This study found wide variation in the proportion who reported receiving social protection benefits by population group. The proportion who reported receiving social protection benefits was lower than the 2017–2019 global average of 45%  in all population groups, except for OVC and AGYW in Eswatini. Commitment 6 may have been too ambitious. AGYW, SW, MSM and PLHIV reported receiving social protection benefits similar to other individuals in Malawi and Zambia. In Tanzania, more WLHIV and FSW reported receiving social protection benefits than women not living with HIV and women who were not sex workers. Fewer AGYW reported receiving social protection benefits than women 25 years or older. In Eswatini, more AGYW reported receiving social protection benefits than women 25 years or older. However, fewer MLHIV reported receiving social protection benefits than men not living with HIV.
The finding that the proportion of the general population reporting receiving any social protection benefit was lower than the global average and varied widely, from 7.7% (95% CI 6.7–8.8) in Zambia to 39.6% (95% CI 36.8–42.5) in Eswatini, is consistent with existing evidence. The International Labour Organization (ILO) estimated that only 45% of the global population accessed at least one social protection benefit as of 2019, whereas only 17.8% of Africans were estimated to be covered by social protection. About one fifth (21.3%) of the total population in Malawi, 15.3% in Zambia, and 86% and 3.2% of older people (persons above statutory retirement age) in Eswatini and Tanzania, respectively, accessed social protection services based on ILO data . In our study, only Eswatini exceeded the Africa regional average social protection coverage of 17.8%. Malawi met the Africa regional average social protection coverage among male PLHIV, and OVC. Tanzania and Zambia did not. Except for AGYW and OVC in Eswatini, the proportion that reported receiving social protection benefits for all countries examined was below the global social protection coverage of 45%.
Based on these findings, Commitment 6 may have been too ambitious. For example, none of the countries in our study reported any population group accessing social protection benefits more than the 2017–2019 global average of 45%, let alone 75% stipulated in Commitment 6. However, the 2016 Political Declaration from which the Ten UNAIDS Fast-Track commitments are derived stated: “… 75 per cent of people living with, at risk of and affected by HIV who are in need [Italics added for emphasis] benefit from HIV-sensitive social protection…”  It focused on a subset of people living with at risk of or affected by HIV in “need” of social protection benefits; not all people living with at risk of or affected by HIV reflected in Commitment 6  and measured by this study. Thus, using the wording of the Political Declaration that includes those in need of social protection benefits, the social protection target might have been achievable. Social protection coverage would have been assessed only among a smaller group of people living with at risk of or affected by HIV in need of social protection benefits; not all of them. Such sub-analysis may still have to be conducted by governments to situate the results in their contexts and identify areas for policy actions. In 2021, UNAIDS revised the social protection target to 45%. The downward revision by UNAIDS of the HIV and social protection target to 45% of people living with, at risk of and affected by HIV and AIDS, have access to one or more social protection benefits by 2026  is appropriate. Social protection coverage rates were low among the countries in our study, which are also among the most HIV affected countries of the world.
We found that the proportions of AGYW, SW, MSM and PLHIV who reported receiving social protection benefits in Malawi and Zambia did not differ from those not in these groups. One possible explanation is that community-based organisations and governments in sub-Saharan Africa have developed social protection programmes to mitigate the impact of the HIV epidemic in the general population. Households with children, girls and women have been disproportionately impacted by HIV. They are also prioritised for many social protection programmes, often with bilateral and multilateral donor support . Zambia’s social protection programmes have historically focused on households with OVC expanding the eligibility criteria to include other vulnerable households such as women-headed households and those with members unable to work. Malawi's social protection programme has focused on the poorest households motivated by the need to reduce poverty and vulnerability . In this study, AGYW, SW, MSM, and PLHIV may be living in households receiving social protection benefits and may report receiving the benefits.
However, in Eswatini and Tanzania, the proportions of AGYW, SW, MSM and PLHIV reported receiving social protection benefits differed between people not in these groups. In Eswatini, more AGYW reported receiving social protection benefits than older women aged 25–59. One explanation is that Eswatini’s social safety nets have included school-going children and adolescents . Fewer MLHIV than men not living with HIV in Eswatini reported receiving social protection benefits. Several factors play a role in this disparity. One reason is that more men living with HIV are mobile populations (i.e., seasonal workers, transport operators, construction workers, long-distance truck drivers and uniformed forces). These mobile populations have been identified by the government of Eswatini as crucial drivers of the HIV epidemic . They may not be at home often to receive social protection benefits or considered in need of social protection benefits. In Tanzania, a higher proportion of PLHIV (male and female) reported receiving social protection benefits than people not living with HIV, reflecting the inclusion of PLHIV in the Productive Social Safety Net (PSSN), the country's flag social protection programme. The PSSN, like other social protection programmes in sub-Saharan Africa, evolved in the context of HIV to alleviate the impact of HIV on orphan and vulnerable children and their caregivers . However, more FSW reported receiving social protection benefits than females who were not sex workers. FSW in Tanzania might have successfully organized themselves to access and provide social protection benefits to each other . At the same time, SW and MSM may face stigma and discrimination related to their social identity. They are also criminalised in many countries, which creates barriers to accessing services that could lead to disclosing their social identities [47, 48]. SW may be poor and yet not eligible for government-provided social protection or economic support to small businesses [47, 49].
The third result from our study was that a larger proportion of PLWHIV, AGYW and OVC groups in Eswatini reported receiving social protection benefits than in Malawi, Tanzania and Zambia. This result is backed by evidence and suggests that a country's income level plays an essential role in more people receiving social protection benefits . A prosperous country is more likely to provide social protection benefits, including to PLHIV. Eswatini's per capita GDP is three times that of Tanzania and Zambia and nine times that of Malawi. Spending 1.31% of its GDP, Eswatini fully funded its social assistance programmes; Malawi did not. Malawi spent only 0.41% of its GDP on social assistance programmes . More of Malawi's people may have depended on limited social assistance, typical among developing countries. Thus, a relatively higher proportion of Malawians reported receiving social protection benefits than the country's income would suggest .
The size of the HIV epidemic and the effectiveness of the HIV response play a role in linking people to social protection benefits. Eswatini outperforms Malawi, Tanzania and Zambia on the HIV testing and treatment cascade and has fewer estimated PLHIV. Eswatini's impressive AIDS response is credited, in part, to an effective multi-sectoral strategy coordinated from the Prime Minister's office by the National Emergency Response Council on HIV/AIDS (NERCHA). NERCHA also directly delivers social protection benefits, including school feeding, food distribution and social services. NERCHA is involved in decision-making about OVC educational grants, supplementary feeding, fee-waivers, agriculture input subsidies, and old age grants delivered by ministries of education, health, agriculture, and others. Moreover, Eswatini's social protection strategies directly include people living with, at risk of and affected by HIV as primary beneficiaries . It has integrated HIV and social protection services within the government. As a result, Eswatini may have had more success linking people living with, at risk of, or affected by HIV to social protection benefits than Malawi, Tanzania and Zambia. However, MLHIV, may lose out on the benefits, even in relatively richer countries. Focused efforts may be required to enhance access to social protection benefits of all people living with, at risk of or affected by HIV.
To our knowledge, our study is the first to estimate social protection coverage among PLHIV, SW and MSM. We used nationally representative data sets from four countries, enabling us to compare the estimates of social protection coverage among seven sub-populations and the general population in four high HIV prevalence countries. United Nations Children's Fund (UNICEF) developed and piloted social protection questions for indicator SDG 1.3.1 in Kenya (2014), Zimbabwe (2015), Vietnam (2015) and Belize (2015), and showed that the questions worked well. UNICEF assessed the adequacy, clarity, and relevance of the questions for various population groups and settings . UNICEF did not estimate social protection coverage for PLHIV, SW and MSM. We documented a methodology in this article to measure Commitment 6 and included SAS code for easy use with PHIA data sets containing HIV-related sub-population groups and social protection variables (Appendix 2).
Other nationally representative surveys measure access to social protection benefits. However, few also include HIV testing or questions relevant to identifying belonging to relevant sub-populations groups. The Multiple Indicator Cluster Survey (MICS) is one such survey. It has been periodically conducted in more than 100 low- and middle-income countries by UNICEF to assess children and women's well-being. Like the PHIA, MICS are nationally representative surveys administered to individuals in households. The MICS 6 survey asks several questions about social protection, PLHIV, AGYW and OVC. The MICS 6 survey data sets have been released for Zimbabwe, Lesotho, the Democratic Republic of the Congo and Punjab province in Pakistan. The MICS survey does not ask questions that allow respondents to identify as MSM or SW . Demographic and Health Surveys (DHS) are also nationally representative cross-sectional surveys that include HIV testing and identify the various population groups of interest. Although DHS surveys have been conducted in 90 countries, allowing for significant cross-country comparisons, they unfortunately do not capture information on social protection. Neither do they capture information on MSM .
Other sources explored that capture social protection coverage estimates in countries included the World Social Protection Database, hosted by the ILO. The database compiles and disseminates social security data by country and population group. It presents the proportion of the population “receiving at least one contributory or non-contributory cash benefit, or actively contributing to at least one social security scheme” among children, mothers with newborns, persons with severe disabilities, unemployed, older persons, vulnerable persons and the poor . Another is the World Bank’s Atlas of Social Protection Indicators of Resilience and Equity, which compiles global social protection and labour indicators. None of the two capture HIV-related information .
There are several limitations to our study. First, receipt of social protection benefits is self-reported, linked to a household and could not be verified independently. Respondents reporting that they or their households received benefits does not confirm that the respondent specifically received the benefit. However, it is assumed that household members shared the benefits a household received. Second, the sample sizes available to estimate the proportion of SW and MSM who reported receiving social protection benefits is small, limiting the precision of our analyses. Third, the PHIA data sets that included HIV status and social protection information were only publicly available for Eswatini, Malawi, Tanzania, and Zambia at the time of this analysis, limiting estimates outside these countries. Fourth, the social protection questions asked in our study does not distinguish between formal and informal support. Among OVC, the social protection benefits received included medical, emotional, material, social and school support. Although emotional support falls under social services and may be offered to social protection beneficiaries, it may not strictly fit in the ILO and World Bank definitions of social protection. Thus, our social protection coverage estimates may not be directly comparable to those of the World Bank and the ILO. Last, the PHIA data sets may not effectively capture receipt of social protection benefits for SW and MSM who have no fixed residence or did not identify as such or feel comfortable disclosing their social identity. People in prison, in the military, hospital, boarding schools and other institutions are not included in household-based surveys. We recommend that surveys being conducted among key populations include questions to capture social protection coverage.