service delivery.7

There is an urgent need for more equitable and efficient health financing. The National Health Insurance (NHI) policy aims to address these disparities, but its success will depend on robust fiscal planning, improved public financial management, and transparent allocation mechanisms. Strengthening provincial budgeting processes and aligning expenditure with population health needs are essential steps towards universal health coverage.110 Furthermore, in alignment with the recommendations of the National Mental Health Investment Case,111 it is essential to establish dedicated mental health directorates in all nine provinces. Building capacity to effectively plan, manage and evaluate integrated mental health services is also critical to strengthening the system and ensuring sustainable delivery.

Table 21.Provincial expenditure by programme per province (Rand million), 2023/24
Financial Year 2024
Programme EC FS GP KZN LP MP NC NW WC
1. Administration 759 317 2 170 1 014 284 339 264 1 081 981
2. District Health Services 15 618 5 820 20 529 27 511 15 873 10 672 2 942 7 827 12 165
3. Emergency Health Services 1 360 977 2 065 1 692 1 577 474 522 447 1 350
4. Provincial Hospital Services 4 253 1 712 12 030 13 188 2 902 1 710 520 2 326 4 801
5. Central Hospital Services 5 133 2 988 21 549 5 925 2 302 1 842 1 249 2 422 8 150
6. Health Sciences and Training 872 280 700 1 341 598 515 321 269 419
7. Health Care Support Services 113 165 439 356 165 361 126 729 619
8. Health Facilities Management 1 018 759 1 832 1 908 888 1 754 453 793 1 169
Local government expenditure 327 52 2 883 438 91 117 34 96 1 249
Grand Total 29 454 13 070 64 196 53 371 24 680 17 783 6 432 15 989 30 902
Table 22.District Health Service expenditure by province (Rand million), 2023/24
Financial year 2024
2. District Health Services
Subprogramme EC FS GP KZ LP MP NC NW WC
2.1 District Management 1 036 146 1 393 372 592 647 376 860 452
2.2 Community Health Clinics 3 284 1 067 2 757 5 645 3 737 1 929 635 1 344 1 741
2.3 Community Health Centres 1 541 178 2 417 2 297 648 1 199 451 1 471 2 919
2.4 Community-based Services 790 711 3 055 1 070 666 20 - 4 477
2.5 Other Community Services 55 0 1 878 469 - 149 519 -
2.6 HIV/AIDS 2 697 1 922 5 853 6 172 1 858 2 603 561 1 735 1 857
2.7 Nutrition 30 17 64 32 5 9 3 1 71
2.8 Coroner Services 143 51 302 300 - - - 50 -
2.9 District Hospitals 6 042 1 728 4 688 9 746 7 899 4 265 768 1 844 4 648
Grand Total 15 618 5 820 20 529 27 511 15 873 10 672 2 942 7 827 12 165

Conclusion and recommendations

Globally, the integration of mental health into broader health and development agendas is gaining momentum. Countries are increasingly recognising the importance of mental health data governance, standardised indicators, and community-based care models. The WHO Mental Health Atlas and the SDGs have catalysed efforts to embed mental health metrics into national surveillance systems. However, challenges persist worldwide, including fragmented data systems, under-reporting, and limited disaggregation by key equity dimensions.

Lessons from countries that have successfully harmonised mental health indicators and strengthened data infrastructure such as Chile,112 Thailand113 and the United Kingdom (NHS Mental Health datasets) offer valuable insights for South Africa. A global shift towards open data access, cross-sectoral collaboration, and investment in digital health platforms underscores the need for South Africa to align its mental health surveillance strategies with international best practices to ensure policy relevance and equitable service delivery.

In the context of mental health, the expansion of routine indicators, policy frameworks, and longitudinal cohort resources presents a significant opportunity for enhanced analysis and system insight. However, fragmented data governance, incomplete inclusion of community and informal care data, and limited disaggregation continue to hinder the generation of actionable evidence. Addressing these challenges will require the adoption of harmonised indicator standards, improved data quality assurance mechanisms, integration of mental health metrics into broader health and development monitoring systems, and greater transparency and accessibility to support effective policy translation.

The current distribution of mental health expenditure in South Africa reflects a system heavily skewed towards specialist and in-patient care, with limited investment in community and PHC services. This imbalance not only undermines equitable access to mental health care, but also diverges from global best practices advocating for integrated, community-based mental health care.

Abbreviations
Abbreviation description
AIDS acquired immunodeficiency syndrome
ALOS average length of stay
AQLI air quality life index
ART antiretroviral therapy
BCG Bacillus Calmette-Guérin
Bt40 Birth–to–Forty
CMS Council for Medical Schemes
DALYs disability-adjusted life-years
DCHS Drakenstein Child Health Study
DHIS District Health Information System
DIMAMO Dikgale, Mamabolo and Mothiba
DS-TB drug-sensitive tuberculosis
FSW female sex worker
GAD generalised anxiety disorder
GBD global burden of disease
GDP gross domestic product
GHS General Household Survey
GLOBOCAN Global Cancer Observatory
HDI Human Development Index
HAALSi Health and Ageing in Africa: A Longitudinal Study of an INDEPTH Community in South Africa
HDR Human Development Report
HDSS health and demographic surveillance systems
HIV human immunodeficiency virus
HPCSA Health Professions Council of South Africa
HRH human resources for health
IDF International Diabetes Federation
MDD major depressive disorder
MDR-TB multi-drug resistant tuberculosis
MHQ mental health quotient
MSM men who have sex with men
MYE mid-year estimates
NCD non-communicable disease
NCR National Cancer Registry
NHI National Health Insurance
NICD National Institute for Communicable Diseases
NMHPFSP National Mental Health Policy Framework and Strategic Plan
NSP National Strategic Plan
ODA official development assistance
PCV pneumococcal conjugate vaccine
PERSAL Personnel and Salary System
PHC primary health care
PLHIV people living with HIV
PMTCT prevention of mother-to-child transmission
PTSD post-traumatic stress disorder
PWID people who inject drugs
RTMC Road Traffic Management Corporation
SA South Africa
SABSSM South African National HIV Prevalence, Incidence, Behaviour and Communication Survey
SACENDU South African Community Epidemiology Network on Drug Use
SADAG South African Depression and Anxiety Group
SAFMH South African Federation for Mental Health
SANAC South African National AIDS Council
SANHANES South African National Health and Nutrition Examination Survey
SAPRIN South African Population Research Infrastructure Network
SDGs Sustainable Development Goals
SGBV sexual and gender-based violence
STI sexually transmitted infection
SUN Scaling Up Nutrition
TB tuberculosis
TG trans-gender
ToP termination of pregnancy
UNAIDS Joint United Nations Programme on HIV/AIDS
UNDP United Nations Development Programme
UNICEF United Nations Children's Fund
WHO World Health Organization
XDR-TB extensively drug-resistant tuberculosis