ASTMH 2018, Iqbal Elyazar: “Individual movement pattern analysis using GPS trackers to forest workers in Aceh, Indonesia”

In collaboration with ASTMH, Image Audiovisuals, and session presenters, MESA brings you this webcast from the 67th ASTMH annual meeting in New Orleans, October 2018

Title: “Individual movement pattern analysis using GPS trackers to forest workers in Aceh, Indonesia“

Speaker: Iqbal Elyazar, Eijkman-Oxford Clinical Research Unit, Jakarta, Indonesia

Session information: 

Symposium 118: Malaria Elimination in Asia and Africa

October 31, 2018, 8:00 AM – 9:45 AM, Marriott – Mardi Gras D (3rd Floor)

Abstract:

Human movement is a known contributor to sustained malaria transmission in low endemic areas. Many methods have been explored to measure human mobility and its impact of movement to malaria transmission, for example, census data, travel diaries, mobile phone usage data and GPS trackers. Our study used commercially available GPS data trackers to identify specific potentially high‐risk locations visited frequently by forest workers in the district of Aceh Besar and Aceh Jaya in Aceh Province, the western province of Indonesia. These districts previously reported the presence of zoonotic malaria species Plasmodium knowlesi among forest workers. Beginning in April 2017, we recruited forest workers who were recent malaria cases, as well as individuals from their peer networks, to be followed for a period of two months each. Following consent, individuals were asked to wear an “i-gotU” (i-gotU model GT100) GPS tracking device continually during all of their activities over a two month period; location data were captured every 15 minutes. As of April 2018, 62 individuals had been recruited into the study, 38 of whom completed the study or dropped out before the end of the 2 month data collection period. Data collection for an additional 24 individuals is ongoing and participant recruitment will continue through September 2018. To date, participants have contributed 1,691 days of GPS data collection with over 236,000 data points. More comprehensive analysis on the individual movement patterns to inform interventions that target for mobile forest workers will be presented.