We are all aware of the impact COVID-19 has on our daily lives, but what about the impact of COVID on science? The COVID-19 pandemic caused an outbreak of scientific evidence. As of April 2021, the number of unique publications indexed by our living evidence database and created to retrieve COVID-19 publications has exceeded 160,000. In our research, we compared the patterns of scientific publications for the two infections, the occurrence of Zika virus in 2016 and SARS-CoV-2, to assess the evolution of the evidence.

The living evidence database was originally created to obtain publications on the Zika virus. In 2016 we added around 50-60 new articles about the Zika virus to our database every week. We thought it would be an easy transition to move to indexing COVID-19 items in late 2019. However, we were shocked by the sheer volume of articles published, reaching around 2,500 articles per week by the end of April 2021.

To assess the evidence score for the Zika virus, we identified and classified 2,286 publications in 2016. For SARS-CoV-2, however, we have recruited a group of international volunteer scientists with a background in health sciences to deal with the volume of just a random sample of 5,294 (24%) out of 21,990 articles published before May 24, 2020 can be analyzed.

A significant number of the articles indexed were not original.

Proportions of epidemiological study designs
Our results showed that a significant proportion of the articles indexed for both Zika virus (55%) and SARS-CoV-2 (34%) were non-original (comments, basic ratings, opinion papers, etc.). [95% Confidence interval (Cl): 33-35] ). The role of preprints was more important than the Zika virus epidemic at the beginning of the SARS-CoV-2 pandemic.

Case reports and case series accounted for approximately 10% of the total 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.

Studies were conducted in fewer numbers (27 / 5.294 for SARS-CoV-2 and 1 / 2.286 for Zika virus) and at the beginning of the outbreak there were more mathematical modeling studies for 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 epidemiological study designs reported along with non-original articles and reviews. Case-control and cohort studies followed later; This delay was more pronounced in Zika virus research.

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

What is that supposed to mean?
New emerging infectious diseases are quickly accompanied by a lot of published evidence. This is a significant challenge that clinicians, scientists, researchers, and even students must face. Keeping up with the evidence available becomes a complicated task.

The rate at which SARS-CoV-2 evidence has accumulated has been unprecedented. Although we have recruited a large team of seasoned scientists, we have reached a point where we could not categorize all of the evidence retrieved from our database in the first few months after the pandemic.

To address this issue, we believe that using natural language processing methods to classify and categorize evidence is a promising approach for identifying release types not only for SARS-CoV-2 but for future diseases as well. In addition, collaborative crowd-sourcing within scientists in this field could increase the efficiency of the researchers and avoid research waste.

Assessing the evidence on emerging infections can help us determine what types of public health questions we can answer and when.

Assessing the evidence on emerging infections can help us determine what types of public health questions we can answer and when. Further research to assess the evidence for emerging outbreaks could help improve public health responses. By accumulating evidence in certain situations like the COVID-19 pandemic, the use of certain resources can save time.

Because of the amount of evidence released each day about this endless pandemic, students, clinicians, and stakeholders must approach the published studies with caution. Some of the studies available may provide incorrect results or conclusions, and people may choose what matches their beliefs. We need critical eyes to review all available evidence.

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