dr Ridha Wahyutomo, M.Arch

The core hypothesis of the study is integrating Computational Fluid Dynamics (CFD) simulation with microbiological data enhances the predictive accuracy of airflow-based infection risk assessment in hospital isolation rooms.

There are two data sources
a. Environmental & Architectural Data
• Location: A retrofitted COVID-19 isolation room in Pati Islamic Hospital, Central Java, Indonesia.
• Measurements: Room geometry, temperature (28.6°C), humidity (68.8%), pressure (-6 Pa), air velocity (11.8 m/s), and ACH (18.87) using calibrated equipment (hot wire anemometer, magnehelic gauge, etc.).
• CFD Modeling: Autodesk CFD was used to simulate airflow based on room design and ventilation layout.

b. Microbiological Data
• Sampling: Passive air sampling via settle plates at five strategic points (e.g., patient bed, entrances, inner corners).
• Analysis: Colony Forming Units (CFU) were counted after 24 hour incubation at 37°C.
• Total Contamination: 177 CFU/m³ across the room, with highest values near inner corners (75 CFU).

The Data Show
a. Airflow-Microbe Correlation
• Low velocity zones (<0.025 m/s), especially near floor and inner corners, correlated with higher microbial counts (e.g., 75 CFU).
• Higher velocity zones (>0.05 m/s) at head level (160 cm) correlated with lower microbial presence, showing effective contaminant removal.
b. Statistical Analysis
• Power law regression showed a strong inverse relationship
CFU density=185.4×(Velocity)−0.67
The model demonstrated strong predictive capability (R² = 0.79, RMSE = 12.3 CFU/m³; F(1,3) = 18.7, p = 0.005), confirming that incremental increases in airflow velocity significantly reduce microbial contamination.

Interpretation and Use of the Data
a. Validation of CFD for Infection Control
• CFD effectively predicted infection risk zones by mapping stagnation areas where microbes settled, validating its use as a preventive design tool in healthcare ventilation planning.
b. Practical Implications
• Redesign recommendations: ceiling mounted HVAC systems, dynamic airflow targeting, and HEPA filters.
• Policy alignment: Findings show gaps between existing hospital infrastructure and Indonesia’s Ministry of Health standards (Permenkes 40/2022).
• Cross-application: Useful for rapid retrofitting of spaces during pandemics, e.g., hotels or emergency departments into temporary isolation rooms.