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Famine in the Horn of Africa Over the Last Decade

Famine in the Horn of Africa Over the Last Decade. Paul B Spiegel MD, MPH 1 Peter Salama MBBS, MPH 2 Susan Maloney MD, MPH 1 Albertien van der Veen, MSc 3 1 CDC , 2 UNICEF, 3 WHO. Somalia 1991-92: Background.

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Famine in the Horn of Africa Over the Last Decade

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  1. Famine in the Horn of AfricaOver the Last Decade Paul B Spiegel MD, MPH1 Peter Salama MBBS, MPH2 Susan Maloney MD, MPH1 Albertien van der Veen, MSc3 1 CDC, 2 UNICEF, 3 WHO

  2. Somalia 1991-92: Background • Drought, civil unrest, collapse of government, destroyed infrastructure led to many deaths among Somalis during 1992 • Difficult to provide aid due to insecurity • In absence of health care infrastructure, health status of population described through epidemiological studies which influenced how aid was provided

  3. Somalia 1991-92 : Results • 23 surveys evaluated which had defined pop. and apparent systematic methodology* • Extensive methodological differences • 12 (52%) not reproducible • Units of measurement and denominator estimates inconsistent • 8 of 16 (50%) surveys examining mortality assessed cause of death * Boss, L. P., Toole, M. J., and Yip, R. Assessments of mortality, morbidity, and nutritional status in Somalia during the 1991-1992 famine. Recommendations for standardization of methods. JAMA. 1994: 272(5); 371-6.

  4. Somalia 1991-92: Results cont • 0 of 11 surveys examining morbidity provided case-definitions • Of 16 surveys examining nutritional status, variety of definitions of malnutr. and measurement methods used • 3 (19%) - MUAC only • 10 (63%) - Referenced wt/ht data using % of reference of median • 4 (25%) - Presented data using z-scores

  5. Somalia 1991-92: Recommendations • Define clear study objectives • Use standard sampling and data collection methods • Ensure precise written documentation of objectives, methods, and results

  6. Ethiopia 1999-2000: Background • Ethiopia subject to recurrent drought and food insecurity exacerbated by civil strife • Crises generally involve massive excess mortality and population displacement without formation of discrete camps • Prior to crisis of 1999-2000, eastern and southern regions of Ethiopia subject to 3 successive years of drought

  7. Ethiopia 1999-2000: Background cont • Beginning in 1999, data from early warning systems in many regions of Ethiopia indicated rapidly deteriorating food security and nutrition situation • More than 10 million people estimated to need food assistance during peak of crisis in early 2000

  8. Ethiopia 1999-2000: Mission • Members of IERHB/CDC seconded to UNICEF as Nutrition Technical Advisors June-Sept. 2000 at request of OFDA • Terms of Reference: • Co-ordinate and identify gaps • Provide technical assistance • WHO sent Nutritionist with whom we collaborated closely

  9. Regions of Ethiopia Region

  10. Zone UNDP

  11. WFP Cereal Allocation in April 2002 vs. Requirements by Woreda

  12. <5 Nutrition Surveys in Ethiopia, Jan.-Jun. 2000 Global Acute Malnutrition (GAM) 0-9% 10-19% 20-29% 30-39% 40+% N=38

  13. Ethiopia 1999-2000: Evaluation • Evaluated 125 nutrition surveys from Nov. 1998-Jun. 2000 by 14 different NGOs • RHA*: 16 (13%) • Cluster: 109 (87%) • 42 surveys part of early warning system with different aim and cluster methodology • 67 surveys were “intended” to provide useful data to direct programs • Only 5 surveys (4%) recorded measles vaccination coverage * RHA= rapid health assessments using convenience samples

  14. Evaluation of “Intentional” Surveys • Valid (i.e. representative): • >30 clusters • PPS and • Precise: • >10 children per cluster 1. Binkin N, Sullivan K, Staehling N, Nieburg P. Rapid Nutrition Surveys: How many clusters are enough? Disasters 1995; 16:97-103. 2. Sullivan KM. The effect of sample size on validity and precision in probability proportionate to size cluster surveys, Society of Epidemiologic Research, Utah, 1995

  15. Categorization of Cluster Surveys (N=25) No. of Clusters No. of Children /Cluster

  16. Valid and Precise Cluster Surveys7 of 67 (10.5%) No. of Clusters No. of Children /Cluster

  17. <5 Nutrition Surveys in Ethiopia, Jan.-Jun. 2000 Global Acute Malnutrition (GAM) 0-9% 10-19% 20-29% 30-39% 40+% N=38

  18. <5 Nutrition Surveys in Ethiopia: Jan-Jun 2000 Global Acute Malnutrition (GAM) 0-9% 10-19% 20-29% 30-39% 40+% Valid and Precise: N=2 (5.3%)

  19. USAID Funding for Ethiopia 1999/2000 1999 2000 Development Assistance Food $ 32,264,600 $ 36,200,741 Non-food $ 38,214,000 $ 42,677,000 Total $ 70,478,600 $ 78,877,741 Humanitarian Assistance Food $288,968,022 $ 82,956,723 Non-food $ 11,740,022 $ 1,350,700 Total $300,708,022 $163,185,164 Grand Total $371,186,622 $163,185,164 Source: USAID Ethiopia office 9-01

  20. Problems with Surveys • Methodology • Sample size inadequate (clusters and/or children) • Non-probabilistic sampling • Not proportional to population size • Targeting of drought-affected areas within woreda • Choosing children most malnourished • Always include measles vaccination coverage

  21. Problems with Surveys cont B. Survey Analysis: • Nutrition indicators (ER setting) • Wt/Ht z-scores for children <5yrs • 95% CIs using C-sample in EpiInfo • Ensure include edema as cases of severe malnutr. • Measles Immunization coverage • Report % recorded on imm. card vs. verbal+card

  22. Problems with Surveys cont C. Survey Reporting: • State objectives and detailed methodology • State results clearly with units, including: • Sample size and number of clusters • Number of household refusals or absences • 95% confidence intervals (+/- DEFF) • Interpret results and compare to baseline data or data from previous surveys if available • Make recommendations (underlying causes)

  23. Recommendations Options for NGOs: • ?Make sampling methodology simpler • Improve training manuals • Ensure field staff appropriately trained • Send “HQ staff” to do surveys • Co-ordinate with 1-2 “survey NGOs” in field • Provide survey form templates with programs for data analysis

  24. Recommendations cont Options for policymakers/donors: • Be wary of data/reports provided by NGOs • Have technical persons available (in country vs. contactable elsewhere) to interpret surveys • Field personnel appropriately trained who make decisions based on survey results

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