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

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

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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: With Applications in Natural and Social Sciences, Engineering, and the Arts
Publisherwiley
Pages121-134
Number of pages14
ISBN (Electronic)9781118853986
ISBN (Print)9781118853887
DOIs
StatePublished - May 8 2015

Fingerprint

antibiotics
Antibiotics
Anti-Bacterial Agents
Modeling
public health
Social Structure
pathogens
Markov chains
Markov Chain Monte Carlo Methods
Infectious Diseases
Pathogens
infectious diseases
Bayesian inference
inference
Mathematical Modeling
Markov processes
health
Monte Carlo method
mathematical models
Health

Keywords

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

ASJC Scopus subject areas

  • Mathematics(all)
  • Physics and Astronomy(all)
  • Chemistry(all)
  • Computer Science(all)

Cite this

Klein, E., Chelen, J., Makowsky, M. D., & Smaldino, P. E. (2015). The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance. In Mathematical and Computational Modeling: With Applications in Natural and Social Sciences, Engineering, and the Arts (pp. 121-134). wiley. https://doi.org/10.1002/9781118853887.ch6

The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance. / Klein, Eili; Chelen, Julia; Makowsky, Michael D.; Smaldino, Paul E.

Mathematical and Computational Modeling: With Applications in Natural and Social Sciences, Engineering, and the Arts. wiley, 2015. p. 121-134.

Research output: Chapter in Book/Report/Conference proceedingChapter

Klein, E, Chelen, J, Makowsky, MD & Smaldino, PE 2015, The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance. in Mathematical and Computational Modeling: With Applications in Natural and Social Sciences, Engineering, and the Arts. wiley, pp. 121-134. https://doi.org/10.1002/9781118853887.ch6
Klein E, Chelen J, Makowsky MD, Smaldino PE. The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance. In Mathematical and Computational Modeling: With Applications in Natural and Social Sciences, Engineering, and the Arts. wiley. 2015. p. 121-134 https://doi.org/10.1002/9781118853887.ch6
Klein, Eili ; Chelen, Julia ; Makowsky, Michael D. ; Smaldino, Paul E. / The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance. Mathematical and Computational Modeling: With Applications in Natural and Social Sciences, Engineering, and the Arts. wiley, 2015. pp. 121-134
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