Skip to main content

Sustaining Gains in Health Programs: Technical Efficiency and its Determinants in Malaria Programs in Sub-Saharan Africa

Applied Health Economics and Health Policy volume 15, pages 249–259 (2017)Cite this article

Abstract

Background

Since the year 2000, Africa has made significant progress in the fight against malaria. Between 2000 and 2015, the incidence and death from malaria fell by 42 and 66%, respectively. However, the African region still accounts for most global cases of malaria. In 2015, the region was home to 89% of malaria cases and 91% of malaria death.

Objective

This study aimed to evaluate efficiency of policies against malaria in 30 malaria-endemic Sub-Saharan African (SSA) countries, from the perspective of sustaining gains.

Methods

The data came from World Malaria Report 2013. Data were analyzed using the double bootstrap method. We first estimated bootstrapped efficiency scores. Then, bootstrapped truncated regression was used to determine factors associated with malaria program efficiency.

Results

This study showed that most malaria programs in SSA are technically inefficient. We also found that aid from international institutions and public expenditures on malaria programs do not significantly affect the efficiency of malaria programs. However, in an enhanced governance context, international aid and public expenditure impact positively on the efficiency of malaria programs. Moreover, intermittent preventive treatment for pregnant women is associated with a positive effect on the efficiency. Surprisingly, the free care policies—artemisinin-based combinations for under five-year-old children in the public facilities, rapid diagnostic tests, and distribution of insecticide-treated bed nets and long-lasting insecticide-impregnated nets—does not significantly affect the efficiency of malaria programs.

Conclusion

Financing alone does not ensure efficiency of malaria programs. Good governance and the targeting of the most vulnerable segments of the population are necessary to reduce malaria deaths and improve efficiency of malaria programs in SSA.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

49,54 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1

References

  1. World Health Organization. Africa Malaria Report 2003. World Health Organization and UNICEF. 2003. http://www.who.int/malaria/publications/atoz/whocdsmal20031093/en/. Accessed 12 Oct 2016.

  2. Phillips RS. Current status of malaria and potential for control. Clin Microbiol Rev. 2001;14:208–26.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  3. World Health Organization. Community involvement in Rolling Back Malaria (archived). World Health Organization. 2002. http://www.who.int/malaria/publications/atoz/who_cds_rbm_2002_42/en/. Accessed 12 Oct 2016.

  4. Rowe A, Rowe S, Snow R, et al. The burden of malaria mortality among African children in the year 2000. Int J Epidemiol. 2006;35:691–704.

    Article  PubMed  PubMed Central  Google Scholar 

  5. World Health Organization. Global strategy for dengue prevention and control 2012–2020. World Health Organization report. 2012. http://www.who.int/denguecontrol/9789241504034/en/. Accessed 12 Oct 2016.

  6. International Monetary Fund. Regional economic outlook: Sub-Saharan Africa. International Monetary Fund. 2015. http://www.imf.org/external/pubs/ft/reo/2015/afr/eng/sreo1015.htm. Accessed 12 Oct 2016.

  7. World Bank. Africa: Low Commodity Prices Continue to Impede Growth. The World Bank for a World Free of Poverty. 2016. http://www.worldbank.org/en/news/press-release/2016/04/11/africa-low-commodity-prices-continue-to-impede-growth. Accessed 12 Oct 2016.

  8. Albert M, Fevre A. Sub-Saharan Africa: hit but not sinking. COFACE economic Publications. 2016. http://www.coface.com/News-Publications/Publications/Sub-Saharan-Africa-hit-but-not-sinking. Accessed 12 Oct 2016.

  9. World Bank. Global Economic Prospects: Sub-Saharan Africa. The World Bank for a World Free of Poverty. 2015. https://www.worldbank.org/en/publication/global-economic-prospects. Accessed 12 Oct 2016.

  10. KPMG. The state of health care in Africa. KPMG. 2012. http://www.kpmg.com/africa/en/issuesandinsights/articles-publications/pages/the-state-of-healthcare-in-africa.aspx. Accessed 12 Oct 2016.

  11. World Bank. Intensifying the fight against Malaria: the World Bank’s Booster Program for Malaria Control in Africa. World Bank. 2009. http://documents.worldbank.org/curated/en/473021468009019995/Intensifying-the-fight-against-malaria-the-World-Banks-booster-program-for-malaria-control-in-Africa. Accessed 12 Oct 2016.

  12. CDC. CDC’s Malaria Program. CDC and Malaria. 2014. https://www.cdc.gov/parasites/resources/pdf/cdc_malaria.pdf. Accessed 12 Oct 2016.

  13. World Health Organization. Malaria. World Health Organization. 2016. http://www.who.int/mediacentre/factsheets/fs094/en/. Accessed 12 Oct 2016.

  14. Aigner D, Lovell CK, Schmidt P. Formulation and estimation of stochastic frontier production function models. J Econom. 1977;6:21–37.

    Article  Google Scholar 

  15. Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. Eur J Oper Res. 1978;2:429–44.

    Article  Google Scholar 

  16. Farrell MJ. The measurement of productive efficiency. J R Stat Soc. 1957;120:253–90.

    Google Scholar 

  17. Meeusen W, Van den Broeck J. Efficiency estimation from Cobb-Douglas production functions with composed error. Int Econ Rev. 1977;18:435–44.

    Article  Google Scholar 

  18. Besstremyannaya G. The impact of Japanese hospital financing reform on hospital efficiency: a difference-in-difference approach. Jpn Econ Rev. 2013;64:337–62.

    Article  Google Scholar 

  19. Evans DB, Tandon A, Murray CJ, et al. Comparative efficiency of national health systems: cross national econometric analysis. BMJ. 2001;323:307–10.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  20. Fizel JL, Nunnikhoven TS. Technical efficiency of for-profit and non-profit nursing homes. Manag Decis Econ. 1992;13:429–39.

    Article  Google Scholar 

  21. Hollingsworth B. The measurement of efficiency and productivity of health care delivery. Health Econ. 2008;17:1107–28.

    Article  PubMed  Google Scholar 

  22. Kooreman P. Nursing home care in The Netherlands: a nonparametric efficiency analysis. J Health Econ. 1994;13:301–16.

    CAS  Article  PubMed  Google Scholar 

  23. Simar L, Wilson PW. Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models. Manage Sci. 1998;44:49–61.

    Article  Google Scholar 

  24. Simar L, Wilson PW. A general methodology for bootstrapping in non-parametric frontier models. J Appl Stat. 2000;27:779–802.

    Article  Google Scholar 

  25. Grosskopf S. Statistical inference and nonparametric efficiency: a selective survey. J Prod Anal. 1996;7:161–76.

    Article  Google Scholar 

  26. Simar L, Wilson PW. Estimation and inference in two-stage, semi-parametric models of production processes. J Econometrics. 2007;136:31–64.

    Article  Google Scholar 

  27. Xue M, Harker PT. Overcoming the inherent dependency of DEA efficiency scores: a bootstrap approach. Working Paper, Wharton Financial Institutions Center, University of Pennsylvania. 1999. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.30.9483&rep=rep1&type=pdf. Accessed 12 Oct 2016.

  28. Coelli T. A multi-stage methodology for the solution of orientated DEA models. Oper Res Lett. 1998;23:143–9.

    Article  Google Scholar 

  29. Wilson PW. FEAR: frontier efficiency analysis with R. R package version. 2013. http://www.clemson.edu/economics/faculty/wilson/Software/FEAR/fear.html. Accessed 7 Aug 2016.

  30. Alexander WRJ, Haug AA, Jaforullah M. A two-stage double-bootstrap data envelopment analysis of efficiency differences of New Zealand secondary schools. J Prod Anal. 2010;34:99–110.

    Article  Google Scholar 

  31. Lépine A, Vassall A, Chandrashekar S. The determinants of technical efficiency of a large-scale HIV prevention project: application of the DEA double bootstrap using panel data from the Indian Avahan. Cost Eff Resour Alloc. 2015;13:1.

    Article  Google Scholar 

  32. Chavasse D, Lo-Phan L, Lavigne M. Insecticide-treated net projects: a handbook for managers. Malaria Consortium; 1999.

  33. Zandu A, Malengreau M, Wery M. Methods and expenses for protection against mosquitoes in households in Kinshasa, Zaire. Ann Soc Belg Med Tr. 1991;71:259–66.

    CAS  Google Scholar 

  34. World Health Organization. World Malaria Report 2011. World Health Organization. 2011. http://www.who.int/malaria/world_malaria_report_2011/en/. Accessed 12 Oct 2016.

  35. Andrews KG, Lynch M, Eckert E, Gutman J. Missed opportunities to deliver intermittent preventive treatment for malaria to pregnant women 2003–2013: a systematic analysis of 58 household surveys in sub-Saharan Africa. Malar J. 2015;14:1.

    Article  Google Scholar 

  36. World Health Organization. Updated WHO policy recommendation: intermittent preventive treatment of malaria in pregnancy using sulfadoxine-pyrimethamine (IPTp-SP). World Health Organization. 2012. http://www.who.int/malaria/iptp_sp_updated_policy_recommendation_en_102012.pdf. Accessed 12 Oct 2016.

  37. World Health Organization. Disease Surveillance for Malaria Control. World Health Organization. 2012. http://www.who.int/malaria/areas/surveillance/operationalmanuals/en/. Accessed 12 Oct 2016.

  38. Bruxvoort K, Kalolella A, Nchimbi H, et al. Getting antimalarials on target: impact of national roll-out of malaria rapid diagnostic tests on health facility treatment in three regions of Tanzania. Trop Med Int Health. 2013;18:1269–82.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Hanson K. Public and private roles in malaria control: the contributions of economic analysis. Am J Trop Med Hyg. 2004;71:168–73.

    PubMed  Google Scholar 

  40. World Health Organization. World Malaria report 2015. World Health Organization. 2015. http://www.who.int/malaria/publications/world-malaria-report-2015/report/en/. Accessed 12 Oct 2016.

  41. Feenstra RC, Inklaar R, Timmer M. PWT 8.0–a user guide. Groningen Growth and Development Centre, University of Groningen. 2013. http://www.rug.nl/research/ggdc/data/pwt/pwt-8.0. Accessed 12 Oct 2016.

  42. Jenkins L, Anderson M. A comparison of data envelopment analysis using fewer variables versus principal components. Dept of Business Administration Royal Military College of Canada. 2004. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.377.9983&rep=rep1&type=pdf. Accessed 12 Oct 2016.

  43. Lewin AY, Morey RC, Cook TJ. Evaluating the administrative efficiency of courts. Omega. 1982;10:401–11.

    Article  Google Scholar 

  44. Eisele TP, Larsen D, Anglewicz A, et al. Malaria prevention in pregnancy, birthweight, and neonatal mortality: a meta-analysis of 32 national cross-sectional datasets in Africa. Lancet Infect Dis. 2012;12:942–9.

    Article  PubMed  Google Scholar 

  45. World Health Organization. Malaria T3: Test Treat Track initiative. World Health Organization. 2012. http://www.who.int/malaria/areas/test_treat_track/en/. Accessed 12 Oct 2016.

  46. Chisholm D, Evans DB. Improving health system efficiency as a means of moving towards universal coverage. World health report Background paper. 2010. http://cdrwww.who.int/healthsystems/topics/financing/healthreport/28UCefficiency.pdf. Accessed 12 Oct 2016.

  47. Mancuso P, Valdmanis VG. Care appropriateness and health productivity evolution: a non-parametric analysis of the italian regional health systems. Appl Health Econ Health Policy. 2016;14:595–607.

    Article  PubMed  Google Scholar 

  48. Medeiros J, Schwierz C. Efficiency estimates of health care systems. Economic papers. 2015. http://ec.europa.eu/economy_finance/publications/economic_paper/2015/pdf/ecp549_en.pdf. Accessed 12 Oct 2016.

  49. Adler N, Liebert V, Yazhemsky E. Benchmarking airports from a managerial perspective. Omega. 2013;41:442–58.

    Article  Google Scholar 

  50. Gitto S, Mancuso P. Bootstrapping the Malmquist indexes for Italian airports. Int J Prod Econ. 2012;135:403–11.

    Article  Google Scholar 

  51. Bulajić M, Jeremić V, Knežević S, Žarkić-Joksimović N. Statistički Pristup Merenju Efikasnosti Banaka. Ekonomska istraživanja. 2013;26:95–104.

    Google Scholar 

  52. Zelenyuk N, Zelenyuk V. Drivers of Efficiency in Banking: Importance of Model Specifications. Centre for Efficiency and Productivity Analysis, Working paper. 2015. http://www.uq.edu.au/economics/cepa/docs/WP/WP082015.pdf. Accessed 12 Oct 2016.

  53. Msellem M, Mårtensson A, Rotllant G, et al. Influence of rapid malaria diagnostic tests on treatment and health outcome in fever patients, zanzibar—a crossover validation study. PLoS Med. 2009;6:e1000070.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Asiimwe C, Kyabayinze DJ, Kyalisiima Z, et al. Early experiences on the feasibility, acceptability, and use of malaria rapid diagnostic tests at peripheral health centres in Uganda-insights into some barriers and facilitators. Implement Sci. 2012;7:1.

    Article  Google Scholar 

  55. Chandler CI, Jones C, Boniface G, et al. Guidelines and mindlines: why do clinical staff over-diagnose malaria in Tanzania? A qualitative study. Malar J. 2008;7:53.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Chandler CI, Whitty CJ, Ansah EK. How can malaria rapid diagnostic tests achieve their potential? A qualitative study of a trial at health facilities in Ghana. Malar J. 2010;9:95.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Ezeoke OP, Ezumah NN, Chandler CC, et al. Exploring health providers’ and community perceptions and experiences with malaria tests in South-East Nigeria: a critical step towards appropriate treatment. Malar J. 2012;11:1–10.

    Article  Google Scholar 

  58. Ruizendaal E, Dierickx S, Grietens KP, et al. Success or failure of critical steps in community case management of malaria with rapid diagnostic tests: a systematic review. Malar J. 2014;13:229.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Van Eijk AM, Hill J, Larsen DA, et al. Coverage of intermittent preventive treatment and insecticide-treated nets for the control of malaria during pregnancy in sub-Saharan Africa: a synthesis and meta-analysis of national survey data, 2009–11. Lancet Infect Dis. 2013;13:1029–42.

    Article  PubMed  Google Scholar 

  60. Berkessa T, Oljira D, Tesfa B. Insecticide treated nets use and its determinants among settlers of Southwest Ethiopia. BMC Public Health. 2016;16:1.

    Google Scholar 

  61. Stevens ER, Aldridge A, Degbey Y, et al. Evaluation of the 2011 long-lasting, insecticide-treated net distribution for universal coverage in Togo. Malar J. 2013;12:1.

    Article  Google Scholar 

  62. Welch K, Fuster M. Barriers in access to insecticide-treated bednets for malaria prevention: an analysis of Cambodian DHS data. J Vector Borne Dis. 2012;49:1.

    PubMed  Google Scholar 

  63. Maslove DM, Mnyusiwalla A, Mills EJ, et al. Barriers to the effective treatment and prevention of malaria in Africa: a systematic review of qualitative studies. BMC Int Health Hum Rights. 2009;9:1–10.

    Article  Google Scholar 

  64. Chatio S, Aborigo R, Adongo PB, et al. Adherence and uptake of artemisinin-based combination treatments for uncomplicated malaria: a qualitative study in northern Ghana. PLoS One. 2015;10:e0116856.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Kaufmann D, Kraay A, Mastruzzi M. Governance matters III: governance indicators for 1996, 1998, 2000, and 2002. World Bank Econ Rev. 2004;18:253–87.

    Article  Google Scholar 

  66. Kaufmann D, Kraay A, Mastruzzi M. Governance matters VI: governance indicators for 1996-2006. World Bank policy research working paper. 2007. http://ssrn.com/abstract=999979. Accessed 12 Oct 2016.

  67. Yaqub JO, Ojapinwa TV, Yussuff RO. Public health expenditure and health outcome in Nigeria: the impact of governance. European Scientific Journal. 2012. http://eujournal.org/index.php/esj/article/view/206. Accessed 12 Oct 2016.

  68. Mills A, Lubell Y, Hanson K. Malaria eradication: the economic, financial and institutional challenge. Malar J. 2008;7:1.

    Article  Google Scholar 

  69. Gupta S, Davoodi HR, Tiongson E. Corruption and the provision of health care and education services. International Monetary Fund. 2000. https://www.imf.org/external/pubs/cat/longres.aspx?sk=3652.0. Accessed 12 Oct 2016.

  70. Wambugu A, Odhiambo SA, Kiriti-Ng’ang’a T. Effect of Health Expenditure on Child Health in Sub-Saharan Africa: Governance Perspective. University of Nairobi. 2015. http://hdl.handle.net/11295/87789. Accessed 12 Oct 2016.

Download references

Acknowledgements

The author would like to thank the African Population and Health Research Center (APHRC) and the International Development Research Center (IDRC) for the technical support accorded to him during his research. The author wishes to express his gratitude to Professor Ega A. AGBODJI and Dr. Djesika AMENDAH for their guidance and comments. He is also grateful to the editors and the two anonymous reviewers who provided constructive comments to help shape this paper.

Author information

Affiliations

  1. Department of Economics Sciences, University of Lome, Lomé, Togo

    Esso-Hanam Atake

Authors
  1. Esso-Hanam Atake
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Esso-Hanam Atake.

Ethics declarations

Funding

This study received no funding

Conflict of interest

The author has no conflicts of interest that are directly relevant to the content of this article.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Atake, EH. Sustaining Gains in Health Programs: Technical Efficiency and its Determinants in Malaria Programs in Sub-Saharan Africa. Appl Health Econ Health Policy 15, 249–259 (2017). https://doi.org/10.1007/s40258-016-0294-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40258-016-0294-6

Keywords

  • Malaria
  • Data Envelopment Analysis
  • Malaria Case
  • Efficiency Score
  • Rapid Diagnostic Test