Evaluasi Robustness Metode Deteksi Cepat Berbasis MPN untuk Legionella pneumophila terhadap Gangguan Mikroflora Non-Target pada Sampel Air dari Menara Pendingin

Abstract

Legionellosis is an infection caused by Legionella pneumophila, commonly transmitted through artificial water systems such as cooling towers. Early detection of this pathogen is crucial, particularly in high-risk facilities. This study aimed to assess the robustness of a rapid detection method based on the Most Probable Number (MPN) principle, focusing on the effectiveness of pretreatment in reducing interference from non-target microorganisms. A total of 30 positive trays from Legiolert™ tests were subcultured on Tryptic Soy Agar (TSA) to identify any surviving non-target microbes. Robustness was defined by the proportion of trays without non-target microbial growth. Results showed a robustness rate of 93.33%, with full robustness (100%) observed in low and moderate microbial load groups, and 75% in the high-load group. A non-parametric binomial test using SPSS was performed to evaluate the statistical significance of the deviation from the robustness cut-off. The resulting p-value was 0.446 (p > 0.05), indicating no statistically significant difference. These findings demonstrate that the Legiolert™ method maintains reliable performance even in complex sample matrices, supporting its use in routine water quality monitoring in accordance with Indonesian Ministry of Health Regulation No. 2 of 2023.