RQ: who are the asymptomatic cases of malaria?
In malaria endemic countries, especially in low-prevalence settings, malaria infections are detected and treated passively, meaning that only symptomatic cases of malaria that turned out in the health facilities are treated. Asymptomatic cases are therefore never treated and sustain the transmission cycle of malaria. To eradicate malaria it is therefore important to be able to also identify and treat asymptomatic cases.
In low malaria prevalence settings, probabilistic sampling scheme are likely to be highly ineffective. Plus, in low endemic settings, research has identified a couple of high-risk populations which often time are hard-to-reach populations such as migrants workers, forest-goers,… In that context I think a respondent-driven sampling (RDS) strategies could help us capture more effectively the targeted population. The seeds would be symptomatic cases and they would be asked to refer friends or family members sharing some of the known epidemiologic risk factors for malaria (spend time outside at night, bednets owners,…).
In terms of advantages, I think this sampling strategy would give us access to a high-risk population that might otherwise be hidden and enable to find more of those asymptomatic cases. In terms of disadvantages, this RDS strategy is likely to introduce uncontrolled selection bias.
I think incorporating RDS strategy would reduce bias of univariate quantities such as prevalence simply by capturing a more accurate representation of the infection levels. On the other hand, the selection bias induced by RDS is probably hard to account for when making causal inference both in terms of the point estimate but also in terms of the confidence intervals as inference methods for the variability of an estimate highly depends on independence assumptions and others.