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Insights into Clustering Patterns in Romania's 2020-2024 Measles Cases
Valerian-Ionuț Stoian1,2, Cătălin Pleșea-Condratovici3, Mădălina Nicoleta Matei4
1Medical Department, Faculty of Medicine & Pharmacy, "Dunărea de Jos" University of Galați, 800008 Galați, Romania.
Abstract:
Background and objectives: During an outbreak, measles cases tend to aggregate into increasingly bigger clusters that show specific characteristics, different from the non-cluster cases. As the measles threat continues throughout Europe in 2025 with a high notification rate in Romania as well, exploring how clustering affects the disease propagation can provide additional insights into how to improve measles surveillance and control. Methods: National measles cases from 2020 to 2024 have been split into cluster (at least three related cases) and non-cluster-related cases and analyzed comparatively based on vaccination status, disease-related data (hospitalization) and patient-related data (age, location). Large outbreaks with at least 150 cases, allowing for more comprehensive R0 analysis, have been described and the basic reproduction numbers computed for each of them. Results: There are statistically significant differences in vaccination status, age, and hospital stay between outbreak and non-outbreak cases. Large outbreaks (≥150 cases) show a high degree of variability, with R0 values varying from as low to 1 to as high as 3.92, indicating limited measles transmission control. Conclusions: The findings in this research highlight the critical impact of clustering on measles transmission dynamics during outbreaks. Significant differences in vaccination status, age, and hospitalization rates between cluster and non-cluster cases underscore the importance of targeted surveillance and intervention strategies while the wide range of R0 values observed in large outbreaks points to inconsistent control measures and emphasizes the need for strengthened vaccination campaigns and improved outbreak response protocols to better contain measles spread.
Insights
Measles clusters significantly impact disease spread, showing distinct characteristics from non-cluster cases. Understanding these differences is key to improving measles surveillance and control strategies.
Area of Science:
- Epidemiology
- Public Health
- Infectious Disease Dynamics
Background:
- Measles outbreaks exhibit clustering, with cases showing unique traits compared to non-clustered cases.
- Ongoing measles threats in Europe, particularly Romania, necessitate understanding clustering's role in disease propagation for enhanced surveillance and control.
Purpose of the Study:
- To analyze how measles case clustering affects disease transmission dynamics.
- To compare characteristics of clustered versus non-clustered measles cases.
- To assess measles transmission control effectiveness through reproduction number (R₀) analysis in large outbreaks.
Main Methods:
- National measles case data (2020-2024) were categorized into cluster (≥3 related cases) and non-cluster groups.
- Comparative analysis included vaccination status, hospitalization, age, and location.
- Basic reproduction numbers (R₀) were computed for large outbreaks (≥150 cases).
Main Results:
- Statistically significant differences were found in vaccination status, age, and hospitalization duration between clustered and non-clustered cases.
- Large measles outbreaks (≥150 cases) displayed high R₀ variability (1.0–3.92), indicating inconsistent transmission control.
- Clustering significantly influences measles transmission patterns during outbreaks.
Conclusions:
- Clustering critically impacts measles transmission dynamics, with distinct case profiles.
- Differences in vaccination, age, and hospitalization highlight the need for targeted interventions.
- Varied R₀ values in large outbreaks underscore the necessity for strengthened vaccination campaigns and improved outbreak response protocols.
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