I am an (almost finished) PhD student in biostatistics and infectious disease modelling (population-level); my research focuses on Bayesian statistical methods to produce improved estimates of the number of new COVID-19 infections. During the pandemic, I was a member of SPI-M-O (the UK government committee providing expert scientific advice based on infectious disease modelling and epidemiology).
I enjoy applying my knowledge broadly, including to models of future pandemics, big picture thinking on pandemic preparedness, and forecasting.
Great post, thank you. I hadn’t considered the anti-synergy of treatment and vaccination explicitly before.
How much weight to put on the vaccine risks you mention in the following sentence seems very important to whether to fund anti-virals or not: “Treatment of the cases that happen later is either useful as a mitigation measure to slightly reduce impact, or a backup plan in case we don’t manage to make vaccines.”.
At the start of this pandemic, most people thought vaccines might be very far off or impossible. I’m not sure how much to update based on exceeding expectations and ongoing with to shorten timelines. However, we seem to be quite good at testing therepeautics which seem to need less customising (hence easier production), especially when the side effects profile is well understood (eg the RECOVERY trial). While not an anti-viral, dexamethasone has probably saved a lot of lives. I don’t know enough biology/medicine to be able to distribution how much we need to separate different classes of drugs.