Keywords
Antibiotic Resistance; Applied Mathematics; Biostatistics; Combinatorics; Horizontal Gene Transfer; Human Microbiome; Mathematical Models; Mutation; Probability; Quantitative Biology
Abstract
Antimicrobial resistance (AMR) combined with the lack of novel antibiotics poses an eminent threat to human survival and to the practicality of medical procedures that depend on antibiotics.
In the most basic terms, AMR will result in more untreatable illnesses and diseases subsequently accelerating mortality rates for those particular conditions. AMR will increase the cost of patient care and tax the already overburdened healthcare system, and will negatively impact individuals, families, and employers and the economy and society worldwide.
How AMR affects treatment and outcome in certain bacterial infections can be described in narrative form, such as: Elevated AMR increases disease and death. However, this brief narrative reveals little about other cofactors or how adjusting one cofactor may affect another cofactor, several cofactors or all cofactors. Thus, it is more practical to develop a mathematical model that depicts such cofactors and their correlations to more readily recognize and more aptly access the effects of AMR on human mortality.
Citation
Kerna NA. Epidemiological Consideration: The Application of Quantitative Biology in the Analysis of Mortality Rates Affected by Antimicrobial Resistance. SM Prev Med Public Health. 2018; 2(3): 1022.