Antimicrobial-Resistance Alarms

For humans, some of the biggest threats come from the tiniest organisms. Bacteria, fungi, parasites, and viruses—collectively known as microorganisms—can cause anything from a common cold and the flu to AIDS and COVID-19. These diseases can be deadly. According to estimates, the Black Death in the 1300s and the flu in 1918 killed as many as 200 million and 100 million people, respectively. Despite the development of drugs to battle many of these diseases, the microorganisms quickly develop ways to resist the drugs. This process, called antimicrobial resistance (AMR), is deemed “one of the top global public health and development threats,” by the World Health Organization (WHO). The complete scope of the threat remains unknown because of inadequate AMR surveillance in many parts of the world.

What scientists know is that AMR arises quickly. Sulfonamides were introduced in 1937 as the first successful antimicrobial, but examples of resistance to these drugs were reported by the end of that decade. Even before penicillin was used clinically in 1941, instances of penicillin resistance had been observed.

Although AMR makes up an important piece of medical history, the related health threats pose even more dangers in today’s world of more than 8 billion people. To track the dangers of AMR today and tomorrow, global surveillance must be vastly improved. The breadth of dangerous microorganisms, the number of drugs used to treat them, and the expanse of populated Earth, however, make effective AMR surveillance a daunting challenge.

The impact of COVID-19

“In 2021, bacterial AMR was responsible for approximately 4.71 million deaths associated with resistant infections, with 1.14 million of these deaths directly attributable to AMR,” said Tomislav Mestrovic, MD, PhD, affiliate associate professor at the Institute for Health Metrics and Evaluation at the University of Washington School of Medicine in Seattle. “These estimates show the ongoing challenge posed by drug-resistant infections on a global level.”

The impacts of these infections depend on many factors. For example, Mestrovic pointed out that the COVID-19 pandemic “exacerbated the inappropriate use of antibiotics, and their overuse can—and does—accelerate the selection pressure for resistant bacteria in many regions.” Conversely, “the introduction of lockdowns and reduced mobility during the pandemic reduced hospital admissions for conditions not related to COVID and, in turn, temporarily decreased transmission of certain resistant pathogens.”

As Mestrovic summarized: “All of this translated to the temporary decline of the AMR burden during 2020 and 2021, which is in a way indirect evidence of the pandemic’s influence on AMR dynamics.”

Some AMR dynamics arise from the age of the global population. “While deaths due to AMR among children under 5 years have continued to decrease globally, likely due to improved vaccination coverage and infection prevention strategies, the burden among adults aged 70 years and older has actually increased,” Mestrovic said. “This underscores the growing vulnerability of older populations to resistant infections, exacerbated by higher rates of co-existing diseases, the decline of immune system function with age, but also much more frequent exposure to healthcare environments during the pandemic period.”

Although COVID-19 was a wakeup call to everyday citizens and healthcare experts around the world, the pandemic also delivered a dire message about AMR. As Mestrovic put it, “The pandemic revealed notable gaps in AMR surveillance and stewardship that necessitate urgent attention as global healthcare systems recover and prepare for future challenges.”

AMR ahead

The danger of AMR in the future must be taken extremely seriously. “The next decade could indeed see a dramatic rise in the AMR burden, with forecasts predicting that by 2050, resistant bacteria could be linked to over 8 million deaths annually,” Mestrovic said. “Of these, nearly 2 million are expected to result directly from drug-resistant infections, which is definitely a sharp increase from 2021 figures.”

In fact, Mestrovic believes that increasing resistance among some pathogens could “overshadow recent public health gains and exacerbate global-health inequalities.” The regions most at risk, he said, are South Asia, sub-Saharan Africa, and parts of Latin America, “where healthcare systems often struggle with inadequate resources, limited access to diagnostics—and also already have high rates of communicable diseases.”

Other demographic factors will contribute to the future of AMR resistance. Today, one of those factors is age. “One of the most critical drivers of the future AMR burden is the aging global population,” Mestrovic said. “By 2050, individuals aged 70 years and older are expected to account for nearly 66% of all deaths attributable to AMR, up from 47% in 2021.” Older people often suffer from a variety of chronic conditions, make more frequent visits to hospitals, and usually undergo more invasive procedures than younger people. All of this, Mestrovic said, “increases their exposure to resistant infections.”

If today’s healthcare system continues operating without changes, AMR will expand. Still, Mestrovic hopes for better future outcomes. “Improved healthcare quality and expanded access to antibiotics could avert up to 92 million deaths by 2050,” he said. “Similarly, the development of new drugs targeting gram-negative bacteria could save millions.”

Even those improvements, however, would not be enough to fight off the potential future of AMR resistance. “We have to be cognizant that overcoming surveillance gaps, reducing antibiotic misuse, and addressing economic barriers in drug development will be indispensable to altering this trajectory,” Mestrovic said. “The next decade is pivotal for global efforts to curb the AMR crisis.”

An ongoing imbalance

AMR surveillance is a crucial part of these global efforts. Given the long history of AMR, a similar history of AMR surveillance might be expected. Nonetheless, AMR surveillance has lagged far behind awareness of this healthcare crisis.

Just a decade ago, the WHO released its Antimicrobial resistance global report on surveillance: 2014 summary, which the organization described as “the first to look at antibiotic resistance globally” and its “first attempt to obtain an accurate picture of the magnitude of AMR and the current state of surveillance globally.”

Despite awareness of the dangers of AMR, the WHO found “significant gaps in surveillance, and a lack of standards for methodology, data sharing, and coordination,” and “an urgent need to strengthen and coordinate collaboration to address those gaps.”

Although Mestrovic pointed out that “a wide range of surveillance programs are currently in place,” he agreed with the WHO’s conclusions. Mestrovic emphasized that current approaches to AMR surveillance vary in geographic focus, from local or national to regional or global. Today’s surveillance priorities also vary from tracking particular antibacterial agents or pathogens to studying specific geographic sites of infection. In addition, inconsistencies in the type and quality of data collected limit the scope of AMR surveillance. “Ideally, these programs involve comprehensive sampling from relevant infection sites, conducted consistently over time and across locations,” Mestrovic said.

Today, AMR surveillance is far from comprehensive or consistent. Instead, it reflects stark inequities in healthcare systems. “In high-income countries, we can say that surveillance systems are relatively well-developed, timely and robust, with adequate and rather consistent reporting,” Mestrovic said. “Conversely, in low- and middle-income countries, where the AMR burden is actually the highest, surveillance is often inadequate and laden with challenges.”

Some data from high-income countries can be used to track trends in AMR. This information can also be used to guide public-health interventions. Even in these countries, Mestrovic said, “there are certain gaps in real-time data integration and insufficient monitoring of community-acquired resistance.”

The problem is even worse in low- and middle-income countries, where inadequate infrastructure, funding, and technical expertise often prevent effective AMR monitoring. “Existing systems are frequently fragmented, relying on limited data from tertiary hospitals or select urban centers, which may not represent the broader population,” Mestrovic said. “Such patchy, sentinel coverage leaves critical blind spots, most notably in rural areas or regions with high levels of antibiotic misuse.”

Even when data is collected, problems remain. “Many laboratories still rely on outdated or inconsistent diagnostic standards, leading to variability in reported resistance rates,” Mestrovic explained. “Likewise, significant portions of AMR data come from hospital settings, often failing to capture resistance patterns in outpatient or environmental contexts, where antibiotic misuse is quite prevalent.”

Improving the surveillance process

As a global problem involving many microorganisms and treatments, effective AMR surveillance poses a gigantic challenge. First, scientists need high-quality and standardized data. That data must cover wide swathes of information and address existing gaps. Then, the information must be integrated to develop a global picture of AMR. “These enhancements are essential to build a rather comprehensive, globally representative system that can effectively inform interventions and policies,” Mestrovic said.

In essence, the global challenge of AMR surveillance requires a global solution. “Establishing globally harmonized protocols for sampling, testing, and reporting would ensure consistency and reliability,” Mestrovic said. “This can be done by strengthening global collaboration and improving data sharing across nations.”

Existing technology could address many of the problems in AMR surveillance. For example, real-time dynamic sequencing can provide “detailed insights into the emergence and spread of resistant traits, and AI-driven predictive modeling can aid in identifying potential hotspots and trends,” Mestrovic said. “Improved digital infrastructure for data sharing and analysis would also enable more rapid and effective responses to emerging threats, and will be increasingly needed in the future.”

Countries collaborating

In 2000, Dominique Monnet, PharmD, PhD—currently head of AMR and healthcare-associated infections at the European Centre for Disease Prevention and Control (ECDC) in Solna, Sweden—reported on the need for timely, representative, multinational, and good-quality AMR data. Thinking back to that time, he said, “There were many different surveillance systems, and people were using different methods.”

That started to change in 1999, when the European Antimicrobial Resistance Surveillance System (EARSS) was established. In 2010, the system was integrated into the ECDC’s activities as the European Antimicrobial Resistance Surveillance Network (EARS-Net). The network uses data provided by European Union (EU) and the European Economic Area (EEA) countries, with the WHO’s Central Asian and European Surveillance of Antimicrobial Resistance (CAESAR) system completing the picture for the whole European region. “When you put all this together, we have a comprehensive picture over a much larger area,” Monnet said. In addition to increasing the geographic representativeness of its data, EARS-Net has been tracking an increasing number of pathogens.

EARS-Net already works with lots of data. For each country, the network provides information on the AMR percentage in invasive isolates—bacteria collected from a bodily fluid that is normally sterile, such as blood or cerebrospinal fluid—as well as the estimated incidence of bloodstream infections due to bacteria with AMR.

Overall, Monnet said, “It’s a very good system for following trends over time, because the methods do not change, but it’s a less good system for picking up emerging AMR.”

For emerging threats, the ECDC uses event-based surveillance as part of its EpiPulse platform as well as through the EU Early Warning and Response System (EWRS). “EU member states report about something they found, most probably at the reference laboratory in the country,” Monnet said. “Then, we at ECDC examine the signal, encourage exchange of information, and sometimes even produce what we call a rapid risk assessment.”

EARS-Net can reveal important trends. In 2024, based on data from EARS-Net, the ECDC reported that “the estimated total EU incidence of carbapenem-resistant Klebsiella pneumoniae bloodstream infections” increased by nearly 60% from 2019 to 2023.

Given the success of EARS-Net, Monnet said, “Other regions of the world really looked at it as an example.”

Integrating information

New approaches to integrating and analyzing data could also approve improve AMR surveillance. In 2024, Babafela Awosile, DVM, PhD—an assistant professor of epidemiology at Texas Tech University School of Veterinary Medicine in Amarillo—and his PhD student Samuel Ajulo, DVM, reported in PLoS One the potential benefits of combining data on AMR and antimicrobial consumption (AMC) to improve surveillance.

Awosile said that including AMR and AMC in the surveillance programs will “provide an opportunity for us to examine how antimicrobial use is likely contributing to AMR in a cause-and-effect manner.”

Ajulo and Awosile’s report already provides an example of the valuable information that can emerge from combining AMR and AMC data. “We found a statistically significant correlation between beta-lactam/cephalosporin and fluoroquinolones consumption and AMR to these antimicrobials associated with bloodstream Escherichia coli and Klebsiella pneumoniae among the participating countries,” Awosile said. “Also, we observed an obvious grouping of the developing countries and developed countries in terms of the AMU and AMR rates.”

In particular, they found that “developed countries, such as Germany, Denmark, Sweden, the United Kingdom, and Belgium are mostly low antimicrobial consumption–low antimicrobial resistance countries, compared to some developing countries that are mostly high use–high antimicrobial resistance or low use–high antimicrobial resistance groups,” Awosile said. “These groupings were consistent for beta-lactam and fluoroquinolone antimicrobial classes.”

Combining AMR and AMC data could also be fundamental to what Awosile called “the new paradigm for a surveillance program, such as the integrated surveillance program as suggested by the World Health Organization,” referring to the WHO’s 2017 report, Integrated surveillance of antimicrobial resistance in foodborne bacteria: application of a one health approach: guidance from the WHO Advisory Group on Integrated Surveillance of Antimicrobial Resistance (AGISAR). In part, Awosile said, this new paradigm shows that “combined analysis of AMR and AMU is critical to every AMR surveillance program.”

As many of the examples here show, effective AMR surveillance depends on collaborations around the world and improvements are underway. Still, as the ECDC’s Monnet says, “We need to be better. We need to improve.”

Mike May is a freelance writer and editor with more than 30 years of experience. He earned an MS in biological engineering from the University of Connecticut and a PhD in neurobiology and behavior from Cornell University. He worked as an associate editor at American Scientist, and he is the author of more than 1,000 articles for clients that include GEN, Nature, Science, Scientific American, and many others. In addition, he served as the editorial director of many publications, including several Nature Outlooks and Scientific American Worldview.