The Journal of hospital infection · 2026
Long-term changes in healthcare-associated infections following the COVID-19 pandemic: a nationwide interrupted time-series analysis.
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Chumchuen K, Sukvichian J, Chusri S
Аннотация
BACKGROUND: Hospital-acquired infections (HAIs) are major causes of morbidity and mortality worldwide. During the COVID-19 pandemic, healthcare facilities were heavily disrupted both in practice and capacity aspects. The long-term effect of such disruption on HAIs in the postpandemic period remains unclear.
AIM: The aims of this study were to investigate the national spatiotemporal trends of HAI admission following the COVID-19 pandemic and to identify associated patient and healthcare factors.
METHODS: Using national admission data, we conducted an interrupted time-series analysis of monthly HAI admissions and assessed spatial pattern. Patient characteristics and history of medical procedures before and breakpoint were assessed using univariate analyses and multi-variable logistic regression.
FINDINGS: A significant slope breakpoint to upward slope in HAI admissions was detected in March of 2022 (P < 0.001). The spike in trends was noticeably higher than the trend forecasted by the autoregressive integrated moving average model. Postbreakpoint admissions were associated with a higher burden of cardiometabolic and renal comorbidities and increased exposure to invasive procedures. Chronic kidney disease and haemodialysis demonstrated the largest effect sizes. Spatial clustering was weak (Moran's I: 0.060-0.134), although higher HAI rates were observed in Northern and Northeastern regions.
CONCLUSION: HAI incidence increased and remained elevated following the COVID-19 pandemic, likely reflecting healthcare system disruption, delayed care, and increasing patient complexity. Strengthening healthcare resilience and continuity of chronic disease management will be essential to mitigate future risk.
AIM: The aims of this study were to investigate the national spatiotemporal trends of HAI admission following the COVID-19 pandemic and to identify associated patient and healthcare factors.
METHODS: Using national admission data, we conducted an interrupted time-series analysis of monthly HAI admissions and assessed spatial pattern. Patient characteristics and history of medical procedures before and breakpoint were assessed using univariate analyses and multi-variable logistic regression.
FINDINGS: A significant slope breakpoint to upward slope in HAI admissions was detected in March of 2022 (P < 0.001). The spike in trends was noticeably higher than the trend forecasted by the autoregressive integrated moving average model. Postbreakpoint admissions were associated with a higher burden of cardiometabolic and renal comorbidities and increased exposure to invasive procedures. Chronic kidney disease and haemodialysis demonstrated the largest effect sizes. Spatial clustering was weak (Moran's I: 0.060-0.134), although higher HAI rates were observed in Northern and Northeastern regions.
CONCLUSION: HAI incidence increased and remained elevated following the COVID-19 pandemic, likely reflecting healthcare system disruption, delayed care, and increasing patient complexity. Strengthening healthcare resilience and continuity of chronic disease management will be essential to mitigate future risk.