Journal of Infection and Public Health (Jan 2025)
Pertussis clinical profile shift, severity, prediction in a tertiary hospital: A comparative study before, during, and after COVID-19 in Southern China
Abstract
Objective: To analyze the epidemiological characteristics, clinical manifestations, antimicrobial resistance and develop a predictive model for severe pertussis spanning five years – before, during, and after the COVID-19 pandemic – in Shenzhen children’s hospital in southern China, aiming to provide insights into the pandemic impact and control measures on the pertussis disease profile. Methods: Demographic, clinical, vaccination, and laboratory data were collected for patients who tested positive for pertussis by polymerase chain reaction and/or culture from January 1, 2019, to March 30, 2024. Analysis included changes in demographic and clinical features, indicators of severe cases, and resistance patterns over the study period. Results: During this period, 3963 patients were diagnosed, with 79 severe (PICU admitted) cases; 1433 isolates underwent antimicrobial susceptibility testing. In late 2023, pertussis cases began to increase. From 2019 to 2024, the proportion of cases among 4–6 year olds rose from 4.9 % to 28.6 %, and among 7–11 year olds from 0.7 % to 21.2 %. Macrolide resistance surged from 46.5 % in 2019 to 97.3 % in 2024, with 80 % of resistant hospitalized cases initially treated with macrolides. Clinical severity and co-infection increased post-pandemic, with a larger number of cases necessitating antibiotic changes and enhanced supportive care. Vaccination protected against severe disease. Indicators such as white blood cell count, lymphocyte to neutrophil ratio, platelet count, cyanosis and pneumonia predicted disease severity. Conclusions: Post-pandemic, pertussis cases shifted from infants to school-aged children, with increased clinical severity and high macrolide resistance. Urgent measures are needed to optimize vaccination schedules and develop management strategies addressing and changing epidemiological patterns.
