M&E IN CHANGING EPIDEMIOLOGIC SETTINGS
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1) The document discusses monitoring and evaluation strategies for malaria as the epidemiological landscape changes. It outlines how M&E has evolved from an initial focus on intervention coverage and mortality to now address subnational heterogeneity, measuring quality of care, and surveillance methods. 2) Current challenges include measuring impact at subnational levels, incorporating private and community providers, and accurately detecting cases as transmission declines. New approaches stratify interventions and sampling based on local transmission patterns. 3) Going forward, as malaria control improves, the focus will shift from mortality measurement to morbidity indicators and tracking elimination. Improved surveillance, health information systems, and novel tools are needed to monitor progress towards elimination goals.
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M&E IN CHANGING EPIDEMIOLOGIC SETTINGS
- 1. 1 M&E IN CHANGING EPIDEMIOLOGIC SETTINGS 6th MIM Conference – Durban, South Africa Erin Eckert, MPH, PhD October 10, 2013
- 2. 2 Outline • Background: M&E from the launch RBM to present • Monitoring our progress and impact • Current M&E strategies • Emerging challenges • Subnational heterogeneity • Measuring the quality of case management • New approaches to epidemiologic monitoring methods • Future directions for elimination
- 3. 3 Global reporting needs • • • • • RBM launched 1998 Abuja Declaration April 2000, revisions 2005 MDGs Global Fund Launch of PMI 2005 • Standardized indicators • Data collection tools: DHS, MICS, MIS • M&E Guidance MERG
- 4. 4 Monitoring Progress: the PMI approach • Monitor scale up through national household surveys; • Track commodities, and provider behaviours through rapid facility assessments; • Monitor epidemiological trends through surveillance and HMIS • Ensure drug efficacy through therapeutic efficacy surveillance • Track vector behaviour and insecticide susceptibility through entomological monitoring
- 5. 5 Where Are We Now: ITN Ownership
- 6. 6 Where Are We Now: Measuring Morbidity Percent prevalence parasitemia 50 Parasitemia Prevalence in PMI Countries With Two or More Measurements 45 40 35 30 28 28 25 20 15 16 13 8 10 5 0 4 3 1 0.5
- 7. Where Are We Now: Measuring Mortality
- 8. 8 Household ITN Ownership and Use, Rwanda, 2000 -2010 ITN Ownership ITN Use %Households owning at least one ITN or persons sleeping under an ITN 100 80 60 2000 2005 72 2007/8 60 2010 82 40 70 57 56 20 15 4 13 4 17 0 Household ownership Children under-five Pregnant women
- 9. 9 All-cause Under-five and Infant Mortality* Rwanda, 1998-2008 250 Deaths per 1,000 live births 196 200 152 150 107 100 Under-five mortality Infant mortality 103 86 76 62 50 50 0 *Mortality is shown at the midpoint of the five-year period.
- 10. 10 Results from Impact Evaluations to Date Country Tanzania Malawi Angola U5 Mortality Decline Malaria Intervention Coverage Increase 45% √ 41% 21% Decline in Malaria Morbidity Do contextual factors explain all mortality decline? Plausible Impact Anemia No √ √ Anemia Parasitemia No √ √ (still low) Parasitemia Likely Subnational No √ Rwanda 61% √ Anemia Parasitemia Malaria Incidence Ethiopia 47% √ Epidemics Malaria Deaths No √ √ Anemia Parasitemia Malaria Incidence No √ Zanzibar 34%* *Overlapping confidence intervals
- 11. 11 Changing Landscape Epidemiological landscape • Malaria burden decreased: foci now in subnational regions and target populations • Cross-border hot-spots between higher and lower burden countries e.g. Angola/Namibia; Rwanda/DRC Programmatic landscape • More emphasis on diagnosis and appropriate treatment • Increased interventions at the community level • Greater involvement of the private sector • Novel control methods e.g. SMC, Screen and treat approaches, school-based interventions etc.
- 12. 12 Subnational Heterogeneity: Tanzania Malaria Prevalence 2007/8 Tanzania HIV/AIDS and Malaria Indicator Survey, 2007-08 and 2011-12 20011/12
- 13. Millions of treatments/tests ACT and RDT Procurements by PMI 2006-2014 90 80 70 60 50 40 30 20 10 2006 2007 2008 2009 RDTs 2010 ACTs 2011 2012 2014 (est)
- 14. Source of antimalarials: public vs. private Source: ACTWatch Group. 2013
- 15. 15 Evolving Questions • At the beginning • What is intervention coverage? • What is national parasitemia estimate? • What is the trend for all-cause child mortality? • Now • How do we target our interventions? – Where, Who, When, What • What is the quality of diagnosis and treatment at facilities? • How to incorporate community and private sector activities? • How do we accurately detect & report malaria cases (burden)? – Different levels and areas of transmission, changing at-risk population, routine (HMIS) vs surveillance • How do we inform cross-border malaria control efforts?
- 16. 16 Stratifying interventions and M&E N W E S ITN and IPTp intervention districts Malaria Cases Malaria cases 0-3 4 - 12 13 - 39 40 - 67 68 - 195 Zimbabwe 2013
- 17. 17 Subnational sampling strategies Zimbabwe Indicator 2010 DHS 2012 MIS* Proportion of households with one or more ITNs 29% 46% Proportion of children under five years old who slept under an ITN the previous night 10% 50% Proportion of pregnant women who slept under an ITN the previous night 10% NA** Proportion of women who received two or more doses of IPTp during their last pregnancy in the last two years 7% 35% Proportion of children under five years old with fever in the last two weeks who received treatment with ACTs 2% NA 2012 MIS was conducted only in malaria endemic districts
- 18. 18 Health Facility Surveys Improved Health Facility Surveys • Reflects overall health system capacity • Monitor availability commodities, trained staff (service readiness) • Monitor quality of care for diagnostics and treatment • Track interventions across disease areas (OPD, ANC, laboratory, etc.) Caveat: How to incorporate private sector and community-based care
- 19. 19 Senegal Continuous Survey Household Survey Sub-sample repeated yearly Health Facility Survey Sub-sample repeated yearly 2012 2013-2016 Complete national sample for Household Survey and Health Facility Survey after 5 years. 2017
- 20. ACT Stocks- PMI End Use Verification Survey Percentage of facilities with any presentation of ACT in stock Country Percentage Date of Survey Angola 85 December 2012 DRC* 78 March 2013 Ethiopia 95 August 2013 Ghana 80 June 2013 Guinea 68 December 2012 Kenya 85 November 2012 Liberia* 94 June 2013 Malawi 98 June 2013 Mali 87 June 2013 Mozambique 75 April 2013 Nigeria^ 98 June 2013 Tanzania 87 May 2013 Zambia 100 June 2013 Zimbabwe 97 July 2013 *denotes countries using AS+AQ, percentage shows facilities with stock for children <5 ^Stock information from PMI supported states in Nigeria
- 21. 21 Surveillance and HMIS Routine data needs • Increased need for • • • • timely, longitudinal data Geographic representivity Assist with risk stratification Data for use by program managers at subnational level Epidemic detection and response Ethiopia Epidemic Detection 2010
- 22. 22 Enhanced HMIS Data: 10 districts in Mali, 2013 80% 100% 60% 75% 40% 50% 20% 25% 0% Oct-12 0% Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 % of malaria suspected cases / Total consultation all ages % of facilities reporting 100% 100% 80% 80% 60% 60% 40% 40% 20% 20% 0% 0% Oct-12 Nov-12 Dec-12 Jan-13 Feb-13 Mar-13 % of suspect cases tested (children under 5 years) Nov-11 Dec-11 Jan-12 Feb-12 Mar-12 Apr-12 % of positive cases / total tested (children…
- 23. 23 Going Forward: Impact Measurement Improvements in Malaria Control • Improved diagnosis and treatment • Better health facility data collection • Improved management at community level, including referral • Vector control at scale Transmission reduction Shift in measurement of impact from mortality measurement to morbidity
- 24. 24 All-cause Under-five and Infant Mortality Ethiopia, 2000-2011 Deaths per 1,000 live births 200 180 166 160 140 123 120 97 88 100 77 80 60 59 Under-five mortality Infant mortality 40 20 0 *Mortality is shown at the midpoint of the five-year period.
- 25. 25 • In 1958—3 million cases, 150,000 deaths • In 1998—33% of malarious districts • In 2003—33% of malarious districts, 70,000 deaths 4000 50,000 45,000 3500 40,000 3000 35,000 2500 30,000 2000 25,000 20,000 1500 15,000 1000 10,000 500 5,000 0 Outbreak villages 0 Deaths all ages Deaths under-five Number of malaria deaths • Malaria outbreaks in: 1953, 1958, 1965, 1973, 1981, 1988, 1991, 1998, 2003 Number of villages experiencing outbreaks Malaria Outbreaks & Deaths in Ethiopia, 2001-2012
- 26. 26 Towards elimination • New interventions require new monitoring tools (i.e. mass drug administration, vaccines) • Improvements in tracking transmission dynamics • Improved detection of asymptomatic infections • Novel analytic techniques including PCR Saudi Arabia from C Cotter et al, Lancet 2013
- 27. 27 THANK YOU!
Editor's Notes
- Discuss 2005 targets, 2010 targets, universal coverageGoal of halving malaria burden…Commitment of resources necessitates tracking of progressX number of countries have surveys in how many roundsLittle coordinated effort on national M&E prior to RBM. Every country had its own systems, loosely following WHO guidelines. Coverage data not systematically collected.When RBM launched, called for systematic monitoring of intervention coverage. Targets set for Abuja Summit. MERG established. USAID funds development of malaria module for DHS/MICS, stand-alone MIS survey tool.
- PMI is the major supporter to household surveys collecting data on key indicators for the key interventions. Implementation of surveys/data collection activities (increase data, fill in gaps, etc.) We are the major collectors of monitoring data globally.We verify that our commodities are reaching health facilities through the EUVWe monitor appropriate diagnosis and treatment through various surveillance models.
- We have also been able to monitor our impact on morbidity (parasitemia) and track progress in the reduction of ACCM.The point is that we are tracking our impact indicators across countries and time. We recognize the caveats with both these indicators and are exploring what the data are telling through our IE activities (to be presented next)
- Source: DHS surveysIn the interest of time we are only showing ITN ownership and use, but several other malaria interventions showed increases coverage over this period.IPTp: <1% in 2005 to 17% in 2007/8, before being discontinued.IRS scaled up in select high burden districts.ACTs rolled out starting in 2006. Used by CHWs. This was followed by an RDT roll out. Since 2009 RDTs have been used by CHWs. Based on HMIS data, diagnosis prior to treatment with an antimalarial increased from 49% in 2008 to 94% in 2010. [Can link to Case Management presentation if the 94% is shown].
- DHS data: 2000, 2005, 2007/8 and 2010 survey estimates plotted at the midpoint of the period. 61% decline in ACCM.Greatest decline in mortality was in the high malaria risk areas (data not shown).
- Tanzania U5MR: 1999-2010 surveys [148/1000 in 1999 to 81/1000 in 2010]Malawi U5MR: 2000-2010 surveys [189/1000 during 1996-2000 period to 112/1000 during 2006-2010]Angola U5MR: 2003-5 vs. 2009-11, based on 2011 survey [117/1000 during 2003-5 to 92/1000 during 2009-11]Rwanda U5MR: 2000-2010 surveys [196/1,000 in 2000 to 76/1,000 in 2010]Ethiopia U5MR: 2000-2011 surveys [166/1000 in 2000 to 88/1000 in 2011]Zanzibar U5MR:Only the Zanzibar values have overlapping confidence intervals, which is due to small sample sizes from the surveys.
- Now, with the successful scale-up of interventions and declining burden, we are facing an epidemiological shift in malaria transmission – with countries all in different phases of malaria control.Our M&E approaches will need to evolve to measure progress and impact in this context, while at the same time developing and testing new tools to meet emerging needs.
- TanzaniaSuccessful control efforts Differing geography and climate lead to varied levels of prevalenceShares borders with countries still in the scale-up phases
- Demonstrates the scale up of ACT and RDT in recent years, requiring better monitoring of availability of commodities, as well as case management in general
- We had 2 key questions early on (coverage and morbidity/mortality). In the face of changing transmission and epidemiology, many more priority question. The other technical areas are looking at and discussing these issues so now M&E needs to provide the tools to measure the changing intervention strategies.
- The Senegal Continuous Survey collects data from both health facilities and at the household level. Conducted in rounds with smaller samples every 5 years to a) provide yearly representative data on key indicators AND b) allow complete coverage of all health facilities and more comprehensive population sample over 5 year period.
- PMI’s EUV tool allows rapid tracking of commodities at the facility level – most PMI countries conduct on a yearly basis – some nationally, some subnationally.
- Mortality is nationwide, not restricted by urban/rural or altitude. Source: 2000, 2005, 2011 DHS data plotted at the midpoint of the survey period. This clearly is not appropriate going forward in a country where malaria is as stratified as Ethiopia.
- Preliminary data: Outbreaks are based on thresholds. The number of villages (kebeles) with outbreaks has declined as has the number of malaria deaths. Data in the Health and Health Related Indicator reports are from July-June. So the 2010 data refers to July 2009-June 2010, etc. For simplicity only one year is given, instead of the range. 2003 epidemic affected 211 districts and the 2012 only affected 12 districts. Historic epidemic in 1958, 10million at risk, 3million cases of malaria (30% attack rate), 150,000 deaths. This epidemic was nationwide, P.f. mostly. There was an outbreak in 1998 associated with CQ resistance. The 2003 epidemic started in July 2013 and lasted until early 2014. Saw a 6X increase in cases and was associated with reduced SP efficacy. In 2011, in the PMI sentinel sites in one health center we saw a 3X increase in cases (~50:50 Pf:Pv). In November 2012 there was an outbreak in Amhara (Trying to get this on the graph). There were 700 hospitalizations, but only 4 deaths. 80:20 Pf:Pv. We are working on generating a better graph to depict this trend in epidemics.