Pandemic is marked major problems in research: many studies are inflated, erroneous, or even fraudulent, and misinformation can spread quickly. But it also proves what’s possible.
Although it usually takes years to test drugs against a new disease, this time it takes less than once to find some vaccines and treatments. Once, scientists discovered new strains of viruses just after an outbreak happened, but now they can use wastewater samples to predict outbreaks.
Not everyone sees the pace of these advances positively: believed that the vaccine was “rushed”, for example, is one of the common reasons that person delay getting them. Many believe do science quickly means removing standards and creating sloppy or even dangerous research.
But that hasn’t always been the case, and the urgency of Covid-19 has led many to adapt, produce, and improve research with quality and speed few would expect. Not only can we avoid those trade-offs, but we can also improve science in ways that make it faster — and the pandemic has shown us how.
General data collection
The speed at which the coronavirus genomes are sequenced is a success story, but it doesn’t show us the big picture. While the UK uses big genomics program sequence nearly 3 million coronavirus genomesmany countries in the order of several thousand total, some less than a hundred.
Disparities like this are common. In many places, across a wide range of topics, a lot of data goes unmeasured or omitted: prevalence of mental illness, National GDPand even registration of deaths and their causes. Instead, it must be estimated with a wide range.
It is difficult and expensive for small research groups to collect data on their own, so they tend to collect what is convenient rather than comprehensive. For example, in psychology, research often “FREAK“—Coming from White, Educated, Industrialized, Wealthy, and Democrat participants. Historically, data has come from anywhere where records are common; in economics, where businesses have registered detailed accounts of their income and expenditure.
Different researchers measure the same data in different ways. Some people contacted by multiple research groups are looking at the same questions, while others are not seen.
Without data that is measured in a standard way, it is difficult to answer questions about whether things are different and why such differences may be present. For example, is anxiety more common in richer countries, or more likely to be detected? Are from The condition is undiagnosed in many countries and surveys are rareWe don’t have a clear answer.
This shows us one way to accelerate science: Large organizations, such as governments and international organisations, should collect and share data regularly rather than leaving the burden on teams small study. It’s a classic example of “advantage of scale,” where larger organizations can use their resources to build tools to easily measure, share, and maintain data, and cheaper at a scale that smaller teams can’t do.