COVID-19 Preprints: How the Topics Change (June Update)
To the lockdown consequences and drug trials
When society is in a global emergency, researchers are all the more inspired to publish their findings fast and open-access. An available option is to publish a preprint, a paper that has not yet received quality evaluation but quickly becomes available online. In this post we show how the preprints on the novel coronavirus SARS-CoV-2 and COVID-19 (the disease caused by it) split into topics, and how these topics have changed between February and June 2020. See page 3 for our methods and data description.
In this overview, we refer to systematic reviews and meta-analyses where possible. Still, we should stress that preprints report the research that has not been certified through peer review and thus should not be used to guide policies or practice.
In the May overview, we identified two notable directions of COVID-19 research: modeling virus transmission and the impact of non-pharmaceutical interventions, and emerging research on socio-psychological consequences of the pandemic. At the same time, large blocks of literature on virology and clinical medicine remained.
Today we are exploring how the prominence of different topics in the papers has changed over the last month. We represent preprints’ titles and abstracts as the topics they discuss. The algorithm statistically estimates how closely the words in these texts are related, and automatically groups them into clusters. We then interpret these clusters as substantive topics.
We use the structural topic modeling algorithm. For each document, it shows which topics are specific to it, and for each topic – which words are the most relevant for it. Thus, we can evaluate how prominent a topic is in our texts. The algorithm also allows us to see how the distribution of topics is affected by the characteristics of the text: in our case, the platform where the preprint is published, and the date of publication.
Topics of Preprints
On the texts of abstracts and titles, we built a model that identified 20 topics in the pool of preprints. In Figure 1, these topics are sorted by how pronounced their presence is in the data. Each topic is accompanied by the five most relevant terms.
The topics are described with the five most relevant terms, reduced to stems. Click on the picture to see the full resolution (opens in a new tab)
The topic of socio-economic impact of the epidemic continues to dominate the body of preprints. Statistical data begin to appear, for example, on the state of the economy during the pandemic and lockdown measures. Therefore, unlike in May, studies are devoted not only to crime and home violence but also to the influence of the epidemic on the economy and life of various social groups, as well as the influence of social characteristics on behavior in a pandemic (for more details, see page 2 of the review).
Compared to others, the topics about the psychological impact of the epidemic and personal protective equipment became more pronounced. During quarantine, data were collected for longitudinal studies of stress and anxiety among the general population and medical personnel in particular. As for masks and personal protective equipment (PPE), if previous work mainly analyzed PPE in the context of hospitals, with the countries gradually lifting the restrictions on social life, data appeared on how wearing masks affects the spread of the virus in society.
Thematic Contexts
The contexts of topics discussed in the preprints can be estimated from Figure 2. The size of the label in this network corresponds to the relative popularity of the respective topic in the corpus of preprints, as in Figure 1. The thickness of lines shows the strength of the association between the topics, based on their common occurrence in preprints.
Links indicate that the topics have appeared together in the same preprint abstract(s), with the width of the links corresponding to the strength of the association (only the links weighted more than 0.05 are shown). Label sizes correspond to the overall popularity of the topics. Click on the map to see the full resolution (opens in a new tab)
Compared to the previous review, studies of the socio-economic consequences of the epidemic have become more clearly related to non-pharmaceutical interventions. Also noticeable are the changes in the biological and medical parts of the map. Preprints about the clinical manifestations of the disease are getting closer to studies of the molecular mechanisms and genetics of the virus. This is because there appear meta-analyses and data on the clinical effects of potential drugs against COVID-19, as well as how drugs for other diseases interact with the virus.
Take an example of drugs for hypertension: angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs). They are prescribed to prevent the harmful effects of the hormone angiotensin on the blood vessels. However, to destroy angiotensin, these drugs stimulate the production of ACE2, which is the “entry point” of the coronavirus into the body. Because of this, concerns were expressed whether ACEIs or ARBs would worsen the condition of patients with COVID-19, making them more vulnerable to the virus.
However, a number of studies and systematic reviews have noted that these drugs do not increase the risk of mortality while reducing the severity of the disease (Abdulhak et al. 2020; Choi et al. 2020; Diaz-Arocutipa, Saucedo-Chinchay, and Hernandez 2020). In a new preprint of a systematic review by Qu et al. (2020), there is also no evidence that drugs worsen the condition of patients. Conversely, evidence has been found that taking ACEIs/ARBs reduces the risk of death in patients. Researchers recommend at least not stop taking these drugs if people were already on them before getting COVID-19.
Read on page 2 how the relative prominence of topics changes over time, and what topics are special to the preprints published in June.