2017/04/28 by Maya Tselios, Tselios, Maya, Yeung, Emily
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · #Antibiotic Resistance in Bacteria #Antibiotic Use and Resistance #Bacterial Identification and Susceptibility Testing #CRE #carbapenem #enterobacteriaceae #epidemic #model #resistance #resistant
paper · doi:10.14288/cjur.v2i2.189309
openalex publication_date 2017/04/28 · openalex created_date 2018/02/23 · openalex updated_date 2026/07/28
Mathematical modeling and optimisation using computer programs can efficiently predict the morbidity of a certain disease. Carbapenem-Resistant Enterobacteriaceae, or CRE, is a family of bacteria that are associated with difficult treatment, and, consequently, high mortality. This is a result of their resistance to all or almost all available antibiotics (“Biggest Threats”, 2016). We created a Python program to analyse the outbreaks of CRE in Canada and the USA, and whether it will become an epidemic under current conditions. We used the program, which uses a mathematical model, to compare and graph relative amounts of infected, susceptible, and dead patients. We started from a deterministic model and moved to a stochastic model. The deterministic model is the initial stage of our CRE model, which includes static rates taken from various data sources. The stochastic model is the second stage of our model, where there are dynamic rates according to other parameters, such as time or increases in infectivity rate. To determine whether CREs will become an epidemic, both the deterministic graph and the stochastic graph must meet particular criteria.