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The control limits, established by this novel method, are based on more than a decade of QC test results from >300 laboratories from 30 countries and provides users of the NRL QC program evidence-based control limits that can be applied in isolation or in conjunction with more traditional methods for establishing control limits.

As testing for infectious diseases moves from manual, biological testing such as complement fixation to high throughput automated autoanalyzer, the methods for controlling these assays have also changed to reflect those used in clinical chemistry. However, there are many differences between infectious disease serology and clinical chemistry testing, and these differences have not been considered when applying traditional quality control methods to serology. Infectious disease serology, which is highly regulated, detects antibodies of varying classes and to multiple and different antigens that change according to the organisms’ genotype/serotype and stage of disease. Although the tests report a numerical value (usually signal to cut-off), they are not measuring an amount of antibodies, but the intensity of binding within the test system. All serology assays experience lot-to-lot variation, making the use of quality control methods used in clinical chemistry inappropriate. In many jurisdictions, the use of the manufacturer-provided kit controls is mandatory to validate the test run. Use of third-party controls, which are highly recommended by ISO 15189 and the World Health Organization, must be manufactured in a manner whereby they have minimal lot-to-lot variation and at a level where they detect exceptional variation. This paper outlines the differences between clinical chemistry and infectious disease serology and offers a range of recommendations when addressing the quality control of infectious disease serology.

Background All individuals should have equitable access to accurate and timely testing for infectious diseases, which underpins diagnosis and treatment, safeguards blood supplies, and is used to determine disease prevalence. Disadvantaged populations have limited access to laboratory-based testing, so near patient or point of care testing (PoCT) has been developed and implemented. Unlike laboratory-based testing, PoCT is often performed by non-laboratory staff and outside regulatory frameworks. Quality assurance (QA) of PoCT is often lacking or inappropriate, meaning inaccurate testing can go undetected, leading to poor patient outcomes. Methods A review of current QA of PoCT was undertaken by experienced quality assurance providers by mapping the points of failure. Barriers to providing PoCT QA includes inappropriate and unstable sample types; expensive shipping to remote sites, including dry ice shipment; cost of international quality assurance programs; regulatory costs; fixed test events and a lack of technology for simple, centralised data collection facilitating rapid analysis and reporting of test results. Based on these findings, a novel, fit-for-purpose model of QA for PoCT for infectious diseases is described. Results The new model for QA for PoCT identifies describes novel sample types, including dry tube samples, dried swabs, or liquid-stable clinical samples that are inactivated and stable at ambient temperature; modified distribution channels; and a method for data collection and analysis using mobile phone technology. Conclusions : The findings of this paper seek to describe a fit for purpose process which aims to improve the quality of testing for infectious diseases at PoCT, globally.