FACT SHEET Rural Health - November 2013

FACT SHEET Rural Health - November 2013 Key: Shading: Pale blue/grey: facts from 2009 fact sheet, White: updated /new facts, Green: provinces with over half rural population Issue Fact/Description Source Comment RURAL HEALTH SPECIFIC Population +/ 43.7 of SA population lives in rural areas Stats are based on Census 2001, which represent the latest official Stats SA statistics on rural population. Current definition used by Stats SA to refer to rural: Proportion of population living in a non-urban environment Human resources for Health (HRH) 2011pg 30 The statistic 43.6% rural was quoted in the HRH document (2011), so is probably the most current stat, although no reference given in HRH Kok & Collison, 2006 pg 20 Kok (2006) says 42% rural (pg 20) Rural population per province Provinces where more than half of the population is rural: Limpopo, Mpumalanga, Eastern Cape, North West, KZN Kok & Collison (2006) urbanisation figures pg 22 (Calculation below (2008): 41%) Stats from Kok & Collison 2006): Rural calculated as everything that is not urbanized: 62 25 4 55 90 61 20 59 10 42 STATSSA 2008 P0100 (Income and expenditure survey 2005/2006) Urban pg 43, rural pg 44 Calculations from STATSSA 2008 (Income and expenditure survey 2005/2006): Percentage rural population 58 20 4 53 88 59 29 55 7 41 Provinces where more than half of the population is rural: Limpopo, Mpumalanga, Eastern Cape, North West, KZN (used as rural provinces in this document) 10 Most deprived districts KZN: Uthukela, Ugu, Sisonke, Zululand, Umkhanyakude and Umzinyathi districts, Eastern Cape: Chris Hani, Alfred Nzo and O.R. Tambo districts), Limpopo: Greater Sekhukhune district Districts with highest HIV prevalence Provinces with highest HIV prevalence Medical scheme coverage (%) 2011 Gert Sibande 46.1% (Mpumalanga) Ugu 41.7% (KZN) Umkhanyakude 41.1% (KZN) Sisonke 39.9% (KZN) Umgungundlovu 39.8% (KZN) KZN: 37.4% Mpumalanga: 36.7% Free State: 32.5% North West: 30.2% HST-District Health Barometer 07/08 The most recent DHB (2012-20130 says there is no new data on this (DHB 2012-2013, pg v) DoH National Antenatal Sentinel HIV and Syphilis Prevalence Survey, 2012, for the year 2011 (pg 17) DoH National Antenatal Sentinel HIV and Syphilis Prevalence Survey, 2012, for the year 2011 (pg 14) SAHR 2012/2013 pg 274 -In 2007, the ten most deprived districts in South Africa were all rural and fell within three provinces: KwaZulu-Natal, EC and LP -Examples of indicators used: household heads who have no schooling, who are adults between 25 and 59 classified as unemployed; living in a traditional dwelling, informal shack or tent; no piped water in their house or on site; a pit or bucket toilet or no form of toilet; no access to electricity or solar power for lighting, heating or cooking All these districts are in provinces where more than half the population is rural KZN, Mpumalanga, and NW are rural 10.5 14.4 27.3 12.1 7.9 15.9 16.6 15.4 24.7 16.9 1

Issue Fact/Description Source Comment Percentage of population covered by medical schemes Only Gauteng and WC have values above the SA average Health expenditure Poor rural households in a Limpopo Goudge J et al, 2009 Based on research by the Agincourt Health and Population Unit (AHPU) District spend up to 80% of monthly income on health expenditure, travel costs being a significant contributor Education and facilities Lacking in rural areas SAHRC 2007 Lack thereof impediment in attracting staff to rural areas Pharmacies Lack/shortage of pharmacies in rural areas NHI proposal Oversupply of pharmacies at proximity of one another in urban areas. Human resources shortages The shortages are highest in the rural areas Equal Treatment, South African Human Rights Commission (SAHRC). Public Enquiry: Access to Health Care Services (2007), Wits Centre for Rural Health Strategy (2008) Of the 1200 medical students graduating in SA yearly, 35 end up working in rural areas (HST and AHP in Equal Treatment, Sept 2009) - Typical urban province: 30 generalists and 30 specialists for each 100 000 pax not covered by medical aid. Rural province; average of 13 generalists and 2 specialists available per 100 000 people (Couper and Hugo, unpublished) -The three provinces with the highest % of rural inhabitants, have the lowest nr of medical practitioners per 100 000 population: NW, EC and LP (Wits Centre for Rural Health Strategy, 2008) -Psychiatric personnel shortages especially in rural areas (SAHRC, 2007), -11% of Pharmacists practice in public sector. 3 times more pharmacists in WC than in NW (Aids Law Project, Health and Democracy (2007) -In 2004, 2/3 of health posts vacant in Mpumalanga (Aids Law Project, Health and Democracy (2007) -Managers highlighted the difficulties associated with attracting staff to rural areas and retaining them in rural areas (SAHRC (2007), -Rural Districts struggle to fill posts for nurses (eg Vrijburg, NW) -Due to staff shortages, higher workload and extremely stressful work environment Human resource distributions The shortages are the highest in the rural areas: Total (public and private): Lowest: NW, EC, Mpumalanga, Limpopo Highest: WC, Gauteng Human Resources for Health (HRH) 2011 Total (public and private) HRH per 10 000 population per province 2010 (HRH 2011 pg 26) 44.83 52.01 69.21 58.83 48.83 45.24 55.53 33.06 74.08 55.67 Lowest HRH per 10 000 population: NW, EC, Mpumalanga, Limpopo Highest HRH per 10 000 population: WC and Gauteng Medical practitioners: Lowest: Limpopo, NW, EC, Mpumalanga Highest: WC Gauteng Nurses: Pharmacists: Lowest: Limpopo, EC, NW Highest: WC, Gauteng Human Resources for Health (HRH) 2011 Medical practitioners: Number of medical practitioners per 10 000 pop: HRH 2011 pg 29 Note: a large percentage of the uninsured also visit private medical practitioners Public 2.97 3.00 4.02 4.69 2.68 3.16 5.39 2.30 4.52 3.66 Private 1.77 3.10 7.32 2.93 0.97 2.11 1.97 2.37 7.64 3.76 Total 2.53 3.04 5.23 4.05 2.06 2.77 4.13 2.32 5.67 3.70 This table shows that WC and Gauteng are best off with regard to medical practitioners Limpopo has the lowest number followed by NW, EC, and Mpumalanga. KZN a rural province has above the national average Gauteng, WC, FS, NW all have more private than public practitioners Dental practitioners: Lowest: NW, Limpopo, EC Highest: WC, Gauteng Econex 2010 Health Reform Note 8: pg 3 (Note: Econex has different figures: Human resources supply constraints, the case of doctors, 2010, source of data for Econex?) Regional distribution of doctors per 100 000, public and private 31 55 102 53 17 50 37 20 135 55 This table has differing figures, but the trend is the same, except for NC. Professional nurses actively working: data only total numbers not per population in HRH 2011 pg 30 Data below taken from SAHR 2012 pg 268: for Nurses in public sector, PN enrolled with SANC (overestimate, according to Econex) SAHR 2012/2013 2

Issue Fact/Description Source Comment PN 160.1 91.2 132.3 154.8 172.1 132.0 130.1 122.1 114.4 140.8 EN 54.4 30.9 67.2 115.0 88.6 51.7 21.7 24.5 55.2 69.9 NA 100.6 84.1 80.9 68.6 119.3 59.3 91.5 89.5 97.4 86.4 PN: Professional nurse per 100 000 population, EN: Enrolled nurse per 100 000 population, NA: Nursing assistants per 100 00 population HRH 2011 pg 29 Pharmacists per 10 000 pop HRH pg 29 Public 0.45 0.63 1.18 0.51 0.54 0.95 1.21 0.38 1.93 0.78 Private 10.89 9.80 9.76 11.86 8.84 7.97 7.88 9.73 11.17 10.20 Total 1.44 1.80 3.72 1.90 1.10 2.06 2.42 1.44 4.40 2.33 This table shows that WC and Gauteng are best off with regard to total pharmacists Limpopo has the lowest number, followed by EC, NW and FS All provinces have more public than private pharmacists HRH 2011 pg 28 Dental practitioners per 100 000 population HRH pg 29 Public 0.14 0.23 0.31 0.10 0.19 0.23 0.31 0.14 0.31 0.20 Private 3.50 3.96 6.39 4.97 3.29 6.23 3.91 1.85 8.13 5.63 Total 0.46 0.70 2.11 0.70 0.40 1.1 0.96 0.33 2.40 1.09 WC and Gauteng are best off with regard total dental practitioners NW has the lowest number followed by Limpopo, EC, FS and KZN Government PERSAL system, reported by HST Government PERSAL system, reported by HST Health practitioners in the public sector: Per 100 000 population Medical practitioners (2012) 24. 9 27. 2 34. 6 33. 9 21. 6 23. 1 38. 8 20. 2 34. 7 29. 4 Professional nurses (2012) 160.1 91. 2 132.3 154.8 172.1 132.0 130.1 122.1 114.1 140.8 Enrolled nurses (2012) 54. 4 30. 9 67. 2 115.0 88. 6 51. 7 21. 7 24. 5 55. 2 69. 9 Vacant posts: Percentage of medical practitioners posts vacant in 2010 37.9 42.5 31.1 37.2 84.0 43.0 56.0 24.6 28.1 49.0 MDG 5: Cut maternal deaths by three-quarters, 3/4 Factors affecting lack of health professionals working in rural areas Each year an estimated 4300 mothers die. KZN most affected. Lancet, 2009, UN estimate HRH 2011 pg 31 Increase from less than a thousand in 1998. KZN has the largest percentage of deaths and that s because KZN is the most populous and its probably the most rural of provinces, says obstetrician, Professor Jack Moodley, chairperson of the ministerial review committee on maternal deaths. Funding Historical deficiencies in infrastructure No additional benefits for working in more inhospitable settings or policy priority settings Fear of safety Lack of opportunities for schooling children Lack of work opportunities for spouses of health workers Poor social infrastructure 3

Issue Fact/Description Source Comment Lack of strategies for recognise and compensate for these negative factors For patients: Access to health care is generally more difficult Rural communities face additional economic costs in accessing the health care system Indirect costs including transport are higher for the rural poor The consequences for individuals of a failing in a poorly resourced health system are more costly to rectify than among the urban poor How the HR are used to achieve desired outcomes are different due to the different circumstances and may require higher staffing ratios with special skills People living in rural areas are often poor and the health status of rural communities is generally poorer thatn communities in urban areas. 4

Issue Fact/Description Source Comment NON RURAL SPECIFIC FACTS POPULATION Total population Population density SA 51.7million SA 42.4 people per km 2 Stats SA, 2012. Census 2011: Provinces at a glance pg 3 SAHR 2012/2013 pg 213 Population density, provincial percentage distribution, population density Population (million) 6.5 2.7 12.2 10.3 5.4 4.0 1.1 3.5 5.8 51.8 Population 12.7 5.3 23.7 19.8 10.4 7.8 2.2 6.8 11.2 100 percentage distribution Population density 38.8 21.1 675. 1 108. 8 43.0 52.8 3.1 33.5 45.0 42.4 Rate of unemployment 29.8% Stats SA, 2012. Census 2011: Provinces at a glance pg 42 Unemployment rates for labour force aged 15-64 (from Census 2011): StatsSA 37.4 32.6 26.3 33.0 38.9 31.6 27.4 31.5 21.6 29.8 Highest unemployment rates: Limpopo, EC, KZN, FS, Mpumalanga Children Distribution of children in the provinces Children living in poverty Young children living in rural areas: 45% Children s Gauge 2012/2013 pg 27 Children s Gauge 2012/2013 pg 86 Children s Gauge 2012/2013 pg 90 Children s Gauge 2013 pg 91 From analysis of General Household Survey 2011 Number of children (millions)(under 18) Children living in income poverty* (%) Children living in HH without an employed adult (%) 2.7 1.1 3.3 4.2 2.2 1.5 0.4 1.3 1.8 18.5 74 59 34 67 76 57 63 64 31 58 51 35 16 43 50 29 42 37 14 35 (*Income poverty: Households (HH) with a monthly per capita income less than R604 in 2011) Poverty Drinking water system (blue drop rating) SAHRC. Public Inquiry: Access to health services- 2007 SA national average 2012: 87.6 SAHR 2012/2013 Poverty has long been recognised as a major cause of ill-health and as a barrier to accessing health care services, and the issue of poverty was raised repeatedly during the public hearings as an impediment to accessing health care services in South Africa. The most deprived districts in SA are rural. Affordability of health care: 16.6% or 5.2 million people experienced difficulties in accessing health care (Shisana et al, 2007) 82.1 73.6 98.1 92.1 79.4 60.9 68.2 78.7 94.2 87.6 Mpumalanga has the lowest rating, followed by FS, NW and Limpopo HEALTH OVERALL LEGAL Access to health Emergency treatment HEALTH INDICATORS Every person has the right to access health services, including reproductive health care services No person may be refused emergency treatment Constitution, section 27 Constitution, section 27 5

MDG 4: Reduce child deaths by two-thirds, 2/3 Infant mortality rate (deaths under 1 year per 1000 lie births Under 5 mortality rate (deaths under 5 years per 1000 live births) 50 000 children die before their 5th birthday. 20 000 babies are stillborn, another 21 900 die before they reach 1 month of age 2011: Rate:29.8, rounded off 30 (Bamford) 2011: Rate: 42.2 rounded off 42 (Bamford) 40.5% of maternal deaths due to non pregnancy related infections 28% of maternal deaths from haemorrhage and hypertension Lancet, 2009 SAHR 2012/2013 pg 244, pg 51 SAHR 2012/2013 pg 246, pg 51 South Africa is one of 12 countries in which mortality rates for children have increased since the baseline for the Millennium Development Goals (MDGs) in 1990, most from preventable and treatable causes and with no measurable progress. South Africa will fall well short of achieving the MDGs 4 and MDGs HIV/AIDS and poor implementation of existing packages of care are the main reasons for the lack of progress towards the MDGs. Full coverage of key packages of interventions such as treatment and prevention of HIV infection and provision of comprehensive maternal and neonatal care would put South Africa on track to achieve MDG 4 and make substantial progress towards MDG 5. To achieve high coverage of priority care for mothers, neonates, and children is financially feasible, requiring a 2 4% increase in expenditure, but this money must be spent strategically. Strengthening of leadership, accountability mechanisms, and high quality of care interventions are also required. Between a quarter and half of maternal, neonatal, and child deaths in national audits have an avoidable health-system factor contributing to the death. Eastern Cape, KwaZulu-Natal and the Free State have by far the majority of deaths. Gauteng, the Northern and Western Cape contribute the least. MDG goal: 18 per 1000 live births MDG goal: 20 per 1000 live births Maternal mortality ratio 333 per 100 000 live births SAHR Bamford pg 51 MDG: Reduce the ratio by three quarters Maternal deaths This is institutional MMR Saving mothers 2008- Institutional maternal mortality ratio has increased overall for 2008-2001 compared with 2005-2007. 2010: report published in 2012 Non pregnancy related infections (NPRI): mainly deaths in HIV infected pregnant women complicated by TB and pneumonia NPRI and haemorrhage and hypertension accounted for nearly 70% of all maternal deaths Maternal deaths due to haemorrhage and hypertension were thought to be possibly preventable (81% of cases) and probably preventable (61% of cases) Maternal health Deliveries occurring in facilities: SA average 89.7% SAHR 2012 pg 60 Preventing maternal deaths due to NPRI, obstetric haemorrhage and hypertension should have the highset priority 81.8 79.1 97.3 83.3 113.1 89.3 83.9 89.4 84.8 89.7 FS has the lowest percentage of facility deliveries, followed by EC, KZN and NC The rates are relatively high HIV prevalence rates MDG 6, target 7, indicator 18: Halt and reverse the spread of HIV HIV population prevalence Emergency medical and rescue services: 5.6 million in SA National prevalence: 17.3% New infections 1.43% Schoon, 2013 ANC surveillance report 2012pg iii Frees State issued dedicated maternity care ambulances. Maternal mortality rates decreased form 279 to 152 per 100 000 love births (2011-2012). Dispatch times decreased. Slightly different figures reported in the ANC surveillance report (2012), and the New Strategic Plan (NSP) (2012) The estimated national prevalence rate has remained stable at 17.3 % since 2005 (cf New Strategic Plan 17.8%) This is 5.6 million people (New Strategic Plan 2012: 5.3 million aged 15 years and older, 334000 children) Estimated new infections in 2011 was 1.43% (cf 1.63% in 2008) HIV antenatal prevalence (AP) women aged 15-49 (2011) 5.3 million adults aged 15 years and NSP 2012 pg 22 older 334 000 children 29.5% ANC surveillance report 2012 pg 15 ANC surveillance report 2012 reports on figures for 2011 6

HIV positive women 15-24 years 2011 % of children aged 0-14 years infected with HIV in 2008 HIV treatment 20.5% ANC surveillance 2012 pg 18 3.8% Children s Gauge 2012 pg 92 Patients receiving ART 2012 adults men: 550 492 2012 adults women: 1 060 579 2012 children: 124 619 Provinces with highest number of people on treatment: KZN, Gauteng, EC SAHR 2012 pg 233 29.3 32.5 28.7 37.4 22.1 36.7 17.0 30.2 18.2 29.5 Suggested proxy measure of incidence according to the report This is from a paediatric model This is a massive public health programme Number of people on ART Women 107 448 68 568 238 663 331 223 96 403 61 035 13 152 77 020 67 071 1 060 579 Men 63 105 31 384 129 768 160 904 39 776 34 440 6 576 43 431 41 108 550 492 Children 10 824 9 732 22 785 43 783 11 547 5 435 3 758 9 847 6 908 124 619 Rural provinces showing high numbers of patients on treatment KZN has the most, followed by Gauteng, then EC Total SA: calculated from the above: 1 735 690 (2012) WHO report 2013 pg 16 For South Africa: 2011 2012 Reported number of people receiving ART 1 702 060 2 150 880 Estimated ART coverage 71% 83% PMTCT MTCT of children <2 months of age Proportion of ANC clients testing for HIV Eligible ANC clients who were initiated on HAART (%) 2.7 SAHR 2012/2013 pg 233 Data from PMTCT survey in 2011(see reference for full report) SA national average is 98 ie nearly all mothers are tested for HIV during pregnancy SAHR 2012/2013 pg 234 SA national average is 78.7% SAHR 201/20132 pg 60 3.8 3.8 2.1 2.1 3.1 3.3 6.1 2.6 2.0 2.7 Rates are higher than the national average in NC, EC, FS Mpumalanga, Limpopo 94.3 97.4 85.1 114.2 101.6 110.9 74.7 106.2 91.3 98.0 This activity is well established, particularly in the rural provinces 71.7 62.6 77.9 90.0 75.4 65.7 71.7 52.3 99.5 78.7 Not all women who should be on treatment are receiving treatment: with particularly low rates in NW (rural), FS (less rural), and Mpumalanga (rural) Early infant diagnosis coverage (2011) SA 63.3 SAHR 2012/2013 pg 232 Reported from DHB 55.5 69.9 68.9 64.6 50.0 56.1 67.7 70.0 79.1 63.3 This is the coverage for HIV exposed babies having the PCR HIV test 7

TB TB Cure rate TB cure rate SA: 73.1% (2010 TB register) (% of new Smear + cases) Provinces with worst cure rates: NW, EC, NC SAHR 2012/ 2013 pg 229 Cure rate for provinces: Percentage 67.1 73.0 78.2 71.3 74.7 72.6 70.9 66.6 81.7 73.1 Provinces with worst cure rates: NW, EC, NC Defaulter rate: SA: 6.8% (2010 TB register) Provinces with worst defaulter rates: NW, EC, MP Defaulter/ interruption rates (new Sm+ cases) for provinces: Percentage 7.8 4.8 5.5 7.2 6.0 7.5 6.4 8.8 6.8 6.8 Provinces with worst defaulter rates: NW, EC, MP, KZN Non-communicable diseases Rising burden of noncommunicable disease in rural communities Lancet, 2009 Non communicable diseases Rising burden of NCDs Presentation by Deputy Minister of Health: G Ramakgopa Recent (date?) Bradshaw 2011presentation(MRC) Increasing number of deaths from diabetes, chronic kidney disease, cancer of the prostate and cervix. Increasing proportion of disability-adjusted life years attributed to neuropsychiatric disorders Mortality in South Africa: Infections, maternal, perinatal and national: 51% Injuries 9% NCDs: Cardiovascular 18%, Cancer 7%, Respiratory 4%, diabetes 2%, other NCDs 9% National Burden of disease study 2000 HIV: 31%, Respiratory infections: 3%, Infectious and parasitic excluding HIV/AIDS: 9%, Perinatal, maternal and nutritional: 10%, Other non communicable diseases: 10%, Neoplasms: 3%, Respiratory disease: 5%, Cardiovascular and diabetes: 7%, neuropsychiatric: 8%, Unintentional injuries: 7%, Intentional injuries: 7% Cardiovascular disease attributable to 8 risk factors: Tobacco smoking, alcohol use, low fruit and veg intake, physical inactivity, excess body weight, high cholesteroal, high blood pressure, diabetes mellitus Househam, 2010 Poverty is the most obvious and significant determinant of poor health outcomes, which includes many NCDs(SAHR 2012/2013 pg 118) UCT has set up the sub- Saharan Africa Centre for Chronic Disease. WHO estimated that the burden of NCDs is 2-3 times higher than in developed countries. The burden of NCDs is rising in rural communities, and affects a disproportionate number of poor people in urban communities. Consequences are far reaching: eg an estimated increase in annual national disability grants to R4.2 billon by 2040, as a result of increases in cardiovascular diseases. Diseases according to socio economic groups 3 tracer conditions: Obstetric care, TB and HIV See results from paper by Cleary et al 2013 under section on affordability McIntyre & Ataguba 2012 Considerably higher levels of illness amongst lower that higher socio economic groups: In the SA context, the burden of some chronic conditions (eg diabetes ) is evenly distributed across socio economic groups, while other (high blood pressure/ hypertension, depression, STD, HIV, diarrhea and TB) are impacting more on low than high income groups (Fig 1, pg 3)(data from General Household survey) Mental health Lifetime prevalence of mental illness among adults : 30.3% South African Stress and Health Survey (2008), quoted in SAHR 2012/2013 pg 104 (Corrigall & Matzopoulos, 2013) 8

Rural mental health Rural mental health is neglected and invisible Disability SA : percentage of persons aged 5 years and older with disability: 5.2% Kanda, M (2013?) General Household Survey 2012 StatsSA (reported in SAHR 2012/2013 pg 222) Rural communities have high rates of mental health disorders: Rural communities are prone to social and economic disadvantages which are risk factors for depression. Also high rates of morbidity and mortality in poor rural communities also could be risk factors for mental disorders such as depression and anxiety. Rural mental health is a handicap to rural development, as it places a socio economic burden on communities. 3 factors which may explain the invisibility and neglect of mental health: - Difficulty in defining mental disorders (unlike physical conditions) - Complex etiological factors and therapeutic interventions - Epidemiological focus on mortality and morbidity which does not include the burden of disease Mental health care is currently mainly hospital based (hospicentric) with the focus on sever mental illnesses (eg schizophrenia and bipolar mood disorder), heavy reliance on psychopharmacology. Few psychosocial interventions. To achieve quality mental health care for rural communities, need: - Prominence for rural mental health meeds in all health and community development agendas - Rural mental health care needs to be holistic and comprehensive (individual and community prevention, psychopharmacological and psychosocial interventions - Must be socio culturally adequate, need community participation Percentage of persons aged 5 years and older with disability 2012 (using a new measurement so not comparable with previous years) (prevalence) 6.1 6.7 3.3 4.6 6.1 5.5 10.2 7.7 4.4 5.2 General facts HIV related disability Sherry, 2013 (Rural disability fact sheet compiled from various sources) Mlambo et al 2011, quoted in Sherry 2013 Links to poverty: Households with a disabled person are more likely to be poor. Disabled people experience higher health care costs, and where transport is an issue, this will be more pronounced. Where rural areas lack access to services, the vicious cycle of disability and poverty will be more significant. Disability on the whole is higher in rural areas (WHO 2011). AS more people live with HIV as a result of ART, higher disability levels must be expected. Disability may be permanent or episodic, and may include physical, developmental and mental health issues. Small study in Zimbabwe: 59 adults on ART: 61% had reduced their usual activities due to the illness, 36% had stopped certain activities completely. Statistics about children Bateman 2012 Sherry, 2013 (Rural disability fact sheet compiled from various sources) Also RURESA presentaion RURESA presentation 2013 Children: Intellectual disability is commonest disability affecting rural African children: 41 per 1 000 children aged 2-9 Autism: 10 per 1000 (RURESA presentation: 2 per 1000) Foetal alcohol syndrome: 25 000 born annually Hearing loss: 17 babies born every day in SA will develop this (RURESA presentation: 6 per 1000 congenital hearing loss) Census 2001: Prevalence in children 0-18 yrs: 2.5% General household survey: prevalence of children with disability (Washington Group short set of questions): Overall 0-9 years: 11.2% Age specific 0-4years: 28%, 5-9 years, 10% Chagan & Kauchali (2011): 10 question screen: Valley of a thousand hills (KZN rural) Prevalence of children with developmental disability: 2-9 years: 7% (RURESA presentation:53per 1000 children 0-14: moderate to severe disability, 7 per 1000 severe disability) UNICEF: 5.1% of children 0-14 years living with moderate/ severe disability, 0.7% living with severe disability Many children with disabilities lack basic health care, mortality may be four times higher than children not living with disabilities Disability- poverty relationship: Exacerbated by poor maternal and child care. Malnutrition is responsible for the large burden of developmental impairment. Cerebral palsy: 2 rural SA studies: report 10 per 1000 live births and 80 per 1000 live births. CP is estimated to be the single biggest cause of childhood disability worldwide. Poor access to maternal and child care exacerbate CP rates (causes mostly related to obstetric care). (RURESA presentation: Corneal scarring resulting in visual impairment: due to lack of Vit A) ARV naïve children 0-2 years: 77.6% motor delay, 63.5% cognitive delay, 49.2% language delay 9

Risk factors for childhood disability in SA McLaren, 2011 Risk factors include: poverty, maternal factors, malnutrition, micronutrient deficiency, poor delivery of basic services, violence, child injury, child abuse Rehabilitation Rehabilitation in rural areas Bateman 2012 Rehabilitation services are scarce in rural areas. One size fits all policies starve the departments of staff, budgets and vehicles, thereby shortening patients lives and reducing their chances of lasting quality of life. Problems: bed occupancy duration, mismatched placement of professionals and community service therapists, and technical support staff, and insufficient dedicated transport (transport allocated first to doctors and admin staff). Dearth of schools for children with special needs in rural areas, children remain unassessed unassisted, and unplaced. Some challenges faced by rural therapists: constant staff turnover, insufficiently skilled or motivated HR departments, little support for staff retention, unclear operational mandates of DoH and DoE that prevent children with disabilities accessing their right to rehabilitation, no clarity regarding which department responsible for provision of assistive devices for school age children especially those already at special schools, significant educational, geographical and socio economic barriers leading to delays in accessing care, poor return to function and sub- optimal rehabilitation outcomes, insufficient budget (eg no ring fencing for appropriate assistive devices). Access to rehabilitation Access to assistive devices RURESA presentation 2013 RURESA presentation 2013 Access to and knowledge of rehabilitative services is poor Only 33% of disabled children are known to the health/ rehabilitation services (at Manguzi after 20 years of continuous rehab services) Only 39% of carers knew about the rehab services (at Manguzi after 20 years of continuous rehab services) Manguzi: only 34% of children had received rehab, Gauteng: 25-40% receiving rehab, Mpumalanga: 42% receiving rehab. 67% of children requiring assistive devices who are not able to access them Teenage pregnancy SA: 4.9% of females aged 13-19 were pregnant during the year preceding the survey. HUMAN RESOURCES General National vacancy rate for 2008 Vacancy rates 34.9% medical practitioner positions vacant in the public sector, 40.3% of professional nurse positions were vacant in 2008. Provincial vacancy rates in the public sector: General Household Survey 2012 StatsSA, Day C and Gray A, 2008. Health and Related Indicators. in Barron P and Roma-Reardon J (eds), South African Health Review, 2008. Durban: Health Systems Trust; 2008 Econex 2010 Doctors, pg 4 HR needs 2006: 225,000. +/64000-80000 needed over next 5 yrs SAHRC 2007 Health Sector Roadmap HR needs Econex 2010 Doctors, pg 4 Different age categories: Percentage of females aged 13-19 who were pregnant during the year preceding the survey: 2012 13y 14y 15y 16y 17y 18y 19y 13-19years 0.3 0.4 1.9 4.5 6.8 9.9 10.2 4.9 Professional nurses, senior doctors account for most of the shortages in expertise Vacancy rates in some hospitals more than 40% Shortage of pharmacists up to 50% in some provinces Some clinics no access to doctors at all Psychiatric personnel shortages especially in rural areas Employers stated reasons for vacancy nurses (HSRC): not a well-paying job, low recognition, low promotion potential, long unsociable hrs of work, risk of HIV infection, migration. NHI proposal states reasons vacancy nurses: cuts in provincial budgets, closing down of nursing colleges, migration out of SA Ageing population of nurses, with a large percentage of nurses expected to retire in the next 5 20 years (Lehmann U, 2008). Forty percent (40%) of registered nurses may retire in the next 5 to 10 years or 70 000 (almost 1/3rd) of all categories of nurses may retire in the next 5 10 years. Since 1994, there has been a dramatic decrease in the ratio of nurses to population in South Africa. In 1994, there was an average of 251 nurses / 100 000, and in 2007 the ratio had decreased to 110.4 / 100 000 (Lehmann U, 2008). In: National Health Insurance: Human Resources Requirements, Professor David Sanders and Bridget Lloyd (2009). No figures, only a graph Limpopo has the highest vacancy rates for all health care professionals, followed by EC, FS and NC Specialists: vacancy rates highest in: Limpopo, KZN, EC GPs: vacancy rates highest in Limpopo, NC, FS and Mpumalanga Staff has increased but not proportionally to the increased burden of disease and not clear where the increases are placed? 9,7 billion to 12 bn needed. There is a decline in the absolute number of doctors in SA. If resources for health improve, there will be an increase in demand, and SA does not have enough doctors to deal with current demand, (see vacancy rates) let alone increased demand. Assumptions: Training: assumption: max training capacity for GPS is 1400 graduates per year Potential net addition of 1400 doctors added each year (GPs 790) and specialists (610) Assumption age: 41.7% of all specialists working in SA are older than 50, 33.5% of all GPs are older than 50 10

Retirement: 398 GPs and 268 specialists retire each year Exiting: 1.4% of specialists exit due to illness and death, 1.4% of GPs exit each year due to illness and death, 1% of all doctors exit due to reasons other than retirement or illness and death Emigration: 25% of those GPs and specialists added to the stock each year will emigrate. Conclusion: large increases in the stock of doctors will be required: there will be a supply constraint Salaries Uncompetitive with private sector Little career planning, poor working conditions Distribution of benefits of using health services McIntyre and Ataguba 2012 The distribution of benefits from using the health services is not in line with the distribution of ill health (see above: The poor bear by far the greatest burden of most major causes of ill health). We would expect to see a pro- poor distribution of use and benefits from health services across all levels of public health services. However, the magnitude of funding for private sector services relative to the size of the population able to use these services impacts on the public sector: eg influences the distribution of health professionals between the two sectors) Career plans of final year medical students in SA Rural origin health science students De Vries et al 2010 There is evidence that students of rural origin, and those who intend to practice rural medicine, are more likely to practise in rural settings after graduation. This study: Final year medical students of rural or small town origin were less likely to want to work abroad, more likely to want to work in rural areas, and less likely to want to spend most of their career in private sector. Most common influences on work location mentioned included: crime and safety issues, opportunities for children and partner/ spouse, opportunities for own continuing education, access to social and family networks, and a sense of professional independence. Tumbo et al, 2009 Study on undergraduate students admitted from 1999-2002 to 9 health science faculties. 59% were from cities, 15% from towns, 26% from rural areas. Proportions of rural origin students were: Medicine: 27.4%, Physiotherapy: 22.4%, Occupational therapy: 26.7%, and dentistry: 24.8%. Thus the proportion of rural origin students was considerably lower than the national rural population ratio. Clinical associates (CAs) New mid level health worker Doherty et al, 2013 Purpose of CAs : to strengthen health care at district hospitals (revitalising primary health care). CAs must work under the supervision of doctors; skills are generalist rather than specialist. Bachelor s degree course currently at 3 of SA s 8 medical schools. Challenges: CAs must be produced in greater numbers, and the required funding, training capacity, public sector posts and supervision must be available. Retaining them will depend on the public system becoming an employer of choice. INEQUITIES : Public/ private, urban/ rural care, hospital/ community care The three big inequities SEE below The big three inequities in terms of health care delivery are private-public care, urban-rural care and hospital-community care. Distribution private/public 60% of the nurses and 40% of the doctors serve the 85% of the population using the public health sector NHI proposal See below % of GPs working in public sector Doctors private sector vs public sector Distribution of GPs and specialists Private sector: 3.34 doctors per 1000 pax / one doctor for 299 people. State sector: 0,34 doctors per 1000 people/ one doctor for 2941 people. Almost equal distribution of GPs: 2.861 people per GP in public sector 2.723 people per GP in private sector 9.581 people per public specialist 1.767 people per private specialist Couper and Hugo (2009) NHI proposal Econex Note 7: GP and specialist numbers 2010 pg 5 See below These figures do not use HPCSA data: HPCSA does not distinguish between doctors working in SA and those not practising here, or not practising as doctors. The researchers used PERSAL for GPS and specialists in public sector, and medical scheme industry estimates for private sector The public private split looks substantially different from Wadee and Kahns estimates GPs: The majority, 61.9%, of GPs work in the public sector, 38.1 in private Specialists: 56.2% of specialists work in private sector, 43.8% work in public sector Total number of doctors: 15 246 in Econex Note 7: GP and specialist numbers 2010 pg 4 11

Population per GP and per specialist: (2010 Econex) Estimates of total number of nurses actively working in SA public and 12 186 in private Total 27 432 Estimates: 2010 Doctors per 100 000 population: 55.3 GPs: 35.9 Specialists: 19.4 Nurses trained in 2009: 15 910 Average attrition rate for last 5 years us 42.9% (ie trained bu t not registered) Total actively working in SA: 2010: 189 718 Total RNs actively working in SA 2010: 92 563 Econex note 8: Human resource supply constraint: the case of doctors: 2010 pg 8 Econex note 9: human resource constraint: the case of nurses 2010, pg 1-5 Update for HRH figures Data source SA Nursing Council registry: problems: includes all nurses registered in SA not only those actively working in the country Nurses working abroad and in other occupations also registered. Public private: 58.6% are working in public, 41.4% are working in private Nurses in private work in pharmacies, clinics, mining hospital and NPOs There has been a decline in RNs as a % of total nurses registered from 42.1% (2000)to 16.6% (2009) The mix of Types of nurse (RNs ENs ENAs) has changed: fewer RNs. This is important in the light of eg task shifting. Age of nurses: 43.7% of RNs are over 50 years, 24.5% of ENs and 25.3% of ENAs There is a great need of more and better qualified nurses in the public sector Urban-rural care Hospital-community care 7.3% of all nurses registered with SANC in 2004 working in 7 OECD countries (an underestimate) Typical urban province:30 generalists and 30 specialists for each 100 000 pax not covered by medical aid. Rural province; average of 13 generalists and 2 specialists available per 100 000 people Private sector, of every R100 that is spent on health care, R36 is spent on hospitals, R27.70 on specialists and only R7.70 is spent in general practice. Public sector: 95% of doctor time is spent in hospital; for every 50 000 people dependent on the public service :16 doctors in the hospital and 1 doctor in the community Couper and Hugo (2009) See rural section above A study done to look at the HR requirements for PHC in South Africa (Daviaud and Chopra, 2008), focussing on six of the poorest districts, found that only 7% of the required doctors were present at clinics and community health centres. INEQUITIES : Affordability, accessibility 12

Affordability People who did not consult a health worker as it was too expensive: 32.9% in 2002 declined to 12.3% in 2008 Econex note 1 2010. Role of PHC in health reform Conclusion: the Governments pubic policy agenda focussing on PHC was successful in rendering basic services more affordable to especially lower income groups Affordability of health care Accessibility (to health care and facilities) Access to medicines Access to hospital beds Health service utilization 16.6% or 5.2 million ppl experienced difficulties in accessing health care People that consulted a health workers across income groups (quintiles): 74.9% in quintile 1 to 83.1% in quintile 5 Shortages of drugs at public facilities, unaffordable medicines in public sector, lack/shortage of pharmacies in rural areas (vs oversupply of pharmacies at proximity of one another in urban areas) More than twice as many hospital beds per private vs public beneficiary. Number of beds in private sector has increased (bed occupancy 65%, 10,000 oversupply) vs decrease in public sector Study of inequities in access to health care: Household survey in SA in 2008 (Shisana et al, 2007) Econex note 1 2010. Role of PHC in health reform (data from general household survey) NHI proposal CMS Annual Report 06/07 Harris et al 2011 pg/ s106 The likelihood of consulting a health workers when ill is relatively high and reasonably constant across income groups There is also a decrease in travel times. However, 15% of the poorest quintile still live more than 1 hour away from nearest clinic and 20% live more than 1 hour away from nearest hospital. Rural Informal - urban Formal -urban Outpatient visits per person / year Clinic / CHC 2.8 2.2 1.6 Public 1.0 0.9 0.8 hospital Private 0.7 0.9 1.7 Total 4.6 4.0 4.1 outpatient Inpatient admissions per 1000 people / year Public 58.3 100.1 93.9 Private 4.0 3.5 33.6 Other results: The poorest quintiles mainly visited PHC facilities, while the richest were thrice as likely to use tertiary hospitals (pg /s111) For rural dwellers and those living in informal urban areas, total utilization of in patient private facilities was a tenth of urban formal residents Also large differentials in private admissions between those in poorer more rural provinces of Limpopo (2.3 admissions)mpumalanga (6.7 admissions) and EC (6.9 admissions) versus urban better resources provinces of Gauteng (32.5admissions) and WC (32.8 admissions) Availability: (Distances and travel mode to facilities): the majority used public transport (45.2%) or walked to outpatients (37.0%) although two thirds of the richest used private means Average travel time was 30.7%, for the poorest 38.2mins, richest 20.2 mins, rural 38.2%(pg/ s112) Delayed care seeking: reason given as unaffordable transport costs: 21.1% of the poorest, and 1.1% of the richest said this. Transport costs were problem for 42.5% in EC and 19.5% in Limpopo Financially catastrophic transport costs occurred in 15.3% of rural, 14.7% of unemployed and 12.0% of uninsured. Financial catastrophe was experienced by 43.0% of uninsured, vs 4.0% of insured using private outpatients 13

Affordability of key health services: 3 tracer conditions: Obstetric care, TB treatment and ART Health care provision and quality Type of health care facility consulted first Cleary et al 2013 General household survey 2012 StatsSA Delayed care seeking also due to acceptability factors: 8.5% said long queues, 6.1% said perceived ineffective care, and 2.9% said disrespectful treatment. Inverse care law: availability of good medical care varied inversely with population health needs. Many poor or disadvantaged social groups are denied equal access to good quality services despite their greater need. A perception that illness was not serious enough to warrant medical attention was the commonest reason for delayed treatment (especially amongst rich and insured) pg/s 117 Amongst the poor and uninsured, unaffordable transport, anticipation of disrespectful providers and a belief that care would be ineffective were more prominent barriers (pg/ S117) Costs of accessing services can be crippling for poor households: the poor bear disproportionate cost burdens A considerable portion of groups exempted from user fees still pay for services (pg/ S118) Overall findings: poor uninsured black Africans and rural groups have inequitable access (pg /S119) Research at 2 urban (in Gauteng and WC) and 2 rural sites (in Mpumalanga and KZN) Affordability: the degree of fit between the costs of seeking health care and a HH s ability to pay Factors associated with indicators of affordability: Differences in affordability between rural and urban: In rural areas: - Costs were higher (particularly transport costs) - Ability to pay was lower - Greater proportion of HHs selling assets or borrowing money Eg: 40% of TB and ART service users in a rural site (Hlabisa) had to borrow or sell assets to cope with health care costs Also: costs for transport for TB patients higher in Mitchell s Plan (urban WC): because of the daily trips for DOT (policy needs revision) Differences among tracers: -higher percentage of HH receiving TB/ HIV treatment borrowing or selling assets than obstetric care TB and HIV require expenses to be incurred on an ongoing basis: therefore how will coping strategies be sustainable? Conclusion: affordability needs to be considered in relation to dynamic costs of treating different conditions, and timing of treatment in relation to diagnosis. The frequently high transport costs associated with treatments involving multiple consultations can be addressed by initiatives that provide close to client services and subsidised patient transport for referrals This study: costs of transport to a health facility higher for obstetric care than TB and ART services: far fewer facilities provide CEOC They found that the free care policy is not being fully implemented in some areas (Obstetric services at one of the rural sites) 69.6% said they would first go to public clinics and hospitals 29.0% said they would first consult a private doctor/ clinic/ hospital Traditional healers: 0.2% Type of health care facility consulted first by HH when members fall ill or get injured (%) Public Pubic clinic Private Private Private Traditional Pharmacy hospital hospital clinic doctor healer 10.0 59.6 2.7 2.4 23.9 0.2 0.5 91.1% of all households: use the nearest facility of its kind Reasons for not using nearest facility of its kind: Prefer private health institutions (41.5%) Waiting period too long: 16.7% Drugs needed not available: 7.8% Staff rude/ uncaring/ turned patient away: 4.8% Level of satisfaction with public health care facilities 2012 (Percentage) Public facility, 64.6 61.4 52.3 51.6 67.5 59.2 61.7 50.7 57.8 57.3 very satisfied Public facility, very dissatisfied 3.9 9.2 8.9 5.0 6.1 7.3 7.4 15.6 10.3 7.7 Percentage of individuals who are members of medical aid schemes: 2012 10.9 18.1 29.0 12.3 8.0 14.5 18.9 14.1 25.2 17.9 14

All the rural provinces are below the national average. Finance/ FUNDING Total public sector spending R116 billion (2011/2012) DHB 2011/2012 pg 1 Total public sector spending increased form R110 billion in 2010/2011 to R116 billion in 2011/2012. 96.2% of this spent through provincial health departments (Increase from R98 billion in 2010/2011 to R111.6 billion in 2011/2012) Expenditure on District Health Services Expenditure on non hospital PHC Provincial PHC expenditure per capita (uninsured) 2012/2013 42.6%of provincial health DHB 2011/2012 pg 1 expenditure 55.2% of total district spending DHB 2011/2012 pg 1 780 spent for SA DHB 2012/2013 pg 220 & 228-238 Provincial PHC expenditure per capita uninsured: 764 740 928 740 656 643 860 802.0 825 780 Limpopo and Mpumalanga have the lowest average PHC per capita expenditure. EC, KZN also below the national average Provincial Health expenditure Total for SA: Rand million: 111 642 SAHR 2012pg 273 Provincial health expenditure (Rand million) 14951 6826 23656 24791 11372 7225 3020 6380 13419 111642 These are absolute not per capita amounts Trend in spending SAHR 2012 pg 273 Overall, public sector expenditure on health as increased strongly in real term, with an annual growth of 8.5% from 2007/2008 to 2011/2012 Finance: % of DHS spend on District hospitals: 37.5% Compiled from DHB 2012/2013 pg 228-237 % of DHS spend on District hospitals: 2012 40.2 35.4 20.7 41.9 49.4 46.6 28.0 26.9 37.6 37.5 % of DHS spend on District management: 5.8% % of DHS spend on District management:2011 7.2 3.5 6.1 2,1 7.2 8.7 9.3 9.5 4.8 5.8 % of DHS spend on PHC: 56.7% % of DHS spend on PHC: 2011 52.6 61.1 73.2 56.0 43.3 47.7 62.7 63.6 57.7 56.7 Provincial and LG expenditure on DHS per capita uninsured: 1 327 Provincial and LG expenditure on DHS per capita uninsured: 2012 1396 1207 1199 1301 1301 1411 1354 1247 1400 1327 Provincial expenditure per PHC Provincial Expenditure per PHC headcount 15

head count: 255 254.7 239.6 334.8 223.8 220.6 227.0 247.9 301.3 233.5 255 Equitable allocation of health care resources in SA Provincial PHC expenditure per capita: 780 D McIntyre 2012 Provincial PHC expenditure per capita: 2011 764 740 928 740 656 643 860 802.0 825 780 In 2009/10: most provinces were close to national average of per capita health care spending, due to: -Changed design of the formula for allocation by national treasury -Establishment of norms and standards for the delivery of health services that provinces are expected to strive towards (this allows provincial health departments to secure a fair share of provincial resources in their negotiations with provincial treasuries) -Conditional grants for specific health services (eg HIV /AIDS conditional grant) HOWEVER: substantial disparities in spending on PHC services among health districts: Provincial health dept must pay more attention to this Eg: Non hospital PHC spending per capita in districts ranges fromr324 in uthukela district (KZN) to R1095 in Namakwa (NC) Per capita health expenditure (2011) Unequal spending private/ public Private: / med schemes: 11 084 Public (provincial): 2 667 State: 33,2 billion health care for 38 million people. Private sector 43 billion for +/ 7 million people Richest 40% receive 60% of health care benefits Health system strengthening and PHC re- engineering, NHI Establishment of ward based PHC outreach teams (WBOTs) Establishment of District Clinical Specialist Teams (DCST) Expansion and strengthening of school health team Public health facility audit NHI SAHR 2012 pg 274 SAHRC (2007) Ataguba & McIntyre, 2009 in ANC NHI proposal 8.7% GDP spent in healthcare, of which the public portion is an equivalent of 3.2% of GDP (SAMA in SAHRC Public Inquiry: access to health care services) Health care benefits not distributed in line with health needs. Richest 20% have a health need share of less than 10%, but receive 36% of total benefits. Poorest 20% have a health need share of more than 25% but receive only 12.5% of benefits. PHC re- engineering SAHR 2012 pg 58 Each team to consist of team leader (professional / enrolled nurse)& 4 to 5CHWs they will be expected to provide services to approx 7500 households To provide routine and curative and other services where these are required. Eventually should cover all 4 227 wards 10 districts have introduced these teams PHC re- engineering SAHR 2012 pg 58 Presentation DCST to be made up of obstetrician, paediatrician, family physician, anaesthetist, advanced midwife, advanced paeds nurse, PHC nurse Teams to improve clinical governance in districts Therefore play a key role in provision of quality MNCWH &N plan at all levels in the district (DCSTs have been established in all pilot districts, but only 2 have full complement of specialists) PHC re- engineering SAHR 2012 pg 58 To contribute to improving health and learning outcomes for children and youth The Integrated School Health Programme will build on existing school health services An audit of 3880 facilities completed Facility improvement teams have covered approx 1000 facilities Inspection of facilities Inspection of NHI districts SAHR2012 pg 24 Rapid appraisal of pilot district 12 month progress: Only 77% of conditional grant spent: Lack of clear guidance on what it could be spent on: equipment, refurbishment, training All districts have nationally appointed full time NHI project managers (none have had training), Task teams established: but lack involvement of clinic committees and hospital boards. No community consultations QI: Assessments; Availability of medicines, Cleanliness, Patients safety and security, IPC, Attitudes, Waiting times Hospitals: 19 hospitals: Overall scores: 71.8% at baseline, 65.5% at follow up ( ie worse) PHC facilities: 122 facilities: 59.2% at baseline, 54.2% at follow up (ie worse) Declines 16