trends in community fever and hf diagnoses in the ifakara
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Trends in community fever and HF diagnoses in the Ifakara DSS Sandra Alba, Manuel Hetzel, Angel Dillip, Iddy Mayumana, Christian Lengeler, Mathew Alexander, Rose Nathan, Brigit Obrist, Alexander Schulze, Flora Kessy, Hassan Mshinda Background :


  1. Trends in community fever and HF diagnoses in the Ifakara DSS Sandra Alba, Manuel Hetzel, Angel Dillip, Iddy Mayumana, Christian Lengeler, Mathew Alexander, Rose Nathan, Brigit Obrist, Alexander Schulze, Flora Kessy, Hassan Mshinda

  2. Background : The ACCESS Programme To understand and improve access to effective malaria treatment and care for all malaria episodes in children and adults. Partners: • Ifakara Health Institute (Ifakara site) • • Swiss Tropical Institute Swiss Tropical Institute • Novartis Foundation for Sustainable Development ACCESS I ACCESS II 2004-2008 2008-2011

  3. Background: Project area Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS (Rural) Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS (Town) Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero District District District District District District District District District ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) Tanzania ) ) ) ) ) ) ) ) ) ) ) ) ) ) K K i i i l l l o o o m m m b b b b b e e e e e r r r r r o o o o o o K K K K K i i i i l l l l o o o o o o m m m m m m b b b b e e e e r r r r o o o K K i i l l D D D i i i s s s t t t t t t r r r r r r i i i i i i c c c c c c t t t t t t D D D D D D D D D D D D i i i i i i i i s s i s s s s s s s t t t t t t r r r r r r i i i i i i c c c c c c t t t t t t Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga District District District District District District District District District 0 0 0 0 0 0 50 50 50 50 50 50 100 100 100 0 0 0 50 50 50 100 100 100 Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga 100 100 100 Ulanga Ulanga Ulanga District District District District District District District District District Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers 0 100 200 Kilometers Kilombero & Ulanga districts: 517‘000 people (Tanzania National Census, 2002)

  4. Background: Project Interventions 1. Community 2. Health Facilities 3. Drug Shops

  5. Background: Monitoring and Evaluation 1. Community 2. Health Facilities 3. Drug Shops

  6. Methods: 1. DSS • 25 villages • Population apx 80 000 • Person exposure data • • Fever incidence (2 week recall) Fever incidence (2 week recall) DSS Community reported fever cases per month fever = rate Person weeks exposed per month

  7. Methods: 2. Treatment seeking survey • Cross sectional • 2004, 2006, 2008 • 100 fever cases • • Quantitative data on treatment Quantitative data on treatment seeking % Fever cases for which HF attendance was the first treatment action

  8. Methods: 3. Health Facilities • 15 health facilities • Number of diagnoses per month from HMIS books • • Under 5 and over 5 Under 5 and over 5 Malaria + pneumonia + ARI + measles + HF typhoid + UTI diagnoses per month (HF) fever = rate Person weeks exposed per month (DSS) HF Malaria diagnoses per month (HF) malaria = rate Person weeks exposed per month (DSS)

  9. Results: DSS fever vs. HF fever rates 6% decrease in DSS fever rates per year (IRR=0.94 p<0.001) 4% decrease in HF fever rates per year (IRR=0.96, p<0.001) (IRR=0.96, p<0.001) 2% decrease in HF malaria rates per year (IRR=0.98, p<0.001)

  10. Results: Differences by age •DSS fever incidence more than twice higher in children (IRR=2.32, p<0.001) •DSS fever rates decreasing more in children (10% vs. 4% per yr, p<0.001) •HF fever rates 5 times higher in children (IRR=5.36, p<0.001) 2006 fever follow-up •Children twice more likely to be brought to a HF as first treatment option (OR=2.23, p=0.045)

  11. Results: Differences by district DSS Fever incidence is 30% lower in Ulanga than in Kilombero (IRR=0.70, p<0.001) HF fever diagnoses are 30% higher in Ulanga than in Kilombero (IRR=1.31, Kilombero (IRR=1.31, p>0.001) 2006 fever follow-up : People in the Kilombero district are 50% less likely to go to a HF as first treatment (OR=0.51, p=0.03)

  12. Conclusions Reduction in fever incidence Between 2005 and 2007: • 6% reduction in community reported fever overall, 10% children • 4% reduction in HF diagnoses � reduction in malaria risk? Between groups (districts, age) • • higher HF rates vs. lower community rates higher HF rates vs. lower community rates • groups with higher HF attendance have more rapid decrease in fever rates � interrelation between HF attendance on wellbeing of the population?

  13. Conclusions Consistency • Internal – Temporal and quantitative relationship between data from community and health facility (especially in children <5) – Consistency between trends and treatment seeking indicator • External – National data collected by the Tanzania Malaria Indicator Survey

  14. Asanteni! • Team pic

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