Changes in Prevalence and Antibiotic Resistance of Haemophilus influenzae in Nanjing, China Before, During, and After the COVID-19 Pandemic
Background: During the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) suppressed the transmission of respiratory pathogens. Following the relaxation of NPIs, the epidemiological characteristics of respiratory pathogens has shifted substantially. Chinese surveillance data reveal a rising isolation rate of Haemophilus influenzae, necessitating a clearer understanding of the pandemic's impact on the prevalence and antibiotic resistance of this pathogen.Aim: To investigate changes in the prevalence and antibiotic resistance of H. influenzae clinical isolates in Nanjing, China, before, during, and after the COVID-19 pandemic.Methods: We retrospectively analyzed epidemiological and antibiotic resistance data from 805 clinical H. influenzae isolates, collected in Nanjing, spanning pre-pandemic (2017-2019), pandemic (2020-2022), and post-pandemic (2023-2024) periods. Whole-genome sequencing (WGS) was performed on 46 randomly selected isolates (stratified by period: n = 14, 12, 20) to determine serotypes, sequence types (STs), resistance determinants, and virulence factors.Results: After the COVID-19 pandemic, the isolation rate of H. influenzae increased, with a demographic shift toward elderly patients. Susceptibility to ampicillin, cefuroxime, and azithromycin progressively declined, while remaining high to meropenem and levofloxacin. The proportion of beta-lactamase-positive isolates rose compared to the pre-pandemic period. Genomic analysis confirmed that all sequenced isolates were nontypeable H. influenzae (NTHi) and identified 26 distinct STs, with the ST-107 complex being dominant. Key antibiotic resistance genes, such as mutated ftsI and blaTEM-1, as well as multiple virulence genes, were detected.Conclusion: The post-pandemic period is marked by increased prevalence and heightened antibiotic resistance in H. influenzae. Continuous monitoring of resistance and virulence is essential to inform effective control strategies.