ArticleBMC bioinformatics2015
Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Molecular Assay to Quantify Male and Female Plasmodium falciparum Gametocytes: Results From 2 Randomized Controlled Trials Using Primaquine for Gametocyte Clearance.The Journal of infectious diseases · 2017Trial
- Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.BMC infectious diseases · 2018Article
- Article
- Plasmodium Gametocytes in Field Studies: Do We Measure Commitment to Transmission or Detectability?Trends in parasitology · 2018Review
- Modeling the impact of Plasmodium falciparum sexual stage immunity on the composition and dynamics of the human infectious reservoir for malaria in natural settings.PLoS pathogens · 2018Article
- Probability of Transmission of Malaria from Mosquito to Human Is Regulated by Mosquito Parasite Density in Naïve and Vaccinated Hosts.PLoS pathogens · 2017Article
- Onchocerciasis transmission in Ghana: the human blood index of sibling species of the Simulium damnosum complex.Parasites & vectors · 2016Article
- Associations between Season and Gametocyte Dynamics in Chronic Plasmodium falciparum Infections.PloS one · 2016Article
- Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness.Malaria journal · 2015Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundQuantitative 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.
resultsThe 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.
conclusionsBayesian 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.
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