Vaccines_and_the_evolution_of_antibiotic_resistance__elucidating_transmission_mechanisms_and_public_health_impact_using_deep_sequencing_of_Streptococcus_pneumoniae_and_mathematical_models
Background and goals Predicting the impact of vaccines on antimicrobial resistance is uniquely challenging due to the interdependent dynamics of vaccine use, infectious disease transmission and antibiotic use. This proposed study aims to develop a new transdisciplinary method which will overcome the current impasse to investigate the short- and long-term dynamics of resistance frequencies on S. pneumoniae during and after the introduction of Pneumococcal Conjugate Vaccine (PCV).  The transdisciplinary method includes using: 1) clinical trial data collected and analysed by Prof Lay Myint Yoshida and Prof Dang Duc Anh  2) genomic data generated by deep sequencing at Sanger institute and analysed using cutting edge genomic tools by Prof Stephen Bentley, Dr Stephanie Lo and Dr Rebecca Gladstone  3) state-of-the-art model calibration methods developed and validated by Dr Katherine Atkins, Dr Nick Davies, Dr Stepfan Flasche, Prof Mark Jit and Prof Marc Lipsitch.  The key deliverable of this proposed study will be a validated mathematical model for decision-making on quantifying the long-term consequences of PCV introduction on the incidence of drug resistance infections. The resulting knowledge will be made available to the public domain through publication in the form of scientific papers, publicly-available databases, and could be used in public engagement. Description of the samples Prof Lay Myint Yoshida's team will prepare and sent 1500 DNA samples to Sanger for carrying out deep sequencing. The number of lanes is 8 on a X10 sequecning platform.