Pathogen Transmission Patterns Research Articles

Development of a protocol for using geo-trackers to identify zoonotic enteric pathogen transmission pathways in a pilot study in Kenya

Abstract Humans and animals can be exposed to fecally-transmitted pathogens in both private and public domain environments. Animals may also acquire pathogen infections from these two environments and transmit them to humans through different pathways. Evidence on how often and where interactions occur between the two environments could improve the effectiveness of public health programs for preventing zoonotic disease transmission and response to disease outbreaks. This study aimed to develop a protocol for using geo-trackers to measure the spatial-temporal movement and interaction between animals and children in households and public areas in low- and middle-income categories of urban neighbourhoods in Kenya. It also aimed to identify opportunities and challenges for the scale-up of these methods’ for surveillance of other zoonotic diseases of public health significance. One commercial geo-tracker device with the best technological performance and usability that met pre-defined criteria for the study context was identified. Community engagement meetings were then conducted to gather input on a proposed study protocol. Afterwards, infants and animals were geo-tracked in 10 households in urban informal settlements of Kibera and Jericho, Nairobi over two consecutive weeks with iterative improvements to protocols. The effectiveness of the geo-tracking exercise was evaluated through in-depth interviews with Community Health Volunteers (CHVs) and infant caregivers. Animal and infant behaviour and battery reliability of the geo-trackers were also monitored; and observed opportunities and challenges in implementing the protocol during the exercise were documented. Community members were receptive and accepted the use of geo-trackers on animals and children. In pilot testing, there was no change of behaviour from 10 infants tracked. Discomfort was observed for up to 30 min after the placement for some of the seven animals tracked, but the animals quickly adjusted. The battery for all geo-tracker devices lasted for the 24-h geo-tracking period. Some caregivers and CHVs were concerned whether the geo-trackers could record personal information. It was shown that geo-tracker devices can be successfully deployed to study animal-child interactions and movement in different categories of urban neighbourhoods. Recommendations have been made on the lessons learnt from the study to help scientists who would use geo-trackers for future community-based human and animal research. One Health impact statement Assessing human and animal risks of acquiring enteric infections from environmental contamination, or contributing to pathogen contamination of the environment requires understanding spatial-temporal patterns of human and animal movement between private households and the community. Movement of domestic animals is relevant for understanding household-community spatial patterns of pathogen transmission because animal ownership and contact with humans is common, and free-roaming animals carrying enteric pathogens can spread diverse faecal pathogens between environments. The community-based participatory research approach of this study evaluated implementation feasibility from the lens of technical usability and reliability of geo-tracking devices, as well as social acceptability and ethics related to using such devices for the community-based study of human and animal subjects in urban settings. Evidence and recommendations from this study will be useful to anyone interested in understanding human-animal-environment interactions and their contributions to infectious disease transmission.

The heterogeneous herd: Drivers of close-contact variation in African buffalo and implications for pathogen invasion.

Many infectious pathogens are shared through social interactions, and examining host connectivity has offered valuable insights for understanding patterns of pathogen transmission across wildlife species. African buffalo are social ungulates and important reservoirs of directly-transmitted pathogens that impact numerous wildlife and livestock species. Here, we analyzed African buffalo social networks to quantify variation in close contacts, examined drivers of contact heterogeneity, and investigated how the observed contact patterns affect pathogen invasion likelihoods for a wild social ungulate. We collected continuous association data using proximity collars and sampled host traits approximately every 2 months during a 15-month study period in Kruger National Park, South Africa. Although the observed herd was well connected, with most individuals contacting each other during each bimonthly interval, our analyses revealed striking heterogeneity in close-contact associations among herd members. Network analysis showed that individual connectivity was stable over time and that individual age, sex, reproductive status, and pairwise genetic relatedness were important predictors of buffalo connectivity. Calves were the most connected members of the herd, and adult males were the least connected. These findings highlight the role susceptible calves may play in the transmission of pathogens within the herd. We also demonstrate that, at time scales relevant to infectious pathogens found in nature, the observed level of connectivity affects pathogen invasion likelihoods for a wide range of infectious periods and transmissibilities. Ultimately, our study identifies key predictors of social connectivity in a social ungulate and illustrates how contact heterogeneity, even within a highly connected herd, can shape pathogen invasion likelihoods.

Habitat connectivity and host relatedness influence virus spread across an urbanising landscape in a fragmentation-sensitive carnivore.

Spatially heterogeneous landscape factors such as urbanisation can have substantial effects on the severity and spread of wildlife diseases. However, research linking patterns of pathogen transmission to landscape features remains rare. Using a combination of phylogeographic and machine learning approaches, we tested the influence of landscape and host factors on feline immunodeficiency virus (FIVLru) genetic variation and spread among bobcats (Lynx rufus) sampled from coastal southern California. We found evidence for increased rates of FIVLru lineage spread through areas of higher vegetation density. Furthermore, single-nucleotide polymorphism (SNP) variation among FIVLru sequences was associated with host genetic distances and geographic location, with FIVLru genetic discontinuities precisely correlating with known urban barriers to host dispersal. An effect of forest land cover on FIVLru SNP variation was likely attributable to host population structure and differences in forest land cover between different populations. Taken together, these results suggest that the spread of FIVLru is constrained by large-scale urban barriers to host movement. Although urbanisation at fine spatial scales did not appear to directly influence virus transmission or spread, we found evidence that viruses transmit and spread more quickly through areas containing higher proportions of natural habitat. These multiple lines of evidence demonstrate how urbanisation can change patterns of contact-dependent pathogen transmission and provide insights into how continued urban development may influence the incidence and management of wildlife disease.

Inferring person-to-person networks of Plasmodium falciparum transmission: are analyses of routine surveillance data up to the task?

BackgroundInference of person-to-person transmission networks using surveillance data is increasingly used to estimate spatiotemporal patterns of pathogen transmission. Several data types can be used to inform transmission network inferences, yet the sensitivity of those inferences to different data types is not routinely evaluated.MethodsThe influence of different combinations of spatial, temporal, and travel-history data on transmission network inferences for Plasmodium falciparum malaria were evaluated.ResultsThe information content of these data types may be limited for inferring person-to-person transmission networks and may lead to an overestimate of transmission. Only when outbreaks were temporally focal or travel histories were accurate was the algorithm able to accurately estimate the reproduction number under control, Rc. Applying this approach to data from Eswatini indicated that inferences of Rc and spatiotemporal patterns therein depend upon the choice of data types and assumptions about travel-history data.ConclusionsThese results suggest that transmission network inferences made with routine malaria surveillance data should be interpreted with caution.

A field sentinel study investigating withering syndrome transmission dynamics in California abalones

We examined the risk of withering syndrome (WS) rickettsia-like organism (WS-RLO) infection in sentinel red abalone (Haliotis rufescens) deployed in modules at two Southern California field sites, one adjacent to an abalone farm and one adjacent to wild abalones. WS-RLO DNA was detected in seawater near modules at the wild abalone site but not near the farm (WS-RLO DNA was detected in the farm effluent). More WS-RLO DNA was detected in tissue from abalone near the farm relative to those near wild abalones (p < 0.05). However, infection prevalence and intensity based on histology were low and similar between sites (p > 0.05) and were independent of WS-RLO DNA loads in abalone tissue and seawater. More stippled (ST)-RLO than WS-RLO were observed with more ST-RLO infections near wild abalone than near the abalone farm (p < 0.05). We demonstrate the utility of caged sentinel abalone to better understand pathogen transmission patterns in the field.

Beyond taxonomy: species complexes in New World phlebotomine sand flies.

A species complex (= species group, species series) is an assemblage of species, which are related morphologically and phylogenetically. Recent research has revealed several arthropod vector species that were believed to be a single nominal species actually representing a group of closely related species, which are sometimes morphologically indistinguishable at one or more developmental stages. In some instances, differences in terms of vector competence, capacity, or both have been recorded. It highlights the importance of detecting and studying species complexes to improve our understanding of pathogen transmission patterns, which may be vectored more or less efficiently by different species within the complex. Considering more than 540 species, about one-third of the phlebotomine sand flies in the New World present males and/or females morphologically indistinguishable to one or more species. Remarkably, several of these species may act in transmission of pathogenic agents. In this article, we review recent research on species complexes in phlebotomine sand flies from the Americas. Possible practical implications of recently acquired knowledge and future research needs are also discussed.

APPLICATION OF COMPARATIVE GENOME IN AQUACULTURE DISEASES DIAGNOSIS

The sustainability of aquaculture industry is critical both for global food security and economic welfare. However, the massive wealth of pathogenic bacteria poses a key challenge to the development of a sustainable bio-control method. Recent advances in genome sequencing study combined with pan-genome analysis can be an efficacious management applied to numerous aquatic pathogens. Thus, routine comparative genome analyses of aquatic pathogens will deduce the phylogenomic diversity and possible evolutionary trendsof aquatic bacterial pathogen strains, elucidate the mechanisms of pathogenesis, as well as estimate patterns of pathogen transmission across epidemiological scales. This study also reviews comparative pan-genome analysis with a particular focus on controlling aquatic diseases, especially for: (i) re-identifying the previously misidentified strain with high accuracy and discovering novel isolates that may be associated with high rateof fish mortalities, (ii) developing routine pan-PCR based on highly informative identified genetic targets that are capable of distinguishing all the clinical isolates, and finally (iii) studying the multivalent vaccine following reverse vaccinology towards the prevention of numerous aquatic animal diseases.

The Problem of Microbial Dark Matter in Neonatal Sepsis.

Neonatal sepsis (NS) kills 750,000 infants every year. Effectively treating NS requires timely diagnosis and antimicrobial therapy matched to the causative pathogens, but most blood cultures for suspected NS do not recover a causative pathogen. We refer to these suspected but unidentified pathogens as microbial dark matter. Given these low culture recovery rates, many non–culture-based technologies are being explored to diagnose NS, including PCR, 16S amplicon sequencing, and whole metagenomic sequencing. However, few of these newer technologies are scalable or sustainable globally. To reduce worldwide deaths from NS, one possibility may be performing population-wide pathogen discovery. Because pathogen transmission patterns can vary across space and time, computational models can be built to predict the pathogens responsible for NS by region and season. This approach could help to optimally treat patients, decreasing deaths from NS and increasing antimicrobial stewardship until effective diagnostics that are scalable become available globally.

Vector-borne Zoonotic Diseases in Turkey: Rising Threats on Public Health

Vector-borne zoonotic diseases (VBZDs) are a major problem for public health and animal welfare all over the world. In recent years, there has been an alarming increase in VBZDs, mainly caused by new or re-emerging arboviruses, bacteria and parasites. The World Health Organization enumerated 10 threats to global health for 2019, notably emphasizing climate change and emerging pathogens as growing priorities. It is important to review potential threats and develop new control programs for rising threats against human health and safety. Changes in host and vector population diversity and density may affect pathogen transmission patterns and influence VBZD emergence processes. In addition to environmental and climate-related changes, human and animal migratory patterns pose future threats. The geographic location and habitat features of Turkey support the establishment of many arthropod species as vectors of various diseases. To date, a total of 107 zoonotic infections have been reported originating from Turkey. Arthropods transmit 19 of 107 such infections, including 2 mosquito-borne, 9 tick-borne, 1 sandfly-borne, 3 flea-borne, 1 simuliid-borne, 1 mite-borne and 2 fly-borne diseases. In this review, we focus on the present status of knowledge on VBZDs as a rising threat to public health in Turkey to provide a foundation for future control efforts.

Commensal bacterial sharing does not predict host social associations in kangaroos.

Social network analysis has been postulated as a tool to study potential pathogen transmission in wildlife but is resource-intensive to quantify. Networks based on bacterial genotypes have been proposed as a cost-effective method for estimating social or transmission network based on the assumption that individuals in close contact will share commensal bacteria. However, the use of network analysis to study wild populations requires critical evaluation of the assumptions and parameters these models are founded on. We test (a) whether networks of commensal bacterial sharing are related to hosts' social associations and hence could act as a proxy for estimating transmission networks, (b) how the parameters chosen to define host associations and delineate bacterial genotypes impact inference and (c) whether these relationships change across time. We use stochastic simulations to evaluate how uncertainty in parameter choice affects network structure. We focused on a well-studied population of eastern grey kangaroos (Macropus giganteus), from Sundown National Park, Australia. Using natural markings, each individual was identified and its associations with other kangaroos recorded through direct field observations over 2years to construct social networks. Faecal samples were collected, Escherichia coli was cultured and genotyped using BOX-PCR, and bacterial networks were constructed. Two individuals were connected in the bacterial network if they shared at least one E.coli genotype. We determined the capacity of bacterial networks to predict the observed social network structure in each year. We found little support for a relationship between social association and dyadic commensal bacterial similarity. Thresholds to determine host associations and similarity cut-off values used to define E.coli genotypes had important ramifications for inferring links between individuals. In fact, we found that inferences can show opposite patterns based on the chosen thresholds. Moreover, no similarity in overall bacterial network structure was detected between years. Although empirical disease transmission data are often unavailable in wildlife populations, both bacterial networks and social networks have limitations in representing the mode of transmission of a pathogen. Our results suggest that caution is needed when designing such studies and interpreting results.

An agent-based approach for predicting patterns of pathogen transmission between aquaculture sites in the Norwegian fjords

The aquaculture industry is a main industry in Norway, and it must be sustainable, i.e. experience long-term growth and development: It is necessary to build an environmentally sustainable aquaculture industry that minimizes risks to the marine environment and biological diversity, – including the transmission of fish diseases. The process of fish disease transmission in aquaculture systems is influenced by many factors, including individual (fish and pathogen) conditions, movement behavior and environmental conditions. Fish disease dynamics originates from a complex system, and the transmission of viruses is an unstable process, making it difficult to predict and analyze. In preparation for this paper, we built an agent-based model to predict patterns of pathogen transmission with the purpose of identifying risks and hazards in the space and time domains. The model presented explores the potential effects of different factors, such as the conditions of agents, movement behavior and environmental conditions, on the simulated spread of a fish disease.We applied the model developed to different case studies in the Norwegian fjords. The results demonstrated how the infection risk at any point around the infected site is dependent on both the pathogen and the fish density at that point, and the infection risk increases when the pathogen or fish densities increase. The pathogen density decreases exponentially as a function of an increase in the water temperature, and the pathogen density increases with the velocity of the current or the fish density at the infected site. The pathogens are moved faster by higher current velocity, so this will slow the infection process at the local infected site. Nevertheless, the current will carry the pathogens to nearby places faster. The direction of the current is very important since the pathogens are predominantly moved by the currents.The agent-based method helps us advance our understanding of pathogen transmission and builds risk maps to help us reduce the spread of infectious fish diseases. By using this method, we may study the spatial and dynamic aspects of the spread of infections and address the stochastic nature of the infection process.

Bacterial genome sequencing and analysis: paving the way for a Switzerland-wide molecular epidemiological surveillance platform.

Facing multidrug resistant (MDR) bacterial pathogens is one of the most important challenges for our society. The spread of highly virulent and resistant pathogens can be described using molecular typing technologies; in particular, whole genome sequencing (WGS) data can be usedf or molecular typing purposes with high resolution. WGS data analysis can explain the spatiotemporal patterns of pathogen transmission. However, the transmission between compartments (human, animal, food, environment) is very complex. Interoperable and curated metadata are a key requirement for fully understanding this complexity. In addition, high quality sequence data are a key element between centres using WGS data for diagnostic and epidemiological applications. We aim to describe steps to improve WGS data analysis and to implement a molecular surveillance platform allowing integration of high resolution WGS typing data and epidemiological data.

Improving the quality and workflow of bacterial genome sequencing and analysis: paving the way for a Switzerland-wide molecular epidemiological surveillance platform.

Facing multidrug resistant (MDR) bacterial pathogens is one of the most important challenges for our society. The spread of highly virulent and resistant pathogens can be described using molecular typing technologies; in particular, whole genome sequencing (WGS) data can be used for molecular typing purposes with high resolution. WGS data analysis can explain the spatiotemporal patterns of pathogen transmission. However, the transmission between compartments (human, animal, food, environment) is very complex. Interoperable and curated metadata are a key requirement for fully understanding this complexity. In addition, high quality sequence data are a key element between centres using WGS data for diagnostic and epidemiological applications. We aim to describe steps to improve WGS data analysis and to implement a molecular surveillance platform allowing integration of high resolution WGS typing data and epidemiological data.

The Emergency Medical Service Microbiome.

Emergency medical services (EMS) personnel are an integral component of the health care framework and function to transport patients from various locations to and between care facilities. In addition to physical injury, EMS personnel are expected to be at high risk to acquire and transmit health care-associated infections (HAIs) in the workplace. However, currently, little is known about EMS biosafety risk factors and the epidemiological contribution of EMS to pathogen transmission within and outside the health care sector. Health care facility microbiomes contain diverse bacterial, fungal, and viral pathogens that cause over 1.7 million HAIs each year in the United States alone. While hospital microbiomes have been relatively well studied, there is scant information about EMS infrastructure and equipment microbiomes or the role(s) they play in HAI transmission between health care facilities. We review recent literature investigating the microbiome of ambulances and other EMS service facilities which consistently identify antibiotic-resistant pathogens causing HAIs, including methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus, and Klebsiella pneumoniae Our review provides evidence that EMS microbiomes are dynamic and important pathogen reservoirs, and it underscores the need for more widespread and in-depth microbiome studies to elucidate patterns of pathogen transmission. We discuss emerging DNA sequencing technologies and other methods that can be applied to characterize and mitigate EMS biosafety risks in the future. Understanding the complex interplay between EMS and hospital microbiomes will provide key insights into pathogen transmission mechanisms and identify strategies to minimize HAIs and community infection.

Evolutionary transitions between beneficial and phytopathogenic Rhodococcus challenge disease management.

Understanding how bacteria affect plant health is crucial for developing sustainable crop production systems. We coupled ecological sampling and genome sequencing to characterize the population genetic history of Rhodococcus and the distribution patterns of virulence plasmids in isolates from nurseries. Analysis of chromosome sequences shows that plants host multiple lineages of Rhodococcus, and suggested that these bacteria are transmitted due to independent introductions, reservoir populations, and point source outbreaks. We demonstrate that isolates lacking virulence genes promote beneficial plant growth, and that the acquisition of a virulence plasmid is sufficient to transition beneficial symbionts to phytopathogens. This evolutionary transition, along with the distribution patterns of plasmids, reveals the impact of horizontal gene transfer in rapidly generating new pathogenic lineages and provides an alternative explanation for pathogen transmission patterns. Results also uncovered a misdiagnosed epidemic that implicated beneficial Rhodococcus bacteria as pathogens of pistachio. The misdiagnosis perpetuated the unnecessary removal of trees and exacerbated economic losses.

Chronic disease in the Mojave desert tortoise: Host physiology and recrudescence obscure patterns of pathogen transmission.

A seminatural, factorial‐design experiment was used to quantify dynamics of the pathogen Mycoplasma agassizii and upper respiratory tract disease in the Mojave desert tortoise (Gopherus agassizii) over 2 years. Groups of initially healthy animals were separated into serologically positive (seropositive), seronegative, and artificially infected groups and paired into 23 pens. We found no evidence of long‐term immune protection to M. agassizii or of immunological memory. Initially seronegative, healthy tortoises experienced an equal amount of disease when paired with other seronegative groups as when paired with seropositive and artificially infected groups—suggesting that recrudescence is as significant as transmission in introducing disease in individuals in this host–pathogen system. Artificially infected groups of tortoises showed reduced levels of morbidity when paired with initially seronegative animals—suggesting either a dilution effect or a strong effect of pathogen load in this system. Physiological dynamics within the host appear to be instrumental in producing morbidity, recrudescence, and infectiousness, and thus of population‐level dynamics. We suggest new avenues for studying diseases in long‐lived ectothermic vertebrates and a shift in modeling such diseases.

Forcing mechanisms and hydrodynamics in Loch Linnhe, a dynamically wide Scottish estuary

Hydrodynamic conditions in Loch Linnhe, a dynamifcally wide estuary on the west coast of Scotland, are primarily influenced by wind forcing, freshwater input, and tides. Winds in the region are orographically steered along the axis of the estuary due to surrounding mountains. A large rainfall catchment area results in a large freshwater inflow into Loch Linnhe which in turn produces low salinity waters at the head of the estuary. This, combined with a connection to the open sea with coastal salinities, leads to salinity gradients in the horizontal and vertical. Even though a range of observational programmes have focussed on Loch Linnhe, the literature still lacks an evaluation of its physical dynamics. Here we present a first description of the hydrodynamics in Loch Linnhe based on observations. Wind stress predominantly influences the surface layer, especially at low frequencies and with a stronger influence than tides during neap tides. The buoyancy-driven flow due to the large river runoff influences the circulation independent of wind stress. Seasonal (spring, autumn) and interannual (2011, 2012) variability of water masses occur especially in the surface layer. Tides are dominated by the semi-diurnal constituent M2 with tidal ellipses aligned in the along-estuary direction and a stronger influence during spring tides compared to wind. An evaluation of dimensionless numbers reveal laterally and vertically sheared exchange flows. Compared to other Scottish estuaries Loch Linnhe is wide enough to be influenced by the Earth's rotation and demonstrates an enhanced freshwater outflow along its north-western coast as the freshwater is diverted to the right in the direction of the flow. These observed patterns are important for the sustainable environmental management of this socio-economically valuable region, e.g. through their relevance to aquaculture pathogen transmission patterns. A thorough understanding of the dynamics of the system is essential for a successful evidence-based marine planning framework.

Familiarity breeds contempt: combining proximity loggers and GPS reveals female white-tailed deer (Odocoileus virginianus) avoiding close contact with neighbors.

Social interactions can influence infectious disease dynamics, particularly for directly transmitted pathogens. Therefore, reliable information on contact frequency within and among groups can better inform disease modeling and management. We compared three methods of assessing contact patterns: (1) space-use overlap (volume of interaction [VI]), (2) direct contact rates measured by simultaneous global positioning system (GPS) locations (<10 m apart), and (3) direct contact rates measured by proximity loggers (PLs; 1-m detection) among female white-tailed deer (Odocoileus virginianus). We calculated the PL∶GPS contact ratios to see whether both devices reveal similar contact patterns and thus predict similar pathogen transmission patterns. Contact rates measured by GPS and PLs were similarly high for two within-group dyads (pairs of deer in the same social groups). Dyads representing separate but neighboring groups (high VI) had PL∶GPS contact ratios near zero, whereas dyads further apart (intermediate VI) had higher PL∶GPS contact ratios. Social networks based on PL contacts showed the fewest connected individuals and lowest mean centrality measures; network metrics were intermediate when based on GPS contacts and greatest when based on VI. Thus, the VI network portrayed animals to be more uniformly and strongly connected than did the PL network. We conclude that simultaneous GPS locations, compared with PLs, substantially underestimate the impact of group membership on direct contact rates of female deer and make networks appear more connected. We also present evidence that deer coming within the general vicinity of each other are less likely to come in close contact if they are in neighboring social groups than deer whose home ranges overlap little if at all. Combined, these results provide evidence that direct transmission of disease agents among female and juvenile white-tailed deer is likely to be constrained both spatially and by social structure, more so than GPS data alone would suggest.

Automated analysis of phylogenetic clusters.

BackgroundAs sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker.ResultsWe explore the effect of different bootstrap and genetic distance thresholds on clusters identified in a data set of publicly available HIV sequences, and compare these results to those of a previously published tool for cluster identification. To demonstrate their utility, we then use the Cluster Picker and Cluster Matcher together to investigate how clusters in the data set changed over time. We find that clusters containing sequences from more than one UK location at the first time point (multiple origin) were significantly more likely to grow than those representing only a single location.ConclusionsThe Cluster Picker and Cluster Matcher can rapidly process phylogenetic trees containing tens of thousands of sequences. Together these tools will facilitate comparisons of pathogen transmission dynamics between studies and countries.

Ignite ESA Session 13: Ecological Analysis Using Network Science and Graph Theory

The complex, interconnected structure and function of ecological systems is apparent in their countless direct and indirect pathways of energy (e.g., a food web), mass (e.g., a movement corridor), and information (e.g., a social network). This Ignite ESA Session united multiple fields of ecology through the lens of a single, rapidly evolving, analytical framework: network analysis. This session examined basic and applied ecological problems in both naturally formed and anthropogenically altered networks of interactions. In particular, diverse examples were presented from disease transmission, social behavior, mutualistic interactions, and species migration. The five-minute, Ignite ESA format provided a fitting outlet for rapid presentation of methods, and opened lines of communication between somewhat disparate fields of study.