Use of open mobile mapping tool to assess human mobility traceability in rural offline populations with contrasting malaria dynamics

PeerJ

article

Gabriel Carrasco-Escobar¹  Marcia C. Castro³  Jose Luis Barboza¹  Jorge Ruiz-Cabrejos¹  Alejandro Llanos-Cuentas⁴  Joseph M. Vinetz⁴  Dionicia Gamboa¹ 

[1] Laboratorio ICEMR-Amazonia, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia;Division of Infectious Diseases, Department of Medicine, University of California;Department of Global Health and Population, Harvard T.H. Chan School of Public Health;Instituto de Medicinal Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia;Department of Infectious diseases, School of Medicine, Yale University;Departamento de Ciencias Celulares y Moleculares, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia

关键词: Amazon;    Human mobility;    Contact network;    Malaria;    Network;    Infectious diseases;    Epidemics;   

DOI  :  10.7717/peerj.6298

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Infectious disease dynamics are affected by human mobility more powerfully than previously thought, and thus reliable traceability data are essential. In rural riverine settings, lack of infrastructure and dense tree coverage deter the implementation of cutting-edge technology to collect human mobility data. To overcome this challenge, this study proposed the use of a novel open mobile mapping tool, GeoODK. This study consists of a purposive sampling of 33 participants in six villages with contrasting patterns of malaria transmission that demonstrates a feasible approach to map human mobility. The self-reported traceability data allowed the construction of the first human mobility framework in rural riverine villages in the Peruvian Amazon. The mobility spectrum in these areas resulted in travel profiles ranging from 2 hours to 19 days; and distances between 10 to 167 km. Most Importantly, occupational-related mobility profiles with the highest displacements (in terms of time and distance) were observed in commercial, logging, and hunting activities. These data are consistent with malaria transmission studies in the area that show villages in watersheds with higher human movement are concurrently those with greater malaria risk. The approach we describe represents a potential tool to gather critical information that can facilitate malaria control activities.

【 授权许可】

CC BY