Novel statistical methods to unlock the potential of routinely collected health data: COVID-19 & beyond

Many pressing public health questions have been raised by the COVID-19 pandemic. Who is most at risk of severe health outcomes from COVID-19? What existing treatments can aid prevention or treatment of COVID-19? Do COVID-19 vaccines work well in practice? 

Throughout the pandemic, routinely collected health data have provided an invaluable resource for addressing such questions rapidly. However, the lack of robust analytic tools to analyse these data led to a lack confidence in insights gained from these data.

My overall aim in this fellowship is to develop statistical methodology to remove barriers that have hampered analyses addressing important public health issues in COVID-19.

Looking beyond COVID-19, more pandemics may arise, be it a different form of COVID-19 or something new. Having state of the art methodological tools embedded in UK’s large health databases will provide us with the ability to adapt and rapidly respond to new threats.