- Chan, YuYen;
- Fornace, Kimberly;
- Wu, Lindsey;
- Arnold, Ben F;
- Priest, Jeffrey W;
- Martin, Diana L;
- Chang, Michelle A;
- Cook, Jackie;
- Stresman, Gillian;
- Drakeley, Chris
- Editor(s): Bradbury, Richard Stewart
Background
Serological surveys with multiplex bead assays can be used to assess seroprevalence to multiple pathogens simultaneously. However, multiple methods have been used to generate cut-off values for seropositivity and these may lead to inconsistent interpretation of results. A literature review was conducted to describe the methods used to determine cut-off values for data generated by multiplex bead assays.Methodology/principal findings
A search was conducted in PubMed that included articles published from January 2010 to January 2020, and 308 relevant articles were identified that included the terms "serology", "cut-offs", and "multiplex bead assays". After application of exclusion of articles not relevant to neglected tropical diseases (NTD), vaccine preventable diseases (VPD), or malaria, 55 articles were examined based on their relevance to NTD or VPD. The most frequently applied approaches to determine seropositivity included the use of presumed unexposed populations, mixture models, receiver operating curves (ROC), and international standards. Other methods included the use of quantiles, pre-exposed endemic cohorts, and visual inflection points.Conclusions/significance
For disease control programmes, seropositivity is a practical and easily interpretable health metric but determining appropriate cut-offs for positivity can be challenging. Considerations for optimal cut-off approaches should include factors such as methods recommended by previous research, transmission dynamics, and the immunological backgrounds of the population. In the absence of international standards for estimating seropositivity in a population, the use of consistent methods that align with individual disease epidemiological data will improve comparability between settings and enable the assessment of changes over time.