Abstract
.There is increasing interest in using dried blood spot (DBS) cards to extend the reach of global health and disease surveillance programs to hard-to-reach populations. Conceptually, DBS offers a cost-effective solution for multiple use cases by simplifying logistics for collecting, preserving, and transporting blood specimens in settings with minimal infrastructure. This review describes methods to determine both the reliability of DBS-based bioanalysis for a defined use case and the optimal conditions that minimize pre-analytical sources of data variability. Examples by the newborn screening, drug development, and global health communities are provided in this review of published literature. Sources of variability are linked in most cases, emphasizing the importance of field-to-laboratory standard operating procedures that are evidence based and consider both stability and efficiency of recovery for a specified analyte in defining the type of DBS card, accessories, handling procedures, and storage conditions. Also included in this review are reports where DBS was determined to not be feasible because of technology limitations or physiological properties of a targeted analyte.
Highlights
Most diagnostics and surveillance programs rely on measurements from an individual’s blood specimen to guide a clinical or public health decision
The intent of this review is to underscore the need to assess the reliability of dried blood spot (DBS)-based bioanalysis in context to a specific biomarker and envisioned field-to-laboratory workflow, before applying this technology into a remote health or surveillance program
Dried blood spot offers several logistical advantages for remote health and surveillance programs, for screening and surveying hard-to-reach populations. For many of these tests, a highly sensitive biomarker analysis is important for reducing the risk of missed positive cases
Summary
Most diagnostics and surveillance programs rely on measurements from an individual’s blood specimen to guide a clinical or public health decision. The other scenario aims to extend epidemiological surveillance that monitors population-level transmission of infection or tracks emerging or recrudescing disease. Both scenarios rely on tools that provide highsensitivity analysis of individual samples to minimize the risk of missed positive cases, in geographies where loss to follow-up remains a significant challenge. Quantitative studies have demonstrated the feasibility of DBS if standardized collection and laboratory protocols are followed.[12,14,15,16,17,18] there are examples where DBS fails to provide reliable results and this review includes a sample of these reports
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