Analyzing the dynamics of complicated and uncomplicated appendicitis during the COVID-19 pandemic in Seoul, Korea: a multifaceted time series approach

Abstract

Objectives: This study investigated the impact of the coronavirus disease 2019 (COVID-19) pandemic and associated control strategies on the incidence of appendicitis in Seoul, using data from 2018 to 2020 from Korea's National Health Insurance.

Methods: We analyzed records of total, complicated, and uncomplicated appendicitis cases, as well as the ratio of complicated to uncomplicated appendicitis, using natural spline and piecewise regression models to identify trends and breakpoints. Bayesian structural time-series (BSTS) models were used to evaluate the causal impact of social distancing on appendicitis incidences.

Results: The spline regression analysis indicated decreasing trends in both total and uncomplicated appendicitis cases. Conversely, the incidence of complicated appendicitis and the ratio of complicated to uncomplicated cases increased. Breakpoints for a decline in uncomplicated appendicitis and a rise in the ratio occurred at 31 weeks in 2020 (95% confidence interval [CI], 23.2 to 38.8) and at 33.9 weeks (95% CI, 28.3 to 39.6), respectively. The BSTS model demonstrated a 7.8% reduction in total appendicitis cases (95% credible interval [CrI], -12.1 to -3.3). It also showed a 17.4% decrease in uncomplicated cases (95% CrI, -22.2 to -12.3) and increases of 12.8% (95% CrI, 4.9 to 22.0) in complicated cases and 39.0% (95% CrI, 27.0 to 53.3) in the ratio of complicated to uncomplicated appendicitis.

Conclusions: The COVID-19 pandemic resulted in a decrease in both total and uncomplicated appendicitis cases, while the number of complicated cases increased. Reduced medical visits likely accounted for these changes. Strategies are needed to manage changes in disease pathophysiology resulting from altered healthcare utilization during health crises.

Keywords: Appendectomy; Appendicitis; COVID-19; Seoul.

Figure 1.

Time series graph of weekly coronavirus disease 2019 (COVID-19) incidence rates in Seoul. The graph includes dashed lines indicating the onset of the first COVID-19 case and the implementation date of the social distancing policy due to the surge in COVID-19 cases.

Figure 2.

Graph showing the weekly counts of total (A), complicated (B), and uncomplicated (C) appendicitis cases, along with the ratio of complicated to uncomplicated cases (D). Weekly counts are marked with dots, and these data points are fitted with a natural spline curve, represented by a red line. COVID-19, coronavirus disease 2019.

Figure 3.

Piecewise regression graph identifying change points in the weekly counts of total (A), complicated (B), uncomplicated (C) appendicitis, and the ratio of complicated to uncomplicated appendicitis (D). Statistical change points occurring after the introduction of coronavirus disease 2019 (COVID-19) are indicated on the graph.

Figure 4.

Time series graph using Bayesian structural time series to demonstrate the causal impact of social distancing policies introduced in response to the spread of coronavirus disease 2019 on appendicitis-related metrics. This graph includes series for total (A), complicated (B), and uncomplicated appendicitis (C), as well as the ratio of complicated to uncomplicated cases (D), highlighting significant changes after policy implementation.