Multiple-Test Pool-Testing Strategy for Estimating HIV/AIDS-Prevalence and Its Extension to Multi-Stage

Testing units of a population one-at-a-time for the presence of a trait is expensive and tedious especially when the population is large. The remedy is to pool the population samples into pools and test each pool for the presence of a trait. There is loss of sensitivity in pooling strategies especially in the presence of inspection errors, and to recover some lost sensitivity is through re-testing pools classified as positive as proposed by Monzon et al. [1]. Pool testing with retesting entails testing the pools, and pools that are classified as positive are retested be-fore being classified as either positive or negative. This study develops a statistical pool-testing model with retesting based on Monzon et al. [1]. Retesting strategy and generalizes it to multi-stage retesting model. The multistage model improves the efficiency of the estimators as evident via the computation of asymptotic relative efficiency. Also studied are moment estimators of prevalence which have been shown to be correlated. Comparison with previous studies have been illustrated through application of the model on an example on estimating HIV/AIDS prevalence of which it was demonstrated that the proposed estimators are superior to previously studied estimators.