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Using GPS loggers, we collected detailed telemetry data to understand how fine-scale movements can be analysed in the context of an infectious disease.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs2\">\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We recruited individuals living in urban slums in Salvador, Brazil, to analyse how they interact with environmental risk factors such as domestic rubbish piles, open sewers, and a local stream. We aimed to identify differences in movement patterns inside the study areas by gender, age, and leptospirosis serological status. Step selection functions, a spatio-temporal model used in animal movement ecology, estimated selection coefficients to represent the likelihood of movement toward specific environmental factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs3\">\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>With 128 participants wearing GPS devices for 24\u201348 hr, recording locations every 35 s during active daytime hours, we segmented movements into morning, midday, afternoon, and evening. Our results suggested women moved closer to the central stream and farther from open sewers compared to men, while serologically positive individuals avoided open sewers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs4\">\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>This study introduces a novel method for analysing human telemetry data in infectious disease research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"abs5\">\n                    <jats:title>Funding:<\/jats:title>\n                    <jats:p>Funding provided by Wellcome Trust, UK Medical Research Council, Brazilian National Research Council, Reckitt Global Hygiene Institute, and National Institute of Allergy and Infectious Diseases.<\/jats:p>\n                  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