Towards a global antibiotic resistance surveillance system: a primer for a roadmap

Figures & data

Text box 1: The drug resistance index

Quantifying antibiotic resistance for each pathogen compound combination separately is only understood by experts. A more meaningful way of defining the burden of antibiotic resistance would aggregate this information into a single index. Such a drug resistance index (DRI) has been recently suggested (16). It combines the antibiotic resistance against all available compounds into an average, weighted by each compound's use. In this manner, a single value can describe the average effectiveness of antibiotic treatment administered in a single facility. The observed prescribing pattern typically adapts to the local antibiotic resistance when antibiotic susceptibility test results are reported to clinicians by a microbiological laboratory. Thus, the index would represent an ‘adaptive drug resistance index' that takes into account prescribing which adjusts to the local resistance patterns. It would assume values between 0 and 1, whereby 1 indicates the extreme that current prescribing would be 100% ineffective given the local resistance pattern. The elegance of indexing lies in the ability to describe the decay of antibiotic effectiveness over time as the antibiotic prescribing pattern can be fixed to a baseline year, i.e. if prescribing had not adapted to a changing antibiotic resistance pattern (‘fixed DRI'). Moreover, an additional index can be determined in situations where treatment options are restricted by availability or access, or by public health decisions such as an essential drug list or an existing standard treatment guideline. This ‘restricted DRI' determines the treatment effectiveness given these constrains in drug use. Indexing therefore provides a compelling tool for influencing decisions at various levels of health care and the public health cascade: at the bedside, for local drug and therapeutics committees, and at the highest policy and public health management level

Text box 2: Whole-genome sequencing.

Whole-genome sequencing (WGS) is the only way reliably to describe the genetic background and genetic repertoire including resistance and virulence markers of bacterial pathogens. The current epidemic of ABR is caused by the spread of HiRiCs or mobile genetic elements that encompass antibiotic resistance genes. Acquisition of these mobile genetic elements does not always raise minimal inhibitory concentrations (MICs) above the accepted clinical breakpoints (defined as susceptible = S, intermediate = I, or resistant = R), meaning that conventional susceptibility testing may miss the presence of HiRiEs in non-permissive genetic backgrounds. If the origins and reservoirs of emerging ABR are to be reliably identified and mapped on a global scale, there will be no other choice than searching the genetic contents of bacteria as the spread of certain extended-spectrum beta-lactamase genes (ESBL) and carbapenemase genes could otherwise be missed. Phenotypic methods based on internationally accepted breakpoints (S,I,R methods) are a good guidance for clinical treatment but have a limited epidemiological sensitivity. Sequencing provides not only information about presence and absence about genes or mutations associated with antibiotic resistance but is the most precise method to determine the genetic relatedness of different isolates which allows for a reconstruction of the population history and identifying the origins of HiRiCs and HiRiEs on geo-temporal scales

While the prices for WGS are decreasing, the amount of data generated increases in an exponential fashion that dwarfs the development of personal computing power during the last 20 years (Moore's law). Indeed, dynamics are four times faster. Results are quickly generated using bench-top equipment, and pipelines are under development which can deal with the amount of data, to zoom in swiftly on targets of choice. The price for sequencing at the time of writing is about $100 per whole bacterial genome at specialized genome centres but also using third-generation personalized genome sequencing equipment

Laxminarayan R, Klugman KP. Communicating trends in resistance using a drug resistance index. BMJ Open. 2011;1:e000135.

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