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Tuberculosis in Brazil and cash transfer programs: A longitudinal database study of the effect of cash transfer on cure rates

Author

Listed:
  • Barbara Reis-Santos
  • Priya Shete
  • Adelmo Bertolde
  • Carolina M Sales
  • Mauro N Sanchez
  • Denise Arakaki-Sanchez
  • Kleydson B Andrade
  • M Gabriela M Gomes
  • Delia Boccia
  • Christian Lienhardt
  • Ethel L Maciel

Abstract

Introduction: Tuberculosis incidence is disproportionately high among people in poverty. Cash transfer programs have become an important strategy in Brazil fight inequalities as part of comprehensive poverty alleviation policies. This study was aimed at assessing the effect of being a beneficiary of a governmental cash transfer program on tuberculosis (TB) treatment cure rates. Methods: We conducted a longitudinal database study including people ≥18 years old with confirmed incident TB in Brazil in 2015. We treated missing data with multiple imputation. Poisson regression models with robust variance were carried out to assess the effect of TB determinants on cure rates. The average effect of being beneficiary of cash transfer was estimated by propensity-score matching. Results: In 2015, 25,084 women and men diagnosed as new tuberculosis case, of whom 1,714 (6.8%) were beneficiaries of a national cash transfer. Among the total population with pulmonary tuberculosis several determinants were associated with cure rates. However, among the cash transfer group, this association was vanished in males, blacks, region of residence, and people not deprived of their freedom and who smoke tobacco. The average treatment effect of cash transfers on TB cure rates, based on propensity score matching, found that being beneficiary of cash transfer improved TB cure rates by 8% [Coefficient 0.08 (95% confidence interval 0.06–0.11) in subjects with pulmonary TB]. Conclusion: Our study suggests that, in Brazil, the effect of cash transfer on the outcome of TB treatment may be achieved by the indirect effect of other determinants. Also, these results suggest the direct effect of being beneficiary of cash transfer on improving TB cure rates.

Suggested Citation

  • Barbara Reis-Santos & Priya Shete & Adelmo Bertolde & Carolina M Sales & Mauro N Sanchez & Denise Arakaki-Sanchez & Kleydson B Andrade & M Gabriela M Gomes & Delia Boccia & Christian Lienhardt & Ethel, 2019. "Tuberculosis in Brazil and cash transfer programs: A longitudinal database study of the effect of cash transfer on cure rates," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-18, February.
    • Handle: RePEc:plo:pone00:0212617
    DOI: 10.1371/journal.pone.0212617
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    References listed on IDEAS

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    2. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    3. Andrea R. Ferro & Ana Lúcia Kassouf & Deborah Levison, 2010. "The impact of conditional cash transfer programs on household work decisions in Brazil," Research in Labor Economics, in: Child Labor and the Transition between School and Work, pages 193-218, Emerald Group Publishing Limited.
    4. Joilda Silva Nery & Susan Martins Pereira & Davide Rasella & Maria Lúcia Fernandes Penna & Rosana Aquino & Laura Cunha Rodrigues & Mauricio Lima Barreto & Gerson Oliveira Penna, 2014. "Effect of the Brazilian Conditional Cash Transfer and Primary Health Care Programs on the New Case Detection Rate of Leprosy," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 8(11), pages 1-7, November.
    5. Glewwe, Paul & Kassouf, Ana Lucia, 2012. "The impact of the Bolsa Escola/Familia conditional cash transfer program on enrollment, dropout rates and grade promotion in Brazil," Journal of Development Economics, Elsevier, vol. 97(2), pages 505-517.
    6. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
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    1. Dalila Camêlo Aguiar & Ramón Gutiérrez Sánchez & Edwirde Luiz Silva Camêlo, 2020. "Hierarchical Clustering with Spatial Constraints and Standardized Incidence Ratio in Tuberculosis Data," Mathematics, MDPI, vol. 8(9), pages 1-12, September.

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