In 2016, Cassidy had been a practicing doctor in Australia for four years. She was thinking about which specialty to pursue in order to help her patients most, when she found 80,000 Hours through Google.
She read our review of medical careers and analysis of how many lives you can save as a doctor compared to working on larger scale health interventions. Having read the philosopher Peter Singer‘s influential essay Famine, Affluence, and Morality in college, Cassidy had long been interested in doing as much good as she could. She decided to switch from individual practice to public health in order to help more people.
Soon after, through conversations with members of the local effective altruism community and a one-on-one discussion with an 80,000 Hours advisor, Cassidy realised she might be able to do even more good by helping to prevent pandemic diseases from taking hold in the first place.
She applied to the Research Scholars Programme at the Future of Humanity Institute and to a PhD programme in pandemic modeling, both in Oxford. In 2018 she was accepted, and received funding for her PhD from the foundation Open Philanthropy.
Cassidy now co-leads the biosecurity team at the Future of Humanity Institute, and is a fellow at the Emerging Leaders in Biosecurity Initiative at Johns Hopkins Center for Health Security.
She has consulted for the World Health Organization on health security and has advised the U.K. government on fighting COVID-19 and preventing future outbreaks. And because Cassidy and her colleagues had already been investigating the topic before COVID-19, they were able to quickly propose policies while there was heightened interest during the early days of the outbreak that will make also a bigger contribution to preventing the next pandemic.
Cassidy plans to continue to advance the state of the art in pandemic prevention in government and beyond, in order to keep outbreaks as bad as COVID-19 (or much worse) from happening again.
To learn more about Cassidy’s work and pandemic prevention more generally, check out: