Enhanced infection control measures during the COVID-19 pandemic significantly reduced healthcare-associated infections in a Chinese cancer hospital: a Bayesian structural time series analysis
Year: 2026
Type: article
Abstract: Background Enhanced infection control measures were widely implemented during the COVID-19 pandemic, but their quantitative impact on healthcare-associated infections (HAIs) in specialized cancer hospitals remains insufficiently evaluated. Methods Monthly surveillance data from January 2016 to June 2022 (78 time points) were collected from a tertiary cancer hospital in Sichuan Province, China. A Bayesian structural time series (BSTS) model was used to construct a counterfactual prediction of HAI incidence under the scenario without enhanced measures, and the causal effect was estimated by comparing observed and predicted values. Model convergence was assessed by Geweke and Heidelberger–Welch diagnostics. Robustness was further assessed through sensitivity analyses on the outcome scale (counts versus incidence rates), the definition of the intervention date, and alternative covariate sets. Results Enhanced infection control measures (June 2020–June 2022) were associated with a cumulative reduction of 525 HAI cases [95% credible interval (CrI): 203–1,051] relative to the pre-pandemic trend, corresponding to a 36% relative reduction (95% CrI: 19–54%; posterior tail probability p < 0.01). Subgroup analyses showed significant reductions in respiratory system HAIs (357 cases; 38% reduction) and urinary system HAIs (56 cases; 46% reduction), while the reduction in oral cavity HAIs was not statistically significant. Conclusion Enhanced infection control measures significantly reduced HAI incidence, particularly in the respiratory and urinary systems. These findings provide evidence for optimizing infection control policies in specialized cancer hospitals in the post-pandemic era.
Source: Frontiers in Public Health
Institution: Sichuan Cancer Hospital
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7225628253