LAUSR

It is challenging to quantitatively measure vulnerability and risk factors of refugees and migrants residing outside of formal settlement settings. For hard-to-reach populations without available sampling frames, researchers have increasingly turned to novel sampling and statistical methods, like respondent-driven sampling (RDS). 'Standard' RDS is typically conducted face-to-face at fixed sites. However, during the COVID-19 pandemic, face-to-face survey methods and recruitment approaches posed high potential risk of virus transmission and infection, making remote RDS approaches optimal. This paper explores the feasibility of implementing phone and Internet RDS strategies to assess challenges faced by Venezuelan refugees and migrants in the city of Bogotá, Colombia's capital, and the department of Norte de Santander, the main Venezuelan-Colombian border crossing site. The authors describe RDS assumptions, survey design, formative research, and the implementation of both strategies and present diagnostics to determine whether assumptions are met. Phone-based recruitment strategies in both locations and the Internet strategy in Bogotá achieved their calculated sample size, however the Internet strategy in Norte de Santander did not. Most RDS assumptions were sufficiently met in sites where sample sizes were reached. These surveys provide valuable lessons learned for implementing innovative remote strategies to study hard-to-reach populations such as refugees and migrants.