Ville Aula at LSE Blogs: “Read the front page of any major newspaper and I guarantee that the latest number of patients who have tested positive for COVID-19 and the number of mortalities will feature heavily. Open your social media accounts and you will quickly encounter graphs that show the mounting numbers of cases in different countries, complemented by modelling projections. These numbers and graphs feed the popular imagination of how well countries are “flattening the curve”, a concept that has brought epidemiological modelling inspired language to everyone’s lips.
Numbers, graphs, and data are thus playing an essential part in how we experience the pandemic. The endless flows of numbers from different countries are meticulously compared with those from others. These comparisons then form the basis to how individual countries are portrayed and ranked in the global pandemic drama.
But, there is also doubt in the air. We distrust the existing numbers and call for ever-more accurate information. For example, there has been a lively debate on how widespread the pandemic has been in China, an issue that connects directly to how tests are administered and cases reported. Equally, numbers from Europe do not provide indisputable or uniform information on the pandemic either, because their collection is subject to vastly different policies, practices, and contexts that make comparisons difficult. We also lack the scientific consensus that would allow us to link the number of mortalities to the prevalence of the virus, yet mortalities are still often taken as the most solid form of information on the pandemic. These doubts have fuelled demands to do systematic population level testing of the virus prevalence, which is just a different way of saying that we need more numbers.
Numbers are thus both the problem and the solution, and we want more of them. However, what makes numbers useful for developing better treatments and policies, does not necessarily lead to the same outcomes when applied to public debate. In the broader sphere of public debate, such tendencies reveal a longing for the veracity of data during times of uncertainty. Even when such calls are founded on demands for transparency in the name of democracy or healthy skepticism of existing data, they are entangled in a faulty logic of data itself eventually providing a solid standing for public debate….(More)”.