First step: commitment

Most countries have commitments under the International Health Regulations, and to global strategies for AMR, including through WHO GLASS. It is important to have local and national commitment to establishing WGS as a surveillance tool in (LMICs) within these broader systems as a first step. In our experience, commitment by the hosting organisation was an important first feature to establish WGS as a feature within each surveillance system. The experiences of other countries currently implementing WGS within their surveillance systems was an important aspect of making the business case for implementation.

Second step: assessment

An important second step in all countries with whom we have worked has been a system assessment of how WGS could be developed for use within existing surveillance systems. System assessments of laboratories, bioinformatics and supporting management systems proved a useful second step for the countries with which we worked, identifying how systems could work together, as well as gaps and needs. For example, WGS can be developed for use in a complementary way with existing phenotypic AST to contextualise bacterial isolates within the background population obtained from retrospective sequencing and the cumulative data from ongoing sequencing.

Third step: technical development

This step establishes the technical capacity within a country to sustain WGS for the long term. Across our work, this has included capacity building for locally,led research projects by providing resources and training, the development of sampling frameworks to address national public health and research needs, data collection to identify high-risk bacterial lineages and AMR genes, provision and integrated use of open-access tools for genomics analysis and data visualisation to understand the distribution of bacterial lineages.

Technical guidance and tools are globally available to support the development of WGS for AMR surveillance. WHO technical guidance32 is available to support the introduction of molecular methods in LMICs. In addition, open-access tools enable health professionals and policy-makers real time access to, and sharing of, genomic pathogen data for national AMR surveillance. Tools such as Pathogenwatch33 and Microreact42 43 enable epidemiological data to be combined with genomics to inform pathogen control strategies and interventions on a local, national and international scale.

A starting point for technical development is to establish a reference database including WHO priority pathogens and species of local importance. This can be achieved by retrospectively sequencing stored isolates that have ideally been collected in a structured way, including those which are susceptible to antibiotics. This is important to discern whether AMR strains originate from pre-existing locally circulating susceptible strains or are imported.

An appropriate prospective sampling strategy can be developed based on identified public health and research needs. Sampling strategies should include both passive surveillance and targeted surveillance of outbreaks and unusual isolates. Passive surveillance can be based on structured surveys in which susceptible and resistant isolates are sequenced to obtain an overview of the population genetic background of circulating bacterial strains. The combination of passive and targeted surveillance can identify putative high-risk clones through the prediction of resistance, virulence and global spread of bacterial lineages.

Capacity building is an essential step at this stage to support WGS within the emerging surveillance system. In our group of countries, workshops and training that included other countries’ experiences were highly beneficial for developing and maintaining a solutions perspective as challenges were experienced. This challenges-and-solutions approach is detailed further in the following sections.

Fourth step: create a business plan and standard operating practice for WGS to ensure long-term sustainability

A business plan covering laboratory, bioinformatics, data flow and financial management is useful to integrate WGS as part of the broader surveillance system. At a practical level, partner countries created a range of sustainable business practices including standard operating and supply chain procedures, quality assurance (QA) and reporting processes, as well as ongoing capacity development, and processes for ongoing governance and financial sustainability. The workflow components that need to be put into place, the associated training and quality assessment that are necessary to efficiently use WGS for AMR surveillance are suggested as a practical business planning framework in figure 2.

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Figure 2

Workflow components required to implement WGS for AMR surveillance. AMR, antimicrobial resistance; AST, antimicrobial susceptibility testing; WGS, whole-genome sequencing.

Integrating WGS within national surveillance systems is an opportunity underpinned by global technical standards and open-access tools. However, it is not without challenges. In the following sections, we review both the challenges and solutions of integrating WGS as part of AMR surveillance, based on our ongoing experiences in developing such surveillance in National Reference Laboratories in Colombia, India, Nigeria and the Philippines.

Laboratory

The first major obstacle faced by many LMICs is the need for a high-performing microbiology laboratory which is not always a given.66 For example, sterility of samples and workspaces can be difficult to maintain. Moreover, resource constraints may hamper a laboratory’s ability to set up microbiological cultures from which the substrate for many sequencing technologies is grown.67

The second major issue is the cost of laboratory equipment and machines. Next-generation sequencing machines are expensive in HICs, but paradoxically, because of supplier-based pricing models that weigh product prices against demand, they can be even more expensive in LMICs. Country-specific regulatory and administrative procedures have to be considered when planning to implement WGS surveillance. For example, laboratory equipment can only be purchased from state-approved suppliers which may further limit available options for WGS technologies in LMICs.

In addition to the initial purchase costs, laboratory equipment and machines need reagents, maintenance and infrastructure that is frequently absent in LMIC settings. For example, sequencing machines need continuous electricity supply, chemical reactions need to be prepared with laboratory-quality clean water and occur at specified optimal temperatures, and many reagents and DNA need to be cooled while stored. As an example, the total cost of installing GeneXpert MTB/RIF for TB diagnostics at several sites in Nigeria was more than twice as much the basic price for installation of the machine alone in a high-income setting.68

In some cases, LMICs acquire laboratory equipment, such as sequencing devices, with the help of international collaborations that provide funding and logistic support. For example, the Philippines purchased a sequencing device for AMR surveillance as part of a UK National Institute for Health Research (NIHR)-funded collaboration with the Centre for Genomic Pathogen Surveillance (CGPS).13 Apart from the high purchasing costs (US$215 000 for the sequencing device plus US$160 000 for presequencing and postsequencing equipment and US$6000 for renovations that were necessary to set up a sequencing laboratory), the Philippines initially faced the problem of finding a local supplier. Some reagents could not be purchased locally and had to be bought and shipped by UK collaborators. The problem with this solution is that it is not sustainable, as long-term financing for laboratory and device maintenance will have to be found and local supply chains ought to be established.

Bioinformatics

Analysing the outputs from sequencing requires significant computing resources. A laboratory setting up a WGS service is faced with two options: either build and maintain local infrastructure that has sufficient computing power for the likely sample throughput or upload the data to computing resources hosted elsewhere. The cost for local setup will be between the equivalent of a minimum of ten and many tens of thousands of dollars, and there are both known (power and cooling) and unknown (component replacement) ongoing costs which are often overlooked, yet significant. As the infrastructure in many LMICs cannot provide all of these requirements, laboratories may have to spend additional resources and space on generators and uninterruptible power supplies. Data upload to online resources relies on continuously available broadband internet connection which may not be available, either. In particular, the relative cost for the same type of connection compared with the cost of living can vary significantly among countries. However, once the data are remotely available, the full economic cost of running routine genome analysis is lower than on premise solutions.

Data flow

Currently, there is little standardisation of laboratory information management systems among different laboratories. In LMICs, data management systems are often paper based, which is error-prone and can hamper integration with digital sequence data. As most LMICs are still to implement WGS for AMR surveillance, there is currently an opportunity for developing standardised digital data management systems. At the same time, these systems must be flexible enough to be applicable in a range of different laboratory settings and pathogens. Data management systems should be based on a documented data standard and provide a user-friendly interface for linking sequence data with patient data and AST data. Moreover, they have to comply with regulations on data protection and privacy by providing options to restrict data sharing to authorised individuals and to define for how long sensitive data will be stored. Open-source free software can save costs and is also more transparent than proprietary software.

Financial

Building capacity for WGS surveillance of AMR in LMICs requires sustainable and flexible funding. In addition to one-off purchase costs for preparation and sequencing machines and the IT infrastructure to process and analyse sequence information, funding also needs to be secured for maintenance and servicing of laboratory machines and computational servers. Ordering machines and equipment, hiring staff and satisfying regulatory procedures all take time, especially when a WGS surveillance laboratory is set up for the first time. Therefore, grants will have to be flexible enough to accommodate delays in timelines and work packages. At the same time, grant approval and management must follow ethical and accountability standards. Formal procedures to ensure these standards may have to be put into place.

Training

Another major difficulty for the implementation of WGS surveillance in LMICs is the lack of trained personnel. Within-country expertise may be lacking both for laboratory scientists with genomics experience and bioinformaticians. Even if qualified bioinformaticians can be found, they often lack desirable epidemiology and microbiology training. Conversely, epidemiologists frequently lack the necessary bioinformatics skills to implement WGS surveillance. An associated concern is the lack of funded permanent positions in many LMICs which hinders the recruitment and retention of trained staff. In addition, even given the availability of trained staff, developing standard protocols for sequencing and genome analysis is a non-trivial task. If the regulations on handling biological specimens are complex, trained administrative staff may have to be hired in addition to specialist scientific staff. Similarly, administrative staff trained in accounting and ethical grant management will be required.

Quality assessment

Many LMICs do not yet have an NAP for AMR surveillance or a functional surveillance system. Consequently, implementing WGS surveillance may not be a priority. However, laboratories that do conduct WGS surveillance should be required to pass an EQA exercise before they form part of a national surveillance system to ensure the collection of high-quality, reliable data. Several national and international AMR surveillance networks and public health institutions have established standards that can be used for proficiency testing, for example, PulseNet, Gen-FS, CDC, FDA, GMI.50 69–71 EQA standards need to be stringent enough to ensure good-quality sequence data and reliable analysis results. However, there is a risk that strict standards at the laboratory level will exclude LMIC laboratories from participating in surveillance networks. An alternative solution could be to initially perform quality testing at the sequence level, while simultaneously providing support to improve laboratory standards. Optimising assays in new WGS laboratories to meet accreditation criteria will take time that needs to be taken into account when setting up surveillance systems.

Where local laboratories cannot be accredited as sequencing centres, another solution could be to ship samples to a centralised laboratory for sequencing. Finding a suitable courier service may be another hurdle. For example, not all couriers accept biological specimens. Moreover, DNA samples should ideally be shipped on dry ice to maintain low temperatures and thus to minimise damage to the samples. However, this method of shipping is expensive and may not be available in all countries. Thus, alternative storage and transport protocols may have to be designed and tested. Shipping samples abroad may further be subject to regulations on biodiversity conservation. In the future, this may also affect the sharing of DNA sequence information.72

Laboratory

In LMICs, the main challenge beyond the initial setup of a laboratory is keeping it up and running. To guarantee continuous operations in surveillance laboratories, stable supply chains for reagents and single-use laboratory items should be established locally. Commercial suppliers are more likely to offer stable goods deliveries if several laboratories within a country or region purchase from them. A sufficient amount of initial investment with a funding horizon of several years is required to kick-start the implementation of WGS surveillance in LMICs. Large-scale funders like the NIHR or philanthropic organisations may be able to exert pressure on suppliers to lower prices or offer alternative and more transparent pricing models to laboratories in LMICs.

Given resource and staff constraints, public health bodies and laboratories in LMICs will have to prioritise which bacterial isolates to sequence. However, prioritisation of isolates also occurs in HICs. For example, in the UK all Salmonella isolates are routinely sequenced, but not all S. aureus isolates.73 74 Prioritisation should be guided by what are the most urgent local public health concerns and associated research questions. Cost-effectiveness also plays a role in the decision on what isolates to sequence.75 Both passive surveillance based on random sampling of susceptible and resistant isolates to establish the population genetic context of circulating bacterial strains and targeted surveillance of highly resistant and outbreak isolates are important. Background surveillance does not need to be continuous, but could be based on structured surveys as in the case for TB surveillance in many countries.76 This may require a change in laboratory outlook from a diagnostic to a surveillance perspective.

Bioinformatics

If the computational infrastructure to conduct bioinformatic analysis is to be set up locally, establishing continuous supply chains for component replacement and upgrades will be important. Where technology has to be imported, custom arrangements should be simplified to guarantee timely delivery. With modern technologies such as workflow managers to describe analytical steps and containers to bundle software dependencies, the technical complexity of setting up analytical pipelines can be greatly simplified.77 This allows for reproducible analyses that can be run on a diverse range of infrastructures with little configuration. For example, the same bioinformatics pipelines for genome assembly, phylogenetic tree construction, Multilocus Sequence Typing (MLST) calling and AMR prediction have been implemented in partner laboratories in Colombia, India, Nigeria, the Philippines and the UK, using Nextflow78 as a workflow manager and Docker79 or Singularity80 containers to ensure that pipelines are compatible with local operating systems. All bioinformatics tools that are part of each workflow are open access and open source. A recent review of bioinformatics tools suitable for workflows in both LMICs and HICs has been published by Hendriksen et al.81

Where building local computing infrastructure is currently too expensive, alternatives are now available using genome analysis pipeline software and cloud-based infrastructure. Examples for cloud-based bacterial genomic analysis tools are the Bacterial Analysis Platform82 and Pathogenwatch.33 However, this requires financial systems within host organisations to allow payment for resource-usage-based subscription services in the cloud, such as Amazon Web Services, Google Compute Platform or Microsoft Azure. It also requires that data transfer via a stable internet connection is reliable and not subject to capped and expensive data plans.

Data flow

Reference databases and software need to be developed to make genomic information accessible across clinical, public health, environmental and agricultural sectors. Such databases already exist but need to be expanded and a single standard for data entry should be agreed. Genomic and associated metadata should be open access, for example, via a data portal on a website. Some information will have to be kept confidential, for example, metadata from hospital outbreaks that could be used to identify patients. WGS data should be stored alongside phenotypic AST data and metadata linked to the isolate sequences. To facilitate the curation of joint databases, the commonalities in reporting these different data types can be assembled and pipelined. The combined analysis of connected data types will give insights into behavioural patterns or events that drive the emergence and spread of resistant bacterial lineages and high-risk clones. Existing application programming interfaces and metadata ontologies are available, for example, the Minimal Data for Matching by the Global Microbial Identifier and System for Enteric Disease Response, Investigation and Coordination by the US CDC.83 84 WHONET is the most widely used example of a database software for the curation of phenotypic AST data. It could be extended with an option to include WGS surveillance data. For example, WGS data could be stored in one of the already existing databases, and the WHONET file could contain a variable that links to the relevant database entry. This separation could also guarantee that sequence data which on their own do not contain sensitive information are easily accessible, whereas metadata which are sensitive can only be accessed by approved public health officials and scientific collaborators. A web interface based on a WHONET configuration file could be produced with a flexible option for WGS data collection. Ideally, the interface should work on portable tablets that do not need constant power.

Financial

Various schemes exist to standardise and simplify grant management practices and to provide accreditation for good financial grant practices, for example, the Global Grant Community.85 The initiative sets out standard guidelines that need to be followed by both grantors (institutions awarding a grant) and grantees (institutions receiving a grant). As part of the assessment process, grantees are rated according to their financial capacity, that is, how large and complex a grant they are able to handle. Accreditation reassures grantors that grantees can responsibly manage received funding. Another advantage for grantees is that once accredited they will not have to repeat the assessment process for each new grant they apply for.

Training

Joint initiatives between HICs and LMICs are great opportunities for training and knowledge transfer. To maximise utility, training programmes should be tailored to the specific needs of participating countries. The curricula should be developed in discussion with local researchers to fill skills gaps and support local research agendas. Importantly, training documents should be accessible via online services such as Google Docs so that they are both easy to share and keep up to date. Keeping the information up to date could be the responsibility of Regional Reference Laboratories in collaboration with WHO or international surveillance networks. In addition, practical exercises should not require specialist IT equipment and should run on a relatively modest local computer. The training material and course structure should be streamed and modular so that they can be adapted for scientists to become trainers of local colleagues (train-the-trainer schemes). Other programmes have emphasised the need to provide incentives for staff retention once training is completed, as failure to retain staff can lead to interruption of surveillance, for instance, the Collaborative African Genomics Network provides funding for staff faculty positions at their home universities.86 To decrease the risk that WGS surveillance will be disrupted when a staff member leaves, training initiatives could be targeted at teams rather than individuals.

Quality assessment

EQA procedures should be standardised among collaborating centres to ensure that results are comparable and of high quality. The genomic-based EQA should be developed in collaboration with QA providers. Samples with known phenotypic and genotypic characteristics can be used as a standard against which the performance of a participating institute in laboratory and bioinformatics techniques can be measured.

Even though few LMICs will have the capacity for implementing WGS surveillance immediately, many more will have AMR surveillance programmes based on phenotypic testing. These programmes can be leveraged and built on to incorporate WGS surveillance later. NAPs can be developed or extended with this goal in mind. In order for WGS surveillance to become part of NAPs, standard operating procedures (SOPs) for sample collection, sample preparation, sequencing of isolates and regulatory procedures concerning access to and handling of samples and DNA sequence information will have to be developed. SOPs should take into account challenges experienced in LMIC settings and offer workable solutions. Once they are tested and approved, SOPs should be published in peer-reviewed journals to make them available to other researchers in LMICs and encourage a broader uptake of standardised protocols.