The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance

Eili Y. Klein, Julia Chelen, Michael D. Makowsky, Paul E. Smaldino

Research output: Chapter in Book/Report/Conference proceedingChapter


Antibiotic resistance has become one of the greatest threats to public and patient health. This chapter examines the history of mathematical modeling of infectious diseases and a selection of its achievements and limitations. It is followed by a discussion of the need to develop models of disease spread that incorporate individual behavior with reference to how this can improve models of bacterial pathogens. As the global epidemic of antibiotic resistance has increased in recent years, mathematical models of the spread of antibiotic resistance have also been developed. Over the past several decades, significant advances have been made in understanding disease transmission, individual behavior, and social structures. For instance, one of the biggest advances in the area of epidemic modeling is use of Bayesian inference in conjunction with Markov chain Monte Carlo methods to impute unobserved data.

Original languageEnglish (US)
Title of host publicationMathematical and Computational Modeling
Subtitle of host publicationWith Applications in Natural and Social Sciences, Engineering, and the Arts
Number of pages14
ISBN (Electronic)9781118853986
ISBN (Print)9781118853887
StatePublished - May 8 2015


  • Antibiotic resistance
  • Bayesian inference
  • Epidemic modeling
  • Individual behavior
  • Infectious diseases
  • Markov chain Monte Carlo methods
  • Mathematical modeling

ASJC Scopus subject areas

  • General Mathematics
  • General Physics and Astronomy
  • General Chemistry
  • General Computer Science


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