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Incidence, Etiology and Risk Factors for Travelers’ Diarrhea during a Hospital Ship-Based Military Humanitarian Mission: Continuing Promise 2011
research-article
Author(s):
Jessica M. Hameed
1 ,
Ramona L. McCaffrey
2 ,
Andrea McCoy
3 ,
Tracy Brannock
4 ,
Gregory J. Martin
5 ,
William T. Scouten
6 ,
Krista Brooks
2 ,
Shannon D. Putnam
2
,
7 ,
Mark S. Riddle
1
,
3
,
*
Publication date (Electronic):
12 May 2016
Journal:
PLoS ONE
Publisher:
Public Library of Science
Read this article at
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
Travelers’ diarrhea (TD) is the most common ailment affecting travelers, including deployed U.S. military. Continuing Promise 2011 was a 5-month humanitarian assistance/disaster response (HA/DR) military and non-governmental organization training mission aboard the hospital ship USNS Comfort, which deployed to Central and South America and the Caribbean between April and September 2011. Enhanced TD surveillance was undertaken during this mission for public health purposes. Passive surveillance (clinic visits), active surveillance (self-reported questionnaires), and stool samples were collected weekly from shipboard personnel. Descriptive statistics and multivariate-logistic regression methods were used to estimate disease burden and risk factor identification. Two polymerase chain reaction methods on frozen stool were used for microbiological identification. TD was the primary complaint for all clinic visits (20%) and the leading cause of lost duties days due to bed rest confinement (62%), though underreported, as the active self-reported incidence was 3.5 times higher than the passive clinic-reported incidence. Vomiting (p = 0.002), feeling lightheaded or weak (p = 0.005), and being a food handler (p = 0.017) were associated with increased odds of lost duty days. Thirty-eight percent of self-reported cases reported some amount of performance impact. Based on the epidemiological curve, country of exercise and liberty appeared to be temporally associated with increased risk. From the weekly self-reported questionnaire risk factor analysis, eating off ship in the prior week was strongly associated (adjusted odds ratio [OR] 2.4, p<0.001). Consumption of seafood increased risk (aOR 1.7, p = 0.03), though consumption of ice appeared protective (aOR 0.3, p = 0.01). Etiology was bacterial (48%), with enterotoxigenic Escherichia coli as the predominant pathogen (35%). Norovirus was identified as a sole pathogen in 12%, though found as a copathogen in an additional 6%. Despite employment of current and targeted preventive interventions, ship-board HA/DR missions may experience a significant risk for TD among deployed US military personnel and potentially impact mission success.
Related collections
Most cited references25
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- Abstract: found
- Article: found
Novel Surveillance Network for Norovirus Gastroenteritis Outbreaks, United States1
Everardo Vega, Leslie Barclay, Nicole Gregoricus … (2011)
Noroviruses are the primary cause of epidemic viral gastroenteritis and the leading cause of foodborne outbreaks in the United States (1–3). Although the course of disease is in most cases self-limiting, young, elderly, and immunocompromised persons are at risk for complications caused by severe vomiting and diarrhea (4–8). In addition to the clinical impact of norovirus disease, the economic effects in lost wages, time, and intervention procedures (e.g., clean-up costs and recalls) can be significant (9–11). Although norovirus outbreaks occur year-round, they are more common during the winter months (12–14). Noroviruses are genetically classified into 5 genogroups, GI–GV, with GI and GII strains responsible for most human disease (2,15). GII viruses can be further divided into at least 19 genotypes, of which GII.4 is responsible for >85% of outbreaks (14,16), although other genotypes and viruses continue to circulate and cause sporadic disease in children (17–19). Over the past 15 years, new GII.4 variants have been identified; several have been associated with a global increase in the number of outbreaks (15). The last pandemic GII.4 variant, GII.4 2006b or GII.4 Minerva, was identified in late 2005/early 2006 and has been the predominant outbreak strain in the United States since then. The successive displacement of GII.4 variants suggests that population immunity is driving the evolution of GII.4 viruses (20,21), and the emergence of a new variant will cause an increase in the number of outbreaks in an immunologically naive population. It is not fully understood why some GII.4 variants become pandemic whereas others do not. The combination of novel antigenic sites in protruding regions of the capsid (centered around amino acids 295 and 396) and the change or expansion of a susceptible population may be responsible for the emergence of pandemic variants (20,22). The latter theory has been supported by the discovery that different norovirus strains may have different histo–blood group antigen (HBGA) binding patterns and that nonsecretors are not susceptible to infection with certain genotypes or variants (23). Most mutations between genotypes and variants occur in the P2 region of the major capsid viral protein (VP), VP1, which contains the HBGA binding sites. Since 2008, all 50 states have had the laboratory capacity for norovirus testing; the Centers for Disease Control and Prevention (CDC) National Calicivirus Laboratory (NCL) provides laboratory support to states that do not have in-house capacity for norovirus strain typing. Recent studies on the molecular epidemiology of norovirus in the US have been based on specimens from a subset of outbreaks that were submitted to CDC (13,24,25). To enhance and harmonize norovirus outbreak surveillance, CDC and its state partners have developed a national norovirus outbreak surveillance network, CaliciNet. CaliciNet was developed to improve standardized typing of norovirus outbreaks, assist in linking geographically different clusters of norovirus illness, allow rapid classification and identification of new norovirus strains, and establish a comprehensive strain surveillance network in the United States. In this article, we describe the CaliciNet network and report first-year results, including the identification of a new GII.4 norovirus variant. Materials and Methods CaliciNet CaliciNet is a novel electronic laboratory surveillance network of local and state public health laboratories in the United States, coordinated by CDC. CaliciNet participants perform molecular typing of norovirus strains by using standardized laboratory protocols for reverse transcription PCR (RT-PCR) followed by DNA sequence analysis of the amplicons. A customized CaliciNet database developed in Bionumerics version 5.1 (Applied Maths, Austin, TX, USA) includes norovirus sequence and basic epidemiologic information (Table 1), which are submitted electronically via a secure connection to the CaliciNet server at CDC. Both epidemiologic and sequence data can then be used to help link multistate outbreaks to a common source (e.g., contaminated food). To ensure high-quality data entry, submissions to the CaliciNet server are performed by certified laboratory personnel of the participating state or local health laboratories, and final quality assurance/quality control is performed at CDC. Table 1 Epidemiologic data fields required for upload to CaliciNet* Required CaliciNet fields Description LabOBNumber Year, outbreak, and number Outbreak date Begin date of outbreak Outbreak city City where outbreak occurred Outbreak state State where outbreak occurred Outbreak setting Select outbreak setting† Outbreak country Country where outbreak occurred Transmission Foodborne, person-to-person, waterborne Conventional RT-PCR Results of RT-PCR‡ Sequence experiment Sequence of region D§ *RT-PCR, reverse transcription PCR.
†Child care center, cruise ships, hospital, long-term care facility, party or event, restaurant, school and community, correctional center.
‡Region C or D.
§Region D is the preferred sequence, but region C is also accepted. CaliciNet certification for participants is a 2-step process that involves evaluation of data entry and analysis of sequences and a laboratory panel test. Each laboratory must pass an annual proficiency test. The laboratory certification and proficiency test consists of analyzing a panel of fecal samples by real-time RT-PCR and conventional RT-PCR analysis followed by bidirectional sequencing as described below. Certified participants are then authorized to upload norovirus outbreak data consisting of >2 samples per outbreak to the national CaliciNet database (Table 1). GII.4 sequences with >2% and 3% difference in region C or D, respectively, and >10% difference with all other noroviruses are further analyzed at CDC by amplification of the VP1 or P2 region. Outbreaks All outbreaks submitted to CaliciNet and the NCL from October 2009 through March 2010 were genotyped by region D analysis (26). To verify GII.4 New Orleans variants, a subset of outbreaks from CaliciNet participating laboratories and 2 specimens from each outbreak received at the NCL from October 2009 through May 2010 were analyzed by using the P2 region as described below. Viral RNA Extraction Viral RNA was extracted from clarified 10% fecal suspensions in phosphate-buffered saline with the MagMax-96 Viral RNA Isolation Kit (Ambion, Foster City, CA, USA) on an automated KingFisher magnetic particle processor (Thermo Fisher Scientific, Pittsburgh, PA, USA) according to the manufacturer’s instructions and eluted into 100 µL of elution buffer (10 mmol/L Tris pH 8.0 and 1 mmol/L EDTA). Extracted RNA was stored at –80°C until further use. Real-time RT-PCR Viral RNA was tested for GI and GII noroviruses in a duplex format by using the AgPath-ID One-Step RT-PCR Kit (Applied Biosystems, Foster City, CA, USA) on a 7500 Realtime PCR platform (Applied Biosystems). The final reaction mix of 25 µL consisted of 400 nmol/L of each oligonucleotide primer, Cog1F, Cog1R, Cog2F, and Cog2R, and 200 nmol/L of each TaqMan Probe Ring 2 (27) and Ring 1C (28) (Table 2). Cycling conditions included reverse transcription for 10 min at 45°C and denaturation for 10 min at 95°C, followed by 40 cycles of 15 s at 95°C and 1 min at 60°C. Table 2 Oligonucleotide primers and probes used for detection and genotype identification of norovirus strains submitted to CaliciNet* Primer or probe name RT-PCR target Sequence, 5′ → 3′ Reference TVN-L1 ORF2–ORF3 GGG TGT GTT GTG GTG TTG T26VN (29) L1 ORF2–ORF3 GGG TGT GTT GTG GTG TTG This study EVP2F P2 (GII.4 specific) GTR CCR CCH ACA GTT GAR TCA This study EVP2R P2 (GII.4 specific) CCG GGC ATA GTR GAY CTR AAG AA This study Cap D1 Region D GII TGT CTR STC CCC CAG GAA TG (26) Cap C Region D GII CCT TYC CAK WTC CCA YGG (26) Cap D3 Region D GII TGY CTY ITI CCH CAR GAA TGG (26) Cog 2F ORF1–ORF2 junction (GII) CAR GAR BCN ATG TTY AGR TGG ATG AG (27) Cog 2R ORF1–ORF2 junction (GII) TCG ACG CCA TCT TCA TTC ACA (27) Ring 2 ORF1–ORF2 junction (GII) Cy5-TGG GAG GGC GAT CGC AAT CT-BHQ (27) Ring 1C ORF1–ORF2 junction (GI) FAM-AGA TYG CGI TCI CCT GTC CA-BHQ (28) Cog 1F ORF1–ORF2 junction (GI) CGY TGG ATG CGI TTY CAT GA (27) Cog 1R ORF1–ORF2 junction (GI) CTT AGA CGC CAT CAT CAT TYA C (27) *RT-PCR, reverse transcription PCR; ORF, open reading frame. Region D RT-PCR The QIAGEN One-Step RT-PCR Kit (QIAGEN, Valencia, CA, USA) was used for region D amplification in a 25-µL reaction volume. RNAse Inhibitor (Applied Biosystems) was added to a final concentration of 15–20 units/reaction. Oligonucleotide primers CapD1, CapD3, and CapC were added to a final concentration of 1 µmol/L each (Table 2). RT-PCR conditions included reverse transcription at 42°C for 30 min and denaturation at 95°C for 15 min, followed by 40 cycles of 30 s at 94°C, 30 s at 40°C, and 30 s at 72°C. A final elongation step was run for 10 min at 72°C. P2 Region Amplification The P2 region was amplified by using the SuperScript III One-Step RT-PCR with Platinum Taq High Fidelity Kit (Invitrogen, Carlsbad, CA, USA). The final reaction volume of 25 µL consisted of 4 µmol/L of EVP2F and EVP2R (Table 2). RT-PCR conditions included reverse transcription at 55°C for 30 min and denaturation at 94°C for 2 min, followed by 40 cycles of PCR at 94°C for 15 s, 55°C for 30 s, 68°C for 1 min, and a final extension step of 68°C for 5 min. Amplification and Cloning of GII.4 New Orleans Novel GII.4 New Orleans sequences were identified by region D sequence analysis and further analyzed by amplification of complete open reading frame 2. Extracted RNA from fecal samples underwent cDNA synthesis with a TVN-L1 primer (29) (Table 2) for 60 min at 50°C by using the Superscript III cDNA synthesis kit (Invitrogen). The reaction mixture was purified by using the DNA Clean and Concentrator-5 (Zymo Research, Orange, CA, USA). The cDNA was amplified by using oligonucleotides (0.5 µmol/L each) L1 and Cog2F (Table 2), using the Phusion PCR Kit with the addition of 3% dimethyl sulfoxide (Finnzymes, Woburn, MA, USA). PCR conditions included denaturation at 98°C for 30 s followed by 40 cycles of 98°C for 10 s, 48°C for 30 s, and 72°C for 1.5 min. A final elongation step was run at 72°C for 10 min. PCR products of ≈2.5 kb were gel purified and cloned by using a TOPO-TA Cloning Kit (Invitrogen). Five clones of each strain were fully sequenced bidirectionally and their respective consensus sequences were submitted to GenBank. The accession no. for GII.4 New Orleans is GU445325. DNA Sequencing All amplicons were purified with the QIAquick Gel Extraction or PCR Purification Kits (QIAGEN) and sequenced by using the BigDye Terminator Kit version 1.1 (Applied Biosystems). Sequence reactions were cleaned up by using the BigDye Xterminator Kit (Applied Biosystems) and analyzed on a 3130XL Automated Sequencer (Applied Biosystems). Phylogenetic Analysis VP1 or P2 sequences were aligned by using MEGA4 software (30). Maximum-likelihood phylogenetic analysis of VP1 amino acids were run in PhyML version 3.0 (www.atgc-montpellier.fr/phyml/binaries.php) by using the LG amino acids replacement matrix (31). The initial tree was the best of 5 random trees, and branches were supported by 100 bootstrap replicates. Branches with bootstrap support 50% during the winter months. Compared with known GII.4 viruses, GII.4 New Orleans had several changes in key amino acids in the P2 region of VP1 and around the sites that have been shown to be important in HBGA binding (20). Because most GII.4 variants that have been identified since 2004 are conserved at these sites, it has been speculated that mutations that change the HBGA binding pattern would decrease the fitness of the virus (36). During the last transitional period when GII.4 Minerva (GII.4 2006b) was identified, another GII.4 variant was co-circulating (21,37). CaliciNet uses the same software as the US bacterial enteric pathogen surveillance network (PulseNet) (38), but it is customized with plug-ins to add CaliciNet-specific functionality. CaliciNet uses sequence data, whereas PulseNet is based on pulsed-field gel electrophoresis restriction digestion patterns of bacterial enteric pathogens. Current typing regions of CaliciNet target small regions of the norovirus genome, which makes it difficult to discern closely related norovirus strains, although the implications to human health may be significant. Our data and data from other studies (39) demonstrated that P2 region analysis enables more sensitive identification of new GII.4 variant strains compared with currently used CaliciNet regions. Use of these analyses would increase the sensitivity of outbreak surveillance to track strains that are part of a single outbreak and likely to have a common source. Hence, P2 is under consideration to be included in CaliciNet. Like CaliciNet, the Foodborne Viruses in Europe network (FBVE) uses a central database to which users can submit norovirus sequences (40). Compared with the FBVE network, CaliciNet focuses primarily on noroviruses, is not web-based, and is based on a secured network connection to CaliciNet servers at CDC where the states log on as clients, enabling them to upload, view, and query outbreak data submitted by other states. CaliciNet also organizes training workshops and sends standardized protocols and annual proficiency panels to its members. The benefit of the FBVE network is that it can be more easily expanded to include laboratories outside its network, whereas to date CaliciNet allows only participants from state and local health laboratories in the US to participate. The success of CaliciNet in linking multistate outbreaks to a common source (e.g., contaminated food) will depend on joint efforts of state and local epidemiologists to rapidly identify the likely common source and on CaliciNet laboratories for the timely upload of outbreak sequences to the national CaliciNet database. Although CaliciNet has selected region D as its preferred sequence region, a region C and soon a P2 region sequence database will be maintained to enable exchange of information with other norovirus surveillance networks. Because the region D assay targets a genetically highly heterogeneous region of VP1, the performance of this assay will be closely monitored over time, and necessary changes will be implemented to improve assay sensitivity and specificity. Future CaliciNet expansion will include other gastroenteritis viruses, such as sapovirus and astrovirus, as well as add capability for CaliciNet members to submit fecal samples from patients involved in norovirus-negative outbreaks to CDC for further testing, including novel pathogen discovery sequencing technologies (18). CaliciNet was launched in March 2009 and helped in the rapid identification of a new GII.4 variant. P2 analysis confirmed that this variant was divergent from previous GII.4 viruses. The widespread presence of GII.4 New Orleans across the US coupled with the decreasing prevalence of the GII.4 Minerva variant, which has been the major cause of outbreaks during 2006–2009, suggests gradual strain displacement. Data from the 2009–2010 winter season showed the importance of CaliciNet and its future potential for norovirus surveillance in the US. To enhance norovirus surveillance globally, CaliciNet will collaborate with other norovirus surveillance networks, such as ViroNet in Canada and the global norovirus network, NoroNet (15), to better predict or determine norovirus epidemiologic or outbreak trends. International surveillance of viral foodborne outbreaks is essential because of the increasing globalization of the food industry. Additional members of the Calicivirus network who contributed data (state represented): Chao-Yang Pan, Tasha Padilla (CA); Justin Nucci, Mary-Kate Cichon (CO); Gregory Hovan (DE); Precilia Calimlim, Cheryl-Lynn Daquip (HI); Edward Simpson (IN); Amanda Bruesch, Kari Getz (ID); Jonathan Johnston, Julie Haendiges (MD); Heather Grieser, John Martha (ME); Laura Mosher (MI); Elizabeth Cebelinski (MN); Alisha M. Nadeau, Fengxiang Gao (NH); Ondrea Shone (NJ); Frederick Gentry (NM); Gino Battaglioli (NY), Eric Brandt, Rebekah Carmen, Steven York (OH); Andrea Maloney (SC); Amy M. Woron, Christina Moore (TN); Chun Wang (TX); Valarie Devlin (VT); Tim Davis, Tonya Danz, and Jose Navidad (WI).
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Global etiology of travelers' diarrhea: systematic review from 1973 to the present.
Andrew Ramsey, Nipam Shah, H Dupont (2009)
Fifty-one published studies of travelers' diarrhea (TD) were examined to look for regional differences in pathogens identified. Enterotoxigenic E. coli was detected in 1,678/5,518 (30.4%) of TD cases overall, with rates in Latin America/Caribbean (L. America), Africa, south Asia, and Southeast Asia of 1,109/3,302 (33.6%), 389/1,217 (31.2%), 153/499 (30.6%), and 36/500 (7.2%), respectively (P < 0.001). Enteroaggregative E. coli was the second most common agent in L. America, found in 166/689 (24.1%), compared with 3/165 (1.8%) in Africa and 33/206 (16%) in south Asia (P < 0.001). Other significantly regional differences were seen for enteropathogenic E. coli, diffusely adherent E. coli, Campylobacter, Shigella spp., Salmonella, Aeromonas spp., Plesiomonas, Vibrios, rotavirus, noroviruses, Giardia, and Entoamoeba histolytica. The regional differences in pathogen identification identified will serve as a baseline for antimicrobial therapy recommendations and vaccines strategies.
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Analysis of culture-dependent versus culture-independent techniques for identification of bacteria in clinically obtained bronchoalveolar lavage fluid.
The diagnosis and management of pneumonia are limited by the use of culture-based techniques of microbial identification, which may fail to identify unculturable, fastidious, and metabolically active viable but unculturable bacteria. Novel high-throughput culture-independent techniques hold promise but have not been systematically compared to conventional culture. We analyzed 46 clinically obtained bronchoalveolar lavage (BAL) fluid specimens from symptomatic and asymptomatic lung transplant recipients both by culture (using a clinical microbiology laboratory protocol) and by bacterial 16S rRNA gene pyrosequencing. Bacteria were identified in 44 of 46 (95.7%) BAL fluid specimens by culture-independent sequencing, significantly more than the number of specimens in which bacteria were detected (37 of 46, 80.4%, P ≤ 0.05) or "pathogen" species reported (18 of 46, 39.1%, P ≤ 0.0001) via culture. Identification of bacteria by culture was positively associated with culture-independent indices of infection (total bacterial DNA burden and low bacterial community diversity) (P ≤ 0.01). In BAL fluid specimens with no culture growth, the amount of bacterial DNA was greater than that in reagent and rinse controls, and communities were markedly dominated by select Gammaproteobacteria, notably Escherichia species and Pseudomonas fluorescens. Culture growth above the threshold of 10(4) CFU/ml was correlated with increased bacterial DNA burden (P < 0.01), decreased community diversity (P < 0.05), and increased relative abundance of Pseudomonas aeruginosa (P < 0.001). We present two case studies in which culture-independent techniques identified a respiratory pathogen missed by culture and clarified whether a cultured "oral flora" species represented a state of acute infection. In summary, we found that bacterial culture of BAL fluid is largely effective in discriminating acute infection from its absence and identified some specific limitations of BAL fluid culture in the diagnosis of pneumonia. We report the first correlation of quantitative BAL fluid culture results with culture-independent evidence of infection. Copyright © 2014, American Society for Microbiology. All Rights Reserved.
Author and article information
Contributors
Niyaz Ahmed: Role: Editor
Journal
Journal ID (nlm-ta): PLoS One
Journal ID (iso-abbrev): PLoS ONE
Journal ID (publisher-id): plos
Journal ID (pmc): plosone
Title:
PLoS ONE
Publisher:
Public Library of Science
(San Francisco, CA USA
)
ISSN
(Electronic):
1932-6203
Publication date
(Electronic):
12
May
2016
Publication date Collection: 2016
Volume: 11
Issue: 5
Electronic Location Identifier: e0154830
Affiliations
[1
]Department of Preventive Medicine & Biostatistics, Uniformed Services University of
the Health Sciences, Bethesda, MD, United States of America
[2
]Enteric Disease Surveillance Program, Operational Infectious Disease Department, Naval
Health Research Center, San Diego, CA, United States of America
Author notes
Competing Interests: The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Department of the Navy, Department of Defense, or the U.S. Government. Approved for public release; distribution is unlimited. Human subjects participated in this study after giving their free and informed consent. This research has been conducted in compliance with all applicable Federal Regulations governing the Protection of Human Subjects in Research. U.S. Government Work (17 USC 105). Not copyrighted in the U.S. The authors have declared that no competing interests exist.
Conceived and designed the experiments: MSR GJM WTS AM. Performed the experiments: JMH RLM KB AM TB GJM WTS MSR. Analyzed the data: JMH RLM MSR. Contributed reagents/materials/analysis tools: JMH RLM MSR SDP. Wrote the paper: JMH RLM MSR WTS. Critical editing and revisions: SDP.
* E-mail:
mark.s.riddle10.mil@
123456mail.mil
Article
Publisher ID: PONE-D-16-06536DOI: 10.1371/journal.pone.0154830
PMC ID: 4865142
PubMed ID: 27171433
SO-VID: 6319e3f6-5aaa-4f3d-807d-4260a31a45ae
License:
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
History
Date
received
: 15
February
2016
Date
accepted
: 19
April
2016
Page count
Figures: 1,
Tables: 5,
Pages: 13
Funding
Funded by: funder-id http://dx.doi.org/10.13039/100000005, U.S. Department of Defense;
Award ID: GEIS Project No. P0298_13_NM
Award Recipient
:
Ramona L. McCaffrey
This work was completed as part of official duties while on mission aboard the USNS
Comfort during Continuing Promise 2011. Microbiological assessment was supported by
the Department of Defense Global Emerging Surveillance and Response Systems under
Project No. P0298_13_NM.
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Custom metadata
Data Availability All relevant data are available via Figshare (
https://dx.doi.org/10.6084/m9.figshare.3144967.v1 &
https://dx.doi.org/10.6084/m9.figshare.3144961.v1).
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Data availability:
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