Association between the COVID-19 pandemic and inflammatory bowel disease presentation in New York City

In a recent study posted to the medRxiv* preprint server, researchers evaluated the association between new inflammatory bowel disease (IBD) diagnoses in New York City (NYC) and the coronavirus disease 2019 (COVID-19) pandemic.

Study: Epidemiologic Assessment of Pediatric Inflammatory Bowel Disease Presentation in NYC During COVID-19. Image Credit: JARIRIYAWAT/Shutterstock
Study: Epidemiologic Assessment of Pediatric Inflammatory Bowel Disease Presentation in NYC During COVID-19. Image Credit: JARIRIYAWAT/Shutterstock

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Several studies have shown an increased presentation of autoimmune diseases linked with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), such as IBD. It is an autoimmune disorder typically observed in late childhood, and its pathogenesis involves a mix of genetic predisposition, microbial exposure, and infections.

About the study

In the present study, researchers fitted an autoregressive integrated moving average model (ARIMA) to the number of cases of Crohn’s Disease (CD) and Ulcerative Colitis (UC) between January 2016 and March 2020 to forecast the case numbers for the subsequent 21 months (between April 2020 and December 2021), with 80% and 95% prediction intervals using the forecast library.

They retrieved the data for the period between 2015 and 2021 from four collaborating institutions using electronic medical records (EMRs), in particular, the date of diagnosis for 349 CD and 145 UC cases diagnosed in NYC pediatric clinics between 2016 and 2021. They also evaluated the robustness of results to monthly versus quarterly periods, data from three participating institutions for the period between 2011 and 2021.

As demographic variables, gender, birth month/year, and age at diagnosis were available for all the participants; therefore, these were accounted for during the study analysis.

The researchers used the Pearson chi-square test and pairwise proportion tests with Holm’s correction to compare the pre-pandemic versus pandemic periods, taking April 2020 as the first month of the COVID-19 pandemic. Further, they plotted the total cases by month with loess regression and 95% confidence intervals (CIs) using ggplot2 stratified by pandemic versus pre-pandemic diagnosis to show seasonal patterns in IBD diagnoses.

The CD model was ARIMA (0,0,0) with a residual standard deviation of 7.07, a mean absolute scaled error of less than one, and the forecast was uniform across the 80% and 95% prediction intervals. Likewise, the UC model was ARIMA (1,0,0) with a lag-1 autocorrelation (AR1) of 0.30, the residual standard deviation of 2.00, and the forecast varied slightly across the intervals.

Study findings

For UC and CD, ARIMA analysis forecasted an average of 1.91 and 4.65 monthly cases with 80% and 95% prediction intervals, respectively. The Durbin-Watson statistic showed no evidence of AR1 for CD for the pre-or pandemic period and UC for the pandemic period.

Patients diagnosed with IBD during pre-pandemic versus post-pandemic times had similar demographic characteristics, including gender, age at diagnosis, country of residence, ethnicity, and race.

Two participating institutions, viz., Downstate and Maimonides, showed opposing results in terms of IBD cases during the pre-pandemic and pandemic times; however, they did not show any other differences. Accordingly, the former had a larger share of cases during the pandemic than during the pre-pandemic time (9.6% vs. 4.3%); however, the latter had fewer cases during the pandemic than during the pre-pandemic time (10.2% vs. 17.5%).

The authors also observed a significant increase in CD diagnoses in NYC in March and April 2020. In the loess plots, the authors observed more CD diagnoses than expected in June and July 2020 during the pandemic than in the pre-pandemic times.

In Q3 of 2020, the authors noted more CD cases than forecasted; likewise, in Q4 of 2020, there were more UC cases than forecasted. For CD, there were 26 cases compared with the upper limit of 95% prediction interval of 23 in the ARIMA analysis.

Robustness checks using monthly data demonstrated similar rates for the CD and UC cases during July and September 2020 and May and October 2021, respectively. Overall, a trend was apparent towards elevation in UC diagnoses over time, with eight cases compared with the upper limit of 95% prediction interval of 6.1.

Conclusions

Overall, the study findings suggested the possible risk of increased IBD diagnoses among pediatric patients in NYC, especially CD, due to increased SARS-CoV-2 cases. Decreases in SARS-CoV-2 cases did not decrease CD and UC diagnoses, suggesting reduced importance of SARS-CoV-2 infections as a pathogenic IBD trigger or reduced ability to drive IBD pathogenesis. The authors emphasized the need for a follow-up investigation of changes in IBD incidence using the current data infrastructure.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

Journal references:

Article Revisions

  • May 12 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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