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

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.

Comparing Mycobacterium tuberculosis transmission reconstruction models from whole genome sequence data.

Genomic epidemiology is routinely used worldwide to interrogate infectious disease dynamics. Multiple computational tools exist that reconstruct transmission networks by coupling genomic data with epidemiological models. Resulting inferences can improve our understanding of pathogen transmission dynamics, and yet the performance of these tools has not been evaluated for tuberculosis (TB), a disease process with complex epidemiology including variable latency and within-host heterogeneity. Here, we performed a systematic comparison of six publicly available transmission reconstruction models, evaluating their accuracy when predicting transmission events in simulated and real-world Mycobacterium tuberculosis outbreaks. We observed variability in the number of transmission links that were predicted with high probability (P ≥ 0.5) and low accuracy of these predictions against known transmission in simulated outbreaks. We also found a low proportion of epidemiologically supported case-contact pairs were identified in our real-world TB clusters. The specificity of all models was high, and a relatively high proportion of the total transmission events predicted by some models were true links, notably with TransPhylo, Outbreaker2, and Phybreak. Our findings may inform the choice of tools in TB transmission analyses and underscore the need for caution when interpreting transmission networks produced using probabilistic approaches.

Using Whole-genome Sequencing to Determine the Timing of Secondary Tuberculosis in British Columbia, Canada.

Combined with epidemiological data, whole-genome sequencing (WGS) can help better resolve individual tuberculosis (TB) transmission events to a degree not possible with traditional genotyping. We combine WGS data with patient-level data to calculate the timing of secondary TB among contacts of people diagnosed with active TB in British Columbia, Canada.

Adjutant: an R-based tool to support topic discovery for systematic and literature reviews.

SUMMARY: Adjutant is an open-source, interactive and R-based application to support mining PubMed for literature reviews. Given a PubMed-compatible search query, Adjutant downloads the relevant articles and allows the user to perform an unsupervised clustering analysis to identify data-driven topic clusters. Following clustering, users can also sample documents using different strategies to obtain a more manageable dataset for further analysis. Adjutant makes explicit trade-offs between speed and accuracy, which are modifiable by the user, such that a complete analysis of several thousand documents can take a few minutes. All analytic datasets generated by Adjutant are saved, allowing users to easily conduct other downstream analyses that Adjutant does not explicitly support. AVAILABILITY AND IMPLEMENTATION: Adjutant is implemented in R, using Shiny, and is available at https://github.com/amcrisan/Adjutant. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT.

MOTIVATION: Data visualization is an important tool for exploring and communicating findings from genomic and healthcare datasets. Yet, without a systematic way of organizing and describing the design space of data visualizations, researchers may not be aware of the breadth of possible visualization design choices or how to distinguish between good and bad options. RESULTS: We have developed a method that systematically surveys data visualizations using the analysis of both text and images. Our method supports the construction of a visualization design space that is explorable along two axes: why the visualization was created and how it was constructed. We applied our method to a corpus of scientific research articles from infectious disease genomic epidemiology and derived a Genomic Epidemiology Visualization Typology (GEViT) that describes how visualizations were created from a series of chart types, combinations and enhancements. We have also implemented an online gallery that allows others to explore our resulting design space of visualizations. Our results have important implications for visualization design and for researchers intending to develop or use data visualization tools. Finally, the method that we introduce is extensible to constructing visualizations design spaces across other research areas. AVAILABILITY AND IMPLEMENTATION: Our browsable gallery is available at http://gevit.net and all project code can be found at https://github.com/amcrisan/gevitAnalysisRelease. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Building the Framework for Standardized Clinical Laboratory Reporting of Next-generation Sequencing Data for Resistance-associated Mutations in Mycobacterium tuberculosis Complex.

Tuberculosis is the primary infectious disease killer worldwide, with a growing threat from multidrug-resistant cases. Unfortunately, classic growth-based phenotypic drug susceptibility testing (DST) remains difficult, costly, and time consuming, while current rapid molecular testing options are limited by the diversity of antimicrobial-resistant genotypes that can be detected at once. Next-generation sequencing (NGS) offers the opportunity for rapid, comprehensive DST without the time or cost burden of phenotypic tests and can provide useful information for global surveillance. As access to NGS expands, it will be important to ensure that results are communicated clearly, consistent, comparable between laboratories, and associated with clear guidance on clinical interpretation of results. In this viewpoint article, we summarize 2 expert workshops regarding a standardized report format, focusing on relevant variables, terminology, and required minimal elements for clinical and laboratory reports with a proposed standardized template for clinical reporting NGS results for Mycobacterium tuberculosis.

Trust and the ethical challenges in the use of whole genome sequencing for tuberculosis surveillance: a qualitative study of stakeholder perspectives.

BACKGROUND: Emerging genomic technologies promise more efficient infectious disease control. Whole genome sequencing (WGS) is increasingly being used in tuberculosis (TB) diagnosis, surveillance, and epidemiology. However, while the use of WGS by public health agencies may raise ethical, legal, and socio-political concerns, these challenges are poorly understood. METHOD: Between November 2017 and April 2018, we conducted semi-structured interviews with 22 key stakeholders across the fields of governance and policy, public health, and laboratory sciences representing the major jurisdictions currently using WGS in national TB programs. Thematic analysis of the interviews was conducted using NVivo 11. RESULTS: Respondents identified several ethical and practical challenges associated with WGS in TB care and surveillance, all related to issues of trust, including: 1) the power of public health; 2) data sharing and profits derived from surveillance efforts; and 3) concerns regarding who has access to, and can benefit from, the technology. Additional challenges included: the potential utility that WGS adds to a public health program, the risks associated with linking necessary epidemiological metadata to the genomic data, and challenges associated with jurisdictional capacity to implement the technology. CONCLUSIONS: Successful implementation of WGS is dependent on fostering relationships of trust between those working with genomics technology and those directly impacted by it, including clinicians. Building trust (a) between the public and the public health agencies and (b) within public health agencies themselves is critical due to the inherent complexity of WGS and its implementation for communicable disease control purposes.

Genotyping and Whole-Genome Sequencing to Identify Tuberculosis Transmission to Pediatric Patients in British Columbia, Canada, 2005-2014.

Background: Tuberculosis (TB) in children is often an indicator of recent transmission. Genotyping and whole-genome sequencing (WGS) can enhance pediatric TB investigations by confirming or refuting transmission events. Methods: Mycobacterium tuberculosis isolates from all pediatric patients <18 years with culture-confirmed TB in British Columbia (BC) from 2005 to 2014 (n = 49) were genotyped by Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeat (MIRU-VNTR) and compared with adult isolates. Genotypically clustered cases underwent WGS. Clinical, demographic, and contact data were reviewed for each case. Results: Twenty-three children were Canadian-born, 7 to Canadian-born parents (CBP) and 16 to foreign-born parents (FBP). Of the 26 foreign-born children, all were born in Asia (81%) or Africa (19%). Using molecular and epidemiological data, we determined that 15 children had acquired their infection within BC, and household transmission explained all 7 Canadian-born (FBP) children that acquired TB locally. In contrast, 6 of 7 Canadian-born (CBP) children were exposed via a non-household community source. Eight Canadian-born (FBP) children acquired their infections through travel to their parents' place of birth. All but 1 of the foreign-born children acquired their infection outside of BC. Conclusions: Genotyping and genomic data reveal that drivers of pediatric transmission vary according to a child's age, birthplace, and their parents' place of birth.

Molecular Epidemiology of Tuberculosis in British Columbia, Canada: A 10-Year Retrospective Study.

Background: Understanding regional molecular epidemiology allows for the development of more efficient tuberculosis prevention strategies in low-incidence settings. Methods: We analyzed 24-locus mycobacterial interspersed repetitive-unit-variable-number tandem repeat (MIRU-VNTR) genotyping for 2290 Mycobacterium tuberculosis clinical isolates collected in the province of British Columbia (BC), Canada, in 2005-2014. Laboratory data for each isolate were linked to case-level clinical and demographic data. These data were used to describe the molecular epidemiology of tuberculosis across the province. Results: We detected >1500 distinct genotypes across the 4 major M. tuberculosis lineages, reflecting BC's diverse population. Disease site and clustering rates varied across lineages, and MIRU-VNTR was used to group the 2290 isolates into 189 clusters (2-70 isolates per cluster), with an overall clustering rate of 42.4% and an estimated local transmission rate of 34.1%. Risk factors for clustering varied between Canadian-born and foreign-born individuals; the former had increased odds (odds ratio, 7.8; 95% confidence interval [CI], 6.2-9.6) of belonging to a genotypic cluster, although nearly one-quarter of clusters included both Canadian- and foreign-born persons. Large clusters (≥10 cases) occurred more frequently within the M. tuberculosis Euro-American lineage, and individual-level risk factors associated with belonging to a large cluster included being Canadian born (adjusted odds ratio, 3.3; 95% CI, 2.3-4.8), residing in a rural area (2.3; 1.2-4.5), and illicit drug use (2.0; 1.2-3.4). Conclusions: Although tuberculosis in BC largely arises through reactivation of latent tuberculosis in foreign-born persons, locally transmitted infections occur in discrete populations with distinct disease and risk factor profiles, representing groups for targeted interventions.

Universal Genotyping for Tuberculosis Prevention Programs: a 5-Year Comparison with On-Request Genotyping.

Prospective universal genotyping of tuberculosis (TB) isolates is used by many laboratories to detect clusters of cases and inform contact investigations. Prior to universal genotyping, most TB prevention programs genotyped isolates on request only, relying on requests from public health professionals whose knowledge of a patient's clinical, demographic, and epidemiological characteristics suggested potential transmission. To justify the switch from on-request to universal genotyping-particularly in the public health domain, with its limited resources and competing priorities-it is important to demonstrate the additional benefit provided by a universal genotyping program. We compared the clustering patterns revealed by retrospective 24-locus mycobacterial interspersed repetitive unit-variable-number tandem repeat genotyping of all culture-positive isolates over a 5-year period to the patterns previously established by our genotyping-on-request program in the low-incidence setting of British Columbia, Canada. We found that 23.8% of isolates were requested during the study period, and while requested isolates had increased odds of belonging to a genotype cluster (adjusted odds ratio, 2.3; 95% confidence interval, 1.5 to 3.3), only 54.6% clustered with the requested comparator strain. Universal genotyping revealed 94 clusters ranging in size from 2 to 53 isolates (mean = 5) and involving 432 individuals. On-request genotyping missed 54 (57.4%) of these clusters and 130 (30.1%) clustered individuals. Our results underscore that TB patient networks are complex, with unrecognized linkages between patients, and a prospective province-wide universal genotyping program provides an informative, bias-free tool to explore transmission to a degree not possible with on-request genotyping.

RNA-Seq Analysis of Gene Expression, Viral Pathogen, and B-Cell/T-Cell Receptor Signatures in Complex Chronic Disease.

Background: Chronic fatigue syndrome (CFS) remains poorly understood. Although infections are speculated to trigger the syndrome, a specific infectious agent and underlying pathophysiological mechanism remain elusive. In a previous study, we described similar clinical phenotypes in CFS patients and alternatively diagnosed chronic Lyme syndrome (ADCLS) patients­individuals diagnosed with Lyme disease by testing from private Lyme specialty laboratories but who test negative by reference 2-tiered serologic analysis. Methods: Here, we performed blinded RNA-seq analysis of whole blood collected from 25 adults diagnosed with CFS and 13 ADCLS patients, comparing these cases to 25 matched controls and 11 patients with well-controlled systemic lupus erythematosus (SLE). Samples were collected at patient enrollment and not during acute symptom flares. RNA-seq data were used to study host gene expression, B-cell/T-cell receptor profiles (BCR/TCR), and potential viral infections. Results: No differentially expressed genes (DEGs) were found to be significant when CFS or ADCLS cases were compared to controls. Forty-two DEGs were found when SLE cases were compared to controls, consistent with activation of interferon signaling pathways associated with SLE disease. BCR/TCR repertoire analysis did not show significant differences between CFS and controls or ADCLS and controls. Finally, viral sequences corresponding to anelloviruses, human pegivirus 1, herpesviruses, and papillomaviruses were detected in RNA-seq data, but proportions were similar (P = .73) across all genus-level taxonomic categories. Conclusions: Our observations do not support a theory of transcriptionally mediated immune cell dysregulation in CFS and ADCLS, at least outside of periods of acute symptom flares.

A microbiological revolution meets an ancient disease: improving the management of tuberculosis with genomics.

Tuberculosis (TB) is an ancient disease with an enormous global impact. Despite declining global incidence, the diagnosis, phenotyping, and epidemiological investigation of TB require significant clinical microbiology laboratory resources. Current methods for the detection and characterization of Mycobacterium tuberculosis consist of a series of laboratory tests varying in speed and performance, each of which yields incremental information about the disease. Since the sequencing of the first M. tuberculosis genome in 1998, genomic tools have aided in the diagnosis, treatment, and control of TB. Here we summarize genomics-based methods that are positioned to be introduced in the modern clinical TB laboratory, and we highlight how recent advances in genomics will improve the detection of antibiotic resistance-conferring mutations and the understanding of M. tuberculosis transmission dynamics and epidemiology. We imagine the future TB clinic as one that relies heavily on genomic interrogation of the M. tuberculosis isolate, allowing for more rapid diagnosis of TB and real-time monitoring of outbreak emergence.

Whole-Genome Sequencing of Measles Virus Genotypes H1 and D8 During Outbreaks of Infection Following the 2010 Olympic Winter Games Reveals Viral Transmission Routes.

We used whole-genome sequencing to investigate a dual-genotype outbreak of measles occurring after the XXI Olympic Winter Games in Vancouver, Canada. By sequencing 27 complete genomes from H1 and D8 genotype measles viruses isolated from outbreak cases, we estimated the virus mutation rate, determined that person-to-person transmission is typically associated with 0 mutations between isolates, and established that a single introduction of H1 virus led to the expansion of the outbreak beyond Vancouver. This is the largest measles genomics project to date, revealing novel aspects of measles virus genetics and providing new insights into transmission of this reemerging viral pathogen.

Lyme Disease Diagnosed by Alternative Methods: A Phenotype Similar to That of Chronic Fatigue Syndrome.

BACKGROUND: A subset of patients reporting a diagnosis of Lyme disease can be described as having alternatively diagnosed chronic Lyme syndrome (ADCLS), in which diagnosis is based on laboratory results from a nonreference Lyme specialty laboratory using in-house criteria. Patients with ADCLS report symptoms similar to those reported by patients with chronic fatigue syndrome (CFS). METHODS: We performed a case-control study comparing patients with ADCLS and CFS to each other and to both healthy controls and controls with systemic lupus erythematosus (SLE). Subjects completed a history, physical exam, screening laboratory tests, 7 functional scales, reference serology for Lyme disease using Centers for Disease Control and Prevention criteria, reference serology for other tick-associated pathogens, and cytokine expression studies. RESULTS: The study enrolled 13 patients with ADCLS (12 of whom were diagnosed by 1 alternative US laboratory), 25 patients with CFS, 25 matched healthy controls, and 11 SLE controls. Baseline clinical data and functional scales indicate significant disability among ADCLS and CFS patients and many important differences between these groups and controls, but no significant differences between each other. No ADCLS patient was confirmed as having positive Lyme serology by reference laboratory testing, and there was no difference in distribution of positive serology for other tick-transmitted pathogens or cytokine expression across the groups. CONCLUSIONS: In British Columbia, a setting with low Lyme disease incidence, ADCLS patients have a similar phenotype to that of CFS patients. Disagreement between alternative and reference laboratory Lyme testing results in this setting is most likely explained by false-positive results from the alternative laboratory.

Whole-genome sequencing and social-network analysis of a tuberculosis outbreak.

BACKGROUND: An outbreak of tuberculosis occurred over a 3-year period in a medium-size community in British Columbia, Canada. The results of mycobacterial interspersed repetitive unit-variable-number tandem-repeat (MIRU-VNTR) genotyping suggested the outbreak was clonal. Traditional contact tracing did not identify a source. We used whole-genome sequencing and social-network analysis in an effort to describe the outbreak dynamics at a higher resolution. METHODS: We sequenced the complete genomes of 32 Mycobacterium tuberculosis outbreak isolates and 4 historical isolates (from the same region but sampled before the outbreak) with matching genotypes, using short-read sequencing. Epidemiologic and genomic data were overlaid on a social network constructed by means of interviews with patients to determine the origins and transmission dynamics of the outbreak. RESULTS: Whole-genome data revealed two genetically distinct lineages of M. tuberculosis with identical MIRU-VNTR genotypes, suggesting two concomitant outbreaks. Integration of social-network and phylogenetic analyses revealed several transmission events, including those involving "superspreaders." Both lineages descended from a common ancestor and had been detected in the community before the outbreak, suggesting a social, rather than genetic, trigger. Further epidemiologic investigation revealed that the onset of the outbreak coincided with a recorded increase in crack cocaine use in the community. CONCLUSIONS: Through integration of large-scale bacterial whole-genome sequencing and social-network analysis, we show that a socioenvironmental factor--most likely increased crack cocaine use--triggered the simultaneous expansion of two extant lineages of M. tuberculosis that was sustained by key members of a high-risk social network. Genotyping and contact tracing alone did not capture the true dynamics of the outbreak. (Funded by Genome British Columbia and others.).

Cross-reactive and vaccine-induced antibody to an emerging swine-origin variant of influenza A virus subtype H3N2 (H3N2v).

BACKGROUND: Cases of infection due to a novel swine-origin variant of influenza A virus subtype H3N2 (H3N2v) have recently been identified in the United States, primarily among children. We estimate levels of cross-reactive antibody to H3N2v by age and assess whether seasonal trivalent inactivated influenza vaccine (TIV), with or without adjuvant, may increase seroprotection. METHODS: Antibody to H3N2v was assessed by hemagglutination inhibition (HI) assay and, for a subset, also by microneutralization assay. Seroprevalence and seroprotection were defined as an HI titer of ≥40, and levels were compared with those for ancestral and contemporary human strains. The analysis included 1116 sera collected during fall 2010, corresponding to approximately 100 sera per decade of life. Vaccine-induced antibody levels were also assessed in sera from 136 children aged <10 years and 65 adults aged 20-59 years before and after receipt of 2010-2011 split TIV and in sera from 182 elderly individuals aged ≥65 years before and after receipt of 2011-2012 split TIV (for 31 individuals), MF59-adjuvanted TIV (for 72), or unadjuvanted subunit TIV (for 79). RESULTS: The overall prevalence of HI titers of ≥40 against A(H3N2)v was 25%. No children aged <5 years and <20% of individuals aged ≤14 years or ≥40 years had an HI titer of ≥40. Conversely, among individuals aged 15-39 years, half of teens and adults showed H3N2v seroprotection. Following TIV receipt, <15% of individuals in any vaccine group developed a 4-fold increase in antibody level. CONCLUSIONS: A substantial proportion of adolescents and young adults have cross-reactive antibody against emerging H3N2v, whereas children and older adults show broad susceptibility. Recent formulations of TIV do not substantially increase seroprotection. A specific vaccine would be needed if H3N2v establishes epidemic spread. CLINICAL TRIALS REGISTRATION: NCT01140009 and NCT01368796.

Estimates of influenza vaccine effectiveness for 2007-2008 from Canada's sentinel surveillance system: cross-protection against major and minor variants.

OBJECTIVES: To estimate influenza vaccine effectiveness (VE) for the 2007-2008 season and assess the sentinel surveillance system in Canada for monitoring virus evolution and impact on VE. METHODS: Nasal/nasopharyngeal swabs and epidemiologic details were collected from patients presenting to a sentinel physician within 7 days of influenza-like illness onset. Cases tested positive for influenza A/B virus by real-time polymerase chain reaction; controls tested negative. Hemagglutination inhibition (HI) and gene sequencing explored virus relatedness to vaccine. VE was calculated as 1 minus the odds ratio for influenza in vaccinated versus nonvaccinated participants, with adjustment for confounders. RESULTS: Of 1425 participants, 21% were vaccinated. Influenza virus was detected in 689 (48%), of which isolates from 663 were typed/subtyped: 189 (29%) were A/H1, 210 (32%) were A/H3, and 264 (40%) were B. Of A/H1N1 isolates, 6% showed minor HI antigenic mismatch to vaccine, with greater variation based on genetic identity. All A/H3N2 isolates showed moderate antigenic mismatch, and 98% of influenza B virus isolates showed major lineage-level mismatch to vaccine. Adjusted VE for A/H1N1, A/H3N2, and B components was 69% (95% confidence interval [CI], 44%-83%), 57% (95% CI, 32%-73%), and 55% (95% CI, 32%-70%), respectively, with an overall VE of 60% (95% CI, 45%-71%). CONCLUSIONS: Detailed antigenic and genotypic analysis of influenza viruses was consistent with epidemiologic estimates of VE showing cross-protection. A routine sentinel surveillance system that combines detailed virus and VE monitoring annually, as modeled in Canada, may guide improved vaccine selection and protection.

A sentinel platform to evaluate influenza vaccine effectiveness and new variant circulation, Canada 2010-2011 season.

BACKGROUND: During the 2010-2011 winter, a large number of outbreaks due to influenza A/H3N2 at long-term care facilities, including higher-than-expected attack rates among vaccinated staff, were reported in some regions of Canada. Interim analysis from the community-based sentinel surveillance system showed circulating H3N2 variants and suboptimal vaccine effectiveness (VE), assessed here for the entire season's data set. METHODS: Nasal/nasopharyngeal swabs and epidemiologic details were collected from patients presenting to sentinel sites within 7 days of onset of influenza-like illness. Cases tested positive for influenza by real-time reverse-transcription polymerase chain reaction; controls tested negative. Odds ratios for medically attended, laboratory-confirmed influenza in vaccinated vs nonvaccinated participants were used to derive adjusted VE. Viruses were characterized by hemagglutination inhibition (HI), and the hemagglutinin genes of a subset were sequenced to explore vaccine relatedness. RESULTS: Final 2010-2011 VE analysis included 1718 participants (half aged 20-49 years), 93 with A(H1N1)pdm09, 408 with A/H3N2, and 199 with influenza B. Among adults aged 20-49 years, adjusted VE was 65% (95% confidence interval [CI], 8%-87%) for A(H1N1)pdm09 and 66% (95% CI, 10%-87%) for influenza B. Vaccine effectiveness was substantially lower for A/H3N2, at 39% (95% CI, 0%-63%). Phylogenetic analysis identified 2 circulating H3N2 variant clades, A/HongKong/2121/2010 (87%) and A/Victoria/208/2009 (11%), bearing multiple amino acid substitutions at antigenic sites (12 and 8, respectively) compared with the H3N2 vaccine component used in Canada (A/Victoria/210/2009[NYMC X-187]). However, HI characterized all H3N2 isolates as well matched to the vaccine. CONCLUSIONS: Public health observations of increased facility H3N2 outbreaks were consistent with the sentinel network's detection of genetic variants and suboptimal VE but not with conventional HI characterization. We highlight the utility of a multicomponent sentinel surveillance platform that incorporates genotypic, phenotypic, and epidemiologic indicators into the assessment of influenza virus, new variant circulation, vaccine relatedness, and VE.

Enabling a systems biology approach to immunology: focus on innate immunity.

Immunity is not simply the product of a series of discrete linear signalling pathways; rather it is comprised of a complex set of integrated responses arising from a dynamic network of thousands of molecules subject to multiple influences. Its behaviour often cannot be explained or predicted solely by examining its components. Here, we review recently developed resources for the systems-level investigation of immunity. Although innate immunity is emphasized here, its considerable overlap with adaptive immunity makes many of these resources relevant to both arms of the immune response. We discuss recent studies implementing these approaches and illustrate the potential of systems biology to generate novel insights into the complexities of innate immunity.

GEViTRec: Data Reconnaissance Through Recommendation Using a Domain-Specific Visualization Prevalence Design Space.

Genomic Epidemiology (genEpi) is a branch of public health that uses many different data types including tabular, network, genomic, and geographic, to identify and contain outbreaks of deadly diseases. Due to the volume and variety of data, it is challenging for genEpi domain experts to conduct data reconnaissance; that is, have an overview of the data they have and make assessments toward its quality, completeness, and suitability. We present an algorithm for data reconnaissance through automatic visualization recommendation, GEViTRec. Our approach handles a broad variety of dataset types and automatically generates visually coherent combinations of charts, in contrast to existing systems that primarily focus on singleton visual encodings of tabular datasets. We automatically detect linkages across multiple input datasets by analyzing non-numeric attribute fields, creating a data source graph within which we analyze and rank paths. For each high-ranking path, we specify chart combinations with positional and color alignments between shared fields, using a gradual binding approach to transform initial partial specifications of singleton charts to complete specifications that are aligned and oriented consistently. A novel aspect of our approach is its combination of domain-agnostic elements with domain-specific information that is captured through a domain-specific visualization prevalence design space. Our implementation is applied to both synthetic data and real Ebola outbreak data. We compare GEViTRec's output to what previous visualization recommendation systems would generate, and to manually crafted visualizations used by practitioners. We conducted formative evaluations with ten genEpi experts to assess the relevance and interpretability of our results. Code, Data, and Study Materials Availability: https://github.com/amcrisan/GEVitRec.