Health SecurityAhead of Print CommentaryOpen AccessChallenges and Opportunities in Pathogen Agnostic Sequencing for Public Health Surveillance: Lessons Learned From the Global Emerging Infections Surveillance ProgramLindsay Morton, Kathleen Creppage, Nazia Rahman, June Early, Laurie Hartman, Ashley Hydrick, and Matthew KasperLindsay MortonAddress correspondence to: Ms. Lindsay Morton, Armed Forces Health Surveillance Division, Global Emerging Infections Surveillance Branch, 11800 Tech Road, Suite 220, Silver Spring, MD 20904, E-mail Address: [email protected]Lindsay Morton, MPH, MS, is a Senior Molecular Epidemiologist, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this author, Kathleen CreppageKathleen Creppage, DrPH, MPH, is a Scientific Program Manager and Technical Lead, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this author, Nazia RahmanNazia Rahman, MPH, is a Molecular Epidemiologist and Portfolio Manager, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this author, June EarlyJune Early, MPH, is Global Emerging Infections Surveillance (GEIS) Deputy Chief, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this author, Laurie HartmanLaurie Hartman, MS, is a former Laboratory Support Specialist, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this author, Ashley HydrickAshley Hydrick, DVM, MPH, is a Major, US Army, and former GEIS Focus Area Chief, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this author, and Matthew KasperMatthew Kasper, PhD, is a Commander, US Navy, and GEIS Chief, GEIS Branch, Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD.Search for more papers by this authorPublished Online:6 Dec 2023https://doi.org/10.1089/hs.2023.0068AboutSectionsPDF/EPUB Permissions & CitationsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail IntroductionPathogen agnostic sequencing has been identified as a tool for biodefense and public health given its role in infectious disease detection and monitoring. US governments interest in this tool is apparent in the most recent US National Biodefense Strategy,1 the American Pandemic Preparedness Plan,2 and fiscal year 2023 Broad Agency Announcements from the US Department of Health and Human Services, including the US Centers for Disease Control and Prevention (CDC) and Biomedical Advanced Research and Development Authority.Next-generation sequencing (NGS) technologies, which are higher-throughput genome sequencing technologies developed after Sanger sequencing and can be used for pathogen agnostic sequencing, have become more affordable and more widely adopted among biomedical and public health laboratories.3 Furthermore, the cost per genome generated or samples sequenced has decreased dramatically, accelerating the transition of NGS from a research activity to an essential component of routine public health surveillance.4,5Pathogen agnostic sequencing—also referred to as metagenomic, shotgun, unbiased, or random-priming sequencing—is typically conducted when more information is desired about the microbial community within a sample or when more specific assays, such as polymerase chain reaction or amplicon sequencing, fail. These assays may fail due to suboptimal design or selection, poor or missing reference genomes, the evolution of target pathogens, or the emergence of a novel or divergent human pathogen.3 Recent approaches to pathogen agnostic sequencing have focused on clinical metagenomics, primarily for patient diagnostics, discovery of novel or unexpected human pathogens, and screening of environmental samples. Some of the earliest advances in routine pathogen agnostic sequencing were made within the field of clinical metagenomics for the detection of unknown pathogens in patient samples to determine the likely cause of underlying illness or mortality.6 Within public health, pathogen agnostic sequencing approaches have long been used in surveillance for novel and emerging animal and human pathogens with risk for spillover or pandemic potential.7,8 This can be a time- and resource-intensive "needle in the haystack" approach, depending on the sample source, collection method, and preservation method. Additionally, local capacity (eg, equipment and information technology infrastructure), interorganizational data-sharing agreements, and capabilities (eg, well-trained laboratories and subject matter experts) are necessary for the development, implementation, and maintenance of a pathogen agnostic sequencing program.While pathogen agnostic sequencing technologies and testing approaches have matured and become more accessible, fewer considerations have been made for the operationalization of agnostic sequencing within the context of an infectious disease surveillance system, such as the Global Emerging Infections Surveillance (GEIS) program of the US Department of Defense (DOD). Given widespread access to sequencing technologies, longstanding surveillance studies with ongoing sample collections and repositories, and robust expertise in NGS and bioinformatics among DOD scientists, the GEIS program is well positioned to implement, maintain, and generate meaningful information from pathogen agnostic sequencing within its surveillance network. We believe the DOD GEIS program has gained experience in several important lessons related to the operationalization and implementation of pathogen agnostic sequencing within an existing infectious disease surveillance program. The purpose of this commentary is to use an existing DOD infectious disease surveillance program to highlight opportunities and challenges for the implementation of pathogen agnostic sequencing in the context of the wider global community.History of Pathogen Agnostic Sequencing in the GEIS ProgramThe GEIS program operates through a global network of US Army, Navy, and Air Force medical research, clinical, and public health laboratory partners in strategic locations, which are engaged on the front lines of global infectious disease surveillance and have longstanding relationships with the US interagency, host-nation, and international partners.9,10 These partners share laboratory-confirmed infectious disease surveillance data within the network, some of which may be indicative of potential emerging threats to US service members. Epidemiological and clinical metadata may also be available due to the existence of robust sentinel site programs and standardized, coordinated data collection processes. This serves to enrich the "picture" of an infectious disease pathogen, connecting etiology, transmission, and clinical outcomes to genomic characterization. However, this reporting is not done in real time. While GEIS-funded partners may facilitate rapid communications on the ground with local organizations if needed, they are required to submit data on a monthly basis, at minimum, to the GEIS program office. When high- or moderate-level threats to force health protection are identified, partners must submit reports in as quickly as 24 hours to the GEIS program office and the geographic combatant commands to inform their decisionmaking.The GEIS program leveraged early DOD biodefense and medical research investments in pathogen sequencing, made in 2014-2015, to enhance infectious disease surveillance activities performed by GEIS partner laboratories. Some of these critical investments included the Global Biosurveillance Technology Initiative operated by the Joint Program Executive Office for Chemical and Biological Defense (now the Joint Program Executive Office for Chemical, Biological, Radiological, and Nuclear Defense), which delivered Illumina MiSeq instruments, ancillary library preparation equipment, and bioinformatics servers to DOD laboratories located throughout the United States and abroad.11,12 These efforts were implemented partly in response to priorities indicated in the 2012 National Strategy for Biosurveillance,13 which included building a coordinated, integrated biosurveillance infrastructure.Pathogen agnostic sequencing gradually integrated into the GEIS program over the past decade as NGS technologies became more widespread among DOD laboratories. Currently, GEIS partners with pathogen agnostic sequencing capabilities are located across North America, Europe, South America, Africa, Southeast Asia, and the Pacific (Figure 1). These laboratory partners are also actively engaged in prospective sample collection, maintenance of pathogen repositories, and studies supporting infectious disease surveillance in the United States and abroad.14-16 Within the GEIS network, a concerted effort is required to harmonize activities from sample collection to sequencing. The sample-collection-to-sequencing pipeline progresses as follows: (1) sample collection from the field or a repository, (2) initial sample processing and testing, (3) samples selection for pathogen agnostic sequencing, (4) performance of wet laboratory sequencing, (5) bioinformatics analysis, (6) generation of actionable sample information, and (7) data sharing (Figure 2). Epidemiological data are often collected in parallel with sample collection through a survey instrument or medical record, although the quality and quantity of this information varies throughout the network. In more resource-constrained environments, it can be challenging to integrate sequencing outcomes with metadata depending on how data are collected and stored.Figure 1. GEIS surveillance activities and GEIS partner laboratories with next-generation sequencing equipment (denoted with dark blue stars). These DOD medical research, clinical, and public health laboratories are operated by the US Army, US Navy, US Air Force, and Defense Health Agency, and include host-nation partners in select locations worldwide.Abbreviations: 18 OMRS, 18th Operational Medical Readiness Squadron; 65th MED BDE, 65th Medical Brigade; ADF-MIDI, Australian Defence Force Malaria and Infectious Disease Institute; AFRICOM, Africa Command; AFRIMS, Armed Forces Research Institute of Medical Sciences; CENTCOM, Central Command; DCPH-Dayton, Defense Centers for Public Health Dayton; DCPH-Portsmouth, Defense Centers for Public Health Portsmouth; DOD, US Department of Defense; EUCOM, European Command; GEIS, Global Emerging Infections Surveillance; INDOPACOM, Indo-Pacific Command; LRMC, Landstuhl Regional Medical Center; NAMRU INDO PACIFIC, Naval Medical Research Unit Indo Pacific; NAMRU EURAFCENT, Naval Medical Research Unit supporting AFRICOM, CENTCOM, and EUCOM; NAMRU SOUTH, Naval Medical Research Unit South; NECE, Navy Entomology Center of Excellence; NHRC, Naval Health Research Center; NMRC, Naval Medical Research Command; NORTHCOM, Northern Command; PHC-P, Public Health Command-Pacific; PVC, Pharmacovigilance Center; SOUTHCOM, Southern Command; TAMC, Tripler Army Medical Center; USAMRD-A, US Army Medical Research Directorate-Africa; USAMRD-G, US Army Medical Research Directorate-Georgia; USAMRIID, US Army Medical Research Institute of Infectious Diseases; USUHS; Uniformed Services University of Health Sciences; WARUN, Walter Reed AFRIMS Research Unit Nepal; WRAIR, Walter Reed Army Institute of Research.Figure 2. Sample collection and processing workflow for pathogen agnostic genomic surveillance.Abbreviations: GEIS, Global Emerging Infections Surveillance; GISAID, Global Initiative on Sharing All Influenza Data; NCBI, National Center for Biotechnology Information; NGSBC, Next Generation Sequencing and Bioinformatics Consortium; USG, US government.Implementation of Pathogen Agnostic Sequencing Within the GEIS NetworkThe GEIS program has implemented several initiatives to use and harmonize pathogen agnostic sequencing within an existing infectious disease surveillance program (Figure 3).Figure 3. Global Emerging Infections Surveillance Program history and pathogen sequencing milestones. Abbreviation: GEIS, Global Emerging Infections Surveillance.Next Generation Sequencing and Bioinformatics ConsortiumIn 2017, the GEIS program established the Next Generation Sequencing and Bioinformatics Consortium, composed of pathogen genome sequencing and bioinformatics experts from DOD medical research laboratories around the world, as shown in Figure 1. This consortium works to promote collaboration, communication, and standardization for NGS and bioinformatics practices among the GEIS network of DOD laboratory partners, with the goal of increasing the availability, utility, and quality of pathogen sequence data. These data feed into timely information products to inform force health protection and DOD public health efforts domestically and worldwide. Furthermore, in 2019, the consortium established a working group of mobile NGS users to provide a forum for discussing and troubleshooting newer technologies, demonstrating a commitment to evolve and respond to both emerging infectious diseases and emerging technologies for pathogen detection and characterization.Pathogen "Discovery" Project 1.0To initially guide GEIS pathogen-sequencing activities, the consortium conducted 2 major efforts to better understand sequencing capabilities and gaps within the network. First, the consortium surveyed GEIS partner laboratories in 2017 to understand current NGS and bioinformatics capabilities, areas of interest, and strategic needs. This was followed by a proficiency testing exercise, referred to as the Pathogen Discovery Project 1.0, in which participating laboratories received a blinded panel of human pathogens in various matrixes and tested it using their existing NGS protocols. Results showed that most laboratories used an agnostic (or metagenomic) sequencing approach. The raw data were used to evaluate laboratory pathogen detection and characterization capabilities. This exercise led to the development of training modules to address gaps, including modules for optimizing metagenomic sequencing and bioinformatics analysis.17GEIS-Funded Surveillance Activities Using Pathogen Agnostic Sequencing, Including Early Outbreak ResponseHistorically, the GEIS program has most frequently supported pathogen agnostic sequencing activities for surveillance projects across its respiratory and febrile and vector-borne infections portfolios. Prior to the COVID-19 pandemic, the GEIS program prioritized "pathogen-negative" samples from routine surveillance activities for agnostic sequencing, focusing on cases of acute respiratory infections or acute febrile illnesses that failed to yield a result using traditional diagnostics.18 Additionally, several instances of pathogen agnostic methods have been used for arbovirus characterization19,20 or for pathogen discovery in vector samples.21-23 Although not strictly "agnostic," GEIS partner laboratories have also developed or used sequencing methods that improve upon traditional metagenomic methods and integrate optimization steps for host depletion or viral pathogen enrichment.24,25 In early outbreak or pandemic responses, pathogen agnostic or panviral sequencing methods were used to characterize Zika virus, SARS-CoV-2, and mpox cases within the GEIS network, before numerous reference genomes were available or standard amplicon-based sequencing protocols were widely adopted.20,26 However, as illustrated in several of these examples, targeted sequencing or enrichment is often used in conjunction with pathogen agnostic methods to confirm findings or generate higher-quality genomes.Lessons From the GEIS ProgramChallenges with operationalizing pathogen agnostic sequencing have been well documented.6,27-29 The GEIS program has firsthand experience with the challenges associated with deploying this method for general biosurveillance, from difficulties with implementation and policy development to technical issues surrounding information technology access and requirements (Box).Box. Challenges to Operationalizing a Pathogen Agnostic Surveillance System1.Identification of appropriate use cases/sample sets2.Rapidly advancing or changing sequencing and bioinformatics technologies/methods3.Lack of community standards4.Reproducibility of results5.Establishment of data- and sample-sharing agreements with partner laboratories and host nations6.Staffing recruitment, retention, and training7.Supply chain and equipment servicing (particularly for low- or middle-income countries)8.Access to computational resources, information technology staff support, and updated reference databases9.Access to stable funding sources for public health surveillance activities10.Integration with existing clinical or public health surveillance systems11.Policy gaps for the use of pathogen agnostic sequencing results for public health actionWhile expertise in the field related to pathogen agnostic methods is abundant, it can be challenging to recruit, retain, and mentor highly trained molecular epidemiologists, laboratorians, and bioinformaticians (particularly in resource-constrained areas).28 Supporting up-to-date training for more complex methods associated with pathogen agnostic sequencing can also be challenging, especially when demands for known pathogen targets (eg, SARS-CoV-2) become prioritized. It can also be extremely difficult to acquire or access sufficient supplies, computing power, and well-maintained databases in resource-limited settings.28One of the most important components of conducting these activities across a broad network with a mixture of stakeholders is establishing necessary agreements and ensuring they are in place for current and future needs. These agreements (whether for data use, sample sharing, or other purposes) are vital to protect the interests of host nations, the US military service laboratories, and other supporting organizations. Even within the GEIS network, the establishment of agreements for sample sharing and data sharing among partners is a complex and time-consuming process. With respect to pathogen agnostic sequencing, the outcomes of pathogen agnostic sequencing could have enormous public health implications for all stakeholders. Having agreements in place is particularly important if there is sensitivity around potential threats that could be detected or for the transport of potentially hazardous samples.There is a general lack of standardization and regulation across the scientific community regarding protocols and agreed-upon methods for pathogen identification and characterization using agnostic sequencing.30 Given the rapid evolution of these technologies and techniques, it is not unexpected to see laboratories use a wide variety of kits, equipment, sample selection criteria, data collection tools and processes, and analytic programs. Even within the GEIS network, similar activities may not incorporate standard, harmonized sample selection criteria to achieve similar ends. This can lead to challenges with reproducibility, compounded by the complexity of technical issues such as sample cross-contamination, complex matrixes, and identifying appropriate thresholds.6Similarly, there are mixed recommendations as to how to best use these technologies and their resulting outcomes to inform public health actions. Few, if any, policies exist that outline how to appropriately interpret, disseminate, and integrate findings from pathogen agnostic sequencing into existing public health systems and decisionmaking processes. One of the more challenging questions to address regarding pathogen agnostic methods is where they fit in the field of public health and emerging infectious disease surveillance, and when it is appropriate to implement them with their inherent risks. Pathogen agnostic sequencing is an informative adjunct to more traditional surveillance activities; without a priori knowledge of what a causative agent might be, it is difficult to use typical laboratory testing methods to characterize a potential emerging threat. Pathogen agnostic sequencing can provide valuable information on previously uncharacterized genomes, including critical mutations that might affect traditional diagnostic outcomes, which can then inform new diagnostic tools and techniques for future use. However, despite its many advantages, it is not always the most appropriate or cost-effective method. For instance, when targets are known and qualitative measures of detection are sufficient, less cost- and labor-intensive methodologies, such as polymerase chain reaction, can be used. There is also a potential risk in using these methods without reward; while pathogen agnostic methods can certainly have high value if and when they result in the detection of an unknown threat, the likelihood of this can vary depending on the epidemiology of the pathogen and the resulting clinical manifestation, the geographic location from which the sample was collected, and the skills and resources available at the laboratory to perform these more challenging techniques and interpret the findings.Opportunities for GEIS to Leverage Pathogen Agnostic SequencingThe incorporation of sequencing capabilities into the GEIS partner laboratory network demonstrates the GEIS program's ability to integrate advanced laboratory methods into the program and ensure that laboratories remain at the forefront of pathogen detection and characterization. With renewed global interest in pandemic preparedness and novel approaches to infectious disease surveillance, the GEIS program has many opportunities to further develop and use pathogen agnostic sequencing: 1.Utilize and standardize testing algorithms that are not reliant on preexisting (biased) targeted or panel molecular tests2.Support novel pathogen discovery among unique sample sets (eg, environmental, vector, human) collected by GEIS partners and to support development of new molecular assays3.Provide more information for "pathogen-negative" samples derived from acute febrile illness and acute respiratory illness cases identified through GEIS surveillance activities4.Access additional USG funding streams and maintain alignment with national and international biosurveillance and biodefense priorities5.Maintain and expand early pandemic preparedness for emerging pathogens within the US DOD and among host-nation partners6.Collaborate with and contribute to USG interagency and international pathogen agnostic sequencing surveillance systems (eg, wastewater surveillance)DiscussionThe relationship between the biodefense and public health communities has evolved and likely been accelerated and enriched by the need for collaboration and communication since the onset of the COVID-19 pandemic.31,32 Regardless of how the surveillance activity is framed, both biodefense and public health perspectives are important components of overall biosurveillance activities. By monitoring infectious disease threats through pathogen agnostic approaches as part of large-scale biosurveillance activities across the DOD, the GEIS program can better prepare to (1) integrate future data and processes into existing DOD systems, much like the CDC Data Modernization Initiative and the US Department of Health and Human Services Trusted Exchange Framework and Common Agreement, (2) collaboratively make critical decisions about pandemic preparedness and response, (3) better understand the gaps in knowledge around emerging infectious threats, and (4) apply innovative and evolving technologies to improve DOD capability for novel pathogen identification and characterization.Much of this is tied into modernizing DOD infrastructure and systems to move the needle toward standardized, integrated data and surveillance systems. While the CDC has developed an initiative that maps a broad, adaptable approach that can be applied to any organization for data modernization, the DOD has leaned in to begin integrating advanced technologies, such as artificial intelligence and cloud-based storage, into its existing systems. These efforts, which will ensure the accessibility of metadata across various domains, are currently underway; upon completion, they will be documented in a future publication. However, other requirements for a harmonized network approach to pathogen agnostic sequencing beyond data modernization include the following:Adequate, stable funding to increase and maintain equipment, information technology infrastructure, resources, personnel, and training to sustain activities over timeA DOD-wide strategy and implementation plan for appropriate operationalization of pathogen agnostic sequencing for both routine surveillance and responses to potential public health emergencies, including coordinated scaling up during times of needTranslation of funding for pathogen agnostic sequencing into robust, measurable, quality surveillance outcomes and force health protection measures within existing surveillance activities and infrastructureData use and sharing agreements that clearly specify requirements around sample shipping, analysis support, and reporting of resultsMaintaining a laboratory network that is capable and prepared to use pathogen agnostic sequencing methodologies to identify and characterize emerging pathogens is challenging. Capital investments must be continuously considered to ensure DOD laboratories remain at the forefront with current equipment. In addition, nothing is more critical than maintaining an elite workforce in a highly competitive talent marketplace. The COVID-19 pandemic has increased demand for public health professionals and scientists to develop clear plans to operationalize a coordinated response to threats detected through a pathogen agnostic surveillance system. The GEIS mission is force health protection, and continued investment in pathogen agnostic technologies offers an opportunity to enhance data products delivered by the GEIS partner network. Regardless of an emerging pathogen's origin, the GEIS program must continue to coordinate among partner laboratories to ensure and maintain a robust capability to detect and respond to infectious disease threats.ConclusionPast DOD medical research and biodefense investments in NGS and pathogen agnostic testing have bolstered public health surveillance and paved the way for capabilities that will likely be critical for preparing and responding to the next pandemic.33 Since its establishment in 1998, the GEIS program has considered the biosurveillance landscape and invested in surveillance and advanced characterization infrastructure accordingly. These investments have continued to support the need for timely information on emerging infectious threats over time within the DOD, which maintains and expands such capabilities for wider public health surveillance. We believe these technologies are more impactful over the long term within a robust and coordinated laboratory network for infectious disease surveillance and response. While the GEIS program continues to incorporate pathogen agnostic sequencing into partner laboratories, a foundation exists upon which capabilities can rapidly scale up to respond to emerging infectious disease threats in support of health protection for US forces and general public health. Continued investment in these capabilities, from workforce and training to next-generation technologies, will be critical for defending against novel future threats.AcknowledgmentsThe authors thank GEIS partner DOD medical research and public health laboratories and GEIS Next Generation Sequencing and Bioinformatics Consortium members. Thank you to Dr. Kim Bishop-Lilly for her thoughtful insights on pathogen agnostic sequencing methods and manuscript suggestions. Material has been reviewed by the US Armed Forces Health Surveillance Division. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors, and are not to be construed as official or as reflecting true views of the US Department of the Army, Department of the Navy, Department of Defense, or the US Government. The use of trade names is for identification only and does not imply endorsement by the US Department of the Army, Department of the Navy, and Department of Defense. This work was prepared as part of the authors' official duties. Title 17 USC §105 provides that "copyright protection under this title is not available for any work of the United States Government." Title 17 USC §101 defines a US Government work as a work prepared by a military service member or employee of the US Government as part of that person's official duties.References1. The White House. 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Accessed March 28, 2022. https://www.who.int/publications/i/item/9789240046979 Google ScholarFiguresReferencesRelatedDetails Volume 0Issue 0 InformationCopyright 2023, Mary Ann Liebert, Inc., publishersTo cite this article:Lindsay Morton, Kathleen Creppage, Nazia Rahman, June Early, Laurie Hartman, Ashley Hydrick, and Matthew Kasper.Challenges and Opportunities in Pathogen Agnostic Sequencing for Public Health Surveillance: Lessons Learned From the Global Emerging Infections Surveillance Program.Health Security.ahead of printhttp://doi.org/10.1089/hs.2023.0068creative commons licenseOnline Ahead of Print:December 6, 2023 PDF download

Abstract Background An outbreak of coronavirus disease 2019 (Covid-19) occurred on the U.S.S. Theodore Roosevelt, a nuclear-powered aircraft carrier with a crew of 4779 personnel. Methods We obtained clinical and demographic data for all crew members, including results of testing by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR). All crew members were followed up for a minimum of 10 weeks, regardless of test results or the absence of symptoms. Results The crew was predominantly young (mean age, 27 years) and was in general good health, meeting U.S. Navy standards for sea duty. Over the course of the outbreak, 1271 crew members (26.6% of the crew) tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by rRT-PCR testing, and more than 1000 infections were identified within 5 weeks after the first laboratory-confirmed infection. An additional 60 crew members had suspected Covid-19 (i.e., illness that met Council of State and Territorial Epidemiologists clinical criteria for Covid-19 without a positive test result). Among the crew members with laboratory-confirmed infection, 76.9% (978 of 1271) had no symptoms at the time that they tested positive and 55.0% had symptoms develop at any time during the clinical course. Among the 1331 crew members with suspected or confirmed Covid-19, 23 (1.7%) were hospitalized, 4 (0.3%) received intensive care, and 1 died. Crew members who worked in confined spaces appeared more likely to become infected. Conclusions SARS-CoV-2 spread quickly among the crew of the U.S.S. Theodore Roosevelt. Transmission was facilitated by close-quarters conditions and by asymptomatic and presymptomatic infected crew members. Nearly half of those who tested positive for the virus never had symptoms.

Background Campylobacter jejuni is a leading cause of bacterial diarrhea worldwide, and increasing rates of fluoroquinolone (FQ) resistance in C. jejuni are a major public health concern. The rapid detection and tracking of FQ resistance are critical needs in developing countries, as these antimicrobials are widely used against C . jejuni infections. Detection of point mutations at T86I in the gyrA gene by real-time polymerase chain reaction (RT-PCR) is a rapid detection tool that may improve FQ resistance tracking. Methods C. jejuni isolates obtained from children with diarrhea in Peru were tested by RT-PCR to detect point mutations at T86I in gyrA . Further confirmation was performed by sequencing of the gyrA gene. Results We detected point mutations at T86I in the gyrA gene in 100% (141/141) of C. jejuni clinical isolates that were previously confirmed as ciprofloxacin-resistant by E-test. No mutations were detected at T86I in gyrA in any ciprofloxacin-sensitive isolates. Conclusions Detection of T86I mutations in C . jejuni is a rapid, sensitive, and specific method to identify fluoroquinolone resistance in Peru. This detection approach could be broadly employed in epidemiologic surveillance, therefore reducing time and cost in regions with limited resources.

Infectious diarrhea affects over four billion individuals annually and causes over a million deaths each year. Though not typically prescribed for treatment of uncomplicated diarrheal disease, antimicrobials serve as a critical part of the armamentarium used to treat severe or persistent cases. Due to widespread over- and misuse of antimicrobials, there has been an alarming increase in global resistance, for which a standardized methodology for geographic surveillance would be highly beneficial. To demonstrate that a standardized methodology could be used to provide molecular surveillance of antimicrobial resistance (AMR) genes, we initiated a pilot study to test 130 diarrheal pathogens (Campylobacter spp., Escherichia coli, Salmonella, and Shigella spp.) from the USA, Peru, Egypt, Cambodia, and Kenya for the presence/absence of over 200 AMR determinants. We detected a total of 55 different determinants conferring resistance to ten different categories of antimicrobials: genes detected in ≥ 25 samples included blaTEM, tet(A), tet(B), mac(A), mac(B), aadA1/A2, strA, strB, sul1, sul2, qacEΔ1, cmr, and dfrA1. The number of determinants per strain ranged from none (several Campylobacter spp. strains) to sixteen, with isolates from Egypt harboring a wider variety and greater number of genes per isolate than other sites. Two samples harbored carbapenemase genes, blaOXA-48 or blaNDM. Genes conferring resistance to azithromycin (ere(A), mph(A)/mph(K), erm(B)), a first-line therapeutic for severe diarrhea, were detected in over 10% of all Enterobacteriaceae tested: these included >25% of the Enterobacteriaceae from Egypt and Kenya. Forty-six percent of the Egyptian Enterobacteriaceae harbored genes encoding CTX-M-1 or CTX-M-9 families of extended-spectrum β-lactamases. Overall, the data provide cross-comparable resistome information to establish regional trends in support of international surveillance activities and potentially guide geospatially informed medical care.

Rickettsia and Leptospira spp. are under-recognized causes of acute febrile disease worldwide. Rickettsia species are often placed into the spotted fever group rickettsiae (SFGR) and typhus group rickettsiae (TGR). We explored the antibody prevalence among humans for these two groups of rickettsiae in four regions of Peru (Lima, Cusco, Puerto Maldonado, and Tumbes) and for Leptospira spp. in Puerto Maldonado and Tumbes. We also assessed risk factors for seropositivity and collected serum samples and ectoparasites from peri-domestic animals from households in sites with high human seroprevalence. In total, we tested 2,165 human sera for antibodies (IgG) against SFGR and TGR by ELISA and for antibodies against Leptospira by a microscopic agglutination test. Overall, human antibody prevalence across the four sites was 10.6% for SFGR (ranging from 6.2% to 14.0%, highest in Tumbes) and 3.3% for TGR (ranging from 2.6% to 6.4%, highest in Puerto Maldonado). Factors associated with seroreactivity against SFGR were male gender, older age, contact with backyard birds, and working in agriculture or with livestock. However, exposure to any kind of animal within the household decreased the odds ratio by half. Age was the only variable associated with higher TGR seroprevalence. The prevalence of Leptospira was 11.3% in Puerto Maldonado and 5.8% in Tumbes, with a borderline association with keeping animals in the household. We tested animal sera for Leptospira and conducted polymerase chain reaction (PCR) to detect Rickettsia species among ectoparasites collected from domestic animals in 63 households of seropositive participants and controls. We did not find any association between animal infection and human serostatus.

Background Meningitis caused by Mycobacterium tuberculosis is a major cause of morbidity and mortality worldwide. We evaluated the performance of cerebrospinal fluid (CSF) testing with the GeneXpert MTB/RIF assay versus traditional approaches for diagnosing tuberculosis meningitis (TBM). Methods Patients were adults (n =37) presenting with suspected TBM to the Hospital Nacional Dos de Mayo, Lima, Peru, during 12 months until 1st January 2015. Each participant had a single CSF specimen that was divided into aliquots that were concurrently tested for M. tuberculosis using GeneXpert, Ziehl-Neelsen smear and culture on solid and liquid media. Drug susceptibility testing used Mycobacteria Growth Indicator Tube (MGIT 960) and the proportions method. Results 81% (30/37) of patients received a final clinical diagnosis of TBM, of whom 63% (19/30, 95% confidence intervals, CI: 44-80%) were HIV-positive. 22% (8/37, 95%CI: 9.8-38%), of patients had definite TBM. Because definite TBM was defined by positivity in any laboratory test, all laboratory tests had 100% specificity. Considering the 30 patients who had a clinical diagnosis of TBM: diagnostic sensitivity was 23% (7/30, 95%CI: 9.9-42%) for GeneXpert and was the same for all culture results combined; considerably greater than 7% (2/30, 95%CI: 0.82-22%) for microscopy; whereas all laboratory tests had poor negative predictive values (20-23%). Considering only the 8 patients with definite TBM: diagnostic sensitivity was 88% (7/8, 95%CI: 47-100%) for GeneXpert; 75% (6/8, 95%CI: 35-97%) for MGIT culture or LJ culture; 50% (4/8, 95%CI: 16-84) for Ogawa culture and 25% (2/8, 95%CI: 3.2-65%) for microscopy. GeneXpert and microscopy provided same-day results, whereas culture took 20-56 days. GeneXpert provided same-day rifampicin-susceptibility results, whereas culture-based testing took 32-71 days. 38% (3/8, 95%CI: 8.5-76%) of patients with definite TBM with data had evidence of drug-resistant TB, but 73% (22/30) of all clinically diagnosed TBM (definite, probable, and possible TBM) had no drug-susceptibility results available. Conclusions Compared with traditional culture-based methods of CSF testing, GeneXpert had similar yield and faster results for both the detection of M. tuberculosis and drug-susceptibility testing. Including use of the GeneXpert has the capacity to improve the diagnosis of TBM cases.

Childhood vaccination with the 13-valent pneumococcal conjugate vaccine (PCV13) was introduced in Cambodia in January 2015. Baseline data regarding circulating serotypes are scarce. All microbiology laboratories in Cambodia were contacted for identification of stored isolates of Streptococcus pneumoniae from clinical specimens taken before the introduction of PCV13. Available isolates were serotyped using a multiplex polymerase chain reaction method. Among 166 identified isolates available for serotyping from patients with pneumococcal disease, 4% were isolated from upper respiratory samples and 80% were from lower respiratory samples, and 16% were invasive isolates. PCV13 serotypes accounted for 60% (95% confidence interval [CI] 52-67) of all isolates; 56% (95% CI 48-64) of noninvasive and 77% (95% CI 57-89) of invasive isolates. Antibiotic resistance was more common among PCV13 serotypes. This study of clinical S. pneumoniae isolates supports the potential for high reduction in pneumococcal disease burden and may serve as baseline data for future monitoring of S. pneumoniae serotypes circulation after implementation of PCV13 childhood vaccination in Cambodia.

Background: Scientific publication in academic literature is a key venue in which the U.S. Department of Defense's Global Emerging Infections Surveillance and Response System (GEIS) program disseminates infectious disease surveillance data. Bibliometric analyses are tools to evaluate scientific productivity and impact of published research, yet are not routinely used for disease surveillance. Our objective was to incorporate bibliometric indicators to measure scientific productivity and impact of GEIS-funded infectious disease surveillance, and assess their utility in the management of the GEIS surveillance program. Methods: Metrics on GEIS program scientific publications, project funding, and countries of collaborating institutions from project years 2006 to 2012 were abstracted from annual reports and program databases and organized by the six surveillance priority focus areas: respiratory infections, gastrointestinal infections, febrile and vector-borne infections, antimicrobial resistance, sexually transmitted infections, and capacity building and outbreak response. Scientific productivity was defined as the number of scientific publications in peer-reviewed literature derived from GEIS-funded projects. Impact was defined as the number of citations of a GEIS-funded publication by other peer-reviewed publications, and the Thomson Reuters 2-year journal impact factor. Indicators were retrieved from the Web of Science and Journal Citation Report. To determine the global network of international collaborations between GEIS partners, countries were organized by the locations of collaborating institutions. Results: Between 2006 and 2012, GEIS distributed approximately US $330 million to support 921 total projects. On average, GEIS funded 132 projects (range 96-160) with $47 million (range $43 million-$53 million), annually. The predominant surveillance focus areas were respiratory infections with 317 (34.4%) projects and $225 million, and febrile and vector-borne infections with 274 (29.8%) projects and $45 million. The number of annual respiratory infections-related projects peaked in 2006 and 2009. The number of febrile and vector-borne infections projects increased from 29 projects in 2006 to 58 in 2012. There were 651 articles published in 147 different peer-reviewed journals, with an average Thomson Reuters 2-year journal impact factor of 4.2 (range 0.3-53.5). On average, 93 articles were published per year (range 67-117) with $510,000 per publication. Febrile and vector-borne, respiratory, and gastrointestinal infections had 287, 167, and 73 articles published, respectively. Of the 651 articles published, 585 (89.9%) articles were cited at least once (range 1-1,045). Institutions from 90 countries located in all six World Health Organization regions collaborated with surveillance projects. Conclusions: These findings summarize the GEIS-funded surveillance portfolio between 2006 and 2012, and demonstrate the scientific productivity and impact of the program in each of the six disease surveillance priority focus areas. GEIS might benefit from further financial investment in both the febrile and vector-borne and sexually transmitted infections surveillance priority focus areas and increasing peer-reviewed publications of surveillance data derived from respiratory infections projects. Bibliometric indicators are useful to measure scientific productivity and impact in surveillance systems; and this methodology can be utilized as a management tool to assess future changes to GEIS surveillance priorities.Additional metrics should be developed when peer-reviewed literature is not used to disseminate noteworthy accomplishments.

BACKGROUND:Data on norovirus epidemiology among all ages in community settings are scarce, especially from tropical settings. METHODS:We implemented active surveillance in 297 households in Peru from October 2012 to August 2015 to assess the burden of diarrhea and acute gastroenteritis (AGE) due to norovirus in a lower-middle-income community. During period 1 (October 2012-May 2013), we used a "traditional" diarrhea case definition (≥3 loose/liquid stools within 24 hours). During period 2 (June 2013-August 2015), we used an expanded case definition of AGE (by adding ≥2 vomiting episodes without diarrhea or 1-2 vomiting episodes plus 1-2 loose/liquid stools within 24 hours). Stool samples were tested for norovirus by reverse-transcription polymerase chain reaction. RESULTS:During period 1, overall diarrhea and norovirus-associated diarrhea incidence was 37.2/100 person-years (PY) (95% confidence interval [CI], 33.2-41.7) and 5.7/100 PY (95% CI, 3.9-8.1), respectively. During period 2, overall AGE and norovirus-associated AGE incidence was 51.8/100 PY (95% CI, 48.8-54.9) and 6.5/100 PY (95% CI, 5.4-7.8), respectively. In both periods, children aged <2 years had the highest incidence of norovirus. Vomiting without diarrhea occurred among norovirus cases in participants <15 years old, but with a higher proportion among children <2 years, accounting for 35% (7/20) of all cases in this age group. Noroviruses were identified in 7% (23/335) of controls free of gastroenteric symptoms. CONCLUSIONS:Norovirus was a significant cause of AGE in this community, especially among children <2 years of age. Inclusion of vomiting in the case definition resulted in a 20% improvement for detection of norovirus cases.

BackgroundThere are limited data on the burden of disease posed by influenza in low- and middle-income countries. Furthermore, most estimates of influenza disease burden worldwide rely on passive sentinel surveillance at health clinics and hospitals that lack accurate population denominators.MethodsWe documented influenza incidence, seasonality, health-system utilization with influenza illness, and vaccination coverage through active community-based surveillance in 4 ecologically distinct regions of Peru over 6 years. Approximately 7200 people in 1500 randomly selected households were visited 3 times per week. Naso- and oropharyngeal swabs were collected from persons with influenza-like illness and tested for influenza virus by real-time reverse-transcription polymerase chain reaction.ResultsWe followed participants for 35353 person-years (PY). The overall incidence of influenza was 100 per 1000 PY (95% confidence interval [CI], 97-104) and was highest in children aged 2-4 years (256/1000 PY [95% CI, 236-277]). Seasonal incidence trends were similar across sites, with 61% of annual influenza cases occurring during the austral winter (May-September). Of all participants, 44 per 1000 PY (95% CI, 42-46) sought medical care, 0.7 per 1000 PY (95% CI, 0.4-1.0) were hospitalized, and 1 person died (2.8/100000 PY). Influenza vaccine coverage was 27% among children aged 6-23 months and 26% among persons aged ≥65 years.ConclusionsOur results indicate that 1 in 10 persons develops influenza each year in Peru, with the highest incidence in young children. Active community-based surveillance allows for a better understanding of the true burden and seasonality of disease that is essential to plan the optimal target groups, timing, and cost of national influenza vaccination programs.

The genus Bartonella contains >40 species, and an increasing number of these Bartonella species are being implicated in human disease. One such pathogen is Bartonella ancashensis, which was isolated in blood samples from 2 patients living in Caraz, Peru, during a clinical trial of treatment for bartonellosis. Three B. ancashensis strains were analyzed by using whole-genome restriction mapping and high-throughput pyrosequencing. Genome-wide comparative analysis of Bartonella species showed that B. ancashensis has features seen in modern and ancient lineages of Bartonella species and is more related to B. bacilliformis. The divergence between B. ancashensis and B. bacilliformis is much greater than what is seen between known Bartonella genetic lineages. In addition, B. ancashensis contains type IV secretion system proteins, which are not present in B. bacilliformis. Whole-genome analysis indicates that B. ancashensis might represent a distinct Bartonella lineage phylogenetically related to B. bacilliformis.

Our understanding of the global ecology of avian influenza A viruses (AIVs) is impeded by historically low levels of viral surveillance in Latin America. Through sampling and whole-genome sequencing of 31 AIVs from wild birds in Peru, we identified 10 HA subtypes (H1-H4, H6-H7, H10-H13) and 8 NA subtypes (N1-N3, N5-N9). The majority of Peruvian AIVs were closely related to AIVs found in North America. However, unusual reassortants, including a H13 virus containing a PA segment related to extremely divergent Argentinian viruses, suggest that substantial AIV diversity circulates undetected throughout South America.

IntroductionInfluenza disease burden and economic impact data are needed to assess the potential value of interventions. Such information is limited from resource‐limited settings. We therefore studied the cost of influenza in Peru.MethodsWe used data collected during June 2009–December 2010 from laboratory‐confirmed influenza cases identified through a household cohort in Peru. We determined the self‐reported direct and indirect costs of self‐treatment, outpatient care, emergency ward care, and hospitalizations through standardized questionnaires. We recorded costs accrued 15‐day from illness onset. Direct costs represented medication, consultation, diagnostic fees, and health‐related expenses such as transportation and phone calls. Indirect costs represented lost productivity during days of illness by both cases and caregivers. We estimated the annual economic cost and the impact of a case of influenza on a household.ResultsThere were 1321 confirmed influenza cases, of which 47% sought health care. Participants with confirmed influenza illness paid a median of $13 [interquartile range (IQR) 5–26] for self‐treatment, $19 (IQR 9–34) for ambulatory non‐medical attended illness, $29 (IQR 14–51) for ambulatory medical attended illness, and $171 (IQR 113–258) for hospitalizations. Overall, the projected national cost of an influenza illness was $83–$85 millions. Costs per influenza illness represented 14% of the monthly household income of the lowest income quartile (compared to 3% of the highest quartile).ConclusionInfluenza virus infection causes an important economic burden, particularly among the poorest families and those hospitalized. Prevention strategies such as annual influenza vaccination program targeting SAGE population at risk could reduce the overall economic impact of seasonal influenza.

Zika virus is an emerging human pathogen of great concern due to putative links to microcephaly and Guillain-Barre syndrome. Here, we report the complete genomes, including the 5' and 3' untranslated regions, of five Zika virus isolates, one from the Asian lineage and four from the African lineage.

There is an increasing role for bioinformatic and phylogenetic analysis in tropical medicine research. However, scientists working in low- and middle-income regions may lack access to training opportunities in these methods. To help address this gap, a 5-day intensive bioinformatics workshop was offered in Lima, Peru. The syllabus is presented here for others who want to develop similar programs. To assess knowledge gained, a 20-point knowledge questionnaire was administered to participants (21 participants) before and after the workshop, covering topics on sequence quality control, alignment/formatting, database retrieval, models of evolution, sequence statistics, tree building, and results interpretation. Evolution/tree-building methods represented the lowest scoring domain at baseline and after the workshop. There was a considerable median gain in total knowledge scores (increase of 30%, p<0.001) with gains as high as 55%. A 5-day workshop model was effective in improving the pathogen-applied bioinformatics knowledge of scientists working in a middle-income country setting.

Co-circulation of influenza A(H5N1) and seasonal influenza viruses among humans and animals could lead to coinfections, reassortment, and emergence of novel viruses with pandemic potential. We assessed the timing of subtype H5N1 outbreaks among poultry, human H5N1 cases, and human seasonal influenza in 8 countries that reported 97% of all human H5N1 cases and 90% of all poultry H5N1 outbreaks. In these countries, most outbreaks among poultry (7,001/11,331, 62%) and half of human cases (313/625, 50%) occurred during January March. Human H5N1 cases occurred in 167 (45%) of 372 months during which outbreaks among poultry occurred, compared with 59 (10%) of 574 months that had no outbreaks among poultry. Human H5N1 cases also occurred in 59 (22%) of 267 months during seasonal influenza periods. To reduce risk for co-infection, surveillance and control of H5N1 should be enhanced during January March, when H5N1 outbreaks typically occur and overlap with seasonal influenza virus circulation.

Three novel isolates of the genus Bartonella were recovered from the blood of two patients enrolled in a clinical trial for the treatment of chronic stage Bartonella bacilliformis infection (verruga peruana) in Caraz, Ancash, Peru. The isolates were initially characterized by sequencing a fragment of the gltA gene, and found to be disparate from B. bacilliformis. The isolates were further characterized using phenotypic and genotypic methods, and found to be genetically identical to each other for the genes assessed, but distinct from any known species of the genus Bartonella, including the closest relative B. bacilliformis. Other characteristics of the isolates, including their morphology, microscopic and biochemical properties, and growth patterns, were consistent with members of the genus Bartonella. Based on these results, we conclude that these three isolates are members of a novel species of the genus Bartonella for which we propose the name Bartonella ancashensis sp. nov. (type strain 20.00T = ATCC BAA-2694T = DSM 29364T).

ABSTRACT Here we present the complete genome sequence of Bartonella ancashensis strain 20.00, isolated from the blood of a Peruvian patient with verruga peruana, known as Carrion's disease. Bartonella ancashensis is a Gram-negative bacillus, phylogenetically most similar to Bartonella bacilliformis , the causative agent of Oroya fever and verruga peruana.