title: Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.
abstract: BACKGROUND
  Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA.
  
  
  RESULTS
  The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance.
  
  
  CONCLUSIONS
  Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens.
authors.affiliation: Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London, W2 1PG, UK. m.walker06@imperial.ac.uk.
authors.forename: Martin
authors.initials: M
authors.lastname: Walker
authors.affiliation: Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London, W2 1PG, UK. m.basanez@imperial.ac.uk.
authors.forename: María-Gloria
authors.initials: MG
authors.lastname: Basáñez
authors.affiliation: Centre National de Recherche et de Formation sur le Paludisme, BP 2208, Ouagadougou, 01, Burkina Faso. andrelin.cnrfp@fasonet.bf.
authors.forename: André Lin
authors.initials: AL
authors.lastname: Ouédraogo
authors.affiliation: Department of Medical Microbiology, Radboud University Medical Centre, Nijmegen, PO Box 9101, 6500 HB, Nijmegen, Netherlands. R.Hermsen@ncmls.ru.nl.
authors.forename: Cornelus
authors.initials: C
authors.lastname: Hermsen
authors.affiliation: Department of Medical Microbiology, Radboud University Medical Centre, Nijmegen, PO Box 9101, 6500 HB, Nijmegen, Netherlands. Teun.Bousema@lshtm.ac.uk.|Department of Immunology and Infection, London School of Hygiene and Tropical Medicine, London, UK. Teun.Bousema@lshtm.ac.uk.
authors.forename: Teun
authors.initials: T
authors.lastname: Bousema
authors.affiliation: MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London, W2 1PG, UK. thomas.churcher@imperial.ac.uk.
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Churcher
mesh_terms: D001499:Bayes Theorem; D016054:DNA, Protozoan / Q000235:genetics; D003627:Data Interpretation, Statistical; D006801:Humans; D016778:Malaria, Falciparum / Q000097:blood / Q000175:diagnosis / Q000469:parasitology*; D010963:Plasmodium falciparum / Q000235:genetics* / Q000302:isolation & purification; D060888:Real-Time Polymerase Chain Reaction / Q000379:methods*; D015203:Reproducibility of Results; D021161:Self-Sustained Sequence Replication; D012680:Sensitivity and Specificity
chemical_list: D016054:DNA, Protozoan