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Use of mortality data in humanitarian response

Use of mortality data in humanitarian response. The case of Sierra Leone Nadine de Lamotte - MSF OCB London Scientific day, 7 June 07. Introduction. Two mortality surveys. Focus on 2 nd survey. Operational response to surveys with specific focus on malaria. Map of Sierra Leone. Guinea.

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Use of mortality data in humanitarian response

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  1. Use of mortality data in humanitarian response The case of Sierra Leone Nadine de Lamotte - MSF OCB London Scientific day, 7 June 07

  2. Introduction • Two mortality surveys. • Focus on 2nd survey. • Operational response to surveys with specific focus on malaria.

  3. Map of Sierra Leone Guinea Freetown Liberia Atlantic ocean

  4. Country background. • War officially over in January 2002. • Sierra Leone “famous”for its poor health indicators (OMS 2006): • MMR: 2,000/100,000 live births. • Under 5 mortality the highest in the world at 282/1000 live births. • Life expectancy at birth: 37 male / 40 women.

  5. Local context: Bo. • Second largest city in Sierra Leone. • Population of the district: 500 000. • Hyper-endemic for malaria. • National malaria protocol changed in 2004 to ASAQ after efficacy studies showed high failure to SP & CQ.

  6. OCB operations in Bo. • MSF in Bo since 1995. • Actual target population: 150 000. • 1 MSF hospital (530 admissions/month). • 1 therapeutic feeding centre (150 admissions/month). • 5 clinics (25 000 consults/month). • Malaria is key morbidity/mortality hence lobbying for country ACT implementation.

  7. 1st mortality survey: April – June 2005 Part of 3-sample access to health care survey to document access barriers in different systems of payment: - Cost recovery in MOH area - Flat fee in MSF H area - Free care in OCB area

  8. Results: death/10.000/day. • Total deaths reported as being due to malaria /fever: 39%. • In < 5 deaths: 62%.

  9. Operational response to survey => Need to do sensitisation of local population on malaria, “show” Paracheck and ACT in the villages, distribute bed nets. • Jan - June 2006: mapping of villages, population data, recruitment & training of outreach teams. Outreach & bed net distribution started in June 06. • Monitoring bed net use: around 80% of the bed nets were seen hanging.

  10. 2nd mortality survey Sept 2006: Reassess mortality following 2005 survey: • Retrospective mortality in catchment area of the clinics. • Causes of death (verbal autopsy). • Health seeking behaviour in those that died.

  11. Methods • Study population: (127 565) 4 chiefdoms Sth Bo. • Sampling method: 3 level cluster; each cluster= 30 children/ families. • Family questionnaire: composition, mortality (recall period 97 days), health seeking behaviour. • Child questionnaire: anthropometric data. • Analysis: EpiInfo, deaths / 10.000 / day.

  12. Results (1) • 907 families included. • Total n = 5179 (<2yrs=8.4%; <5yrs=76%) • 89 deaths (<2yrs=32, 2-5yrs=13, >5yrs=44)

  13. Results (2)Malaria related mortality. • < 2 yrs = 71% (n=23), but recall period covering peak season (39% in June 05). • < 5yrs = 53% (n=7) (62% in June 05). • All malaria deaths = 42% (n=37). • Died at home (all) = 74%. • Died at hospital (all) = 25%.

  14. Limitations • Sampling error: sampling methodology, rainy season means remote villages inaccessible and more malaria (versus 2005 survey). • Measurement error: definition of malaria as fever in survey (over-estimation?). • Recall bias: long period of recollection, lack of maternal deaths (stigma?).

  15. Operational response to 2nd survey: 3 year pilot plan. => Bring ACT closer to population via PHUs: • Identification / mapping of 5 PHUs per clinic, staff training on RDT & ACT use (March 07). • Prospective mortality follow-up through weekly data collection at community level. • Continue sensitisation of population on malaria and health seeking behaviour. • Op research agenda: study ACT efficacy < 2, mortality surveys, baseline study…

  16. Rendez-vous in 3 years…

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