Background: At the time of the COVID-19 epidemic, it is useful to look at what lessons (digital) history can give us about the past pandemics and dealing with them. We show that the Google Ngram (GNV) can discover
hidden patterns in history and, therefore, can be used as a window into history. By using the approach of Digital Humanities, we analysed the epidemiological literature on the development of the Russian flu pandemic for hints on how the COVID-19 might develop in the following years.
Objective: Our study is searching for evidence that the COVID-19 is not a unique phenomenon in human history. We are testing the hypothesis that the flu-like illness that caused loss of taste and smell in the late 19th
century (Russian flu) was caused by a coronavirus. We are aware that it is difficult to formulate a hypothesis for a microbiological aetiology of a pandemic that occurred 133 years ago. But differentiating an influenza virus infection from a COVID-19 patient purely on the clinical ground is difficult for a physician because the symptoms overlap. The most crucial observation of similarities between the Russian flu pandemic and COVID-19 is the loss of smell and taste (anosmia and ageusia). The objective was to calculate the ratio of increasing to decreasing trends in the changes in frequencies of the selected words representing symptoms of the Russian flu and COVID-19.
Methods: The primary methodological concept of our approach is to analyse the ratio of increasing to decreasing trends in the changes in frequencies of the selected words representing symptoms of the Russian flu and COVID-19 with the Google NGram analytical tool. Initially, keywords were chosen that are specific and common for the Russian flu and COVID-19. We show the graphic display on the Y-axis what percentage of words in the selected corpus of books (collective memory) over the years (X-axis) make up the word. To standardise the data, we requested the data from 1800 to 2019 in English, German and Russian (to 2012) book corpora and focused on the ten years before, during and after the outbreak of the Russian flu. We compared this frequency index with “non-epidemic periods” to test the model’s analytical potential and prove the signification of the results.
Results: The COVID-19 is not a unique phenomenon because the Russian flu was probably the coronavirus infection. Results show that all the three analysed book corpora (including newspapers and magazines) show the increase in the mention of the symptoms “loss of smell” and “loss of taste” during the Russian flu (1889-1891), which are today undoubtedly proven to be key symptoms of COVID-19.