Innovative Strategies for Remotely Sampling Hard-to-Reach Populations: Assessing Phone Versus Internet Respondent-Driven Sampling Approaches Among Venezuelan Refugees and Migrants in Colombia

Abstract

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.

Using Respondent-Driven Sampling (RDS) to Identify the Healthcare Needs among Women of Reproductive Age Who Migrated from Venezuela to Brazil, 2018–2021

“…As found in previous studies involving migrant individuals [33][34][35][36], the hypothesis that Venezuelan migrants are connected in social networks and have ties with other migrants was confirmed. Networks in both cities developed quickly.…”

“…Using traditional sampling methods, very large samples would be needed to gather a sufficient number of migrants to make it possible to estimate reproductive health indicators, disaggregated by variables of interest, such as age, educational level and place of residence, which would not be feasible due to operational difficulties and costs [ 37 , 38 ]. During the COVID-19 pandemic, a survey implemented RDS strategies to assess the challenges faced by Venezuelan refugees, and the methodology was suitable at sites where the sample size was reached [ 36 ]. A study that collected health information from Syrians who had migrated to Germany concluded that the RDS method was more appropriate and had a much higher response rate than that achieved by random sampling of population records [ 34 ].…”