Trends in community fever and HF diagnoses in the Ifakara DSS - - PowerPoint PPT Presentation

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:

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 2004-2008 ACCESS II 2008-2011

Background:

Project area

) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) ) )

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i s t r i c t D i s t r i c t D i s t r i c t D i s t r i c t D i s t r i c t D i s t r i c t D i s t r i c t D i s t r i c t D i s t r i c t Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Ifakara DSS Areas Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero Kilombero District District District District District District District District District Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga

Ifakara DSS (Town)

Tanzania

Ifakara DSS (Rural)

Kilombero & Ulanga districts: 517‘000 people

(Tanzania National Census, 2002)

50 50 50 50 50 50 50 50 50 Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers Kilometers 100 100 100 100 100 100 100 100 100

D D i s t r i c t D i s t r i c t D D i s t r i c t D Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga District District District District District District District District District Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga Ulanga District District District District District District District District District

• 3. Drug Shops
• 2. Health Facilities
• 1. Community

Background:

Project Interventions

• 3. Drug Shops
• 2. Health Facilities
• 1. Community

Background:

Monitoring and Evaluation

Methods:

• 1. DSS
• 25 villages
• Population apx 80 000
• Person exposure data
• Fever incidence (2 week recall)
• Fever incidence (2 week recall)

Community reported fever cases per month Person weeks exposed per month = DSS fever rate

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

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

HF fever rate Malaria + pneumonia + ARI + measles + typhoid + UTI diagnoses per month (HF) Person weeks exposed per month (DSS) = HF malaria rate Malaria diagnoses per month (HF) Person weeks exposed per month (DSS) =

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)

Results:

DSS fever vs. HF fever rates

(IRR=0.96, p<0.001) 2% decrease in HF malaria rates per year (IRR=0.98, p<0.001)

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)

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)

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?

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

Asanteni!

• Team pic

Methods:

Project M&E (Phase I)

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