Bacterial resistance: a sensitive issue complexity of the challenge and containment strategy in Europe

Abstract

The development of antimicrobial agents has been a key achievement of modern medicine. However, their overuse has led to an increasing incidence of infections due to antibiotic-resistant microorganisms. Quantitative figures on the current economic and health impact of antimicrobial resistance are scant, but it is clearly a growing challenge that requires timely action. That action should be at the educational, ethical, economic and political level. An important first step would be to increase public awareness and willingness to take the necessary measures to curb resistance. Hence, studies are needed that would provide solid, quantitative data on the societal impact of antibiotic resistance. This review discusses the complexity of resistance, identifies its main drivers and proposes measures to contain it on a European scale.

Fig. 1

Annual European resistance data for three major human pathogens. Data are adapted from The European Antimicrobial Resistance Surveillance System (EARSS). The graph only shows species for which broad surveillance data between 2000 and 2005 are available in the EARSS database. There is a slow increase in antibiotic resistance for most pathogen/antibiotic regimen combinations.

Fig. 2

Simplified scheme of different routes to develop new classes of antibiotics. The ‘target-based’ approach implies the development of new antibacterials starting from a unique bacterial target. This target may comprise essential or accessory (e.g. virulence) genes. Only a very limited number of (broad-spectrum) targets may exist. A ‘compound-based’ approach aims at identifying new lead compounds by means of screening compound libraries or human, bacterial or phage peptides with functional in vitro assays. In principle, small molecules are better drug candidates than, for example peptides. Thus, the resulting targets, small molecules and peptides have to be translated into (non-protein) lead compounds. This involves complex technology like structural biology, computer-assisted drug design and (combinatorial) chemistry. During the next cycles, lead compounds are optimised for functionality, minimal side effects and undesirable pharmacokinetic and dynamic properties.

Fig. 3

Intervention measures, their effect on resistance levels, and the most important relations with relevant outcome parameters. The colour scale from yellow to red indicates the need for low- to high-priority research, respectively. Infection prevention measures include hygiene-control and isolation policies in hospitals and vaccination programs in the community and veterinary sector. Antibiotic development implies the need for better technologies in order to develop new antibiotics and alternative strategies. Antibiotic use refers to prudent use in the hospitals, restricted use in the community (i.e. better compliance with the prohibition of over-the-counter sales of antibiotics), and therapeutic use only in the veterinary sector. Standardized evidence-based guidelines and education programs for healthcare professionals and the public are needed to implement intervention measures. Well-designed standardized surveillance programs are needed to study the cost-effectiveness of intervention measures in the hospital, the community, and other resistance reservoirs such as the veterinary sector. Resistance levels, in turn, should be linked to relevant outcome parameters like mortality, morbidity, economic costs of resistance, and cost-effectiveness of intervention measures. Finally, resistance dynamics should be analysed in relation to intervention measures using mathematical modelling, and the spread and mechanisms of resistance should be addressed by coupling resistance data to the genetic background of the strains.