Liverpool Centre for Mathematics in Healthcare

Wednesday 11th April 2018 Seminar by Theo Kypraois Nottingham University


'Recent Developments in Identifying Transmission Routes of Healthcare Associated Infections using Whole Genome Sequence Data'



Healthcare-associated infections (HCAIs) remain a problem worldwide, and can cause severe illness and death. It is estimated that 5-10% of acute-care patients are affected by nosocomial infections in developed countries, with higher levels in developing countries.

Statistical modelling has played a significant role in increasing understanding of HCAI transmission dynamics. For instance, many studies have investigated the dynamics of MRSA transmission in hospitals, estimating transmission rates and the effectiveness of various infection control measures. However, uncertainty about the true routes of transmission remains and that is reflected on the uncertainty of parametres governing transmission.

Until recently, the collection of whole genome sequence (WGS) data for bacterial organisms has been prohibitevely complex and expensive. However, technological advances and falling costs mean that DNA sequencing is becoming feasibile on a larger scale.

In this talk we first describe how to construct statistical models which incorporate WGS data with regular HCAIs surveillance data (admission/discharge dates etc) to describe the pathogen's transmission dynamics in a hospital ward. Then, we show how one can fit such models to data within a Bayesian framework accounting for unobserved colonisation times and imperfect screening sensitivity using efficient Markov Chain Monte Carlo algorithms. Finally, we illustrate the proposed methodology using MRSA surveillance data collected from a hospital in North-East Thailand.