Introducing AMR surveillance systems

Introduction

Antimicrobial resistance is a serious global public health problem. This module introduces you to AMR surveillance systems and the One Health approach to AMR surveillance, and provides an overview of the relationships between AMR surveillance systems in humans, animals and the environment. It also introduces local, national and global AMR surveillance networks and covers the functions of these networks, the types of data that are collected and the uses of this data. Finally, it takes you through surveillance system design using examples. This module builds on concepts and learnings from the module An introduction to surveillance. You should start by watching Video 1, which introduces the importance of AMR surveillance (CDC, 2018a).

After completing this module, you will be able to:

• describe the objectives and requirements of AMR surveillance systems
• describe the One Health approach to AMR surveillance
• outline the differences between AMR, AMU and AMC surveillance
• describe the types of data collected by surveillance networks
• provide examples of AMR surveillance systems in humans and animals
• outline the importance of and relationships between local, national and global AMR surveillance networks and systems
• explain integrated surveillance systems, providing examples
• identify local and national surveillance networks or systems relevant to your work context
• describe how surveillance systems can be designed.

1 How do we define surveillance?

Surveillance is defined as (CDC, 2018):

In clearer language, surveillance is the routine collection of health-related data, analysis of these data and feedback of the results, and interpretation to the relevant stakeholders. Surveillance is a widely used public health activity for many forms of infectious and non-infectious diseases. Surveillance is not in itself a scientific research activity, though some research projects make use of data that are collected in surveillance systems. Sometimes, surveillance systems in low and middle-income countries (LMIC) are funded or operated by research organisations, which adds to the confusion. The main differences between research and surveillance is that research is trying to ‘generate new knowledge’ whereas surveillance aims to monitor the size of a known health issue and/or monitor for emerging health issues.

2 What is AMR?

Antimicrobial resistance (AMR) defines a situation where microbes (e.g. bacteria, fungi, parasites or viruses) causing infections in humans, plants or animals develop the ability to remain unaffected by the drugs designed to kill them, making such ‘antimicrobial-resistant infections’ difficult to treat (CDC, 2020).

As noted in other modules, this course focuses on bacteria and will generally use AMR to mean bacterial resistance to antibiotics, but strictly speaking, AMR encompasses all the different micro-organisms.

Antimicrobials are used to treat infections in humans, animals (terrestrial and aquatic, companion and food-producing), and plants (crops, fruit trees, ornamental, etc). As antimicrobial resistance is a growing global issue across all sectors and since antimicrobials used in one sector can contribute to the emergence and spread of AMR in other sector(s), a ‘One Health approach’ is needed to fight AMR. (See more on One Health in the module Introducing a One Health approach to AMR.)

It is clear that antimicrobial resistance is an unavoidable evolutionary consequence of the selective pressure resulting from the use of antimicrobials. However, strategic decision-making and coordinated action at local, national and global levels to promote the prudent use of antimicrobials is key to mitigate the spread of resistance and the resulting morbidity and mortality. Figure 1 below, taken from the Review on Antimicrobial Resistance (also referred to as the O’Neill Report) highlights the projected mortality in humans in 2050 as a consequence of AMR.

Figure 1 The projected mortality (per 100,000 population) in humans as a consequence of AMR (Review on Antimicrobial Resistance, 2014). Specific numbers of deaths are also indicated for each continent.

Show description|Hide description

A map of the world that illustrates regional mortality per 10,000 population (where light blue is 5 and purple is 10+) and includes number of deaths: North America (light blue), 317,000 deaths; Latin America (medium blue), 392,000 deaths; Europe (light blue), 390,000 deaths; Africa (purple), 4,150,000 deaths; Asia (dark blue), 4,730,000 deaths; and Oceania (light blue), 22,000 deaths.

Figure 1 The projected mortality (per 100,000 population) in humans as a consequence of AMR (Review on Antimicrobial Resistance, 2014). ...

2.1 The importance of AMR surveillance

As you saw in Video 1, AMR surveillance is central to:

• assessing the scale of the AMR problem at a local, national or global level
• measuring patterns of AMR over time in a particular place or places
• informing public health policies on antimicrobial usage
• improving health outcomes in people and animals.

Surveillance is one of the five strategic priorities to tackle the rise in AMR globally (WHO, 2015) as outlined in the Global Action Plan (GAP) on AMR.

Surveillance data (animal or human) can be utilised to support patient care by informing treatment decisions (i.e. choice of therapy). Individual results might be used to determine treatment for a patient, and, when aggregated and analysed at local and/or national level, surveillance data can inform prescribing guidelines (Figure 2).

Figure 2 Surveillance data can help promote key actions at local, national and global levels (Review on Antimicrobial Resistance, 2014).

Show description|Hide description

Three concentric circles titled ‘How surveillance can improve health outcomes’. The smallest circle is labelled ‘Locally: Allow healthcare professionals to make better informed clinical decisions to ensure better patient outcomes’. The next circle is labelled ‘Nationally: Guide policy and ensure appropriate and timely public health interventions’. The largest circle is labelled ‘Globally: Provide early warnings of emerging threats and data to identify and act on long-term trends’.

Figure 2 Surveillance data can help promote key actions at local, national and global levels (Review on Antimicrobial Resistance, 2014).

2.2 Why is a One Health approach needed to fight AMR?

The concept of ‘One Health’ is covered in detail in the module Introducing a One Health approach to AMR, but here is a summary:

As you saw above, antimicrobial resistance can spread between humans, animals, plants and the environment, and it is therefore important to take a ‘One Health’ approach to AMR surveillance. The WHO defines ‘One Health’ as ‘an approach to designing and implementing programmes, policies, legislation and research in which multiple sectors communicate and work together to achieve better public health outcomes’ (WHO, 2017). The WHO’s Global Action Plan on AMR recommends that in practice AMR surveillance systems should include data from all sectors, and that there is a coordinated effort across local, national and global levels (Figure 2) to mitigate the risk posed by AMR (WHO, 2015).

Figure 3 shows some of the ways that antimicrobials and antimicrobial resistant bacteria can travel around the environment and come into contact with humans, animals and the environment, reiterating the importance of a collaborative, multisectoral, and transdisciplinary approach across multiple sectors to control AMR (CDC, 2018).

Therefore, a tripartite partnership composed of the United Nations agencies the World Health Organization (WHO), the Food and Agriculture Organization (FAO), and the World Organisation for Animal Health (OIE) has been instigated. These three bodies signed a joint Memorandum of Understanding (MoU) in 2018 in which they committed to cooperate to address the issue of AMR, and to take a One Health approach to do so. The tripartite partnership has three main goals to:

• ensure that antimicrobial agents continue to be effective and useful for curing diseases in humans and animals
• promote the prudent and responsible use of antimicrobial agents
• ensure global access to medicines of good quality.

Maximise

Figure 3 Ways that antibiotics and antibiotic resistant bacteria can travel around the environment and come into contact with humans and animals (Linton, 1977).

These three organisations have each produced their own action plan to achieve these joint goals. You will learn more about the plans in the following activity.

2.3 AMR, AMU and AMC – what are the differences?

Surveillance of AMR can track changes in bacterial resistance patterns over time in order to inform treatment strategies at a local level, policy decisions at a national level, and global strategy to mitigate the risk of resistant infections and the associated morbidity and mortality in the human, animal and agricultural sectors.

Antimicrobial use (AMU) and antimicrobial consumption (AMC) monitoring are important complementary activities to One Health AMR surveillance (IACG, 2018). It should be noted that AMU and AMC are two closely related concepts, with the terminology often used inconsistently.

Antimicrobial use, or AMU, refers to data on the antimicrobials taken by individual patients (humans or animals). Data are collected at patient level, which allows for a more comprehensive set of data to be gathered, such as information on indication, treatment regimen, route of administration and patient characteristics. In general, the collection of data on antimicrobial use requires more resources but provides additional information on prescribing practices, which is important for guiding antimicrobial stewardship activities.

AMU data centres on monitoring antibiotic use, typically using a metric involving a measured mass of antimicrobials, e.g. milligram (mg), gram (g) or kilogram (kg) of antimicrobials used in the human or animal sector. A raw total of ‘kg of antibiotics’ is therefore a simple and widely used AMU metric, usually with information regarding the indication (e.g. prophylaxis, treatment, etc).

Antimicrobial consumption, or AMC, is defined in terms of the ‘sale’ of antimicrobial medicines. This ‘sale’ of antimicrobials is captured by way of national-level estimates of the quantities of antimicrobials imported and manufactured (and then sold to distributors) in a country. These estimates of antimicrobial ‘sale’ data are mainly derived from import, sales or reimbursement databases. Such data are usually more accessible and can serve as a proxy for the actual use of antibiotics, for which data collection is often more laborious.

AMC data is typically expressed in terms of a defined daily dose (DDD) (WHO, 2020). For all medicines, a WHO resource is maintained that describes what is the expected dosing of that medicine for a 70 kg adult human – this is the defined daily dose. The AMC metrics may then further adjust the DDD quantity by dividing by numbers of individuals and/or periods of time to allow comparisons of consumption levels between populations of different sizes.

An example of a system which captures this type of AMC data in human health is the European Surveillance of Antimicrobial Consumption Network (ESAC-Net). ESAC-Net is a European Centre for Disease Control (ECDC) program which monitors AMC in human health and helps generate the evidence base necessary to promote AMR interventions at both local and national levels. ESAC-Net performs this using The European Surveillance System (TESSy) to collect data on the consumption of antimicrobials intended for systemic use and their related costs in EU/EEA/EFTA countries. The platform collects data in the community and hospital sectors at product level on:

• antibacterials for systemic use
• antimycotics for systemic use
• antimycobacterials
• antivirals for systemic use.

The resulting data are expressed as a number of DDD per 1000 inhabitants per day. AMC DDD data then permit comparisons to be made across local, national and global settings on trends in antimicrobial consumption over time, providing evidence of the impact of educational or regulatory interventions. See the Fundamentals of data for AMR module for more information, specifically the section on ‘drug utilisation methodology’.

An example of a system that captures data on antimicrobials for use in animals is the system designed and used by the OIE. Annually, the OIE invites its members to submit data on the quantities of antimicrobial agents intended for use in animals, using a specifically designed tool. While some countries have advanced systems in place to report sales data at the prescribers’ level, most countries are only able to report sales data at wholesalers’ level and/or import data as declared by custom authorities.

The data collected on quantities of antimicrobial agents used in animals in a country is analysed at OIE central level alongside the corresponding biomass of the animals present in country according to international databases held by the OIE and the FAO, (mg – quantity of antimicrobials used/kg – animal biomass). This allows for comparisons across OIE regions, and for trends in usage of antimicrobials over time to be understood. Section 8.1 discusses the OIE tool in further detail (OIE, 2020).

3 An introduction to AMR surveillance: local, national and global systems

AMR data are collected at local, national and global levels and provide information on local, national, regional and global trends. Figure 4 illustrates how AMR data (which can include hospital patient samples, veterinary samples, animal product samples for food safety or environmental samples) might flow between these three levels, and where the feedback, typically comprising appropriately summarised information, should occur. Depending on the surveillance results there may also be some strategic interventions that are fed back from the national or global levels to the local levels.

Figure 4 An overview of a comprehensive AMR surveillance network.

Show description|Hide description

An image of an AMR surveillance network. Local hospital veterinary, food safety and environmental laboratories all gather samples. This research feeds into national policy, and national policies feed into global policy. Information flow goes from local to national to global, and feedback goes from global to national to local.

Figure 4 An overview of a comprehensive AMR surveillance network.

Although progress in developing national and global surveillance systems is greatest in the human (healthcare) sector, it is important to remember that AMR-related surveillance systems are being developed and implemented in other sectors, as you learned in Section 2.3.

In the following sections you will look at some of the features of local, national and global surveillance systems.

4 Local surveillance systems

Local surveillance is the cornerstone of all AMR surveillance networks. Data collected by local surveillance sites are used to inform local decision-making and can also be reported centrally to a national system to provide a national overview of AMR. How surveillance is carried out can vary widely, but Figure 5 (Seale et al., 2017) is a good representation of how such systems look at a local level, and how they link into national systems.

Figure 5 An example of a local AMR surveillance process.

Show description|Hide description

A flow chart, with arrows between a series of boxes and circles. The first box is labelled ‘Sampling’. The next circle is labelled ‘Specimen’. The next box is labelled ‘Laboratory testing organism ID, antimicrobial susceptibility testing’. The next circle is labelled ‘Result’. The next box is labelled ‘Surveillance network’.There is an arrow going back from ‘Result’ to ‘Sampling’ that is labelled ‘Inform care: choice of antibiotics, further testing; informs local guidlines/policies’, and ‘Surveillance network’ has a note: ‘Uses data to inform regional/national policies’.

Figure 5 An example of a local AMR surveillance process.

In order to ensure consistent results across different surveillance sites or sectors participating in the surveillance network, it is important that standard procedures are used in each of these steps. If different methods or standards of testing are used in different local laboratories then the results cannot be easily compared or interpreted alongside one another. You will look in more detail at the importance of standardisation and quality assurance in the Quality assurance and AMR surveillance module. The importance of standardisation and quality assurance in how the data are managed, analysed, reported and interpreted are covered in depth in the Fundamentals of data for AMR and Processing and analysing AMR data modules.

4.1 Local surveillance systems in practice: patient care and surveillance

Laboratory teams working in microbiology laboratories regularly perform bacterial identification and antimicrobial susceptibility tests on samples collected by the clinical team (nurses, doctors, veterinarians) or animal owners, to provide information that can be used to treat the patient (human or animal). However, in many low and middle-income settings, bacterial identification and antimicrobial susceptibility testing (AST) are rarely performed due to financial, technical and logistical limitations.

To try to improve clinical care, laboratory capacity and AMR surveillance, a small number of laboratories may be specially supported in their microbiology capacity. Information obtained for clinical care can be collated and used as (passive) surveillance data, analysed and reported on by local surveillance teams and finally fed into a national AMR surveillance system, as detailed in Figure 6.

Figure 6 The relationship between patient care and surveillance (WHO, 2020).

Show description|Hide description

A flow chart. There is a box labelled ‘Clinical team’ that has an arrow, labelled ‘Patient’s specimen’, pointing to another box, labelled ‘Laboratory team’. Another arrow, labelled ‘Patient’s laboratory results’, points from this box back to to ‘Clinical team’. A second arrow from ‘Laboratory team’, also labelled ‘Patient’s laboratory results’, points to another box, ‘Surveillance team’. There’s an arrow from this box that points to a label, ‘Surveillance data’. Surveillance data has three arrows; one points to a new box, ‘National AMR surveillance system’; the other two, labelled ‘Empirical treatment guidelines’ and ‘Local AMR control strategies’, point back to ‘Clinical team’.

Figure 6 The relationship between patient care and surveillance (WHO, 2020).

Now that you have looked at some aspects of local surveillance it is time to think about how this applies to your work by completing Activity 3.

Activity 3: the AMR surveillance process in your workplace

Timing: Allow about 45 minutes

By signing in and enrolling on this course you can view and complete all activities within the course, track your progress in My OpenLearn Create. and when you have completed a course, you can download and print a free Statement of Participation - which you can use to demonstrate your learning.

Part 2

Figure 7 is an example of a local surveillance system.

Figure 7 The relationship between patient care and surveillance (WHO, 2020).

Show description|Hide description

A flow chart. There is a box labelled ‘Clinical team’ that has an arrow, labelled ‘Patient’s specimen’, pointing to another box, labelled ‘Laboratory team’. Another arrow, labelled ‘Patient’s laboratory results’, points from this box back to to ‘Clinical team’. A second arrow from ‘Laboratory team’, also labelled ‘Patient’s laboratory results’, points to another box, ‘Surveillance team’. There’s an arrow from this box that points to a label, ‘Surveillance data’. Surveillance data has three arrows; one points to a new box, ‘National AMR surveillance system’; the other two, labelled ‘Empirical treatment guidelines’ and ‘Local AMR control strategies’, point back to ‘Clinical team’.

Figure 7 The relationship between patient care and surveillance (WHO, 2020).

Try to match each example action/activity listed below to the aspect of local surveillance (included on the figure) that it most closely relates to.

Laboratory team

Receiving a sample and the action of performing identification and a susceptibility testing according to standard methods

Surveillance team

A team responsible for data collection gives a report to a hospital committee about the use of antibiotics in the hospital

Clinical team

A patient with a suspected infection is seen and an appropriate sample is taken for further investigation

Surveillance data

Data are formatted and standardised according to set guidelines for submission

National surveillance system

A team collates and analyses data to guide public health policy on AMR

Using the following two lists, match each numbered item with the correct letter.

1. Laboratory team

2. Surveillance team

3. Clinical team

4. Surveillance data

5. National surveillance system

• a.A team collates and analyses data to guide public health policy on AMR

• b.Receiving a sample and the action of performing identification and a susceptibility testing according to standard methods

• c.Data are formatted and standardised according to set guidelines for submission

• d.A patient with a suspected infection is seen and an appropriate sample is taken for further investigation

• e.A team responsible for data collection gives a report to a hospital committee about the use of antibiotics in the hospital

The correct answers are:

• 1 = b
• 2 = e
• 3 = d
• 4 = c
• 5 = a

5 National and multinational surveillance systems

Many countries now collate local AMR, AMU and AMC surveillance data to provide either a regional or national overview of AMR, AMU and AMC trends that can inform policy and health interventions.

5.1 National surveillance systems

Let us begin with looking at examples of national surveillance systems.

5.2 Multinational surveillance systems

Now that you have looked at two systems which operate at national level, let’s consider two examples of multinational systems which operate across several nations. You will then look at the WHO’s GLASS programme, a standardised international programme for collecting AMR data and provides guidance on how to set up a national surveillance system which can submit data to its international platform.

5.3 Setting up national surveillance systems – the WHO’s GLASS

Obtaining reliable, accurate national data requires standardised approaches to sample collection, transport, storage, analysis and reporting at local sites. Similarly, national data must be reliable and comparable if they are to be integrated into regional or global surveillance reports, and examples such as EARS-NET and ReLAVRA are testament to this commitment.

To support international AMR surveillance, the WHO has developed the Global Antimicrobial Resistance Surveillance System (GLASS). GLASS promotes and supports a standardised approach to data collection, analysis and sharing at the global level, as well as providing a portal for submission of data and an annual report on results. As part of the standardised approach, GLASS provides guidance on the key components and functions of a national surveillance system so that data reported to GLASS are readily comparable between countries.

According to GLASS, a national surveillance system should comprise three core components (WHO, 2020) (Figure 8):

• a national coordinating centre
• a national reference laboratory
• selected AMR surveillance sites.

Figure 8 The core components of a national AMR surveillance system (WHO, 2020).

Show description|Hide description

A graphic showing the core components of a national AMR surveillance system: surveillance sites, a national coordinating centre and a national reference laboratory.

Figure 8 The core components of a national AMR surveillance system (WHO, 2020).

In addition to the core components, GLASS prompts national coordinating sites to standardise their reporting of antibiotic susceptibility testing (AST) data in line with internationally recognised standards – either the European Committee on Antimicrobial Susceptibility Testing (EUCAST) or the Clinical and Laboratory Standards Institute (CLSI).

5.4 Core surveillance system components as outlined by GLASS

For the rest of this section you will look at each of these core components of a national AMR surveillance system. Currently GLASS is focused on the surveillance of priority bacterial pathogens relating to human health (GLASS-AMR), although it is, over time, expanding into AMU and One Health surveillance.

• Surveillance sites collect clinical, microbiological and demographic data from patients. These are usually hospitals or out-patient health facilities with access to relevant laboratory support. There is no fixed number of surveillance sites that is needed for a National AMR surveillance system; there could be as few as one site, which might be appropriate in a small nation or if very limited funds are available. There could be 5 or 10 or 50 surveillance sites, depending on the size and diversity of the country and the resources available for running the surveillance program. There is no need for every hospital in the country to be contributing data to the AMR surveillance system – this is unlikely to be practically possible anyway.
• The primary function of a national reference laboratory is to promote good microbiology laboratory practice by compiling and disseminating standard methods to surveillance sites. It may also perform confirmatory testing and support surveillance sites by providing training. Different sectors may have their own national reference laboratories; for example in the UK, where this course was written, the national reference laboratory for healthcare-associated bacteria is the AMR and Healthcare Associated Infections (AMRHAI) laboratory, while the National Reference Laboratory for Food Microbiology monitors AMR in the food chain.
• The national coordinating centre (NCC) establishes and oversees the WHO’s Glass national surveillance system. It gathers AMR data from the surveillance sites and national reference laboratories and communicates this information to national policymakers and global surveillance systems. In many countries this is one of the roles of the AMR coordinating committee (AMRCC).

An example of a country utilising this approach in the animal health sector is Canada. AMC surveillance in animal health is accomplished through the mandatory reporting of antimicrobial sales data from members of the Canadian Animal Health Institute (CAHI), the trade association representing manufacturers and distributors of veterinary pharmaceuticals in Canada. The Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) – which we will discuss in detail in Section 7 – also collects AMU and AMR data in animals through surveillance in the animal health sector.

6 Global surveillance systems

Global surveillance programmes that monitor antibiotic resistance in specific bacterial pathogens, such as Mycobacterium tuberculosis (Zignol et al., 2016) and Neisseria gonorrhoeae (Wi et al., 2017) have been in place for many years. However, significant gaps remain in the surveillance of many other important bacterial pathogens that cause infections in humans. Addressing this problem and developing common standards for data collection, analysis and sharing at local, national, regional and global levels led to the establishment of the WHO’s GLASS platform in 2015.

As you may recall, the Global Action Plan on AMR recommends that a One Health approach be applied to AMR surveillance (WHO, 2015). It should be noted that GLASS does not yet (at the time of writing in 2020) constitute a truly global One Health AMR surveillance system as it is in its early implementation phase and continues to undergo development. It should also be noted that although there is currently no global cross-sector (human, animal, agriculture)-integrated surveillance system, the WHO Advisory Group on Integrated Surveillance of Antimicrobial Resistance (AGISAR) has worked in close collaboration with the FAO and the OIE to promote the development of harmonised surveillance across different sectors in order to inform public health, animal health and global food security. The WHO is also working on a protocol called ‘Tricycle’ aimed at supporting countries to take a One Health approach to AMR surveillance in humans, animals and the environment.

As of April 2020, 92 countries were enrolled in GLASS (Figure 9). Enrolment does not necessarily mean that the countries have provided AMR data to GLASS, but it does confirm the country is in the process of developing a national AMR surveillance system. Countries who enrol in GLASS are expected to nominate a national focal point that operates as the national communication hub and represents the AMR surveillance system in that country. The GLASS IT (information technology) platform also operates via the national focal point, and once aggregated AMR data are available, such as isolate-specific antimicrobial susceptibility data, they can be shared with GLASS.

Maximise

Figure 9 GLASS country enrolment status as of April 2020 (WHO, 2020).

Show description|Hide description

A map of the world showing which countries have enrolled in GLASS.

Figure 9 GLASS country enrolment status as of April 2020 (WHO, 2020).

7 Integrated national surveillance platforms: CIPARS

You have looked at local, national (including multinational) and global surveillance systems, so it is now time to discuss integrated systems.

Integrated systems aim to collect, analyse, and communicate trends in AMU and AMR for select bacteria from different sectors. Information from these integrated systems supports measures to contain the emergence and spread of resistant bacteria among animals, food and people, with the aim of prolonging the effectiveness of antimicrobials. One example of a comprehensive, national, integrated One Health AMR and AMU surveillance system is the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS).

CIPARS monitors the trends in AMU of all antimicrobial agents and AMR in selected bacteria in humans, animals and food sources from all over Canada. Figure 10 shows the composition of the CIPARS surveillance approach. It is important to note that the CIPARS system shares similarities with EARS-NET and ReLAVRA in the key system components it relies on, e.g. sentinel sites, reference laboratories and epidemiology units in charge of collating, analysing and interpreting data.

At this point it is worth noting that AMR surveillance in animals can serve different purposes, depending on whether the end goal is to secure animal and/or human health, and its design (i.e. area surveyed, microbe – antimicrobial (or ‘bug-drug’) combinations and choice of standards) should be adapted accordingly – such considerations are covered in more depth in the AMR surveillance in animals and the Introducing a One Health approach to AMR modules.

Provision of data to an integrated surveillance system is made possible using standardised collection and testing procedures to ensure that results from different studies can be compared and contrasted. In this way trends in AMR, AMU and AMC in each sector and between sectors can be investigated. This allows for effective measures to reduce the emergence and spread of resistant organisms between people, animals, agricultural and animal produce to be developed.

Maximise

Figure 10 CIPARS surveillance components in 2016 (CIPARS, 2018).

8 Surveillance methods and design

In this section you will first look at the data that is collected by surveillance systems before moving on to see how the data are reported.

8.1 Data collected by surveillance networks

Data reported to surveillance systems should be based around:

• what the surveillance system is designed to do
• guidelines set out by the WHO, OIE, FAO, or global surveillance networks
• the types of infection that are present in the setting or country where the data is being collected
• which types of samples can be collected, for example, blood, faeces, or swabs from patients or equipment.

AMR surveillance is usually limited to a number of priority pathogen-antimicrobial (bug-drug) combinations. Section 5 gave details on the data required for some surveillance systems such as EARS-NET, ReLAVRA and GLASS. It is not possible to monitor all forms of resistance in all microbes continuously, so any surveillance system must make a pragmatic choice about the highest priority and the easiest organisms to collect AMR data on.

As discussed above, data collected by surveillance networks are not restricted to antimicrobial susceptibility and resistance data: data on antibiotic usage and consumption can also be collected in the same systems. The choice of what data to collect depends on the purpose of the system. Clinical, patient demographic and epidemiological information often accompany AMR/C/U data and provide crucial contextual information, which is vital to interventions or decisions made as a result of communicating these data.

In local surveillance networks, this contextual data might include:

• the patient’s date of birth and gender
• the type of specimen
• the patient’s diagnosis
• any antimicrobial therapy that has already been given
• whether the infection was hospital- or community- acquired.

Patient information is important because it helps to inform practical guidelines for antimicrobial use. For example, if a particular organism is most commonly found in samples taken from outpatient clinics to treat a human health condition, then the treatment guidelines for this type of infection in this setting could be revised in light of the AMR levels detected by the surveillance system.

Data must be collated and reported in a format that can be readily used, for example to determine antimicrobial susceptibility and resistance patterns across multiple bug-drug combinations, or to compare antibiotic use in animals between different countries or over time. You will now look at data submitted via the OIE tool and go through a specific example which highlights the need for complete, context-rich data.

An example: data reported via the OIE tool

As discussed in Section 2.3, the OIE has established a worldwide database that monitors quantities of antimicrobials intended for use in animals. In 2019, data to the OIE was submitted by 153 countries (OIE, 2020), as shown in Table 1.

Table 1 Number of countries that responded to the OIE survey in the fourth round of data collection, by OIE region.

OIE region	Number of countries that submitted reports	Number of OIE members Footnotes   1	Proportion of response (%)
Africa	44	54	81
Americas (OIE members)	29	31	94
Americas (non-contiguous territories) Footnotes   2	1	n/a	n/a
Asia, Far East and Oceania	25	32	78
Europe	48	53	91
Middle East	6	12	50

Footnotes  

^{Footnotes   1} Distribution of countries by OIE region is done according to the OIE Note de Service 2010/22 – Annex 9 Back to main text

Footnotes  

^{Footnotes   2} Due to geographic distribution, non-contiguous territories were included in the Americas Back to main text

• Can you recall what variable AMU data is adjusted by to provide a rate, e.g. by country, allowing for comparisions between countries and regions?

• AMU data are often adjusted for animal biomass.

Meaningful comparisons need to be made between antimicrobial reports intended for use in animals and those which take into account total animal populations (which vary yearly and between countries and regions). A calclulation known as ‘animal biomass’ enables these comparisons to be made, and this is calculated as the total weight of live animals in a given population, country and year. Animal biomass is used as a proxy measure for animals likely to be exposed to antimicrobials. The approach to calculating animal biomass varies between species and is not covered in this module. Antimicrobial use is adjusted for animal biomass according to the following calculation:

Show description|Hide description

An equation, with ‘antimicrobial agent use reported (mg)’ over ‘animal biomass (kg)’.

AMU data that has been adjusted by animal biomass allows for patterns to be analysed (Figure 11).

Maximise

Figure 11 Quantities of antimicrobial agents intended for use in animals adjusted by animal biomass, 2016 regional comparison (mg/kg) (OIE, 2020).

• From Figure 11, how does the quantity of antimicrobial agents figure for ‘Asia, Far East and Oceania’ compare to that of Europe?

• The quantity of antimicrobial agents figure for Asia, the Far East and Oceania is higher than that of Europe.

• By what factor does the quantity of antimicrobial agents figure for Asia, the Far East and Oceania exceed that of Africa?

• By approximately a factor of 5.

• What factors might explain the differences in these figures for the quantity of antimicrobial agents, between regions?

• Socio-economic, geographical, predominant method of animal husbandry are some of the factors that could explain the differences.

8.2 Surveillance system design

Finally for this module, you will learn about the design of surveillance systems using some examples.

In an active surveillance system, cases are sought out and sampled purposefully. This is often undertaken in response to a stimulus, for example in response to an increasing rate of particular infections. An example would be an increase in post-operative wound infections not responding to first-line antimicrobials in a specific healthcare facility. This may prompt active case finding and sampling of all patients who have a wound infection to see if the infections are caused by the same bacterial strain with a specific antimicrobial resistance mechanism, and if this resistant strain may have been transmitted between patients.

An example of an active surveillance methodology used in the animal sector to help monitor rates of resistance, is the work undertaken by the European Antimicrobial Susceptibility Surveillance in Animals (EASSA). The potential for transmission of antimicrobial resistant bacteria from food-producing animals to humans via contaminated food is a serious public health concern. The EASSA programme collects bacterial isolates using standard and uniform methods from healthy food-producing animals, focusing on bacterial species such as Salmonella and Campylobacter spp. as well as commensal Escherichia coli and Enterococcus spp. Slaughterhouses from countries which participate in the programme are purposefully chosen based on animal throughput, with samples sent to a central laboratory for antimicrobial susceptibility testing. The results derived help illustrate the scope of antimicrobial resistance in the food-producing animal sector (De Jong, 2013).

A passive surveillance system is defined by cases not being actively sought, but rather obtained using information that is already being generated for other (typically clinical) purposes. For example, in the UK and many other high-income settings, there is regular reporting by healthcare institutions of their routinely collected AMR data to a central platform. Hospitals in England report on all cases of certain bacterial infections, along with their antimicrobial susceptibilities, to Public Health England (PHE) which then collates these data and analyses trends on a region or population basis. Such systems rely on a cooperative platform made up of healthcare institutions, laboratories and central public health bodies.

An example of passive surveillance systems in the animal sector is the work done by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) in Canada. CIPARS relies partially on diagnostic samples submitted routinely by producers to local animal health laboratories, which are then submitted to a central laboratory for further analysis. A particular focus is Salmonella, with continual analysis through passive surveillance allowing for trends in resistance within this bacterial species to be observed over time.

Passive surveillance systems are often (though not always) less time-consuming and less expensive than active surveillance systems. However, active surveillance systems typically allow more comprehensive data gathering, i.e. data gathered against a larger number of variables, targeted to answer a specific question from a representative sample, than passive surveillance, but at a greater cost. Most national AMR surveillance systems in high-income countries are based around a passive surveillance system.

Lastly let us look at a sentinel surveillance system, which selects key sites within an area of interest for the population rather than collecting data from all sites in a region or country. In a passive surveillance system this could be a cohort of hospitals chosen to be representative of the healthcare system. These sentinel sites report high-resolution data on all isolates/patients with a laboratory-confirmed specimen in line with particular standards.

The WHO’s GLASS AMR programme supports a sentinel site approach, particularly for low and middle-income countries where it is neither feasible nor necessary, to collect data from every healthcare facility. Countries focus their efforts on collecting good quality data from a selection of sites chosen to represent different levels of healthcare and reasonable population coverage, making establishing a surveillance system more affordable and achievable. Further sites can be added to the system at any stage, providing they meet the data quality requirements.

A point prevalence survey can also be used as a less resource-intensive way to collect AMR and AMU data. Point prevalence surveys gather data (such as the proportion of people or animals with infections caused by resistant bacteria) at a particular location and point in time (the ‘point’ in the name). The survey assesses what proportion of the individuals at the sampling point are receiving antimicrobials, or are known to have a particular form of infection (the ‘prevalence’). These surveys can be used to assess the current AMR and/or AMU situation in a location such as a hospital ward or abattoir at a specific point in time, and surveys can be repeated to show changes over time. The WHO has published a methodology for undertaking PPS for AMU in hospitals (WHO Methodology for Point Prevalence Survey on Antibiotic Use in Hospitals, version 1.1). Another widely used scheme is the Global Point Prevalence Survey of Antimicrobial Consumption and Resistance. These programmes can be used to measure and monitor antimicrobial use in hospitals worldwide to assess and compare quantity and quality of antimicrobial prescribing.

Activity 7: Self-assessment

Timing: Allow 2 minutes

Select the answer for

Activity 7: Self-assessment

here

Which type of surveillance system do you think Figure 12 below best represents?

Figure 12 The core components of a national AMR surveillance system (WHO, 2020).

Show description|Hide description

A graphic showing the core components of a national AMR surveillance system: surveillance sites, a national coordinating centre and a national reference laboratory.

Figure 12 The core components of a national AMR surveillance system (WHO, 2020).

Select an option from the list below and explain in a couple of sentences why you chose this option:

Active surveillance system

Sentinel surveillance system

Passive surveillance system

All of the above

None of the above

 

a. 

Active surveillance system

b. 

Sentinel surveillance system

c. 

Passive surveillance system

d. 

All of the above

e. 

None of the above

The correct answer is d.

An antibiogram is a pictorial representation of the antimicrobial susceptibility data for multiple bug-drug combinations obtained from one or more bacterial isolates. If data from multiple bacteria are combined, this information can be used to provide a summary of antimicrobial susceptibility patterns for a large number of bacteria.

Note that if antibiograms are being used to summarise across a collection of bacteria then we ought to ensure:

• isolates belong to the same species
• the method by which the isolates are collected is similar or comparable
• that the analysis includes a minimum of ten isolates in order for the final analysis to be meaningful.

Antibiograms can be used to track resistance trends and compare susceptibility rates between different hospital departments, healthcare facilities, farms, regions or countries. Antibiograms can also be used by clinicians and veterinarians to guide treatment decisions.

Activity 8: Analysing AMR susceptibility data

Timing: Allow about 30 minutes

Part 1

Figure 13 shows an example of an antibiogram. The first column lists the organisms that were included. The second column shows the number of isolates of that organism that were tested and included in the antibiogram. As a rule of thumb, to make general statements about patterns of antibiotic resistance you should have at least ten bacterial isolates of a particular species – but the more, the better. The remaining columns show the antimicrobials that were tested. The values show the percentage of organisms susceptible to each antibiotic.

Some antibiograms are colour-coded to reflect their general patterns of resistance. Bug-drug combinations that are mainly susceptible are coloured green, whereas combinations that are predominantly resistant are coloured red. Intermediate levels of resistance are coloured yellow. These results reflect many individual susceptibility tests, which are determined using standardised susceptibility testing methods as described in the Antimicrobial susceptibility testing module.

Maximise

Figure 13 An example of an antibiogram.

Study Figure 13 and use it to answer the following questions:

1. Which Gram-negative organisms are included?

Answer

K. pneumoniae and E. coli.

2. What percentage of E. coli isolates are susceptible to ampicillin?

Answer

51%.

3. Which pathogen-antimicrobial combinations show high levels of resistance?

Answer

K. pneumoniae-ampicillin and MRSA-erythromycin. K. pneumonia is intrinsically resistant to ampicillin so this result is expected. However, the antibiogram also indicates that infections due to MRSA are highly likely to be resistant to erythromycin, and that nearly half of the infections due to E. coli are also likely to be resistant to ampicillin.

Part 2

Does your workplace use antibiograms to report cumulative antimicrobial susceptibility data?

If you have access to an antibiogram from your workplace, you should use it for the rest of this activity. If you do not have access to an antibiogram from your workplace, use the interactive antibiogram tool provided by Stanford University to select three organisms and three antimicrobials, and generate your own antibiogram. Note that data are not available for all combinations of pathogens and antimicrobials.

Once you have your antibiogram, make a note of any bug-drug combinations where resistance is reported and consider the following points:

1. Which levels of susceptibility/resistance would you colour code red, yellow, green?
2. How would you explain to a clinician what a 25% susceptible rate means? Does it mean the antibiotic will work 25% as well as if there was no antibiotic resistance?
3. What are the likely local effects on an antibiogram of different stewardship activities (eg increased/decreased local use of particular antibiotic)? What period of time might it take for changes to be seen?

Please add your thoughts and reflections to your reflective blog, and discuss them with your colleagues to see what they would say.

9 End-of-module quiz

Well done – you have reached the end of this module and can now do the quiz to test your learning.

This quiz is an opportunity for you to reflect on what you have learned rather than a test, and you can revisit it as many times as you like. 

• End-of-module quiz

Open the quiz in a new tab or window by holding down ‘Ctrl’ (or ‘Cmd’ on a Mac) when you click on the link.

10 Summary

In this module you have learned how a quality management system underpins the operational efficiency of a laboratory, and the internal and external checks that guarantee AMR data quality and integrity. You have also been introduced to the idea of accreditation for laboratories as a way of ensuring that quality standards are maintained.

You should now be able to:

• describe the objectives and requirements of AMR surveillance systems
• describe the One Health approach to AMR surveillance
• outline the differences between AMR, AMU and AMC surveillance
• describe the types of data collected by surveillance networks
• provide examples of AMR surveillance systems in humans and animals
• outline the importance of and relationships between local, national and global AMR surveillance networks and systems
• explain integrated surveillance systems, providing examples
• identify local and national surveillance networks or systems relevant to your work context
• describe how surveillance systems can be designed.

Now that you have completed this module, consider the following questions:

• What is the single most important lesson that you have taken away from this module?
• How relevant is it to your work?
• Can you suggest ways in which this new knowledge can benefit your practice?

When you have reflected on these, go to your reflective blog  and note down your thoughts.

11 Your experience of this module

Now that you have completed this module, take a few moments to reflect on your experience of working through it. Please complete a survey to tell us about your reflections. Your responses will allow us to gauge how useful you have found this module and how effectively you have engaged with the content. We will also use your feedback on this pathway to better inform the design of future online experiences for our learners.

Many thanks for your help.

Now go to the survey.

References

Acknowledgements

This free course was collaboratively written by Kay Saunders, Siddharth Mookerjee and Patrick Murphy, and reviewed by Alexander Aiken, Emma Zalcman, Melanie Bannister-Tyrrell, Claire Gordon, Natalie Moyen, Ben Amos, Rachel McMullan and Hilary MacQueen.

Except for third party materials and otherwise stated (see terms and conditions), this content is made available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Licence.

The material acknowledged below is Proprietary and used under licence (not subject to Creative Commons Licence). Grateful acknowledgement is made to the following sources for permission to reproduce material in this free course:

Module image: andreus/123RF.

Figure 1: from Antimicrobial Resistance: Tackling a Crisis for the Health and Wealth of Nations, 2014. This file is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence, https://creativecommons.org/ licenses/ by/ 4.0/.

Figure 2: Review on Antimicrobial Resistance, ‘How surveillance can improve health outcomes’, https://amr-review.org/ infographics.html. This file is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence, https://creativecommons.org/ licenses/ by/ 4.0/.

Figure 3: Government of Canada, ‘Epidemiology of antimicrobial resistance’, published at https://www.canada.ca/ en/ public-health/ services/ surveillance/ canadian-integrated-program-antimicrobial-resistance-surveillance-cipars/ background.html.

Figures 4 and 5: The Open University.

Figures 6 and 7: reproduced from Diagnostic Stewardship: A Guide to Implementation in Antimicorbial Resistance Surveillance Sites, copyright 2016 World Health Organization. Available online at https://apps.who.int/ iris/ bitstream/ handle/ 10665/ 251553/ WHO-DGO-AMR-2016.3-eng.pdf?sequence=1.

Figures 8 and 12: reproduced from ‘National antimicrobial resistance surveillance systems and participation in the Global Antimicrobial Resistance Surveillance System (GLASS)’, copyright 2016 World Health Organization. Available online at https://apps.who.int/ iris/ bitstream/ handle/ 10665/ 251554/ WHO-DGO-AMR-2016.4-eng.pdf?sequence=1&isAllowed=y.

Figure 9: Global Antimicrobial Resistance Surveillance System (GLASS) Report: Early Implementation 2020. Geneva: World Health Organization; 2020. Available online at https://apps.who.int/ iris/ bitstream/ handle/ 10665/ 332081/ 9789240005587-eng.pdf?ua=1.

Figure 10: © All rights reserved. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) 2016 Annual Report, Public Health Agency of Canada, 2016. Adapted and reproduced with permission from the Minister of Health, 2021.

Figure 11: World Organisation for Animal Health (OIE) (2020) OIE Annual Report on Antimicrobial Agents Intended for Use in Animals: Better Understanding of the Global Situation, fourth report, Paris: OIE, p. 61, Figure 36. Available at https://www.oie.int/ fileadmin/ Home/ eng/ Our_scientific_expertise/ docs/ pdf/ A_Fourth_Annual_Report_AMU.pdf (accessed 25 January 2021).

Figure 13: Fleming Fund.

Table 1: World Organisation for Animal Health (OIE) (2020) OIE Annual Report on Antimicrobial Agents Intended for Use in Animals: Better Understanding of the Global Situation, fourth report, Paris: OIE, p. 22, Table 1. Available at https://www.oie.int/ fileadmin/ Home/ eng/ Our_scientific_expertise/ docs/ pdf/ A_Fourth_Annual_Report_AMU.pdf (accessed 25 January 2021).

Every effort has been made to contact copyright owners. If any have been inadvertently overlooked, the publishers will be pleased to make the necessary arrangements at the first opportunity.