LOGISTIC REGRESSION MODEL FOR PREDICTING MICROBIAL GROWTH AND ANTIBIOTIC RESISTANCE OCCURRENCE IN SWIFTLET (Aerodramus Fuciphagus) FAECES

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