The demographics of human and malaria movement and migration patterns in East Africa

Pindolia, Deepa K., Garcia, Andres J., Huang, Zhuojie, Smith, David L., Alegana, Victor A., Noor, Abdisalan M., Snow, Robert W. and Tatem, Andrew J. (2013) The demographics of human and malaria movement and migration patterns in East Africa. Malaria Journal, 12 (397), 1-12. (doi:10.1186/1475-2875-12-397). (PMID:24191976)

Abstract

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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Contributors

Author: Andrew J. Tatem

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