High burden to high impact: a targeted malaria response Malaria Policy Advisory Committee (MPAC) October 2018, Geneva
Malaria in numbers 445 000 216m 12b 60 90 2 47 6.5b 10+1
The problem Rising number of malaria cases 260 251 252 246 250 243 241 239 237 239 238 237 240 230 230 225 Million cases 217 216 220 210 210 211 210 200 190 180 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Initial focus: high burden African countries Additional cases between 2015 and 2016 0 200 000 400 000 600 000 800 000 1 000 000 0 20000 40000 60000 80000 100000 Nigeria DR Congo India Niger Mali UR Tanzania Mozambique Burkina Faso Ghana Uganda Cameroon
An urgent and credible response Four key mutually reinforcing response elements Best global Political guidance commitment Impact Coordinated Strategic response use of information
More impact by improving value for money Economy Efficiency Effectiveness Resources Inputs Outputs Outcome Impact Cost effectiveness Equity
Theory of change Delivery of Socio- Finances and HRH and Reduced malaria optimal mix of economic political capital commodities mortality interventions development Political Commitment Health governance and financing 1 2
Translating political will into domestic funding Million US$ 0 50M 100M 150M 200M 250M 300M 350M 0 50,000,000 100,000,000 150,000,000 200,000,000 250,000,000 300,000,000 350,000,000 Nigeria DR Congo DRC Mozambique Ghana Mali Burkina Faso Government Funding Niger External Funding Uganda Tanzania Cameroon India
Improving budget execution Achieving efficiency through better health governance Realized expenditure Unspent budget 100 90 80 Percentage 70 60 50 40
Improving the health delivery system UHC Physicians Hospital beds Country SCI per 1000 population per 10 000 population Burkina Faso 39 Less than 0.05 4 Cameroon 44 0.1 13 DR Congo 40 0.1 8 Ghana 45 0.1 9 Mali 32 0.1 1 Mozambique 42 0.1 7 Niger 33 0.05 2.8 Nigeria 39 0.4 5 Uganda 44 0.1 5 Tanzania 39 Less than 0.05 7 India 56 0.7 6.6 Greece (for reference) 70 6.3 42.5
Improving efficiencies By truly aligning behind an evidence based approach
Theory of change Delivery of Socio- Finances and HRH and Reduced malaria optimal mix of economic political capital commodities mortality interventions development Political Commitment Health governance and financing Market shaping Strategic use of local information 1 2 3 4
10+1 response elements Galvanize national and global political attention to reduce 1 malaria deaths 2 Drive impact in country through strategic use of information Establish best global guidance, policies and strategies suitable 3 for the broad range of contexts 4 A coordinated country response
Estimation of funding need and gap RBM funding gap analysis 2.50 NSP period Funding gap 2018-2020 DRC 2016-2020 2.00 Funding available 2018-2020 Ghana 2014-2020 Nigeria 2014-2020 1.50 Uganda 2015-2020 Mozambique 2017-2022 Billions (US$) 1.00 0.50 0.00
Estimation of funding need and gap 350.0 288.1 300.0 US$ per case averted based estimated need 250.0 200.0 177.3 150.0 124.4 82.5 100.0 70.7 50.0 0.0 DRC Ghana Mozambique Nigeria Uganda Are the differences due to varying efficiencies or poor costing?
Equity – data from a high burden country 100 90 80 Access to ITNs: percentage 70 Percentage of people with enough 60 50 ITNs in their households 40 30 20 10 0 Most poor Least poor 100 2x more children under the age 90 80 of five years die in poorest 70 Percentage households compared to the 60 wealthiest!! 50 40 30 20 10 0 None or primary education Secondary or higher education
Equity – data from a high burden country 100 90 80 Treatment seeking for fevers 70 Percentage in children under the age of 60 50 five years 40 30 20 10 0 Most poor Least poor 100 2x more children under the age 90 of five years die in poorest 80 70 Percentage households compared to the 60 wealthiest!! 50 40 30 20 10 0 None or primary education Secondary or higher education
Efficiency – data from a high burden country 100 Access to ITNs: Percentage 80 of people with enough Percentage 60 ITNs in their households 40 20 0 Urban Rural 57 million 54% 44 million 29 million Population 2017 LLINs distributed Number of nets Population access 2015-2017 required for to LLINs in 2017 universal coverage in 2017
Stratification – metric and geography DRC Uganda Nigeria
Use of strategic information – LLIN targeting in Kenya, 2010 A) A 3D population map showing areas where Pf PR 2-10 was <1% (pink) and >1% (dark red) B) Map showing percentage ITN use from low C) Population that need LLINs in areas to be targeted based on a criteria of >1% Pf PR 2-10 and >1 person per square km (green) and those additional who will need LLIN if the whole country was targeted (pink) From 16 to 6 million nets, or US$ 55 million difference in costs of LLLINs at the time
Use of strategic information – Tanzania, 2008 NSP 2008-2013 LLINs everywhere! MARA climate suitability map
Use of strategic information – Tanzania, 2018 Reduction in prevalence until 2019, CM and LARV not enough to reduce prevalence but enough to maintain low prevalence until 2020. In practice ITN distribution might need to be considered in specific areas. Reduction in prevalence until 2019, CM and LSM not enough to reduce prevalence and ITN continuous needs to be considered Annual ITNs maintaining coverage of 70% with increase in CM to 85% reduces the Prevalence % trend by stratum prevalence in moderate strata by xx% High reduction in prevalence in high strata with CM, ITNs, IRS (LAKE) IPTsc might add additional impact With CM and LARV only prevalence is increasing in this stratum ITN distribution need to follow epidemiological strata to achieve decrease in all urban districts
What is new in the analysis approach? Current Monitoring Country NSP development, adoption and action National and status • Re-stratification (usually province and Strategic Evaluation review occasionally district) Plan • Update vision, mission, objectives and goals (e.g. MIS, (e.g. MTR, • Building the right data platforms and databases programme MPR, impact (Vision, • Strategic intervention approaches data, routine evaluations mission, goals, • HIS data etc.) etc.) Performance framework objectives, • Better stratification with improved spatial resolution interventions, • Action plan action plan, • Resource mobilization (funding need and gap) cost, funds) • Optimized intervention mixes guided by a robust analysis • Implementation of anticipated impact • • • Low data Low quality reviews No clear approach to stratification and intervention coverage (space mixes • Better tools to cost funding need and gap more precisely • and time) Largely qualitative • Selection of interventions not determined by • • Poor data quality No clear pathway of knowledge of likely impact • Better measurement of progress, including improved MPRs action based on • • Weak capacity recommendations Performance framework underpinned by weak data for data analysis systems and impact evaluations • Does not cover • • Adhoc use of adequately the Action plan not always subnational and often is top data relevant health down and malariacentric • It is not about perfection, but improving things! system areas • • Poor tracking of Approaches to estimating funding need and gap is • programmatic Mostly top down inconsistent and imprecise activities and nor based on subnational reviews
Strategic use of information – purpose and process 1 Reviewing current status situation analysis – national, province and district (or equivalent) 4 2 Measuring Planning progress and impact of more efficient and revised strategic targeted future (subnational (district) approach through level stratification and routine, national, district routine mix of intervention) surveillance and surveys 3 Operationalizing through subnational (district) operational plans, village level action
NMCP leadership, a collective partnership resource Environment Technical Implementation Funding MoH HMIS Advocacy MoH/NMCP MoH HSD Research MoH Policy Meteorology Community Other sectors
Process Country and partnership dialogue Desk review Data Stratification NSP revision, assembly & & intervention costing & analysis mixes reprioritization Analysis partnership National and subnational data and M&E platforms
Activities • Partnership and NMCP dialogues advanced • 5 Phase 1 countries identified (Nigeria, DRC, Mozambique, Tanzania, Uganda) • Desk review started • Analysis framework document and tools in development • Subnational operational planning guidance • Subnational of new geospatial data assemblies
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