Estimating the size of hidden populations using respondent-driven sampling data: Case examples from Morocco

Abstract

Background: Respondent-driven sampling is used worldwide to estimate the population prevalence of characteristics, such as HiV/aiDS and associated risk factors in hard-to-reach populations. estimating the total size of these populations is of great interest to national and international organizations; however, reliable measures of population size often do not exist.

Methods: Successive sampling-population size estimation (SS-PSE) along with network size imputation allows population size estimates to be made without relying on separate studies or additional data (as in network scale-up, multiplier, and capture–recapture methods), which may be biased.

Results: ten population size estimates were calculated for people who inject drugs, female sex workers, men who have sex with other men, and migrants from sub-Saharan africa in six different cities in Morocco. SS-PSE estimates fell within or very close to the likely values provided by experts and the estimates from previous studies using other methods. Conclusions: SS-PSE is an effective method for estimating the size of hard-to-reach populations that leverages important information within respondent-driven sampling studies. the addition of a network size imputation method helps to smooth network sizes allowing for more accurate results. However, caution should be used particularly when there is reason to believe that clustered subgroups may exist within the population of interest or when the sample size is small in relation to the population.