Towards a genomics-informed, real-time, global pathogen surveillance system

Abstract

The recent Ebola and Zika epidemics demonstrate the need for the continuous surveillance, rapid diagnosis and real-time tracking of emerging infectious diseases. Fast, affordable sequencing of pathogen genomes - now a staple of the public health microbiology laboratory in well-resourced settings - can affect each of these areas. Coupling genomic diagnostics and epidemiology to innovative digital disease detection platforms raises the possibility of an open, global, digital pathogen surveillance system. When informed by a One Health approach, in which human, animal and environmental health are considered together, such a genomics-based system has profound potential to improve public health in settings lacking robust laboratory capacity.

Figure 1. A genomics-informed surveillance and outbreak response model.

Portable genome sequencing technology and digital epidemiology platforms form the foundation for both real-time pathogen and disease surveillance systems and outbreak response efforts, all of which exist within the One Health context, in which surveillance, outbreak detection and response span the human, animal and environmental health domains. PowerPoint slide

Figure 2. Challenges to in-field clinical metagenomics for rapid diagnosis and outbreak response.

A mobile medical unit deploying a portable clinical metagenomics platform has been established at the epicentre of an infectious disease outbreak, but the team faces challenges throughout the diagnostic process and epidemiological response. For example, in the case of Zika virus, samples, such as blood, with low viral titres, a small genome of <11 kb and transient viraemia combine to complicate detection of viral nucleic acid by use of a strictly metagenomic approach. Furthermore, obtaining a sufficient amount of viral nucleic acids for genome sequencing beyond simple diagnostics requires a tiling PCR and amplicon sequencing approach. Other challenges include, for example, access to a reliable Internet connection, the ability to collect sample metadata and translating genomic findings into real-time, actionable recommendations. PowerPoint slide

Figure 3. Inferring transmission events from genomic data.

Genomic approaches to identifying transmission events typically involve four steps. In the first step, outbreak isolates, and often non-outbreak control isolates, are sequenced and their genomes either assembled de novo or mapped against a reference genome. Next, the genomic differences between the sequences are identified — depending on the pathogen and the scale of the outbreak, these may include features such as genetic variants, insertions and deletions or the presence or absence of specific genes or mobile genetic elements. In the third step, these features are examined to infer the relationships between the isolates from whence they came — a variant common to a subset of isolates, for example, suggests that those cases are epidemiologically linked. Finally, the genomic evidence for epidemiological linkages is reviewed in the context of known epidemiological information, such as social contact between two cases or a common location or other exposure. Recently, automated methods for inferring potential epidemiological linkages from genomic data alone have been developed, greatly facilitating large-scale genomic epidemiological investigations. PowerPoint slide

Figure 4. Emergence of infectious diseases.

In spillover, a pathogen previously restricted to animals gradually begins to move into the human population. During stage one (pre-emergence), as a result of changing demographics and/or land use, a pathogen undergoes a population expansion, extends its host range or moves into a new geographic region. During stage two (localized emergence), contact with animals or animal products results in spillover of the pathogen from its natural reservoir(s) into humans but with little to no onward person-to-person transmission. During stage three (pandemic emergence), the pathogen is able to sustain long transmission chains, that is, a series of disease transmission events, such as a sequential series of person-to-person transmissions, and its movement across borders is facilitated by human travel patterns. PowerPoint slide

Figure 5. A future model for surveillance and early outbreak response.

It is 2027, and our planet's changing climate and land-use patterns have meant that new emerging infectious diseases (EIDs) are spilling over into humans from wildlife reservoirs with increasing frequency. Building off EID hotspot maps developed in 2008 (Ref. 55), a global public health consortium has implemented an online surveillance tool that scans the digital output of citizens, news organizations and governments in those regions, including data from local retailers on key health-related products, such as tissues and over-the-counter cold remedies. In one such region, the syndromic surveillance system reports higher-than-average sales of a common medication used to relieve fever. Spatial analysis of the data from the pharmacies in the region suggests that the trend is unique to a particular district; a follow-up geographic information system (GIS) analysis using satellite data reveals that this area borders a forest and is increasingly being used for the commercial production of bat guano. An alert is triggered, and the field response team meets with citizens in the area. Nasopharyngeal swabs are taken from humans and livestock with fever as well as from guano and bat tissue collected in the area. The samples are immediately analysed using a portable DNA sequencer coupled to a smartphone. An app on the phone reports the clinical metagenomic results in real time, revealing that in many of the ill humans and animals, a novel coronavirus makes up the bulk of the microbial nucleic acid fraction. The sequencing data are immediately uploaded to a public repository as they are generated, tagged with metadata about the host, sample type and location and stored according to a pathogen surveillance ontology. The data release triggers an announcement via social media of a novel sequence, and within minutes, interested virologists have created a shared online workspace and open lab notebook to collect their analyses of the new pathogen. PowerPoint slide