The BloodCounts! project is gearing up towards one of the largest-scale applications yet of machine learning in medicine and healthcare.

A mathematical, and personal, look into how we all had to balance the different harms of the virus and the steps we took against it.

Was the mathematical modelling projecting the course of the pandemic too pessimistic, or were the projections justified? Matt Keeling tells our colleagues from SBIDER about the COVID models that fed into public policy.

Some diseases spread far more quickly in care homes and other settings with vulnerable people. How can maths help? And what help does maths need?

Invading mosquitoes and food poisoning in the production chain — there are a lot of questions epidemiologists address in their research.

Was vaccinating vulnerable people first a good choice? Hindsight allows us to assess this question.

Hear from the epidemiologists who have devoted their lives to fighting the pandemic.

In this interview Emma tells us about what drew her to maths, an exciting summer internship which allowed her to experience life as a maths researcher, and what she is planning for the future.

What can we learn from the COVID crisis about finding consensus?

The COVID-19 pandemic has amplified the differences between us. Understanding these inequalities is crucial for this and future pandemics.

Epidemiologist Matt Keeling tells us about his work on the roadmap out of lockdown, whether the models have been too pessimistic, and what it's been like producing scientific results that carry so much weight.