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Published in: Malaria Journal 1/2017

Open Access 01-12-2017 | Research

Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations

Published in: Malaria Journal | Issue 1/2017

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Abstract

Background

The high burden of malaria and limited funding means there is a necessity to maximize the allocative efficiency of malaria control programmes. Quantitative tools are urgently needed to guide budget allocation decisions.

Methods

A geospatial epidemic model was coupled with costing data and an optimization algorithm to estimate the optimal allocation of budgeted and projected funds across all malaria intervention approaches. Interventions included long-lasting insecticide-treated nets (LLINs), indoor residual spraying (IRS), intermittent presumptive treatment during pregnancy (IPTp), seasonal mass chemoprevention in children (SMC), larval source management (LSM), mass drug administration (MDA), and behavioural change communication (BCC). The model was applied to six geopolitical regions of Nigeria in isolation and also the nation as a whole to minimize incidence and malaria-attributable mortality.

Results

Allocative efficiency gains could avert approximately 84,000 deaths or 15.7 million cases of malaria in Nigeria over 5 years. With an additional US$300 million available, approximately 134,000 deaths or 37.3 million cases of malaria could be prevented over 5 years. Priority funding should go to LLINs, IPTp and BCC programmes, and SMC should be expanded in seasonal areas. To minimize mortality, treatment expansion is critical and prioritized over some LLIN funding, while to minimize incidence, LLIN funding remained a priority. For areas with lower rainfall, LSM is prioritized over IRS but MDA is not recommended unless all other programmes are established.

Conclusions

Substantial reductions in malaria morbidity and mortality can be made by optimal targeting of investments to the right malaria interventions in the right areas.
Appendix
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Literature
3.
go back to reference Gamble C, Ekwaru PJ, Garner P, Ter Kuile FO. Insecticide-treated nets for the prevention of malaria in pregnancy: a systematic review of randomised controlled trials. PLoS Med. 2007;4:e107.CrossRefPubMedPubMedCentral Gamble C, Ekwaru PJ, Garner P, Ter Kuile FO. Insecticide-treated nets for the prevention of malaria in pregnancy: a systematic review of randomised controlled trials. PLoS Med. 2007;4:e107.CrossRefPubMedPubMedCentral
4.
go back to reference Pluess B, Tanser FC, Lengeler C, Sharp BL. Indoor residual spraying for preventing malaria. Cochrane Database Syst Rev. 2010;4:CD006657. Pluess B, Tanser FC, Lengeler C, Sharp BL. Indoor residual spraying for preventing malaria. Cochrane Database Syst Rev. 2010;4:CD006657.
5.
go back to reference Tusting LS, Thwing J, Sinclair D, Fillinger U, Gimnig J, Bonner KE, et al. Mosquito larval source management for controlling malaria. Cochrane Database Syst Rev. 2013;8:CD008923.PubMedCentral Tusting LS, Thwing J, Sinclair D, Fillinger U, Gimnig J, Bonner KE, et al. Mosquito larval source management for controlling malaria. Cochrane Database Syst Rev. 2013;8:CD008923.PubMedCentral
6.
go back to reference Meremikwu MM, Donegan S, Sinclair D, Esu E, Oringanje C. Intermittent preventive treatment for malaria in children living in areas with seasonal transmission. Cochrane Database Syst Rev. 2012;2:CD003756. Meremikwu MM, Donegan S, Sinclair D, Esu E, Oringanje C. Intermittent preventive treatment for malaria in children living in areas with seasonal transmission. Cochrane Database Syst Rev. 2012;2:CD003756.
7.
go back to reference Wilson AL. A systematic review and meta-analysis of the efficacy and safety of intermittent preventive treatment of malaria in children (IPTc). PLoS ONE. 2011;6:e16976.CrossRefPubMedPubMedCentral Wilson AL. A systematic review and meta-analysis of the efficacy and safety of intermittent preventive treatment of malaria in children (IPTc). PLoS ONE. 2011;6:e16976.CrossRefPubMedPubMedCentral
8.
go back to reference Walker PG, Griffin JT, Ferguson NM, Ghani AC. Estimating the most efficient allocation of interventions to achieve reductions in Plasmodium falciparum malaria burden and transmission in Africa: a modelling study. Lancet Glob Health. 2016;4:e474–84.CrossRefPubMed Walker PG, Griffin JT, Ferguson NM, Ghani AC. Estimating the most efficient allocation of interventions to achieve reductions in Plasmodium falciparum malaria burden and transmission in Africa: a modelling study. Lancet Glob Health. 2016;4:e474–84.CrossRefPubMed
10.
go back to reference Hamilton M, Mahiane G, Werst E, Sanders R, Briët O, Smith T, et al. Spectrum-malaria: a user-friendly projection tool for health impact assessment and strategic planning by malaria control programmes in sub-Saharan Africa. Malar J. 2017;16:68.CrossRefPubMedPubMedCentral Hamilton M, Mahiane G, Werst E, Sanders R, Briët O, Smith T, et al. Spectrum-malaria: a user-friendly projection tool for health impact assessment and strategic planning by malaria control programmes in sub-Saharan Africa. Malar J. 2017;16:68.CrossRefPubMedPubMedCentral
11.
go back to reference Kerr CC, Stuart RM, Gray RT, Shattock AJ, Fraser-Hurt N, Benedikt C, et al. Optima: a model for HIV epidemic analysis, program prioritization, and resource optimization. J Acquir Immune Defic Syndr. 2015;69:365–76.CrossRefPubMed Kerr CC, Stuart RM, Gray RT, Shattock AJ, Fraser-Hurt N, Benedikt C, et al. Optima: a model for HIV epidemic analysis, program prioritization, and resource optimization. J Acquir Immune Defic Syndr. 2015;69:365–76.CrossRefPubMed
12.
go back to reference Fraser N, Kerr CC, Harouna Z, Alhousseini Z, Cheikh N, Gray R, et al. Reorienting the HIV response in Niger toward sex work interventions: from better evidence to targeted and expanded practice. J Acquir Immune Defic Syndr. 2015;8(Suppl 2):S213–20.CrossRef Fraser N, Kerr CC, Harouna Z, Alhousseini Z, Cheikh N, Gray R, et al. Reorienting the HIV response in Niger toward sex work interventions: from better evidence to targeted and expanded practice. J Acquir Immune Defic Syndr. 2015;8(Suppl 2):S213–20.CrossRef
13.
go back to reference World Bank. Optimizing HIV investments in Armenia. 2015. World Bank. Optimizing HIV investments in Armenia. 2015.
14.
go back to reference Grantham K, Reagan D, Law M, Wilson DP. Optimizing investments in the national HIV responses of Indonesia and Thailand. Report, World Health Organization, South-east Asia Regional Office. 2016. Grantham K, Reagan D, Law M, Wilson DP. Optimizing investments in the national HIV responses of Indonesia and Thailand. Report, World Health Organization, South-east Asia Regional Office. 2016.
15.
go back to reference Kelly S, Shattock A, Kerr CC, Gama T, Nhlabatsi N, Zagatti G, et al. HIV mathematical modelling to support Swaziland’s development of its HIV investment case. Washington: World Bank; 2014. Kelly S, Shattock A, Kerr CC, Gama T, Nhlabatsi N, Zagatti G, et al. HIV mathematical modelling to support Swaziland’s development of its HIV investment case. Washington: World Bank; 2014.
16.
go back to reference Masaki E, Fraser N, Haacker M, Obst M, Wootton R, Sunkutu R, et al. Zambia’s HIV response: prioritised and strategic allocation of HIV resources for impact and sustainability. Washington: World Bank; 2015. Masaki E, Fraser N, Haacker M, Obst M, Wootton R, Sunkutu R, et al. Zambia’s HIV response: prioritised and strategic allocation of HIV resources for impact and sustainability. Washington: World Bank; 2015.
19.
go back to reference National Malaria Elimination Programme (NMEP), National Population Commission (NPopC), National Bureau of Statistics (NBS), ICF International: Nigeria malaria indicator survey 2015: key indicators. Abuja and Rockville: NMEP, NPopC, and ICF International; 2016. https://dhsprogram.com/pubs/pdf/MIS20/MIS20.pdf. Accessed 11 Sept 2017. National Malaria Elimination Programme (NMEP), National Population Commission (NPopC), National Bureau of Statistics (NBS), ICF International: Nigeria malaria indicator survey 2015: key indicators. Abuja and Rockville: NMEP, NPopC, and ICF International; 2016. https://​dhsprogram.​com/​pubs/​pdf/​MIS20/​MIS20.​pdf. Accessed 11 Sept 2017.
23.
go back to reference National Malaria Elimination Programme (NMEP), Federal Ministry of Health (FMOH). End of project malaria household survey in nine states of Nigeria. 2015. National Malaria Elimination Programme (NMEP), Federal Ministry of Health (FMOH). End of project malaria household survey in nine states of Nigeria. 2015.
27.
28.
go back to reference Aron JL. Mathematical modelling of immunity to malaria. Math Biosci. 1988;90:385–96.CrossRef Aron JL. Mathematical modelling of immunity to malaria. Math Biosci. 1988;90:385–96.CrossRef
29.
go back to reference Labadin J, Kon C, Juan S. Deterministic malaria transmission model with acquired immunity. In: Proceedings of the world congress on engineering and computer science, vol II WCECS 2009, October 20–22, 2009, San Francisco, USA: 2009. P. 779–784. Labadin J, Kon C, Juan S. Deterministic malaria transmission model with acquired immunity. In: Proceedings of the world congress on engineering and computer science, vol II WCECS 2009, October 20–22, 2009, San Francisco, USA: 2009. P. 779–784.
31.
go back to reference Silal SP, Little F, Barnes KI, White LJ. Hitting a moving target: a model for malaria elimination in the presence of population movement. PLoS ONE. 2015;10:e0144990.CrossRefPubMedPubMedCentral Silal SP, Little F, Barnes KI, White LJ. Hitting a moving target: a model for malaria elimination in the presence of population movement. PLoS ONE. 2015;10:e0144990.CrossRefPubMedPubMedCentral
32.
go back to reference Laneri K, Paul RE, Tall A, Faye J, Diene-Sarr F, Sokhna C, et al. Dynamical malaria models reveal how immunity buffers effect of climate variability. Proc Natl Acad Sci USA. 2015;112:8786–91.CrossRefPubMedPubMedCentral Laneri K, Paul RE, Tall A, Faye J, Diene-Sarr F, Sokhna C, et al. Dynamical malaria models reveal how immunity buffers effect of climate variability. Proc Natl Acad Sci USA. 2015;112:8786–91.CrossRefPubMedPubMedCentral
33.
go back to reference Filipe JA, Riley EM, Drakeley CJ, Sutherland CJ, Ghani AC. Determination of the processes driving the acquisition of immunity to malaria using a mathematical transmission model. PLoS Comput Biol. 2007;3:e255.CrossRefPubMedPubMedCentral Filipe JA, Riley EM, Drakeley CJ, Sutherland CJ, Ghani AC. Determination of the processes driving the acquisition of immunity to malaria using a mathematical transmission model. PLoS Comput Biol. 2007;3:e255.CrossRefPubMedPubMedCentral
35.
go back to reference Lengeler C. Insecticide-treated bed nets and curtains for preventing malaria. Cochrane Database Syst Rev. 2004;2:CD000363. Lengeler C. Insecticide-treated bed nets and curtains for preventing malaria. Cochrane Database Syst Rev. 2004;2:CD000363.
36.
go back to reference National Population Commission (NCP), National Malaria Control Programme (NMCP), International. I: Nigeria Malaria Indicator Survey 2010, Final Report. Abuja: NPC, NMCP, and ICF International 2012. National Population Commission (NCP), National Malaria Control Programme (NMCP), International. I: Nigeria Malaria Indicator Survey 2010, Final Report. Abuja: NPC, NMCP, and ICF International 2012.
37.
go back to reference Kerr C, Smolinski T, Dura-Bernal S, Wilson D. Optimization by Bayesian adaptive locally linear stochastic descent. Nature Scientific Reports under review. Kerr C, Smolinski T, Dura-Bernal S, Wilson D. Optimization by Bayesian adaptive locally linear stochastic descent. Nature Scientific Reports under review.
38.
go back to reference Kanario A. Adherence to intermittent preventive treatment for malaria with sulphadoxine–pyrimethamine and outcome of pregnancy among parturients in South East Nigeria. Patient Prefer Adherence. 2014;8:447–52. Kanario A. Adherence to intermittent preventive treatment for malaria with sulphadoxine–pyrimethamine and outcome of pregnancy among parturients in South East Nigeria. Patient Prefer Adherence. 2014;8:447–52.
39.
go back to reference Tesfazghi K, Hill J, Jones C, Ranson H, Worrall E. National malaria vector control policy: an analysis of the decision to scale-up larviciding in Nigeria. Health Policy Plan. 2015;31:91–101.CrossRefPubMedPubMedCentral Tesfazghi K, Hill J, Jones C, Ranson H, Worrall E. National malaria vector control policy: an analysis of the decision to scale-up larviciding in Nigeria. Health Policy Plan. 2015;31:91–101.CrossRefPubMedPubMedCentral
40.
go back to reference Aron JL, May RM. The population dynamics of malaria. In: Andersin RM, editor. The population dynamics of infectious diseases: theory and applications. Boston, MA: Springer; 1982. p. 139–79.CrossRef Aron JL, May RM. The population dynamics of malaria. In: Andersin RM, editor. The population dynamics of infectious diseases: theory and applications. Boston, MA: Springer; 1982. p. 139–79.CrossRef
41.
go back to reference Chitnis N, Cushing J, Hyman J. Bifurcation analysis of a mathematical model for malaria transmission. SIAM J Appl Math. 2006;67:24–45.CrossRef Chitnis N, Cushing J, Hyman J. Bifurcation analysis of a mathematical model for malaria transmission. SIAM J Appl Math. 2006;67:24–45.CrossRef
42.
go back to reference Tumwiine J, Mugisha J, Luboobi L. A mathematical model for the dynamics of malaria in a human host and mosquito vector with temporary immunity. Appl Math Comput. 2007;189:1953–65. Tumwiine J, Mugisha J, Luboobi L. A mathematical model for the dynamics of malaria in a human host and mosquito vector with temporary immunity. Appl Math Comput. 2007;189:1953–65.
43.
go back to reference Maire N, Smith T, Ross A, Owusu-Agyei S, Dietz K, Molineaux L. A model for natural immunity to asexual blood stages of Plasmodium falciparum malaria in endemic areas. Am J Trop Med Hyg. 2006;75(2 suppl):19–31.CrossRefPubMed Maire N, Smith T, Ross A, Owusu-Agyei S, Dietz K, Molineaux L. A model for natural immunity to asexual blood stages of Plasmodium falciparum malaria in endemic areas. Am J Trop Med Hyg. 2006;75(2 suppl):19–31.CrossRefPubMed
Metadata
Title
Maximizing the impact of malaria funding through allocative efficiency: using the right interventions in the right locations
Publication date
01-12-2017
Published in
Malaria Journal / Issue 1/2017
Electronic ISSN: 1475-2875
DOI
https://doi.org/10.1186/s12936-017-2019-1

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