Abstract
Antibiotic resistance is a major global threat to the provision of safe and effective health care. To control antibiotic resistance, vaccines have been proposed as an essential intervention, complementing improvements in diagnostic testing, antibiotic stewardship, and drug pipelines. The decision to introduce or amend vaccination programmes is routinely based on mathematical modelling. However, few mathematical models address the impact of vaccination on antibiotic resistance. We reviewed the literature using PubMed to identify all studies that used an original mathematical model to quantify the impact of a vaccine on antibiotic resistance transmission within a human population. We reviewed the models from the resulting studies in the context of a new framework to elucidate the pathways through which vaccination might impact antibiotic resistance. We identified eight mathematical modelling studies; the state of the literature highlighted important gaps in our understanding. Notably, studies are limited in the range of pathways represented, their geographical scope, and the vaccine–pathogen combinations assessed. Furthermore, to translate model predictions into public health decision making, more work is needed to understand how model structure and parameterisation affects model predictions and how to embed these predictions within economic frameworks.
| Original language | English |
|---|---|
| Pages (from-to) | e204-e213 |
| Journal | The Lancet Infectious Diseases |
| Volume | 18 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2018 |
Bibliographical note
Funding Information:We thank Marc Lipsitch and Ben Cooper for their helpful discussions before the writing of the manuscript. This work was supported by the National Institute for Health Research Health Protection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine and Antibacterial Resistance at University of Oxford and Imperial College London, in partnership with Public Health England. The views expressed are those of the authors and not necessarily those of the National Health Service, National Institute for Health Research, Department of Health, or Public Health England.
