Dataset Information

Modelling the impact of social protection on tuberculosis: the S-PROTECT project.

ABSTRACT: BACKGROUND:Tackling the social determinants of Tuberculosis (TB) through social protection is a key element of the post-2015 End TB Strategy. However, evidence informing policies are still scarce. Mathematical modelling has the potential to contribute to fill this knowledge gap, but existing models are inadequate. The S-PROTECT consortium aimed to develop an innovative mathematical modelling approach to better understand the role of social protection to improve TB care, prevention and control. METHODS:S-PROTECT used a three-steps approach: 1) the development of a conceptual framework; 2) the extraction from this framework of three high-priority mechanistic pathways amenable for modelling; 3) the development of a revised version of a standard TB transmission model able to capture the structure of these pathways. As a test case we used the Bolsa Familia Programme (BFP), the Brazilian conditional cash transfer scheme. RESULTS:Assessing one of these pathways, we estimated that BFP can reduce TB prevalence by 4% by improving households income and thus their nutritional status. When looking at the direct impact via malnutrition (not income mediated) the impact was 33%. This variation was due to limited data availability, uncertainties on data transformation and the pathway approach taken. These results are preliminary and only aim to serve as illustrative example of the methodological challenges encountered in this first modelling attempt, nonetheless they suggest the potential added value of integrating TB standard of care with social protection strategies. CONCLUSIONS:Results are to be confirmed with further analysis. However, by developing a generalizable modelling framework, S-PROTECT proved that the modelling of social protection is complex, but doable and allowed to draw the research road map for the future in this field.

SUBMITTER: Boccia D

PROVIDER: S-EPMC6020219 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Modelling the impact of social protection on tuberculosis: the S-PROTECT project.

Boccia D D Rudgard W W Shrestha S S Lönnroth K K Eckhoff P P Golub J J Sanchez M M Maciel E E Rasella D D Shete P P Pedrazzoli D D Houben R R Chang S S Dowdy D D

BMC public health 20180626 1

<h4>Background</h4>Tackling the social determinants of Tuberculosis (TB) through social protection is a key element of the post-2015 End TB Strategy. However, evidence informing policies are still scarce. Mathematical modelling has the potential to contribute to fill this knowledge gap, but existing models are inadequate. The S-PROTECT consortium aimed to develop an innovative mathematical modelling approach to better understand the role of social protection to improve TB care, prevention and co ...[more]

PMID: 29940906

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Project description:The End TB Strategy places great emphasis on increasing social protection and poverty alleviation programmes. However, the role of social protection on controlling tuberculosis has not been examined fully. We analysed the association between social protection spending and tuberculosis prevalence, incidence, and mortality globally.We used publicly available data from WHO's Global Tuberculosis Programme for tuberculosis burden in terms of yearly incidence, prevalence, and mortality per 100,000 people, and social protection data from the International Labour Organization (ILO), expressed as the percentage of national gross domestic product (GDP) spent on social protection programmes (excluding health). Data from ILO were from 146 countries covering the years between 2000 and 2012. We used descriptive assessments to examine levels of social protection and tuberculosis burden for each country, then used these assessments to inform our fully adjusted multivariate regression models. Our models controlled for economic output, adult HIV prevalence, health expenditure, population density, the percentage of foreign-born residents, and the strength of the national tuberculosis treatment programme, and also incorporated a country-level fixed effect to adjust for clustering of datapoints within countries.Overall, social protection spending levels were inversely associated with tuberculosis prevalence, incidence, and mortality. For a country spending 0% of their GDP on social protection, moving to spending 1% of their GDP was associated with a change of -18·33 per 100,000 people (95% CI -32·10 to -4·60; p=0·009) in prevalence, -8·16 per 100,000 people (-16·00 to -0·27; p=0·043) in incidence, and -5·48 per 100,000 people (-9·34 to -1·62; p=0·006) in mortality. This association was mitigated at higher levels of social protection spending, and lost significance when more than 11% of GDP was spent.Our findings suggest that investments in social protection could contribute to a reduced tuberculosis burden, especially in countries that are investing a small proportion of their GDP in this area. However, further research is needed to support these ecological associations.National Institutes of Health National Center for Advancing Translational Science (University of California, Los Angeles [CA, USA] Clinical and Translational Science Institute).

Project description:BackgroundTuberculosis (TB) still represents a major public health problem in Latin America, with low success and high default rates. Poor adherence represents a major threat for TB control and promotes emergence of drug-resistant TB. Expanding social protection programs could have a substantial effect on the global burden of TB; however, there is little evidence to evaluate the outcomes of socioeconomic support interventions. This study evaluated the effect of a conditional cash transfer (CCT) policy on treatment success and default rates in a prospective cohort of socioeconomically disadvantaged patients.Methods and findingsData were collected on adult patients with first diagnosis of pulmonary TB starting treatment in public healthcare facilities (HCFs) from 16 health departments with high TB burden in Buenos Aires who were followed until treatment completion or abandonment. The main exposure of interest was the registration to receive the CCT. Other covariates, such as sociodemographic and clinical variables and HCFs' characteristics usually associated with treatment adherence and outcomes, were also considered in the analysis. We used hierarchical models, propensity score (PS) matching, and inverse probability weighting (IPW) to estimate treatment effects, adjusting for individual and health system confounders. Of 941 patients with known CCT status, 377 registered for the program showed significantly higher success rates (82% versus 69%) and lower default rates (11% versus 20%). After controlling for individual and system characteristics and modality of treatment, odds ratio (OR) for success was 2.9 (95% CI 2, 4.3, P < 0.001) and default was 0.36 (95% CI 0.23, 0.57, P < 0.001). As this is an observational study evaluating an intervention not randomly assigned, there might be some unmeasured residual confounding. Although it is possible that a small number of patients was not registered into the program because they were deemed not eligible, the majority of patients fulfilled the requirements and were not registered because of different reasons. Since the information on the CCT was collected at the end of the study, we do not know the exact timing for when each patient was registered for the program.ConclusionsThe CCT appears to be a valuable health policy intervention to improve TB treatment outcomes. Incorporating these interventions as established policies may have a considerable effect on the control of TB in similar high-burden areas.

Project description:BackgroundIn the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R0) below 1 for TB.MethodsWe adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035.ResultsExtending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level.ConclusionsActive case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets.

Project description:BackgroundRecent studies have confirmed that the COVID-19 lockdown has caused massive job losses. However, the impact of this loss on food security is not well-understood. Moreover, a paucity of evidence exists regarding social protection grants' countervailing effects against such shocks. This study examined the effects of job loss (labour income loss) on child and household hungers (our two measures food insecurity) during COVID-19 pandemic in South Africa. It also ascertained whether these effect were offset by alternative social grant programs to document the protective role of the latter.Data and methodsWe used South Africa's National Income Dynamics Study (NIDS) and the Coronavirus Rapid Mobile Survey (CRAM) data. These data cover a nationally representative sample of 7073 individuals. We employed a probit model to estimate the effect of job loss and receipts of various social grants on child and households' hungers. We also estimated the double-selection logit model to account for the model's uncertainty surrounding the variable selection and treatment-effects estimation using lasso (Telasso) for causal inference of our analysis.ResultsOur analyses showed that households exposed to a labour market shock during the pandemic experienced a significant increase in our measures of food insecurity (child and household hungers). Specifically, we found that compared with households containing employed respondents, households with respondents who lost their jobs due to COVID-19 lockdown were 5.4% more likely to report child hunger and 2.6% more likely to report household hunger in the past seven days A receipt of child support grant reduces the likelihood of reporting child hunger and household hunger by 21.7%and 16.9% respectively among these households. A receipt of old age pension grant reduces the likelihood of reporting household hunger by 24% with no significant effect on child hunger.ConclusionThe COVID-19 lockdown resulted in unprecedent job losses with significant implications for food insecurity. Job loss due to COVID-19 lockdown significantly increased food insecurity in South Africa. Receipts of social grants effectively offset this adverse effect. The protective effect of the social grant is heterogenous across its alternative programs (child support grant and old age pension grant) and food insecurity, suggesting the differences in the size of transfers and motivations for sending these transfers.

Dataset Information

Modelling the impact of social protection on tuberculosis: the S-PROTECT project.

Publications

Modelling the impact of social protection on tuberculosis: the S-PROTECT project.

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