Addressing the Overlooked Frontier in AMR Research and Surveillance

Rishu Thakur^1*Hena Dhar²Teresa M Wozniak³Supriya Mathew¹

• ¹Menzies School of Health Research, Charles Darwin University, Darwin, Australia
• ²RIMT University, Gobindgarh, India
• ³CSIRO, Brisbane, Australia

Antimicrobial Resistance (AMR) has been declared as one of the top ten global public health threats (1). There were an estimated 4.95 million deaths globally due to AMR in 2019, in which bacterial AMR alone was directly responsible for killing up to 1.27 million people (2). A World Bank report projected that a high AMR impact scenario could lead to a 3.8% decline in global annual GDP by 2050 (3). Humans are exposed to AMR through interconnected pathways, such as healthcare, agriculture, animals and environment (4). Figure 1 illustrates the interlinked factors that drive AMR in the environment. However, the reality is more complex than depicted in the figure. AMR predominantly occurs from overuse of antimicrobials, that creates selective pressure, leading to the development of resistance against antimicrobials (5). Recent COVID-19 pandemic has significantly increased the use of antibiotics (6). This rise was influenced by several factors including uncertainty in early diagnosis, limited treatment guidelines, concern over secondary bacterial infections, and overwhelmed healthcare systems (7). Besides antibiotic, other factors such as socio-cultural and economic factors also influence the AMR spread (8). Vulnerable groups with pre-existing health conditions and high burden of diseases are most vulnerable to AMR. For instance, remote Indigenous communities in Australia recorded higher rates of azithromycin resistance, methicillin resistant Staphylococcus aureus and gram-negative resistance in urinary tract (9)(10)(11). Behavioural factors such as unnecessary antibiotic use and easily available antibiotics without requiring a prescription in low and middle-income countries (LMICs), might also affect the spread of AMR (12).Overuse of antimicrobials is not exclusive to human; tonnes of antimicrobials are use in foodproducing animals (13). In healthcare settings, AMR surveillance is mainly used to guide immediate actions such as selecting the right antimicrobials or changing how antimicrobials are used (14). But for environmental AMR, it is harder to link the results directly to immediate actions. One of the main reasons is that antimicrobial resistance genes (ARGs) genes present in the natural environment such as in soil with no known anthropogenic activity (15). The extent to which anthropogenic activities, such as the release of antimicrobials into the environment influencing the naturally occurring AMR in environmental settings is largely unknown. There is no baseline data for AMR in environmental settings where antimicrobial residues are supposed to be runoff. Next, how ARGs and antibiotic residues changes over time due to anthropogenic activities is largely unexplored. Estimating the level of AMR in these environments is difficult without sufficient baseline data to provide a proper reference point for effective monitoring. According to the Lancet Countdown on Health and Climate Change, climate change has gradually increased disease risks which is expected to have significant impacts on the emergence and severity of AMR (16). Temperature variability and extreme weather events such as heatwaves are increasing in frequency (17). Warmer temperatures have led to the emergence of climate-sensitive infections and also associated with accelerating bacterial reproduction which enhances the possibilities of horizontal gene transfer among bacteria (18,19). Elevated temperatures also influence heavy metal concentrations in the environment and their uptake by bacteria which can contribute to the proliferation of AMR (20). Climate uncertainties increase farmers reliance on antimicrobials as a defence against disease outbreaks and reduced crop yields (21). Other climate-mediated consequences, such as droughts exacerbate water and food insecurity, which can lead to weakened immune systems, malnutrition, and increased susceptibility to infections (22). Floods also increase the risks of displacing populations and inadequate sanitation, which make ideal circumstances for infection spread (23). These challenges are further worsened by poor living conditions, overcrowded spaces and substandard housing, as well as limited access to clean water and healthcare in low resource settings. Climate change is an underappreciated but critical driver of AMR, and that adaptive public health strategies must account for these emerging risks. The World Health Assembly initiated a global action plan to tackle AMR which varies for LMICs and high-income countries (HICs) (24). In LMICs, the focus is on issues like poor regulatory enforcement, and the unrestricted use of antibiotics, while in HICs, such as the European Union, action plans aim to strengthen AMR knowledge through surveillance, improve infection control and raise public awareness. Though the antibiotics use in healthcare in high-income countriesHICs is well monitored, environmental factors are needed to be monitored frequently to get a clear picture of AMR occurrence and propagation. The World Health Organisation (WHO) has made global efforts to enhance the AMR data collection through Global Antimicrobial Resistance and Use Surveillance System (GLASS) (25). GLASS collaborates with many regional AMR networks such as the Central Asian and European Surveillance of Antimicrobial Resistance (CAESAR), the European Antimicrobial Resistance Surveillance Network (EARS-Net), the Latin American Network for Antimicrobial Resistance Surveillance (ReLAVRA), and the Western Pacific Regional Antimicrobial Consumption Surveillance System (WPRACSS) and over 100 countries participate in this surveillance till date. Despite the wealth of data collected through GLASS, some challenges continue in understanding and interpreting this data due to variable data quality across diverse regions and healthcare. GLASS report also indicated that many countries lack sufficient surveillance data on AMR, particularly LMICs. Another initiative such as Global Antibiotic Research & Development Partnership (GARDP) provides data on AMR surveillance in LMICs Formatted: Font: (Default) Times New Roman, 12 pt (26). Recently, the G7 compliance report on AMR also emphasised on the AMR data collection across human, animal, and environmental health sectors under a "One Health" framework (27). Limited research on environmental AMR Though global efforts have been made to improve AMR surveillance, still studies are more focused on clinical settings. Substantial efforts have been made towards monitoring AMR in clinical and veterinary settings (28). At present, many studies investigated AMR in relation to humans, largely from the health perspective, followed by slightly fewer showing interest in the spread of AMR among animals and significantly less focusing on environmental factors contributing to AMR emergence. Given that the environment plays a significant role in the emergence and spread of AMR, it is needed to develop more holistic approaches that comprise both healthcare and environmental settings. The absence of environmental surveillance is a critical gap in AMR research and providing evidenced-based recommendation to the policymakers. This imbalance emphasises the urgent need for research in the direction of elucidating pathways of AMR development in the environment. One significant challenge is the lack of understanding of which environmental settings are most susceptible to AMR transmission. Such understanding is essential for targeted surveillance and intervention strategies. High-risk environments where AMR transmission is most likely to occur need to be clearly defined. Another major obstacle is the research funding. Generally, clinical research, such as hospital infections related AMR receives more funding than environmental settings. Funding is generally allocated to antimicrobial stewardship in health care. Funding for One Health initiative is crucial to address the environmental AMR. A recent One Health initiative SAAFE AMR surveillance program funded by Australian Government recognises the interconnection between people, animals, plants and their shared environments (29). More programs like this are needed to tackle this complex AMR issue. Local AMR surveillance through a multi-disciplinary approach Global efforts are essential for AMR mitigation but local solutions that can address the root causes of resistance in specific settings are also equally important. Several local factors can influence the AMR emergence. For instance, social determinants of health such as limited access to healthcare, poor housing and sanitation and geographical remoteness are well-known AMR contributors (8). Traditional farming practices such as the use of fertilisers and economic pressure to increase production could have an impact on antimicrobial use. Such factors can be monitored by Local local surveillance that can be conducted on smaller geographical scales that can provide insight into the micro-dynamics of AMR at ground levels. Local surveillance enables early detection of AMR reservoirs and can address the community specific needs. This can be achieved by establishing a local AMR monitoring among local/place-based researchers, health workers, farmers, community members and stakeholders which can help in identifying high-risk areas and prioritise local needs. A combined qualitative and quantitative approach (Figure 2) can offer a comprehensive understanding, context and depth of the problem. Qualitative approaches can provide insights into how cultural practices and social behaviours influence the use of antimicrobials (30). Knowing the concerns of the community and stakeholders and collecting environmental data through a citizen science approach with community involvement can unlock many benefits, including improving data quantity and quality, engaging communities and stakeholders and increasing awareness. Samples that citizen scientists can gather might come from a broader range of locations than researchers are unable to access. Metagenomics including whole genome sequencing (WGS) can provide useful information about how resistance spreads within and between different reservoirs (31). Recently, many studies showed the potential of machine learning methods in predicting AMR combining with WGS methods (32). Using these techniques in local settings could quickly gather data on resistant genes and strains and outcome can help translate a practical implementation by making interventions more context specific. However, the application of genomic approaches has been mostly restricted to research, and a lack of awareness/global effort/political will to invest in using these technologies in active monitoring is a major obstacle. Stable funding is critical for long-term efforts to monitor and combat AMR. More funding should be allocated to multi-disciplinary approaches and studies that also aim for environmental AMR surveillance.