Investigating of the Link between Antibiotic Resistance in Patients and the Environment: A Contribution to the One Health Approach

doi:10.21203/rs.3.rs-3946399/v1

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Investigating of the Link between Antibiotic Resistance in Patients and the Environment: A Contribution to the One Health Approach

https://doi.org/10.21203/rs.3.rs-3946399/v1

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Purpose

Antibiotic resistance is a growing global concern with far-reaching implications for public health. This study investigates the link between human and environmental health monitoring data in Lower Saxony, adopting the One Health approach.

Methods

Health and environmental monitoring data are analyzed to examine the prevalence of antibiotic-resistant bacteria (ARB). To achieve this goal, existing reports publicly available in internet were reviewed and spatial and statistical tools such as ArcGIS Pro and R programming language were utilized. Health monitoring data is collected annually as part of the sentinel system ARMIN (Antimicrobial Resistance Monitoring), launched in 2006 by the Public Health Agency of Lower Saxony (Germany). Environmental monitoring data were extracted from one study conducted in 2018.

Results

Key findings suggest that the role of wastewater treatment plants (WWTPs) as sources of ARB in the environment, highlighting their limited efficiency in removing ARB. Spatial analysis reveals regional variations in ARB rates, with vancomycin-resistant enterococci (VRE) more prevalent in the East and multi-drug resistant Gram-negative bacteria (3MRGN) evenly distributed across the Western and Eastern regions in Lower Saxony.

Conclusion

Overall, this study underscores the need for comprehensive One Health surveillance programs encompassing human health and the environment to address the complex challenge of antibiotic resistance effectively.

Antibiotic Resistance

One Health

Environment

Hospital

Lower Saxony

Antibiotic resistant bacteria

Antibiotics are the most effective agents available to treat infectious diseases by inhibiting the growth of bacterial cells. They are employed not just for human patients and livestock who suffer from infections but also to maintain the health of livestock and aid in proactive disease outbreak prevention. Antibiotic resistance (AR) is the capability of bacteria to resist and overcome exposure to antibiotics. This ability is facilitated by the acquisition of antibiotic resistance genes (ARGs) (Davison et al., 2000).

The use of antibiotics has led to the emergence and spread of AR, posing significant public health challenges globally. Although antibiotic resistance may naturally occur at low levels in most ecosystems, the high occurrences of ARBs and ARGs are mainly due to human activities (Uluseker et al., 2021). Antibiotics are categorized into five primary groups based on their mode of action: bacterial cell wall, cell membrane, protein synthesis, DNA and RNA synthesis, and folic acid (vitamin B9) metabolism. Meanwhile, bacteria have developed four primary types of resistance mechanisms against antibiotics: target modification, efflux, immunity and bypass, and enzyme-catalyzed destruction (Wright, 2010). Resistance to antibiotics arises as an evolutionary response to the strong selective pressure that is caused by the exposure to these substances. The current use of antimicrobials in clinical practice and in agriculture (animal husbandry) may be responsible for the horizontal spread of resistance genes in bacteria species and genera with no intrinsic resistance, and for the maintenance of vertical resistance mutations in populations (Wright, 2010).

Dimension of the problem

Antibiotics have earned the title of miracle drugs. However, their excessive usage and abuse over six decades have led to a surge in bacterial resistance to most antibiotics. The bacterial adaptive evolution has been so effective that particular bacterial infections have become almost impossible to treat using antibiotics (Andersson, 2003). It is paradoxical that research into new antibiotics and mechanisms of action is decreasing while antibiotic resistance and associated morbidity and mortality are increasing. The main reasons for this trend are believed to be the expensive development costs and the low potential return on investment. At present, only a handful of new antibiotics are undergoing clinical trials (Exner et al., 2017).

Morbidity and mortality are significant outcomes of antimicrobial resistance (AMR) in patients (Founou et al., 2017). Resistant bacteria double the likelihood of developing a severe health issue and triple the likelihood of death compared to non-resistant strains (Cecchini et al., 2015). It is extremely important to address AMR in a comprehensive manner to mitigate the impact on public health. These adverse effects are exacerbated by the severity of resistant infections and the susceptibility of the host (Friedman et al., 2016). Currently, approximately 700,000 individuals worldwide die annually due to drug-resistant infections (O’Neill, 2016). Recent research conducted by the World Bank indicates that AMR will accelerate poverty rates, particularly in low-income countries, when compared to the global average. As expected, the AMR crisis would widen the gap between these countries and their developed counterparts, thereby increasing income inequality (Jonas et al., 2017).

One health concept from WHO

It is challenging to imagine a topic that better represents the principles of One Health than AMR (Robinson et al., 2016). The One Health approach, characterized as a collaborative effort of various disciplines at local, national, and global tiers to achieve optimal health for people, animals, and the environment, acknowledges the interconnectedness of human health with animal health and the environment (American Veterinary Medical Association, 2008). One Health considers the impact of interconnected and nearby ecosystems on the emergence and spread of AMR, hence addressing AMR by implementing integrated AMR interventions at the city or regional level. The transmission of antibiotic resistance crosses boundaries between different ecosystems such as farms, hospitals, wastewater treatment plants, and natural environments. The well-being of a particular ecosystem can affect the health of other ecosystems, including humans (Hernando-Amado et al., 2019).

Antibiotic resistance monitoring in hospitals

Surveillance is crucial to managing healthcare-associated infections and antibiotic resistance. It provides the information needed to develop and monitor therapy guidelines, infection control policies, and public health interventions (Tacconelli et al., 2018). Active monitoring of antibiotic resistance is crucial for the successful management of antibiotics, which facilitates appropriate antibiotic utilization that optimizes clinical outcomes for patients while minimizing unintended antibiotic effects (Barlam et al., 2016).

The Governmental Institute of Public Health of Lower Saxony established the sentinel system ARMIN (Antimicrobial Resistance Monitoring in Lower Saxony) to recognize the regional trends of antimicrobial resistance in both inpatient and outpatient care. Many laboratories, acting as sentinel sites, presently contribute single case data of their microbiological results. The data are available for interactive queries on the internet from 2006 (Scharlach et al., 2011).

Antibiotic resistance monitoring in the environment

Global and national action plans have generally adopted a One Health framework to address AMR (Hernando-Amado et al., 2019). However, there is growing recognition that more emphasis should be placed on environmental dimensions. Although there is evidence suggesting that water environments play a role, there is a lack of studies quantifying this role and associated risks (Liguori et al., 2022). The occurrence and fate of antibiotics in the environment are determined by several factors, including their excretion (metabolism) by humans or animals, their interaction with solid environmental matrices (sorption), and their persistence in different environmental matrices (transformation) (Schmitt et al., 2017). A significant challenge of monitoring environmental antimicrobial resistance is that without a clearly defined objective, the mission can become an unrealistic task of monitoring everything, everywhere (Bengtsson-Palme et al., 2023).

There were two environmental monitoring studies conducted in Lower Saxony. In 2018, the Governmental Institute of Public Health of Lower Saxony (NLGA) carried out a measurement program to gain insights into the occurrence and spread of antibiotic-resistant bacteria in the state's bathing waters (NLGA, 2019). In addition, the Lower Saxony State Agency for Water Management, Coastal Protection and Nature Conservation (NLWKN) implemented a special monitoring program in the aquatic environment. The primary objective of this program was to obtain an overview of the possible contamination of water bodies in Lower Saxony with antibiotic-resistant bacteria and antibiotic residues (NLWKN, 2019).

Study area

The focus of this study is the federal state of Lower Saxony, which is located in northwest Germany. The state covers an area from the North Sea to the Harz Mountains and is intersected by three primary rivers running from east to west: the Ems, the Weser, and the Elbe. Additionally, there are other major rivers such as the Aller, Leine, and Oker. The study area is divided into an eastern and western part to reflect regional differences as presented in Figure 1.

Sampling strategies

ARMIN has been tracking the antibiotic resistance in the population since 2006. Participating microbiological laboratories in Lower Saxony and nearby states collect information about the patient and the sample analyzed. The data is electronically recorded in each laboratory information and management system and transmitted to the NLGA once a year in an anonymized form. These laboratories only reported results of tests indicating positive pathogen detection (Scharlach & Ziehm, 2019a).

Environmental monitoring only took place in 2018. Sampling was conducted at 80 sites, with 120 samples collected from water bodies and wastewater treatment plants. The samples were collected in sterile containers and transported under cool and dark conditions to the lab. Laboratory analyses were performed within 24 hours after the collection of the samples (NLWKN, 2019).

Microbiological Parameters

The Commission for Hospital Hygiene and Infection Prevention (KRINKO) recommends using two acronyms, 3MRGN and 4MRGN, to refer to multidrug resistant Gram-negative bacteria (Robert Koch Institute, 2012). 3MRGN means multidrug-resistant Gram-negative bacteria that are resistant to three of four specific groups of antibiotics, 4MRGN means resistance to all four groups. The antibiotic groups are ureidopenicillins (piperacillin), third- or fourth-generation cephalosporins (cefotaxime, ceftazidime), carbapenems (imipenem, meropenem), and fluorquinolones (ciprofloxacin).

Methicillin-resistant Staphylococcus aureus (MRSA) poses a growing public health challenge as it extends beyond methicillin to other beta-lactam antibiotics that are primary drugs for treating staphylococcal infections (NLWKN, 2019).

The unique characteristic of Vancomycin-resistant enterococci (VRE) is its resistance to glycopeptide antibiotics, specifically vancomycin. This resistance can spread not only to other enterococci, but also to other Gram-positive pathogens, albeit very infrequently (Robert Koch Institute, 2018).

The benefit of these classifications are that it enables improved identification of the essential antibiotic resistance that require immediate action in clinical practice. This identification is particularly relevant for vulnerable populations (NLWKN, 2019).

Data preparation

Monitoring of antibiotic resistance in humans and in the environment is carried out in Lower Saxony. However, the two monitoring data sets have different temporal resolutions. Only the ARMIN data is a time series, making it impossible to establish a temporal correlation between the two data sets. Nevertheless, each environmental sample has a specific location, and the ARMIN data is classified into the East and West regions. Therefore, it is feasible to conduct a spatial analysis to detect correlations between the data.

Several reports from the ARMIN database, published by NLGA, list various antibiotic-resistant bacteria. In order to ensure consistency between the health and environmental monitoring data only health reports with the same parameters as the environmental report were selected, while regional differences were also considered in.

To assess 3MRGN, the ARMIN data on "Development of the proportion of 3MRGN E. coli and the number of E. coli isolates tested compared to cefotaxime in a regional comparison" was used (Scharlach & Ziehm, 2018a). It was assumed that E.coli is representative of Gram-negative bacteria and a the proportion of 3MRGN E. coli was calculated from the ARMIN data as the proportion of cefotaxime-resistant E. coli with additional resistance to ciprofloxacin in relation to all E. coli with a test for cefotaxime. There was no ARMIN report available to extract 4MRGN data.

To assess MRSA, the ARMIN data on "Development of S. aureus with resistance to oxacillin and number of S. aureus isolates tested in a regional comparison" was used (Scharlach & Ziehm, 2018b). Oxacillin is a type of antibiotic that belongs to the class of drugs known as penicillinase-resistant penicillins and S. aureus with resistance to oxacillin is considered to be MRSA.

To assess VRE, the ARMIN data on "Development of resistance of E. faecium and number of tested E. faecium isolates to vancomycin from blood culture isolates from the inpatient care area in a regional comparison" was used (Scharlach & Ziehm, 2019b). In fact, all parameters are based solely on data from hospitalized patients and the time period ranges from 2006 to 2018.

Development of GIS database

The geographic information system (GIS) database was created using ArcGIS Pro software. The geospatial data was obtained from Lower Saxony's special measurement program for the occurrence of antibiotic-resistant bacteria in surface waters (NLWKN, 2019). The environmental monitoring program consisted of the investigated sampling points and their locations in the respective counties. A point feature was used to manage the sample point data, allowing for efficient storage, retrieval, and analysis. Attribute data was manually entered into the GIS database, and a unique identifier was assigned to each record along with spatial coordinates to seamlessly integrate the attribute information with the geographic location. Various spatial analysis, query and visualization tasks were conducted using the developed GIS database.

Environmental monitoring

Multiple isolates can be obtained from a single sample through laboratory cultivation. To identify hotspots, which are areas with a high prevalence of antibiotic resistance, at least two bacterial isolates from a single sample must test positive. These are the results of the spatial analysis of the samples, as shown in following Figures. No positive MRSA isolate was identified in Lower Saxony. However, positive VRE isolates were detected, especially in the eastern part of the state, and three locations identified as hotspots for VRE monitoring, as shown in Figure 2. The first hotspot is located in Ottersberg, where a water sample was taken from the Wümme River. The second and third hotspots are located upstream and downstream of the Medingen wastewater treatment plant, where water samples were taken from the Ilmenau River. It can be inferred that these two cities are likely to have an impact on vancomycin-resistant enterococci in their respective areas, especially to ensure the health of the Wümme and Ilmenau rivers in the surrounding area.

It is evident that the frequency of positive 3MRGN is markedly higher than previous indicators (MRSA and VRE) and is evenly spread across the western and eastern regions of the Lower Saxony, with the majority of hotspots concentrated in the western part. There are six sites designated as 3MRGN monitoring hotspots as presented in Figure 3. The first and second hotspots lie in Cloppenburg, where water and sediment samples were taken from the Soeste River. The third and fourth hotspots are found in Oldenburg, where water and sediment samples were collected from the Hunte River. The fifth hotspot is located in Ottersberg, where a water samples were collected from the Wümme River. Finally, the sixth hotspot is located in Medingen, where a water samples were collected from the Ilmenau River. It can be concluded that these four cities are likely to have an impact on 3MRGN within their respective regions, especially in maintaining the health of the nearby Soeste, Hunte, Wümme, and Ilmenau rivers.

Only a small number of positive 4MRGN isolates were detected in Lower Saxony, and all of them were identified in the eastern region without any positive isolates in the western part. It is worth noting that unlike 3MRGN, no significant 4MRGN hotspots were found in the study region as presented in Figure 4.

In order to evaluate the effect of the wastewater treatment plant (WWTP), solely samples from both upstream and downstream of the WWTP were taken into consideration. In addition, the indicators with hotspots, specifically 3MRGN and VRE, have been chosen. There are seven locations that meet this criterion, as depicted in Figures 5 and 6. As can be seen, two out of seven samples (approximately 30%) have tested positive for VRE in the downstream area, while no VRE isolates were detected in the upstream area. The first site is located in Bovenden, where a water sample was taken from the Weende River. The second site is located in Walkenried, where a water sample was taken from the Wieda River. It can be suggested that the WWTP is the origin of this difference. WWTPs are designed to remove pollutants from wastewater, but they may not effectively eliminate all antibiotic-resistant bacteria.

One sample tested positive for 3MRGN in the downstream area, while no such isolates were detected in the upstream area. However, one sample exhibited contradictory behavior, making it difficult to draw definitive conclusions regarding the influence of the WWTP on this indicator in comparison to the previous one. The first site is located in Wolfsburg, where a water sample was taken from the Aller River. The second site is located in Medingen, where a water sample was taken from the Ilmenau River.

Health monitoring

The percentage of 3MRGN in Lower Saxony increased from less than 2% during the observation period to more than 10%, while MRSA showed a significant decrease to about 15% within the same period, as shown in Figure 7. The percentage of VRE remained stable at 8% for the most part, but has recently undergone a substantial increase, effectively doubling its share. It is evident that there were similarities in the trends of 3MRGN and MRSA between western and eastern Lower Saxony during the time period. The percentage of 3MRGN was approximately equal in the east and west, whereas MRSA was more prevalent in the east. On the other hand, the percentage of VRE was markedly greater in the western region prior to 2012, whereas since then it has been higher in the east than in the west.

Integration of results

It is important to note that environmental monitoring only occurred in 2018, while health monitoring data is collected during several years. Thus, the mean of annual health monitoring data after 2012 was calculated. The percentage of environmental monitoring data is calculated by dividing the number of samples with a positive isolate result over the total number of samples in the region. Generally, antibiotic resistant bacteria are more prevalent in the environment compared to healthcare settings, as demonstrated in Figure 8. However, this is also due to the low number of tests in environment, which leads to a high percentage even with just a few cases.

To gain a better understanding, the data is divided into western and eastern regions and normalized based on the overall value, as shown in Figure 9. The main purpose of data normalization is to facilitate its comparison. To achieve this, the value for the entire Lower Saxony is set to 100, and then the values for the western and eastern parts are adjusted. It is visible that 3MRGN values remained fairly consistent in both western and eastern parts in regards to health and environmental monitoring, whereas the VRE value was remarkably greater in the East in comparison to the West within both types of monitoring.

The findings of this study suggested that WWTP serves as the origin of antibiotic-resistant bacteria in the environment near the urban settlement, and may not efficiently eliminate AMR. In addition, there is a spatial correlation between health and environmental monitoring in Lower Saxony. The percentage of VRE was significantly higher in the East than in the West, whereas the percentage of 3MRGN remained fairly similar in both western and eastern parts. In conclusion, despite the existence of a robust health monitoring program in Lower Saxony, there is a deficit in consistent environmental monitoring that can identify antibiotic resistance, particularly in water bodies. In order to implement a One Health approach, a comprehensive surveillance program is needed that includes both the human population and the environment.

It is important to acknowledge a key limitation of this report. The specific bacteria considered as 3MRGN in environmental monitoring are not clear, while it was assumed that only E.coli bacteria were considered as 3MRGN for health monitoring. This introduces a level of uncertainty and limits the direct comparability of data. Therefore, the results of the report should be interpreted in the context of this limitation.

Data availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Funding No funding was received for conducting this study.

Ethical approval The authors confirm that the submitted manuscript is based on original findings. We also affirm that the involved research was conducted ethically, and the final form of this manuscript has been approved by all involved authors.

Consent to participate The authors fully provide consent for their participation in this manuscript.

Conflict of interest The authors declare that there is no conflict of interest in this paper.

Author Contribution

Mohammad Sarailoo wrote the main text of the manuscript, conducted data analysis, and prepared the figures. Regina Nogueira contributed to the study design and provided critical revisions to the manuscript. Markus Wallner also revised the manuscript.

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No competing interests reported.

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Investigating of the Link between Antibiotic Resistance in Patients and the Environment: A Contribution to the One Health Approach

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Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Antibiotic resistant bacteria

Dimension of the problem

One health concept from WHO

Antibiotic resistance monitoring in hospitals

Antibiotic resistance monitoring in the environment

Materials and methods

Study area

Sampling strategies

Microbiological Parameters

Data preparation

Development of GIS database

Results and discussion

Environmental monitoring

Health monitoring

Integration of results

Conclusion

Declarations

Author Contribution

References

Additional Declarations

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