Surveillance for control of antimicrobial resistance

Abstract

Antimicrobial resistance poses a growing threat to public health and the provision of health care. Its surveillance should provide up-to-date and relevant information to monitor the appropriateness of therapy guidelines, antibiotic formulary, antibiotic stewardship programmes, public health interventions, infection control policies, and antimicrobial development. In Europe, although the European Antimicrobial Resistance Surveillance Network provides annual reports on monitored resistant bacteria, national surveillance efforts are still fragmented and heterogeneous, and have substantial structural problems and issues with laboratory data. Most incidence and prevalence data cannot be linked with relevant epidemiological, clinical, or outcome data. Genetic typing, to establish whether trends of antimicrobial resistance are caused by spread of resistant strains or by transfer of resistance determinants among different strains and species, is not routinely done. Furthermore, laboratory-based surveillance using only clinical samples is not likely to be useful as an early warning system for emerging pathogens and resistance mechanisms. Insufficient coordination of surveillance systems of human antimicrobial resistance with animal surveillance systems is even more concerning. Because results from food surveillance are considered commercially sensitive, they are rarely released publicly by regulators. Inaccurate or incomplete surveillance data delay a translational approach to the threat of antimicrobial resistance and inhibit the identification of relevant target microorganisms and populations for research and the revitalisation of dormant drug-discovery programmes. High-quality, comprehensive, and real-time surveillance data are essential to reduce the burden of antimicrobial resistance. Improvement of national antimicrobial resistance surveillance systems and better alignment between human and veterinary surveillance systems in Europe must become a scientific and political priority, coordinated with international stakeholders within a global approach to reduce the burden of antimicrobial resistance.

Triple Versus Double Therapy for the Treatment of Severe Infections Caused by Carbapenem-Resistant Enterobacteriaceae: A Systematic Review and Meta-Analysis

“…A previous meta-analysis involving 3,627 participants demonstrated that prior antibiotic use such as carbapenem and aminoglycoside was an important risk factor of carbapenemresistant Klebsiella pneumoniae infection (Liu et al, 2018). Given that roughly 30%-50% of the antibiotic use in hospitals is unnecessary and the limitation of antimicrobial drugs has the potential to reduce the prevalence of CRE, strong antibiotic stewardship policies are urgently needed to curb unnecessary prescribing to ensure more judicious use of antibiotics (Yong et al, 2010;Fleming-Dutra et al, 2016;Tacconelli et al, 2018). Our meta-analysis is in accord with a previous in vitro study which observed that adding a third antibiotic did not enhance synergistic effect in multidrug-resistant Klebsiella pneumonia isolates (Stein et al, 2015).…”

Choosing Your Battles: Which Resistance Genes Warrant Global Action?

“…Besides, Rank I was maintained at a significantly low abundance in FMT donors with no antibiotic consumptions. These observations suggested that Rank I could strongly and rapidly respond to clinical antibiotics 56 and was effectively controlled by current policy in developed countries 54 (such as therapy guidelines, antibiotic formularies, antibiotic stewardship programmes, and public health interventions 58 ). However, we found that Rank II was not directly correlated with the clinical antibiotics and was not observed to be effectively controlled in industrialized countries.…”

Prioritising pathogens for the management of severe febrile patients to improve clinical care in low- and middle-income countries

“…1). Based on a review of related literature [24,28], the following criteria were determined to be relevant for the current use case: number of annual cases (as reported globally and positivity rates reported by Prasad et al); case fatality rate; morbidity using disease-adjusted life-years [29]; and impact on treatment decisions (measured from high to low depending on treatment available for a specific pathogen and the diagnostic potential to reduce complications and/or death). Each criterion had defined sub-criteria, as presented in Fig.…”