Background
There is a large body of work, dating back over a century, that emphasizes the close relationship between poverty and tuberculosis (TB). Indeed, Robert Koch himself described the disease as ‘the outcome of social misery’[
1]. Rene and Jean Dubois, who authored the seminal book ‘The White Plague: Tuberculosis, Man and Society’ called TB ‘a social disease’[
2]. The prevalence of TB is higher in poorer countries[
3] and among poorer communities in wealthy countries[
4]. Indeed, in South Africa, a country of profound income inequality[
5], TB has been called a ‘barometer of poverty’[
6].
South Africa has one of the highest burdens of TB in the world, which can be attributed, at least in part, to conditions of poverty that favor its transmission[
7]. In addition, the high prevalence of HIV infection has played a central role in increasing and maintaining the high burden of TB in the country and may also be responsible for undermining outcomes of patients on TB treatment. The association between poverty and poor adherence to anti-retroviral treatment[
8,
9] has profound implications for the role of HIV in adherence to anti-TB treatment and for outcomes of patients on that treatment. At present, the outcomes of patients on TB treatment in South Africa remain below the targets set by the World Health Organization[
10]. Although these outcomes have improved over the last decade, the transmission rate of TB has increased dramatically over this time and it has been suggested that the current national strategy for TB control, based on the Directly Observed Treatment Strategy, is insufficient to control the epidemic[
11].
The association between poverty and TB exists over the entire course of the disease[
12]. Although effective treatment is available for drug-susceptible TB, and this is provided free of charge in public sector clinics in South Africa, there is a wealth of research that shows that the effect of poverty on TB outcomes is due, at least in part, to the costs of accessing and adhering to treatment[
13‐
17]. In addition, the poor nutrition that often accompanies poverty is not only a risk factor for the development of TB[
18‐
20], but undermines the outcomes of those on TB treatment[
21].
Although the association between poverty and TB is well documented, there are very few programs which directly address this relationship with economic interventions, and even fewer research studies which evaluate them[
12]. Such research is difficult to do. Because of the scale on which poverty occurs, its inherent complexity and the complex relationship between different aspects of poverty and disease, such studies may be difficult to design and enormously costly to conduct. Addressing this point, the Commission on the Socio-economic Determinants of Health recently noted that, in spite of the growing body of evidence to support action in this field, ‘there is a pressing need to invest in a great deal more research, bringing together different disciplines and areas of expertise, to work out how social determinants create health inequity, and how action on these determinants can produce better, fairer health’”[
22].
The call for research in the field of economic support for improving TB outcomes has been echoed by several authors who have conducted reviews on the effects on health of results-based financing[
23], conditional cash transfers[
24], economic incentives[
25], and cash transfers and microfinance[
26]. A recent expert consultation on Social Protection Interventions for Tuberculosis Control, held at Chatham House in London in February 2012, concluded that ‘a) despite the indirect evidence gathered in a recent review from Boccia
et al. (2011)[
26], the actual impact of social protection on TB indicators (e.g. incidence, mortality, case finding, TB treatment adherence) remains unknown; b) it is unclear how social protection initiatives may be best integrated with current TB control activities and which forms of social protection are most likely to be successful, depending on the objectives posed’[
27].
Our trial aimed to generate evidence on both of these areas. It aimed to investigate the feasibility of delivering a form of economic support to patients with TB as an integrated part of the TB control program of government-run clinics in South Africa, and to determine whether such support was effective in improving the outcomes of patients with TB in these clinics.
Discussion
This was the first trial in Africa to investigate the effect of economic support (a monthly voucher) on the outcomes of patients on TB treatment. The trial found a 5.6% improvement in treatment success rates among patients who received the voucher, meaning that for every 1,000 patients who received the voucher, an additional 56 would have achieved treatment success. This was lower than the 15% difference that the study was powered to detect, which explains in part, the failure of the trial to achieve a significant result. This failure may be further explained by low fidelity to the intervention, which is discussed further in the process evaluation (to be reported elsewhere). The exploratory analysis, which compared patients in intervention clinics who had received at least one voucher to the control group, showed significantly higher treatment success rates in intervention compared to control clinics. A powerful dose–response effect was demonstrated, with patients who received vouchers more frequently being more likely to complete treatment.
This trial aimed both to reward adherence behavior, and to make adherence easier by ameliorating two features of poverty which are commonly associated with TB: under-nutrition and limited access to health care[
12]. We hypothesized that the voucher (if used for purchasing food) would improve patients’ food security and release household funds for use elsewhere, such as for transport to the clinic[
14]. In 2008, 71% of the households in KwaZulu-Natal lived on less than 40% of the median per capita income of ZAR569.00 per month[
36]. This suggests that, although the value of the voucher was small relative to the median per capita income at the time of the trial, the voucher may nonetheless have facilitated a substantial improvement in the food purchases of households.
The evidence for the efficacy or effectiveness of economic support in improving the outcomes of patients on TB treatment is slim. No conditional cash transfer programs have been evaluated for their effect on TB outcomes[
24,
26]. Although several randomized controlled trials have tested the effects of economic incentives in the context of TB ([
25], only one has focused on patients with active TB and only one (the same trial) was conducted in a low-income country[
41]. In that study, food supplements to patients on TB treatment were found to have no effect on cure rates. Other non-randomized studies investigating the use of financial incentives in patients with active TB have had varying results. One such project in China, where both patients and providers received cash incentives, showed no impact on TB outcomes[
42]. A second project in Cambodia, where patients with TB received nutritional supplementation and participated in a microfinance program, showed improved cure rates in the intervention group[
43]. To our knowledge, no studies have tested the impact of economic support on TB outcomes in Africa.
Social and economic interventions to strengthen TB control are rare[
12]. In South Africa, patients with TB may be given food parcels when they collect their treatment, and may also be eligible to receive a disability grant. Disability grants, which are income replacement grants, may be given to patients with TB if authorized by a doctor. However, the determination of eligibility for these grants is neither clear nor standardized and varies both between and within provinces[
44]. Neither the food parcels nor the disability grants are conditional on any outcomes or behaviors on the part of the patients. Although data on receipt of food parcels and disability grants are not recorded in the TB registers at South African clinics, and were therefore not collected in this trial, we expect that, due to randomization, the proportions of patients receiving them would be the same across intervention and control clinics.
In our study, the lack of a statistically significant effect in the intention to treat analysis may be due in part to the low fidelity to the intervention. It is likely that eligible patients who did not receive any vouchers at all were considered by nurses not to need them. Nurses in the trial, who are used to rationing food supplements to those patients whom they consider most needy, tended to give vouchers out in the same way (process evaluation, to be reported elsewhere). This is illustrated by the finding that unemployed patients in intervention clinics were more likely to receive vouchers than patients who were employed (Table
7). Interestingly, eligible children younger than 13 years were less likely to receive vouchers. Although this seems surprising, it must be noted that the majority of these children would have been in receipt of a child support grant. One of the criteria reported by nurses for not giving eligible patients vouchers was their receipt of other forms of state grants (process evaluation, to be reported elsewhere). Women, who in South Africa are more likely to be poorer than men, were also more likely to receive vouchers.
The analysis of treatment success rates in unemployed patients shows that, within the intervention group, unemployed patients who did receive a voucher achieved better treatment success rates than those who did not. However, reverse causality may be responsible for these findings, as those who received vouchers may have been those who attended the clinics more regularly. Thus this finding should be interpreted with caution, and be investigated in further research.
Further issues that may have contributed to the low fidelity of our trial were the preference of some nurses to give vouchers out in batches at month end, and the logistical difficulties in ensuring that clinics did not run out of vouchers (process evaluation, to be reported elsewhere). That there was no quantification of the impact of these issues on the fidelity to the trial protocol is an important limitation of this trial. More rigorous monitoring of our intervention may have improved fidelity, and made it easier for a trial of this size to detect a significant effect. However, an important aim of this pragmatic trial was to assess the feasibility of administering such vouchers under normal public sector clinic conditions[
31].
The exploratory analysis, which investigated the effect of the vouchers in eligible patients who received at least one, attempted to ‘estimate maximum achievable treatment effect’[
33] in a particular subgroup of patients. The patients in intervention clinics who received a voucher at least once were systematically different from the patients in intervention clinics who received no vouchers, and so not only is the potential bias in this analysis acknowledged, it can also to a certain extent be described[
31]. The patients who received the vouchers were more likely to be unemployed, and therefore more deprived, than those who did not, because of the nurses’ sense that they should give vouchers preferentially to patients who needed them more (process evaluation, to be reported elsewhere). This exploratory analysis suggests that, in patients who received vouchers, they did have a significant effect on treatment outcomes. Although the intention to treat analysis is presented as the main and most important finding of this trial, the exploratory analysis is included because it adds possible explanatory detail to the trial, and because it raises questions for further research. Such research questions include:
-
Would it be feasible to deliver these vouchers (or a similar form of economic support) to poorer patients only?
-
How feasible would the means testing inherent in such delivery be?
-
Would such means testing be susceptible to manipulation and corruption?
-
How would other patients react to the targeting of poorer patients for the receipt of a voucher?
-
Would the effect demonstrated in the exploratory analysis be replicated or increased if this voucher were only given to more deprived patients?
The findings of the dose–response analysis support those of the exploratory analysis by suggesting that these vouchers have the potential to improve outcomes on TB treatment. The fact that the subgroups of patients who received the vouchers more frequently achieved significantly better TB outcomes than those who received it less frequently implies that higher fidelity to the intervention may produce a significant benefit. In addition, the dose–response analysis argues against a perverse incentive effect of the voucher. If patients did try to remain ill in order to continue receiving the voucher, treatment success rates would have fallen with frequency and duration of receipt. This is an important finding, given the local and global concern about this unintended consequence of conditional cash transfers, economic incentives and results-based financing[
23]. However, reverse causality cannot be ruled out here: it is possible that patients who came to the clinic more often of their own accord were more likely to receive vouchers, and that it was their own motivation to adhere that was responsible for their improved outcomes on treatment, rather than the vouchers
per se. Future studies should investigate this phenomenon further.
Subgroup analysis showed that treatment success rates were better in women, patients who were employed, children under 13 years of age, and smear-positive patients. Although such results are not found in all settings, they do reflect the findings of many other studies in Africa and elsewhere. In the African[
45] and South African contexts[
46], women have been shown to have better adherence to TB treatment. However, women in some settings may need to seek permission to attend clinics and may therefore have poorer adherence than men[
14]. In our study setting, employed patients appeared to be better off financially than those who were unemployed (assessment of patient poverty, to be reported elsewhere). Although unemployed patients were more likely to receive the voucher than those who were employed, it is likely that the value of the voucher was too small to overcome the barriers to adherence imposed by unemployment and consequent poverty (process evaluation, to be reported elsewhere). The poorer outcomes of unemployed patients are reflected in the findings of several studies in Africa and elsewhere, where low income has been shown to be associated with poorer adherence to TB treatment[
14,
45]. Further trials should investigate the effect of greater values of economic support on TB treatment outcomes, as well as possible confounders that might affect this relationship. In our study, children younger than 13 years had better outcomes on treatment than those older than 13. Although in some contexts adherence of children to TB treatment is low[
47,
48], adherence of children in South Africa has been shown to be high[
49]. Finally, smear-positive TB was associated in our study with better outcomes on treatment. A possible explanation for this is that these patients are less likely to be infected with HIV, which has been identified as an independent risk factor for default from TB treatment[
45,
46].
The omission of HIV from the analysis of patients’ responses to the vouchers, due to the lack of data on participating patients’ HIV status and treatment, is an important limitation of this trial. The co-infection rate of TB and HIV in KwaZulu-Natal is high and both the incidence and the geographical distribution of TB in the country have been affected profoundly by HIV. Importantly, under-nutrition, TB and HIV also seem to act synergistically, thus creating the ‘perfect storm’ for epidemics in South Africa[
50]. The high co-infection rate of HIV and TB, and the effect of poverty on adherence to treatment for both diseases, make it possible that patients infected by HIV in this trial may have benefited even more from these vouchers than those uninfected by the virus. It is imperative that future research in this field investigate whether and how co-infection with HIV modifies the impact of economic support for patients on TB treatment.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
EL conceptualized the trial, designed the data collection tools, monitored data collection for the whole trial, wrote the statistical analysis plan, cleaned the data, and drafted and revised the paper. SL and JV conceptualized the trial, designed the data collection tools, wrote the statistical analysis plan, and drafted and revised the paper. IF conceptualized the trial and drafted and revised the paper. CL wrote the statistical analysis plan, cleaned the data, analyzed the data and drafted and revised the paper. All authors read and approved the final manuscript.