中央研究院 資訊科學研究所

Two key processes that shape infectious disease dynamics are the invasiveness of pathogens and their capacity to spread. To explore these processes, I use Streptococcus pneumoniae as an example and generate quantitative estimates of both traits using bacterial whole-genome data from the Global Pneumococcal Sequencing (GPS) Project. Specifically, I investigate which pneumococcal strains are most likely to progress from asymptomatic carriage to invasive pneumococcal disease (IPD), and estimate the progression rate for each strain based on their serotypes and genetic background. I then examine the role of non-capsular genetic determinants and epidemiological factors in driving invasiveness. Further, I assess how accurately invasive disease risk can be inferred using genomic data from only disease-causing isolates. As for the dissemination of the transmissible pathogens, I explore the extent and speed at which newly introduced strains become geographically well-mixed within and across national borders. Throughout this work, I extend and develop a suite of bioinformatic tools, including a Bayesian Invasiveness Model, rrspread, and a Birth–Death–Sampling framework, to enable improved inference of invasiveness and transmission, hoping to close existing methodological gaps in the field.

I am a Research Associate at 【MRC Centre for Global Infectious Disease Analysis, Imperial College London】 in Dr. Nicholas Croucher's group and collaborate with Stephen Bentley's group at Wellcome Sanger Institute. I did my PhD at Wellcome Sanger Institute, University of Cambridge with Prof. Stephen Bentley. My work focuses on the development of mathematical models that help describe the underlying evolutionary process and transmission dynamics of infectious diseases, with the ultimate goal of helping disease control. I am particularly focusing on the use of genomic data. I am working on the evolution of Streptococcous pneumoniae and group B Streptococcus, and I am generally interested in evolutionary biology.
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