Logistic regression model for predicting microbial growth and antibiotic resistance occurrence in swiftlet (Aerodramus fuciphagus) faeces

Sui Sien, Leong and Lihan, Samuel and Ling, Teck Yee and Hwa, Chuan Chia (2021) Logistic regression model for predicting microbial growth and antibiotic resistance occurrence in swiftlet (Aerodramus fuciphagus) faeces. Journal of Sustainability Science and Management., 16 (4). pp. 113-123. ISSN 2672-7226

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Abstract

This study proposes a logistic model of the environmental factors which may affect bacterial growth and antibiotic resistance in the swiftlet industry. The highest total mean faecal bacterial (FB) colonies counts (11.86±3.11 log10 cfu/ g) were collected from Kota Samarahan in Sarawak, Malaysia, and the lowest (6.71±1.09 log10 cfu/g) from Sibu in both rainy and dry season from March 2016 till September 2017. FB isolates were highly resistant against penicillin G (42.20±18.35%). Enterobacter and Enterococcal bacteria were resistant to streptomycin (40.00±51.64%) and vancomycin (77.50±41.58%). The model indicated that the bacteria could grow well under conditions of higher faecal acidity (pH 8.27), dry season, higher mean daily temperature (33.83°C) and faecal moisture content (41.24%) of swiftlet houses built in an urban area with significant regression (P<0.0005, N=100). The probability of the development of antibiotic resistance (%) increased 0.50 times if the faecal acidity increased by one unit with significant contribution to the prediction (P = 0.012). Understanding how these microbial species react to environmental parameters according to this model, allowed us to estimate their interaction outcomes and growth, especially in an urban environment, which may pose a health hazard to people.

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