An epidemic story caused by an epidemic: Zika and SARS-CoV-2

We are all aware of the effect COVID-19 has had on our day-to-day lives, but what about the effects of COVID on academia? The COVID-19 pandemic has sparked an explosion of scientific evidence. In April 2021, the number of unique publications indexed by our living evidence database, created to retrieve COVID-19 publications, has exceeded 160,000. In our research, we compared the models of scientific publications for the two infections, the emergence of the Zika virus in 2016 and SARS-CoV-2, to assess the evolution of the evidence.

The Living Evidence Database was originally created to retrieve publications on the Zika virus. In 2016, we included approximately 50-60 new Zika virus articles per week in our database. We thought it would be an easy transition to move to indexing COVID-19 articles at the end of 2019. However, we were shocked at the volume of published articles retrieved, which stood at around 2,500 articles per week at the end of April 2021.

To assess the evaluation of the evidence for Zika virus, we identified and classified 2,286 publications in 2016. However, for SARS-CoV-2, although we did recruit a group of international volunteer scientists with a background in science and technology. health to cope with the volume, we were only able to analyze a random sample of 5,294 (24%) out of 21,990 articles published before May 24, 2020.

A substantial proportion of the articles indexed were not original.

Proportions of epidemiological study plans
Our results showed that a substantial proportion of the articles indexed were not original (commentaries, core reviews, opinion pieces, etc.) for Zika virus (55%) and SARS-CoV-2 (34% , [95% Confidence interval (Cl): 33-35]). The role of preprints was more important at the start of the SARS-CoV-2 pandemic than the Zika virus outbreak.

Case reports and case series made up about 10% of all evidence for SARS-CoV-2 (10.7% [95% CI: 9.9-11.6]) and Zika virus (9.7%) research.

Case-control and cohort studies accounted for 4.0% [95% CI: 3.5-4.6] for SARS-CoV-2 and 0.8% for Zika virus.

Trials appeared in smaller numbers (27/5294 for SARS-CoV-2 and 1/2286 for Zika virus) and at the start of the epidemic there were more mathematical modeling studies for the SARS-CoV-2 (10.1%, [95% CI: 9.3-11.0]), compared to the Zika virus (3.2%).

Time study type trends
Case reports, case series and cross-sectional studies were the first models of epidemiological studies to be reported, along with non-original articles and reviews. Case-control and cohort studies followed later; this delay was more important in the research on the Zika virus.

In vivo and in vitro laboratory studies followed between case reports and observational controlled studies. The trials were the last type of study to be published.

What does all this mean?
With emerging infectious diseases quickly come a large body of published evidence, which is a significant challenge facing clinicians, scientists, researchers and even students. Keeping up to date with the available evidence becomes a complicated task.

The rate of accumulation of evidence for SARS-CoV-2 was unprecedented. Although we recruited a large team of experienced scientists, we reached a point where we could not categorize all the evidence collected by our database during the first months of the pandemic.

To solve this problem, we believe that using natural language processing methods to help classify and categorize evidence seems to be a good idea. promising approach to sorting publications types not only for SARS-CoV-2 but for future emerging diseases. In addition, collaborative crowdsourcing among scientists in the field could increase the efficiency of researchers and prevent waste of research.

Assessing the evidence in emerging infections can help us identify what kinds of public health questions we can answer and when.

Assessing the evidence in emerging infections can help us identify what kinds of public health questions we can answer and when. Further research on assessing evidence during emerging epidemics could help improve the public health response. With the accumulation of evidence during particular situations such as the COVID-19 pandemic, using specific resources can save time.

Due to the amount of evidence published each day on this endless pandemic, students, clinicians and stakeholders should approach published studies with caution. Some of the studies available may provide the wrong results or conclusions, and people can “choose” what fits their beliefs. We need a critical eye to examine all the available evidence.

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