Human movement data for malaria control and elimination strategic planning

Area of Science:

• Epidemiology
• Public Health
• Geographic Information Systems (GIS)

Background:

• Malaria control funding has increased, leading to reduced transmission and elimination targets in 36 countries.
• Previous malaria elimination efforts failed due to reintroduction of the disease via human population movement (HPM).
• Accurate planning for malaria control, elimination, and surveillance requires quantitative data on HPM patterns and parasite dispersion.

Purpose of the Study:

• To review relevant types of HPM across spatial and temporal scales.
• To document existing datasets for quantifying HPM.
• To identify data gaps and propose methods for integrating datasets in a GIS framework for malaria movement analysis.

Main Methods:

• Review of existing literature and datasets on human population movement.
• Analysis of data sources including mobile phone call records, transport infrastructure, and malaria transmission maps.
• Proposal for integrating diverse datasets within a Geographic Information System (GIS) framework.

Main Results:

• Existing studies using mobile phone data have addressed within-country HPM but gaps remain in quantifying cross-border movement, demographic/socioeconomic stratification, transport modes, and personal protection factors.
• Multiple datasets, including spatial data on transport and malaria transmission, can be combined to address these gaps.
• A GIS framework can be utilized to analyze and model human population and Plasmodium falciparum malaria infection movements.

Conclusions:

• Addressing data gaps in HPM is essential for effective malaria elimination strategies.
• Integrating diverse HPM data within a GIS framework can improve the accuracy of malaria control and surveillance planning.
• Understanding and quantifying HPM is critical to prevent the reintroduction of malaria and achieve sustained elimination.