MoVe: an integrated tool to explore the relationship between human mobility and vector-borne disease
Issued Date
2026-12-01
Resource Type
eISSN
20452322
Scopus ID
2-s2.0-105029608388
Pubmed ID
41644983
Journal Title
Scientific Reports
Volume
16
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Scientific Reports Vol.16 No.1 (2026)
Suggested Citation
Sa-ngamuang C., Yin M.S., Barkowsky T., Lawpoolsri S., Bicout D.J., Haddawy P. MoVe: an integrated tool to explore the relationship between human mobility and vector-borne disease. Scientific Reports Vol.16 No.1 (2026). doi:10.1038/s41598-026-39007-3 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/115120
Title
MoVe: an integrated tool to explore the relationship between human mobility and vector-borne disease
Corresponding Author(s)
Other Contributor(s)
Abstract
Understanding the role of human mobility in disease transmission is crucial for effective intervention. Analyzing mobility patterns can identify routes of transmission and highlight vulnerable populations. While tools exist for mobility analysis and disease simulation, none integrates all the needed capabilities into a single platform. Such integration is essential for seamless exploration of key questions and what-if scenarios. The MoVe (Mobility analysis for Vector-borne disease) platform meets this need by combining mobility analysis with agent-based simulation. It enables exploratory data analysis, generates mobility metrics, identifies stop locations, visualizes data, and allows users to run simulations based on mobility and risk factors. To demonstrate MoVe’s effectiveness, the platform was used in a case study of malaria transmission along the Thai-Myanmar border, where importation of infection complicates elimination efforts in Thailand. The spatial analysis shows distinct mobility patterns into high-risk areas among different occupational groups. By removing different types of cross-border mobility from the simulation, we quantify the impact of Thai and Myanmar migration on malaria infection rates in Thailand. These findings highlight the tool’s potential for understanding vector-borne disease transmission dynamics and its applicability to other regions and diseases.