Multidrug resistance analysis method for pathogens of cow mastitis based on weighted-association rule mining and similarity comparison

Mastitis is one of the most common diseases and causes the greatest economic loss in dairy farming. Antibiotics are the most effective drugs to prevent and treat bacterial infection of mastitis. However, yet the growing problem of drug resistance, especially multidrug resistance (MDR), poses a great threat to disease control. To understand the MDR rules in bacteria of cow mastitis from national level, the main bacteria from cows with mastitis in large-scale farms were isolated and identified in China, and then drug sensitivity tests were conducted to establish a drug resistance data set. Aiming at the problem of numerous and disordered drug resistance data and lack of extensive correlations, a weighted Apriori association rule mining algorithm in conjunction with the bacterial drug resistance prevalence is proposed. We analyzed the associations between different antibiotics of key bacteria, extracted and visualized the key trends of high resistance prevalence and frequent occurrence, and discovered MDR patterns. Finally, a similarity comparison method based on Euclidean measurement was proposed to compare the relative MDR rules of different bacteria from the overall level with support, confidence, and promotion as characteristic parameters. The drug resistance data set showed that staphylococcus were the main bacteria isolated from dairy cow mastitis in China. Then based on the association rule algorithm, the important rules between different antibiotics resistance in this dataset were identified. In addition, the MDR patterns of different bacteria were visualized and analyzed by using the chord diagram. The results showed the bacteria are highly resistant to penicillin, gentamicin, and ampicillin, and most other antibiotics were linked with these three antibiotics. Finally, the high correlations and main rules in different bacteria were confirmed by a similarity comparison method. The assessment model and conclusions of this study are potentially valuable for assessing the evolution of MDR patterns, providing a scientific basis for relevant authorities to guide the rational use of antibiotics in the farming industry.