Long-form writing
Here, you can find a collection of my writing on other platforms.
2026
Why were Covid vaccine trials so fast? The timeline to develop coronavirus vaccines blew many predictions out of the water. [Clinical Trials Abundance blog]
Clinical trial reforms that once seemed radical How randomized controlled trials, preregistration, and results reporting became standard practice. [Clinical Trials Abundance blog]
The Golden Age of vaccine development The first vaccine was a lucky accident. Now we can design new vaccines in weeks, atom by atom. [Works in Progress]
The case for sharing clinical trial data The story behind the first statin and how its development was almost derailed, and the implications of sharing clinical trial data. [Clinical Trials Abundance blog]
2025
Death rates from cardiovascular disease have fallen dramatically Over a century of progress in surgery, drugs, prevention, and emergency response has driven down death rates from heart disease and stroke. [Our World in Data]
The Demographic and Health Surveys brought crucial data for more than 90 countries Cuts to US aid could end the Demographic and Health Surveys. This would leave a massive gap in our understanding of global health, mortality, and development. [Our World in Data]
Measles leaves children vulnerable to other diseases for years Measles causes more than an acute illness: it suppresses immune memory and increases the risk of complications for years. [Our World in Data]
Childhood leukemia: how a deadly cancer became treatable Before the 1970s, most children affected by leukemia would quickly die from it. Now, most children in rich countries are cured. [Our World in Data]
Measles vaccines save millions of lives each year Measles once killed millions every year. Vaccines changed this, preventing disease, long-term immune damage, and deadly outbreaks. [Our World in Data]
How effective and safe are measles vaccines? Data from large meta-analyses show that measles vaccination is highly effective and safe, giving a 95% reduction in the risk of measles. [Our World in Data]
The baby boom in seven charts The baby boom reshaped family life and drove population growth in many countries. In this article, we explore the key patterns in seven charts. [Our World in Data]
Why the total fertility rate doesn’t necessarily tell us the number of births women eventually have The fertility rate is commonly confused with the eventual number of births per woman. This can result in misinterpreting the impact of policies and trends over time. [Our World in Data]
2024
What was the Golden Age of Antibiotics, and how can we spark a new one? Many antibiotics were developed during the “Golden Age of Antibiotics”. How did it happen, why has antibiotic development slowed down since then, and what can we do to reignite it? [Our World in Data]
How do antibiotics work, and how does antibiotic resistance evolve? To use antibiotics more effectively, it’s important to know how different antibiotics work and how antibiotic resistance can evolve and spread. [Our World in Data]
How our team at Our World in Data became a global data source on COVID-19 Our small team made COVID-19 data clear, reliable, and accessible to a global audience. This is how it happened. [Our World in Data]
17 key charts to understand the COVID-19 pandemic The pandemic has resulted in over twenty million deaths. In this article, we review the key insights from global data on COVID-19. [Our World in Data]
HPV vaccination: How the world can eliminate cervical cancer HPV vaccines offer a rare opportunity to effectively eliminate one type of cancer. [Our World in Data]
Antipsychotic medications: a timeline of innovations and remaining challenges Scientists have developed effective and safer antipsychotic medications, but much improvement is still needed. [Our World in Data]
Measuring the Black Death Reports suggest that between 40 and 60 percent of the population died during the bubonic plague that swept through Europe in the mid-1300s. [Asimov Press]
How do global statistics on suicide differ between sources? To better monitor and prevent suicides globally, it’s crucial to understand how they are measured and estimated by different sources. [Our World in Data]
Trachoma: how a common cause of blindness can be prevented worldwide The world has seen a large decline in trachoma, but millions are still at risk. How can we make more progress against it? [Our World in Data]
New polio vaccines are key to preventing outbreaks and achieving eradication To reach the goal of polio eradication, we can use new vaccines to contain outbreaks and improve testing, outbreak responses, and sanitation. [Our World in Data]
The rise in reported maternal mortality rates in the US is largely due to a change in measurement Maternal mortality rates appear to have risen in the last 20 years in the US. [Our World in Data] (NB: This article won the Royal Statistical Society’s Best Statistical Commentary Award in 2025)
How political gridlock could kill the best global health program the US ever passed PEPFAR saved millions of people from AIDS. Don’t let it die. [Vox]
2023
What are the different types of cardiovascular diseases, and how many deaths do they cause? Cardiovascular diseases are a range of related health conditions that develop in the heart and blood vessels. What are the different diseases, and what is their impact worldwide? [Our World in Data]
What were the death tolls from pandemics in history? Pandemics have killed millions of people throughout history. How many deaths were caused by different pandemics, and how have researchers estimated their death tolls? [Our World in Data]
Why do women live longer than men? Women tend to live longer than men in all countries — but the sex gap in life expectancy is not a constant. [Our World in Data]
Period versus cohort measures: what’s the difference? What do the terms “period” and “cohort” mean in statistics? How do they differ, and why does it matter? [Our World in Data]
How does the risk of death change as we age – and how has this changed over time? Death rates decline rapidly after birth but rise again in adolescence. From adulthood onwards, they rise exponentially. [Our World in Data]
Why we didn’t get a malaria vaccine sooner (written with Rachel Glennerster & Siddhartha Haria) Hundreds of thousands of people die from malaria each year, but it took 141 years to develop a vaccine for it. [Works in Progress]
Why isn’t it possible to sum up the death toll from different risk factors? Deaths caused by each risk factor can’t be added up. By understanding why, we will have a better understanding of how many lives can be saved with each intervention. [Our World in Data]
Risk ratios, odds ratios, risk differences: How do researchers calculate the risk from a risk factor? The effects of risk factors can be calculated in different ways. How are they calculated and interpreted? [Our World in Data]
How are causes of death registered around the world? In many countries, when people die, the cause of their death is officially registered in their country’s national system. How is this determined? [Our World in Data]
How do researchers estimate the death toll caused by each risk factor? Risk factors are important to understand because they can help us identify how to save lives. How do researchers estimate their impact? [Our World in Data]
How do researchers study the prevalence of mental illnesses? Global data on mental health is essential to understand the scale and patterns of these illnesses, and how to reduce them. How do researchers collect this data, and how reliable is it? [Our World in Data]
2022
The big idea: Should we give people diseases in order to learn how to cure them? With the right ethical safeguards, could ‘challenge trials’ defend against future pandemics? [The Guardian]
How many people die from the flu? The risk of death from influenza has declined over time, but globally, hundreds of thousands of people still die from the disease each year. [Our World in Data]
The Pandemic Uncovered Ways to Speed Up Science There doesn’t have to be a trade-off between good research and fast research. [Wired]
Guinea worm disease is close to being eradicated – how was this progress achieved? In the late 1980s, there were near a million new cases of guinea worm disease recorded worldwide. In 2021, there were only 15. How was this achieved? [Our World in Data]
We need more testing to eradicate polio worldwide The world is close to eradicating polio, but has been set back in the last few years. To achieve the goal of global eradication, it’s crucial to improve testing. [Our World in Data]
What is the lifetime risk of depression? Depression is one of the world’s most common health conditions. It’s estimated that one-in-three women and one-in-five men have an episode of major depression by the age of 65. [Our World in Data]
At what age do people experience depression for the first time? People are being diagnosed with depression at an earlier age than in the past because of increased openness to mental health disorders and improved diagnostic guidelines. [Our World in Data]
Why randomized controlled trials matter and the procedures that strengthen them Randomized controlled trials are a key tool to study cause and effect. Why do they matter and how do they work? [Our World in Data]
Real peer review has never been tried Outdated forms of peer review create bottlenecks that slow science. But in a world where research can now circulate rapidly on the Internet, we need to develop new ways to do science in public. [Works in Progress]
2021
The crisis in Covid vaccine messaging is leaving pregnant women unprotected from Omicron Vaccines don’t increase the risk of miscarriage, preterm birth or stillbirth – they reduce them, by protecting women from Covid-19. [New Statesman] (NB: This article was runner up in the Royal Statistical Society’s Best Statistical Commentary Award in 2022)
Depression is complicated — this is how our understanding of the condition has evolved over time Our understanding of depression has evolved over time, with wider screening for depression, new questionnaires, and better statistical tools. [Our World in Data]
What does fading vaccine efficacy mean for the fight against Covid-19? A higher proportion of people will now need to be vaccinated to achieve herd immunity. [New Statesman]
Where will the next pandemic come from and how can we prevent it? From factory farming to climate change, the connections between humanity and nature carry increasing risk. [New Statesman]
The speed of science Critics of scientific reform say that transparency comes at the cost of speed. What can disciplines learn from each other to break away from this crisis? [Works in Progress]
2020
Can we eradicate Covid-19? (written with Stuart Ritchie) Only two contagious diseases have ever been wiped out — but coronavirus could be next. [UnHerd] (NB: I’ve changed my mind on this piece; beyond the obvious reasons, I think we missed an early window for eradication but also that the disease is a poor candidate, especially given chronic infections and animal reservoirs, which weren’t known at the time)
In praise of the Covid superforecasters Superforecasters make testable predictions, unlike certain commentators. [UnHerd]
The trouble with ‘Covid denialism’ (written with Matthew Lesh) Our actions should reflect, not dismiss, the possibility of a second wave. [UnHerd]
When will the Covid-19 vaccine arrive? Thanks to the most skilled forecasters, we now have a pretty good idea of when the nightmare will end. [UnHerd]
The story of Viktor Zhdanov Although Viktor Zhdanov’s name is little known today, he spearheaded one of the greatest projects in history. Who was he and what did he do? [Works in Progress]
Why are minorities so hard hit by Covid-19? A combination of social conditions and health factors has turned coronavirus into a disaster for black and Asian Britons. [UnHerd]
Why the Government changed tack on Covid-19 The sudden change in strategy regarding the pandemic is welcome — if dangerously overdue. [UnHerd]
2019
The truth about the female brain A part of popular science is unthinkingly biased. [UnHerd]
2018
Steven Pinker’s Counter-Counter-Enlightenment Peter Harrison took exception to his “teleological view of history” and “misplaced faith in data, metrics and statistical analysis.” [Quillette]