The Role of Mathematical Modeling in Designing and Evaluating Antimicrobial Stewardship Programs

Caudill, Lester; Wares, Joanna R.

doi:10.1007/s40506-016-0074-8

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…The field of AMR modeling is growing but is limited by both the quantity and quality of available data. Success stories include accurate predictions of the emergence of resistance in malaria [152], MDR-TB [153], and influenza [154], and modeling is also frequently used to inform AMR stewardship programs in healthcare facilities [155]. Our review suggests a need for more applied, data-driven models, better tuned to and diversified to reflect the public health concerns highlighted by the WHO and the CDC.…”

Section: Discussionmentioning

confidence: 99%

Population-level mathematical modeling of antimicrobial resistance: a systematic review

Niewiadomska

Jayabalasingham

Seidman

et al. 2019

BMC Med

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Background Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006–2016) to gauge the state of research and identify gaps warranting further work. Methods We performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens. Results We identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals. Conclusions The AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae ; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR. Electronic supplementary material The online version of this article (10.1186/s12916-019-1314-9) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Population-level mathematical modeling of antimicrobial resistance: a systematic review

Niewiadomska

Jayabalasingham

Seidman

et al. 2019

BMC Med

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“…Widespread use of antibiotics has led to the rise of resistance in S. pneumoniae (49)-even though pneumococci are often not the direct target of antibiotics, as they are usually asymptomatically carried and not treated [invasive disease might be more than three orders of magnitude lower than carriage (50,51)]. Existing models of antibiotic resistance typically aim to define the conditions minimizing resistance emergence or spread under different antibiotic regimes (52)(53)(54)(55)(56)(57). Fewer efforts have been made to study the effects of pneumococcal vaccination on the evolution and spread of antibiotic resistance (44,58,59).…”

Section: Discussionmentioning

confidence: 99%

Vaccination can drive an increase in frequencies of antibiotic resistance among nonvaccine serotypes ofStreptococcus pneumoniae

Obolski

Lourenço

Thompson

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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The bacterial pathogen is a major public health concern, being responsible for more than 1.5 million deaths annually through pneumonia, meningitis, and septicemia. Available vaccines target only a subset of serotypes, so vaccination is often accompanied by a rise in the frequency of nonvaccine serotypes. Epidemiological studies suggest that such a change in serotype frequencies is often coupled with an increase of antibiotic resistance among nonvaccine serotypes. Building on previous multilocus models for bacterial pathogen population structure, we have developed a theoretical framework incorporating variation of serotype and antibiotic resistance to examine how their associations may be affected by vaccination. Using this framework, we find that vaccination can result in a rapid increase in the frequency of preexisting resistant variants of nonvaccine serotypes due to the removal of competition from vaccine serotypes.

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“…Existing models of antibiotic resistance typically aim to define the conditions minimizing resistance emergence or spread under different antibiotic regimes [34][35][36][37]. Fewer efforts have been made to study the effects of pneumococcal vaccination on the evolution of antibiotic resistance [38][39][40] and only in one of these (Lehtinen et al [40]), as far as we are aware, has a mechanism been proposed by which vaccination may induce an increase in antibiotic resistance.…”

Section: Discussionmentioning

confidence: 99%

Vaccination can drive an increase in frequencies of antibiotic resistance among non-vaccine serotypes ofStreptococcus pneumoniae

Obolski

Lourenço

Gupta

2017

Preprint

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The bacterial pathogen Streptococcus pneumoniae is a major public health concern, being responsible for more than 1.5 million deaths annually through pneumonia, meningitis and septicemia. In spite of vaccination efforts, pneumococcal carriage and disease remain high, since available vaccines target only a subset of serotypes and vaccination is often accompanied by a rise in non-vaccine serotypes. Epidemiological studies suggest that such a change in serotype frequencies is often coupled with an increase of antibiotic resistance among non-vaccine serotypes. Building on previous multi-locus models for bacterial pathogen population structure, we have developed a theoretical framework incorporating variation in serotype and antibiotic resistance to examine how their associations may be affected by vaccination. Using this framework, we find that vaccination can result in rapid increase in frequency of pre-existing resistant variants of non-vaccine serotypes due to the removal of competition from vaccine serotypes.

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The Role of Mathematical Modeling in Designing and Evaluating Antimicrobial Stewardship Programs

Cited by 7 publications

References 28 publications

Population-level mathematical modeling of antimicrobial resistance: a systematic review

Population-level mathematical modeling of antimicrobial resistance: a systematic review

Vaccination can drive an increase in frequencies of antibiotic resistance among nonvaccine serotypes ofStreptococcus pneumoniae

Vaccination can drive an increase in frequencies of antibiotic resistance among non-vaccine serotypes ofStreptococcus pneumoniae

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