Central Data Catalog

Citation Information

Type Journal Article - Malar Journal
Title The demographics of human and malaria movement and migration patterns in East Africa
Volume 12
Issue 397
Publication (Day/Month/Year) 2013
Page numbers 10-1186
URL http://malariajournal.biomedcentral.com/articles/10.1186/1475-2875-12-397
Introduction: The quantification of parasite movements can provide valuable information for control strategy
planning across all transmission intensities. Mobile parasite carrying individuals can instigate transmission in
receptive areas, spread drug resistant strains and reduce the effectiveness of control strategies. The identification of
mobile demographic groups, their routes of travel and how these movements connect differing transmission zones,
potentially enables limited resources for interventions to be efficiently targeted over space, time and populations.
Methods: National population censuses and household surveys provide individual-level migration, travel, and other
data relevant for understanding malaria movement patterns. Together with existing spatially referenced malaria data
and mathematical models, network analysis techniques were used to quantify the demographics of human and
malaria movement patterns in Kenya, Uganda and Tanzania. Movement networks were developed based on connectivity
and magnitudes of flow within each country and compared to assess relative differences between regions
and demographic groups. Additional malaria-relevant characteristics, such as short-term travel and bed net use,
were also examined.
Results: Patterns of human and malaria movements varied between demographic groups, within country regions
and between countries. Migration rates were highest in 20–30 year olds in all three countries, but when accounting
for malaria prevalence, movements in the 10–20 year age group became more important. Different age and sex
groups also exhibited substantial variations in terms of the most likely sources, sinks and routes of migration and
malaria movement, as well as risk factors for infection, such as short-term travel and bed net use.
Conclusion: Census and survey data, together with spatially referenced malaria data, GIS and network analysis
tools, can be valuable for identifying, mapping and quantifying regional connectivities and the mobility of different
demographic groups. Demographically-stratified HPM and malaria movement estimates can provide quantitative
evidence to inform the design of more efficient intervention and surveillance strategies that are targeted to specific
regions and population groups.

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