Pooled Testing for Imperfect Multiplex Assays: The Optimal Pool Size for Estimating Coinfections

Music City Center 

Pooled testing consists of combining biomaterial from multiple individuals into 'pools' which are tested for evidence of infection (e.g. pathogens, antibodies, etc.). Pooled testing is widely used to estimate the prevalence of infectious diseases and can offer substantial cost savings over individual testing. The optimal pool size has been well-studied for the singleplex case and depends on the test accuracy and disease prevalence. We develop a method to determine the optimal pool size for multiplex pool testing data with imperfect assays. We use an expectation-maximization algorithm to estimate the prevalences of infection with all subsets of pathogens under consideration. We use Louis's method to obtain the asymptotic covariance matrix of these estimators. Our approach reliably estimates the prevalence of co-infections and can determine if infections with different pathogens are independent. We also present an approach for determining the optimal pool size for estimating co-infection prevalence. We apply our method to pooled testing data from a multiplex assay for four pathogens conducted on lone star ticks (Amblyomma americanum) collected in South Carolina to investigate co-infections between Rickettsia spp. and Ehrlichia spp. pathogens.

pooled testing

group testing

imperfect multiplex assays

optimal pool size 

Section on Statistics in Epidemiology