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Peer-reviewedCC BY 4.0Journal of Clinical Medicine

From Prevalence to Incidence: Validation of Healthcare-Associated Infection Incidence Estimations from Prevalence Data in a Serbian University Hospital

  • Nikola Milenkovic1,2
  • Ljiljana Markovic-Denic3,4
  • Sonja Novak1,2
  • Bojan Stanojevic2
  • Dane Krtinić5,6
  • Gorana Nedin Rankovic5
  • Aleksandar Nikolic7,8
  • Vladimir Nikolić3
  • Aleksandar Rankovic1,9
9 affiliations
  1. 1Department of Infectious Diseases and Epidemiology, Faculty of Medicine, University of Niš, 18000 Niš, Serbia
  2. 2Department of Sanitary and Epidemiological Surveillance, University Clinical Center Niš, 18000 Niš, Serbia
  3. 3Institute of Epidemiology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia
  4. 4Department of Healthcare-Associated Infections Prevention, University Hospital Medical Center “Bezanijska Kosa”, 11070 Belgrade, Serbia
  5. 5Department of Pharmacology with Toxicology, Faculty of Medicine, University of Niš, 18000 Niš, Serbia
  6. 6Clinic of Oncology, University Clinical Center Niš, 18000 Niš, Serbia
  7. 7Department of Surgery and Anesthesiology with Reanimatology, Faculty of Medicine, University of Niš, 18000 Niš, Serbia
  8. 8Clinic for Anesthesia and Intensive Care, University Clinical Center Niš, 18000 Niš, Serbia
  9. 9Clinic for Infectious Diseases, University Clinical Center Niš, 18000 Niš, Serbia
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Abstract

Introduction: Continuous prospective surveillance is considered the reference method for monitoring healthcare-associated infections (HAIs), but it requires substantial personnel and organizational resources. Point prevalence surveys provide a simpler alternative, although they primarily measure prevalence rather than incidence. The aim of this study was to evaluate the validity of the estimation of cumulative incidence of healthcare-associated infections (HAIs) from a point prevalence survey (PPS) across different hospital wards. Methods: A HAI PPS was conducted between 14 November and 2 December 2022, at the University Clinical Center Nis, Serbia, using the European Centre for Disease Prevention and Control (ECDC) protocol. Data from 774 patients were analyzed. Prevalence data from the Surgical Intensive Care Unit (SICU) and the Orthopedics and Traumatology department were converted into estimated cumulative incidence using the Rhame and Sudderth formula. These estimates were compared against the actual 2022 cumulative incidence obtained via continuous surveillance. Results: The overall HAI prevalence was 3.6% (28 HAIs among 27 patients; 95% CI: 2.5–5.2%). In the SICU, the formula-derived calculated incidence (5.3 per 100 admissions) demonstrated an excellent fit with the observed continuous surveillance incidence (5.54 per 100 admissions; ratio: 0.96), falling well within its 95% CI (4.24–7.22%). Conversely, in the Orthopedics department, the formula significantly overestimated the true incidence by a factor of 10.7 (2.6 vs. 0.24 per 100 admissions), lying far above the upper limit of the observed 95% CI (0.09–0.62%). Conclusions: Converting prevalence data into cumulative incidence estimates is an accurate tool for estimating HAI incidence in stable, high-risk environments like intensive care units. However, it should be applied with extreme caution in low-prevalence specialty wards, where small sample sizes and individual outliers can lead to profound misestimation.

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Cite

BibTeXRIS
BibTeX
@article{milenkovic2026from,
  title = {{From Prevalence to Incidence: Validation of Healthcare-Associated Infection Incidence Estimations from Prevalence Data in a Serbian University Hospital}},
  author = {Nikola Milenkovic and Ljiljana Markovic-Denic and Sonja Novak and Bojan Stanojevic and Dane Krtinić and Gorana Nedin Rankovic and Aleksandar Nikolic and Vladimir Nikolić and Aleksandar Rankovic},
  journal = {Journal of Clinical Medicine},
  year = {2026},
  month = oct,
  doi = {10.3390/jcm15207981},
  url = {https://www.mdpi.com/2077-0383/15/20/7981},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - From Prevalence to Incidence: Validation of Healthcare-Associated Infection Incidence Estimations from Prevalence Data in a Serbian University Hospital
AU  - Nikola Milenkovic
AU  - Ljiljana Markovic-Denic
AU  - Sonja Novak
AU  - Bojan Stanojevic
AU  - Dane Krtinić
AU  - Gorana Nedin Rankovic
AU  - Aleksandar Nikolic
AU  - Vladimir Nikolić
AU  - Aleksandar Rankovic
PY  - 2026
DA  - 2026/10/01
JO  - Journal of Clinical Medicine
DO  - 10.3390/jcm15207981
UR  - https://www.mdpi.com/2077-0383/15/20/7981
AB  - Introduction: Continuous prospective surveillance is considered the reference method for monitoring healthcare-associated infections (HAIs), but it requires substantial personnel and organizational resources. Point prevalence surveys provide a simpler alternative, although they primarily measure prevalence rather than incidence. The aim of this study was to evaluate the validity of the estimation of cumulative incidence of healthcare-associated infections (HAIs) from a point prevalence survey (PPS) across different hospital wards. Methods: A HAI PPS was conducted between 14 November and 2 December 2022, at the University Clinical Center Nis, Serbia, using the European Centre for Disease Prevention and Control (ECDC) protocol. Data from 774 patients were analyzed. Prevalence data from the Surgical Intensive Care Unit (SICU) and the Orthopedics and Traumatology department were converted into estimated cumulative incidence using the Rhame and Sudderth formula. These estimates were compared against the actual 2022 cumulative incidence obtained via continuous surveillance. Results: The overall HAI prevalence was 3.6% (28 HAIs among 27 patients; 95% CI: 2.5–5.2%). In the SICU, the formula-derived calculated incidence (5.3 per 100 admissions) demonstrated an excellent fit with the observed continuous surveillance incidence (5.54 per 100 admissions; ratio: 0.96), falling well within its 95% CI (4.24–7.22%). Conversely, in the Orthopedics department, the formula significantly overestimated the true incidence by a factor of 10.7 (2.6 vs. 0.24 per 100 admissions), lying far above the upper limit of the observed 95% CI (0.09–0.62%). Conclusions: Converting prevalence data into cumulative incidence estimates is an accurate tool for estimating HAI incidence in stable, high-risk environments like intensive care units. However, it should be applied with extreme caution in low-prevalence specialty wards, where small sample sizes and individual outliers can lead to profound misestimation.
SN  - 2077-0383
ER  -