Profile

After completing my PhD in sunny Sydney, I came to work in London. And London, being true to itself, was as wet as it could get when I arrived. Despite the weather, I absolutely love living and working in London. I am incredibly lucky to have travelled to every continent except Antartica (which is on my bucket list). My pronouns are she/her.

It never ceases to amaze me that in mathematics, humans have devised a language that can roughly approximate our wild and crazy natural world. In my job, I use mathematics and statistics to figure out how infectious disease spread from one place to another. Never before COVID-19 has been my job so much in focus and in the public eye. While working on COVID-19, I have been looking at the very early days of spread from Wuhan to literally every single country around the world. In the beginning of the pandemic, one question that I tried to answer was – how many cases of COVID-19 might we be missing? To answer this question, I looked at the number   of passengers that fly out of Wuhan to different countries. Say if every 1 in a million people in Wuhan has COVID, and if say 10 in a million people fly from Wuhan to Thailand, and 100 people fly from Wuhan to Singapore, we should expect to see 10 times as many cases of COVID in Singapore than in Thailand. If in fact we only see 5 times as many cases in Singapore as in Thailand, it is very likely that we are missing some cases. Similarly, to look at how an outbreak is expected to spread within a country rather than from one country to another, we can look at data from mobile phones, or data that facebook shares with us on how its users move around the country. I combine this data with data on where a hotspot of outbreak is to understand how it might spread, so that governments can plan actions.

The having coffee part was of course before COVID happened. I now work from home so have a nice, strong cup of tea with two tea bags in it. Then I start up my laptop and the real work starts. I use a programming language called R which makes it really easy for me to statistics. Almost my entire day is spent writing code that captures our approximation or understanding of diseases spread (what we call a mathematical model). I then look at the outputs of the model to compare them with data from the real world to make sure my model is behaving sensibly. If I didn’t do this, I would not have the confidence to say that my model can predict disease spread in the future. I also spent a lot of time discussing science with my colleagues – this involves virtual whiteboards and a lot of stick figures, and these days of lot of skyping and Zooming.