Combining Entomological, Epidemiological, and Spacial

Combining Entomological,
Epidemiological, and
Space Mapping data for
Malaria Risk-mapping in
Northern Uganda
Findings and Implications
Ranjith de Alwis, Abt Associates
November 15, 2012
 Malaria and malaria control in Uganda
 Indoor residual spraying (IRS) in Uganda
 Impact of IRS on malaria prevalence
 Entomological monitoring activities and findings
 Risk mapping
 Lessons learned
 Recommendations
Abt Associates | pg 2
Malaria and Malaria Control
 Malaria transmission
 highly endemic and
 90% of population at risk
 99% Plasmodium falciparum
 Major vectors
 Anopheles gambiae
 Anopheles funestus
 Interventions
Improved diagnosis/case
Abt Associates | pg 3
Indoor Residual Spraying (IRS)
 IRS—most effective malaria vector control method
 Currently, the primary factor for deciding where to
use IRS is malaria incidence, which results in
expensive blanket coverage
 Stratification based on risk—more effective strategy
but requires reliable and representative data over
Abt Associates | pg 4
Indoor Residual Spraying (IRS)
Data needed for planning IRS
Vector bionomics (species and behaviour)
Vector susceptibility to insecticides
Suitability of structures and population compliance
Malaria prevalence patterns to determine time to spray
On-going monitoring needs for decision making
 Vector bionomics
 Vector susceptibility
 Residual efficacy of insecticide
Data needed for decisions on phase-out or scale-up of IRS
 Malaria epidemiological data over the time
 Meteorological information
 Feasibility of carrying out of other interventions
Abt Associates | pg 5
Indoor Residual spraying (IRS)
 Started in 2006 in
South Western districts
 Moved to Northern
districts in 2007
 7-8 rounds have
 Started with Lambda-Cyhalothrin
 Then moved to Alpha-Cypermethrin
 DDT was used in 2 districts for one
 Since 2010 Bendiocarb
Target Population – 2.8 million
Approx. 900,000 structures
Abt Associates | pg 6
Impact of IRS on Malaria
 Marked reduction in
malaria cases,
especially after
Abt Associates | pg 7
Impact of IRS on Malaria
 Location based data not available
in health institutions
 Difficulties in combining
epidemiological data with other
Abt Associates | pg 8
Entomological Monitoring Activities
 Pre- and post-spraying
 Post-spraying wall
 Monthly wall bioassays
 National Susceptibility
Study (2011)
 Vector bionomics ****
Abt Associates | pg 9
Pyrethroid Spray Collections
Abt Associates | pg 10
Monthly Wall Bioassays (200912)
Abt Associates | pg 11
National Susceptibility Study
Abt Associates | pg 12
Risk Mapping
2005 risk map based on malaria endemicity.
2012 risk map detailed at district level to facilitate
development of national vector control policy.
 Planned to used a spatial model based on district-level
Malaria prevalence data
Entomological data
Intervention data
Meteorological data
Demographic, physical and geographical data
 Data challenges
 Malaria data is not representative or reliable
 No recent entomological data
 Low, predictive power of the risk map model – Need to
Abt Associates | pg 13
Malaria Risk Maps
Abt Associates | pg 14
Lessons Learned
 IRS effectiveness
 Combining all these data help us to
– Use correct insecticide
– Manage resistance
– Understand residual efficacy
 Indoor resting behavior
 Reduction of malaria prevalence / When to phase out IRS
Strengthen other control methods.
 Importance of location based data at lower administration
 Risk mapping in project area
 Will allow scale up of malaria control activities nationally
while phasing out/reducing IRS in on-going areas
Abt Associates | pg 15
To scale up vector control nationally while reducing IRS
in on-going areas, we will need:
Location based data
Confirmed malaria cases
Establishment of indicators institutions
Spatial analysis of population distribution
Spraying time and frequency
Vector bionomics
Resistance status
Abt Associates | pg 16

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