The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study

SUMMARY Mathematical modelling of infectious diseases has gradually become part of public health decision-making in recent years. However, the developing status of modelling in epidemiology and its relationship with other relevant scientific approaches have never been assessed quantitatively. Herein, using antibiotic resistance as a case study, 60 published models were analysed. Their interactions with other scientific fields are reported and their citation impact evaluated, as well as temporal trends. The yearly number of antibiotic resistance modelling publications increased significantly between 1990 and 2006. This rise cannot be explained by the surge of interest in resistance phenomena alone. Moreover, modelling articles are, on average, among the most frequently cited third of articles from the journal in which they were published. The results of this analysis, which might be applicable to other emerging public health problems, demonstrate the growing interest in mathematical modelling approaches to evaluate antibiotic resistance.

[1]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[2]  E Massad,et al.  Modeling and simulating the evolution of resistance against antibiotics. , 1993, International journal of bio-medical computing.

[3]  N. Høiby.  Epidemiologic aspects on antibiotic resistance. , 1995, Microbial drug resistance.

[4]  The within-host population dynamics of antibacterial chemotherapy: conditions for the evolution of resistance. , 2007, Ciba Foundation symposium.

[5]  A. Perelson,et al.  Mathematical and Computational Challenges in Population Biology and Ecosystems Science , 1997, Science.

[6]  S Bonhoeffer,et al.  Evaluating treatment protocols to prevent antibiotic resistance. , 1997, Proceedings of the National Academy of Sciences of the United States of America.

[7]  A. Valleron,et al.  Modeling the Spread of Resistant Nosocomial Pathogens in an Intensive-Care Unit , 1997, Infection Control & Hospital Epidemiology.

[8]  M Kakehashi,et al.  The transmission dynamics of antibiotic–resistant bacteria: the relationship between resistance in commensal organisms and antibiotic consumption , 1997, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[9]  B. Levin,et al.  The population dynamics of antimicrobial chemotherapy , 1997, Antimicrobial agents and chemotherapy.

[10]  F. M. Stewart,et al.  The population genetics of antibiotic resistance. , 1997, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[11]  B. Levin,et al.  Population dynamics of tuberculosis treatment: mathematical models of the roles of non-compliance and bacterial heterogeneity in the evolution of drug resistance. , 1998, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[12]  F. M. Stewart,et al.  The population genetics of antibiotic resistance. II: Analytic theory for sustained populations of bacteria in a community of hosts. , 1998, Theoretical population biology.

[13]  A S Perelson,et al.  Drug concentration heterogeneity facilitates the evolution of drug resistance. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[14]  R. Anderson,et al.  Vancomycin-resistant enterococci in intensive-care hospital settings: transmission dynamics, persistence, and the impact of infection control programs. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[15]  R. Anderson,et al.  The relationship between the volume of antimicrobial consumption in human communities and the frequency of resistance. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[16]  R. Anderson.  The pandemic of antibiotic resistance , 1999, Nature Medicine.

[17]  R. Anderson,et al.  Studies of antibiotic resistance within the patient, hospitals and the community using simple mathematical models. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[18]  Carl T. Bergstrom,et al.  The epidemiology of antibiotic resistance in hospitals: paradoxes and prescriptions. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[19]  Herbert W. Hethcote,et al.  The Mathematics of Infectious Diseases , 2000, SIAM Rev..

[20]  B G Williams,et al.  Criteria for the control of drug-resistant tuberculosis. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[21]  B. Levin,et al.  Compensatory mutations, antibiotic resistance and the population genetics of adaptive evolution in bacteria. , 2000, Genetics.

[22]  M. Lipsitch,et al.  Understanding the spread of antibiotic resistant pathogens in hospitals: mathematical models as tools for control. , 2001, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[23]  C. Dye,et al.  Will tuberculosis become resistant to all antibiotics? , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[24]  G. Webb,et al.  The impact of persistent gastrointestinal colonization on the transmission dynamics of vancomycin-resistant enterococci. , 2002, The Journal of infectious diseases.

[25]  D. Austin,et al.  Risk factors for the transmission of methicillin-resistant Staphylococcus aureus in an adult intensive care unit: fitting a model to the data. , 2002, The Journal of infectious diseases.

[26]  O. Diekmann,et al.  How to assess the relative importance of different colonization routes of pathogens within hospital settings , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[27]  David L. Smith,et al.  Animal antibiotic use has an early but important impact on the emergence of antibiotic resistance in human commensal bacteria , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[28]  A. Dannenberg,et al.  Use of epidemiology in clinical medical publications, 1983-1999: a citation analysis. , 2003, American journal of epidemiology.

[29]  L. Temime,et al.  Bacterial Resistance to Penicillin G by Decreased Affinity of Penicillin-Binding Proteins: A Mathematical Model , 2003, Emerging infectious diseases.

[30]  Martin A Nowak,et al.  Evolutionary dynamics of escape from biomedical intervention , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[31]  Marc Lipsitch,et al.  Geographic diversity and temporal trends of antimicrobial resistance in Streptococcus pneumoniae in the United States , 2003, Nature Medicine.

[32]  D. Smith,et al.  Assessing risks for a pre-emergent pathogen: virginiamycin use and the emergence of streptogramin resistance in Enterococcus faecium. , 2003, The Lancet. Infectious diseases.

[33]  Marc Lipsitch,et al.  Projected benefits of active surveillance for vancomycin-resistant enterococci in intensive care units. , 2004, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[34]  David L. Smith,et al.  Persistent colonization and the spread of antibiotic resistance in nosocomial pathogens: resistance is a regional problem. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[35]  T. Chou,et al.  Modeling the emergence of the 'hot zones': tuberculosis and the amplification dynamics of drug resistance , 2004, Nature Medicine.

[36]  B. Cooper,et al.  Methicillin-resistant Staphylococcus aureus in hospitals and the community: stealth dynamics and control catastrophes. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[37]  Jim Koopman,et al.  Modeling infection transmission. , 2004, Annual review of public health.

[38]  Zaid Abdo,et al.  Combining Mathematical Models and Statistical Methods to Understand and Predict the Dynamics of Antibiotic-Sensitive Mutants in a Population of Resistant Bacteria During Experimental Evolution , 2004, Genetics.

[39]  P. Böelle,et al.  Short- and Long-Term Effects of Pneumococcal Conjugate Vaccination of Children on Penicillin Resistance , 2004, Antimicrobial Agents and Chemotherapy.

[40]  Carl T. Bergstrom,et al.  Ecological theory suggests that antimicrobial cycling will not reduce antimicrobial resistance in hospitals. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[41]  R. May.  Uses and Abuses of Mathematics in Biology , 2004, Science.

[42]  M. Lipsitch,et al.  The analysis of hospital infection data using hidden Markov models. , 2004, Biostatistics.

[43]  Ted Cohen,et al.  Modeling epidemics of multidrug-resistant M. tuberculosis of heterogeneous fitness , 2004, Nature Medicine.

[44]  Christopher A. Gilligan,et al.  Invasion of drug and pesticide resistance is determined by a trade-off between treatment efficacy and relative fitness , 2004, Bulletin of mathematical biology.

[45]  G. Webb,et al.  A model of antibiotic-resistant bacterial epidemics in hospitals. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[46]  M. Feldman,et al.  EVOLUTION OF ANTIBIOTIC RESISTANCE BY HUMAN AND BACTERIAL NICHE CONSTRUCTION , 2005 .

[47]  J. Hotchkiss,et al.  An agent-based and spatially explicit model of pathogen dissemination in the intensive care unit* , 2005, Critical care medicine.

[48]  M. Bonten,et al.  Control of vancomycin-resistant enterococci: one size fits all? , 2005, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[49]  J. Magee.  The resistance ratchet: theoretical implications of cyclic selection pressure. , 2005, The Journal of antimicrobial chemotherapy.

[50]  P. Joyce,et al.  Modeling the impact of periodic bottlenecks, unidirectional mutation, and observational error in experimental evolution , 2005, Journal of mathematical biology.

[51]  Sam P. Brown,et al.  Avoid, attack or do both? Behavioral and physiological adaptations in natural enemies faced with novel hosts , 2005, BMC Evolutionary Biology.

[52]  Timothy C. Reluga,et al.  Simple models of antibiotic cycling. , 2005, Mathematical medicine and biology : a journal of the IMA.

[53]  A. Pettitt,et al.  Use of Stochastic Epidemic Modeling to Quantify Transmission Rates of Colonization With Methicillin-Resistant Staphylococcus Aureus in an Intensive Care Unit , 2005, Infection Control & Hospital Epidemiology.

[54]  M. Halloran,et al.  Infectious Disease Modeling Contributions to the American Journal of Epidemiology , 2005 .

[55]  D Guillemot,et al.  Penicillin-resistant pneumococcal meningitis: high antibiotic exposure impedes new vaccine protection , 2005, Epidemiology and Infection.

[56]  J. Giesecke,et al.  Modelling the spread of penicillin‐resistant Streptococcus pneumoniae in day‐care and evaluation of intervention , 2005, Statistics in medicine.

[57]  David L. Smith,et al.  Strategic interactions in multi-institutional epidemics of antibiotic resistance. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[58]  G. Webb,et al.  A mathematical model quantifying the impact of antibiotic exposure and other interventions on the endemic prevalence of vancomycin-resistant enterococci. , 2005, The Journal of infectious diseases.

[59]  M. Loeb,et al.  Modeling Transmission of Methicillin-Resistant Staphylococcus Aureus Among Patients Admitted to a Hospital , 2005, Infection Control & Hospital Epidemiology.

[60]  R. Atun,et al.  Impact of an effective multidrug-resistant tuberculosis control programme in the setting of an immature HIV epidemic: system dynamics simulation model , 2005, International journal of STD & AIDS.

[61]  M. Nikolaou,et al.  A New Modeling Approach to the Effect of Antimicrobial Agents on Heterogeneous Microbial Populations , 2006, Journal of mathematical biology.

[62]  Marc Lipsitch,et al.  Beneficial and perverse effects of isoniazid preventive therapy for latent tuberculosis infection in HIV-tuberculosis coinfected populations. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[63]  B. Levin,et al.  Non-inherited antibiotic resistance , 2006, Nature Reviews Microbiology.

[64]  Marc Lipsitch,et al.  Upgrading antibiotic use within a class: tradeoff between resistance and treatment success. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[65]  O. Diekmann,et al.  Controlling methicillin-resistant Staphylococcus aureus: quantifying the effects of interventions and rapid diagnostic testing. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[66]  R. Kitching,et al.  Use and abuse of mathematical models: an illustration from the 2001 foot and mouth disease epidemic in the United Kingdom. , 2006, Revue scientifique et technique.

[67]  Matthew H Samore,et al.  Mechanisms by which antibiotics promote dissemination of resistant pneumococci in human populations. , 2006, American journal of epidemiology.

[68]  David L. Smith,et al.  The Role of Institutional Epidemiologic Weight in Guiding Infection Surveillance and Control in Community and Hospital Populations , 2006, Infection Control & Hospital Epidemiology.

[69]  Christoph Steininger,et al.  A Mathematical Model Investigating the Impact of an Environmental Reservoir on the Prevalence and Control of Vancomycin- Resistant Enterococci , 2006 .