The threat of the unknown: is lack of global burden data slowing down work on antibiotic resistance?

2021-01-28

The World Health Organization (WHO) classify antimicrobial resistance as one of the ten most considerable global public health threats humanity is facing. Medical and scientific communities have been aware for a long time. Still, the global burden of antibiotic resistance remains unknown.

What is burden?

Burden is a broad concept that could mean different things. It is commonly defined as mortality caused by a disease or condition of interest, but could also be measured in for example excess morbidity or additional economic costs (for individuals, health-care providers or society at large).

There are also different ways to measure and calculate mortality, which further complicates estimations and data comparisons. When considering burden of antibiotic resistance as the number of lost lives, do we mean the number of people that die while suffering from any antibiotic resistant infection (irrespective of presence of other diseases or conditions), the excess number of deaths caused by specific resistant infections or something else? And what do we compare to?

Important factors that influence the generation of mortality data is the diagnostic capacity of health systems and the procedures for determining and recording deaths due to antibiotic resistance. These are some important aspects that need to be addressed to improve the estimates of global burden.

Mortality burden data from low- and middle-income countries are particularly scarce, although it is well-recognized that these countries generally are more afflicted by antibiotic resistance. Health systems strengthening and efforts to ensure universal health coverage are therefore crucial also for data generation purposes.

Some initiatives generating burden estimates

In June 2020, the WHO published a master protocol for estimating attributable mortality of antimicrobial resistant bloodstream infections, as part of the Global Antimicrobial Resistance Surveillance System (GLASS) framework. The protocol focuses, at first hand, on attributable in-hospital mortality of bloodstream infections caused by extended-spectrum beta-lactamase-producing (ESBL) E. coli and methicillin-resistant S. aureus (MRSA). Both these are relatively common pathogens that are resistant to clinically important antibiotics.

Although the initiative is very welcome, it is important to be aware of the limitations. The data will only be as good as the circumstances allow and will be influenced by everything from health-care seeking behavior to availability of clinical diagnostics, laboratories and trained personnel. The prerequisites for generating useful, representative data therefore varies substantially between countries.

The Global Burden of Disease (GBD) study make burden estimates for a lot of different conditions and diseases in 195 countries. In 2018, it was announced that GBD also will include human mortality and morbidity data on resistant infections. The work is carried out in partnership with the Global Research on AntiMicrobial resistance (GRAM) project, with the initial aim to generate antibiotic resistance burden estimates from year 1990 and onwards for 17 pathogen-antibiotic combinations. The first results are expected in 2021. However, making these estimations is far from straight-forward. Factors complicating burden estimations of antibiotic resistance are described in this article, and include:

• the unique characteristics of antibiotic resistance (for example that it is not a disease in itself and that bacteria may develop resistance to multiple antibiotics)
• the lack of microbiological data linked to patient data
• the choice of methodology

The importance of reliable global burden estimates

Why then is it important to have reliable burden estimates of antibiotic resistance? Isn’t it enough to simply know that antibiotic resistance is a profound problem? Probably not. There is a difference between knowing that something is an issue and being informed about the extent of the problem.

One could make an analogy to for example traffic. When driving a car on a road where many car accidents happen, the driver is hopefully paying more attention. However, if the driver knows that on average one traffic accident with deadly outcome happens every week at that specific road, the response is likely different. Maybe she or he cancels the trip or chooses an alternative, statistically safer, route. Besides, it is probably likelier that authorities and decision makers prioritize finding solutions to reduce the problem and make the road safer.

The same applies to antibiotic resistance. Knowing the extent of the problem in countries as well as globally would help communicating the urgency of the crisis. It could help inform policies, target interventions and increase general awareness, which all are important components of the antibiotic resistance response. With other words – lack of antibiotic resistance burden data may slow down national and global efforts, which is why it is so important to address. We must look more into how we can overcome the data gap. This includes continuing to strengthen health systems capability and capacity to detect and record the outcome of resistant infections, but also to complement data collection with for example point prevalence studies.

While continuing our efforts to overcome the data gap, we must recognize that we have enough knowledge and insight to take action here and now. We have no time to lose.

Further reading

WHO factsheet on antimicrobial resistance

Improving the estimation of the global burden of antimicrobial resistant infections (not open access)

GLASS method for estimating attributable mortality of antimicrobial resistant bloodstream infections

Measuring and mapping the global burden of antimicrobial resistance

The challenges of estimating the human global burden of disease of antimicrobial resistant bacteria