Tracking progress towards meeting the SDGs

In 2019, The Bertelsmann Stiftung and The Sustainable Development Solutions Network co-produced a 2019 SDG Index and Dashboards report [8]. This report gives annual overviews of countries’ performance against the 17 SDGs, basing its findings on publicly available data published by key international institutions (World Bank, WHO, ILO etc.) and organizations, including research centers and non-governmental organizations. In 2019, Denmark, Sweden and Finland topped the index charts with good performance towards achieving the SDGs, whereas the Democratic Republic of Congo, Chad and the Central African Republic ranked last among the 162 countries assessed. South Africa placed 113^th on the list.

A similar exercise was conducted for Africa specifically, by The Sustainable Development Goals Centre for Africa and Sustainable Development Solutions Network, where South Africa ranks 10^th out of 52 African countries assessed (top ranked in Africa in 2019 was Mauritius, a country deemed two thirds of the way towards achieving the SDGs) [9].

South Africa’s dashboard in 2019 reported the country’s average performance (yellow, orange, or red) on each of the SDGs (Table 2). In 2019, South Africa did not fully achieve any of the SDGs. This may be attributed to a lack of actual progress towards goal achievement or to inadequate sources of information or data to assess real progress.

In 2017, South Africa was able to report on 66% of the SDGs’ social targets (SDGs 1–5 and 11), 73% of the economic targets (SDGs 7–10 and 12), 57% of the environmental targets (SDGs 6 and 13–15), 73% of the peace and security targets (SDG 16) and 29% of the targets grouped under the 17th SDG which is associated with the means of overall implementation towards achieving the goals [10].

These statistics are useful to understand how well certain locations in South Africa are faring towards SDG achievement especially when compared to data nationally and from other countries. The country’s first full-scale SDG progress tracking report was compiled by Statistics South Africa in 2017 and outlined a National SDG Indicator Framework. The report illustrated progress towards selected 2030 targets as specified by the SDGs and their published indices [3, 11]. Most of the 232 SDG indicators have internationally established and agreed upon standards and methodologies for computation (Tier I and II SDG indicators), with only a few indicators for which the methodology or standards are still being developed or tested (Tier III SDG indicators) [12]. In its 2019 Country Report, South Africa was able to report on 128 of the 232 indicators. Tracking progress towards SDG goals, targets and indicators is complex as the technical process of developing methodologies to measure some of the proposed indicators, especially the non-quantitative indices, is a constant work in progress [11, 13].

The benefit of tracking goals locally

Success towards meeting goals and targets is typically measured at a national scale to enable a comparison towards global progress. However, tracking smaller scale, local progress assists in better identifying and understanding gaps that need to be addressed to meet the targets within a country’s own borders. When considered at a global scale, African countries frequently appear as “red” (meaning major challenges exist) in the global SDG tracking dashboards, even though work is being done in those countries to progress. A higher resolution assessment at local scale, instead of a national scale, could help highlight progress made towards SDG target achievement which would ordinarily be masked by an amalgamated national index. Showcasing local government efforts could help illustrate whether countries are on the appropriate track towards meeting the SDGs and provide a basis for shared experiences and best practices [9].

The aim of this study was to assess progress towards achievement of the SDGs in four low-income, rural villages in South Africa. Findings are compared with national indicators where possible. Results of this exercise help to identify data gaps, areas for potential research and development, as well as to stimulate discussion about the types of data needed for SDG target and index computation for South Africa. This work provides a model for how local-scale assessments can be approached and how the results can then be contextualized within national progress.

Study site and data collection

A cross-sectional survey was used to collect data from 400 dwellings in the greater Giyani local municipality located in Limpopo Province, South Africa in September 2016 (Figure 1). The municipality has a population size of 247,657 inhabitants, living in 57,537 households, the majority of which are clustered in hamlets or villages. Dwellings for the study were randomly selected from four villages. A cluster sampling method was used to select 100 households in each village. Ethics clearance for the study was granted by the South African Medical Research Council Research Ethics Committee (Certificate clearance no. EC005-3/2014, 9 May 2017) and permission was sought from the provincial, local and traditional leadership of the study areas.

Questionnaire and data analysis

Following written informed consent, a structured questionnaire was administered by a trained field worker to a respondent from each of the 400 households participating in the study. A household member of at least 18 years of age provided socio-economic and demographic information for their household (defined as the people who eat a meal together). Questionnaire data were double-data-entered into Microsoft Excel and analyzed for descriptive frequencies using STATA version 14.

Comparison of Giyani results with SDG targets and indices

Responses to questions in the Giyani study questionnaire which aligned with SDG indicators were used to calculate a Giyani-specific index which was then compared to the corresponding index listed in the South African Country Report [12]. Existing reports focusing on South Africa’s progress towards the SDGs targets and indices were used to contextualize the results from the Giyani study [8, 11, 12]. Where responses matched SDG indices, a direct comparison was possible. This was mostly the case for relative indices, e.g. percentage of population living below the international poverty line. Indicative comparisons were made for absolute indices, e.g. total number of social grants received. An overview of the model used is illustrated in Figure 2.

Direct comparison of Giyani and South African SDG indicator scores (Using South African reports as a baseline)

The income of nearly one third of Giyani’s population ranks below the international and the national poverty lines (Table 4). The proportion of the Giyani population (17.7%) with an income below the international poverty line exceeds the national proportion which is 7.4%. Compared to South Africa as a whole (25.2%), a smaller proportion of people lives with an income below the national poverty line (17.7%). The unemployment rate in Giyani (49.0%) was higher than the figure reported for South Africa (27.3%) [13]. Given the definition of access to clean and affordable drinking water and sanitation, as outlined by the SDG South Africa Baseline Report (percentage of population using an improved basic drinking water source, i.e. piped water into dwelling, yard or plot; public taps or standpipes; boreholes; protected dug wells; protected springs and rainwater and the total number of population using improved sanitation: flush or pour flush toilets to sewer systems, septic tanks or pit latrines, ventilated improved pit latrines, pit latrines with a slab, and composting toilets), data suggested that Giyani villages fared well in these water-focused indices as almost 100% of the surveyed households reported to have some form of water access or sanitation [11, 13]. Generally, it seemed that more people living in Giyani live in formal dwellings, when compared to the rest of the country. Fewer people (4.2%) were reported to have access to the Internet in Giyani compared to the rest of the country (61.8%).

Contextualization of further Giyani results with the SDGs using unofficial methods

Two supplementary tables illustrate progress towards the SDGs in Giyani villages in relation to the rest of the country. Table S1 lists those indices for which data from the Giyani survey were available for comparison with SDG target indices. Results from the Giyani villages were also compared to South Africa’s outcomes, where the colors red, orange or green were allocated to each score (Table S1). The colors translate to “Giyani is doing worse than the rest of South Africa in this index”, “Giyani is on par with the rest of South Africa in this index” and “Giyani scores better than South Africa in this index”, respectively.

Table S2 highlights instances in which the Giyani survey results did not provide enough information to officially calculate a given index, or where there is no existing South African score available to make a comparison, but where results are nevertheless of contextual value in relation to the SDGs. Table S2 is useful as a broad indication of how Giyani is faring compared to the rest of the country in relation to a particular index. For instance, the assessment illustrated that more than two thirds of households sampled received income through a state grant (69.5% of households received at least one child grant, 43.4% received at least one old age grant, 4.2% received a disability grant and 2.7% benefited from other grants).

Giyani is grappling with many of the same socio-economic issues which persist in other parts of South Africa. Poverty affects almost a third of households. Access to drinking water and sanitation, though “present”, is not always reliable or safe, and requires urgent attention [14]. Unemployment is high with almost half of households listing at least one household member as unemployed, and internet access, an essential amenity for meaningful participation in today’s economy, is not nearly at a desired level.

Study limitations

Here we underline the challenges associated with holistic, local and national assessments of SDG progress, including masking of extreme under-development in a society as unequal as South Africa. Data collected in Giyani yielded insights on various socio-economic issues covered by the SDGs. The original study survey was not designed for the primary purpose of an SDG progress assessment, and so the data were mostly not useful according to the globally accepted official calculation methodologies. This is frequently a pitfall in project-specific surveys: they are often not created with other assessments in mind. As data gaps represent one of the main reasons why progress towards the SDGs in RSA cannot be adequately computed and expressed, it is advisable that researchers be mindful of the opportunity for data compatibility between the SDG framework and survey data, for example in respect of socio-economic and human health. If this is done, survey data can contribute to the understanding of local, as well as national, progress towards SDG achievement. This is particularly important in countries where the lack resources focused on socio-economic surveys may also represent a limiting factor into why large data gaps exist.