Login / Signup

Pneumonia hospitalizations of children aged <2 years in Poland before (2013-2016) and after (2017-2018) universal mass vaccination with 10-valent pneumococcal non-typeable Haemophilus influenzae protein D conjugate vaccine.

Amit B BhavsarJanusz ZaryczańskiAnna WasilewskaDelphine SaragoussiRaghavendra DevadigaChris ColbyEnas BaharJacek Wysocki
Published in: Human vaccines & immunotherapeutics (2022)
As infection with Streptococcus pneumoniae is an important cause of pneumonia in children, the World Health Organization recommends childhood pneumococcal conjugate vaccines (PCVs). In January 2017, PCV universal mass vaccination (UMV) was introduced in Poland for children aged <2 years. The objective of this study was to estimate and describe the trends in the incidences of various types of pneumonia hospitalizations in Poland before (2013-2016) and after (2017-2018) introduction of the UMV program. The study was conducted at the regional hospitals of Opole and Bialystok and included all hospitalized children aged <2 years with a primary or secondary diagnosis of pneumonia in their electronic medical records. Pneumonia diagnoses were identified based on International Classification of Diseases 10 th revision (ICD-10) codes for bacterial, viral, and other/unknown-cause pneumonias. The effect of the implementation of PCV UMV was modeled via an inferential multivariate model. Among 4,168 children included in the study, 64.3% were admitted before PCV UMV. The number of radiograph-confirmed likely bacterial pneumonia cases varied between 55 and 176 cases per 100,000 person-years, and no trend was observed over time. However, inferential modeling showed statistically significant decreasing trends in the incidence rates of bacterial-coded pneumonia (28.48%), viral-coded pneumonia (35.36%), all-cause pneumonia (24.60%), and radiograph-confirmed likely non-bacterial pneumonia (24.98%) among children eligible for UMV. This might be the first indication of the impact of the PCV UMV program in Poland.
Keyphrases
  • young adults
  • respiratory failure
  • community acquired pneumonia
  • healthcare
  • machine learning
  • quality improvement
  • sars cov
  • intensive care unit
  • deep learning
  • early life
  • acute respiratory distress syndrome