Using step selection functions to analyse human mobility using telemetry data in infectious disease epidemiology: a...

Area of Science:

• Human movement ecology
• Infectious disease epidemiology
• Spatial analysis of health risks

Background:

• Human mobility is crucial for infectious disease transmission, particularly zoonotic diseases like leptospirosis, which are linked to environmental factors.
• Understanding fine-scale human movements is essential for analyzing disease spread in populations with environmental exposures.

Purpose of the Study:

• To analyze human movement patterns in relation to environmental risk factors for infectious diseases in urban slums.
• To identify differences in movement behaviors based on gender, age, and leptospirosis serological status.

Main Methods:

• Utilized GPS loggers to collect detailed telemetry data from 128 participants over 24-48 hours.
• Applied step selection functions, a spatio-temporal modeling technique from animal ecology, to human movement data.
• Segmented movement data into time periods (morning, midday, afternoon, evening) and analyzed interactions with environmental factors like sewers and streams.

Main Results:

• Women's movement patterns differed from men's, with women moving closer to a central stream and farther from open sewers.
• Individuals with positive leptospirosis serological status demonstrated avoidance of open sewers.
• Movement data was collected every 35 seconds during active daytime hours.

Conclusions:

• Introduced a novel methodology for analyzing human telemetry data in the context of infectious disease research.
• Demonstrated the utility of movement ecology models in understanding human-environment interactions relevant to disease transmission.